diff --git a/.gitignore b/.gitignore
index 46d75a5410082a51eb532e21aa8ac516bee675c1..10c2abc5ba957035aaf9170b97f62593d3c193e8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,11 +1,18 @@
*.pyc
+*.so
+*.log
+hysop.egg-info/
+
hysop/__init__.py
-.#*
+hysop/constants.py
hysop/.pyflymakercc
-.DS_Store
+hysop/f2hysop.pyf
+
build/
debug/
release/
+
+.#*
+.DS_Store
.cache/
-hysop/f2hysop.pyf
.ycm_extra_conf.py
diff --git a/CMakeLists.txt b/CMakeLists.txt
index ac3fd48459c81c43adfa0b07b32f5b6e058aa51f..272e114a95609f6da23bf16eae300be216361131 100755
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -28,19 +28,19 @@ include(OutOfSourceBuild)
include(MyTools)
# User defined options
-option(VERBOSE_MODE "enable verbose mode for cmake exec. Default = on" ON)
-option(DOUBLEPREC "set precision for real numbers to double precision when this mode is enable. Default = on." ON)
-option(USE_MPI "compile and link HySoP with mpi when this mode is enable. Default = on." ON)
-option(WITH_TESTS "Enable testing. Default = off" ON)
+option(VERBOSE_MODE "Print cmake-hysop state summary. Default = on" ON)
+option(DOUBLEPREC "switch between single and double precision for real numbers. Default = on, ie double precision." ON)
+option(USE_MPI "compile and link HySoP with mpi when this mode is enable. Default = on. WARNING: off mode is bugged." ON)
+option(WITH_TESTS "Enable testing. Default = OFF" ON)
option(BUILD_SHARED_LIBS "Enable dynamic library build, default = ON." ON)
-option(WITH_LIB_CXX "Generate libhysop from c++ files in src, wrapped into hysop.cpp2hysop module. Default = ON." ON)
+option(USE_CXX "Expand hysop with some new functions from a generated c++ to python interface, wrapped into hysop.cpp2hysop module. Default = ON." ON)
option(WITH_SCALES "compile/create scales lib and link it with HySoP. Default = ON." ON)
option(WITH_FFTW "Link with fftw library (required for some HySoP solvers), default = ON" ON)
option(WITH_EXTRAS "Link with some extra fortran libraries (like arnoldi solver), default = OFF" OFF)
option(WITH_GPU "Use of GPU (required for some HySoP solvers), default = ON" ON)
-option(WITH_MAIN_FORTRAN "Create an executable (test purpose) from fortran sources in src/main, linked with libhysop, default = ON" ON)
+option(WITH_MAIN_FORTRAN "Create an executable (test purpose) from fortran sources in src/main, linked with libhysop, default = ON" OFF)
option(WITH_MAIN_CXX "Create an executable (test purpose) from cxx sources in src/hysop++/main, linked with libhysop, default = ON" ON)
-option(DEBUG "Enable debug mode for HySoP (0:disabled, 1:verbose, 2:trace, 3:verbose+trace). Default = 0" 0)
+option(DEBUG "Enable debug mode for HySoP (0:disabled, 1:verbose, 2:trace, 3:verbose+trace). Default = 0" 1)
option(FULL_TEST "Enable all test options (pep8, mpi ...) - Default = OFF" OFF)
option(PROFILE "Enable profiling mode for HySoP. 0:disabled, 1: enabled. Default = 0" 0)
option(OPTIM "To allow python -OO run, some packages must be deactivated. Set this option to 'ON' to do so. Default = OFF" OFF)
@@ -49,7 +49,7 @@ option(WITH_GOOGLE_TESTS "Enable google tests (c++). Default = OFF." OFF)
option(FORTRAN_LAYOUT "Choose default data layout ('fortran', column-major or 'C' order, row-major) for arrays. Default = column-major." ON)
option(WITH_DOCUMENTATION "Build Documentation. Default = OFF" OFF)
option(ENABLE_LONG_TESTS "Enable tests that may run for long time with important memory print. Default = OFF." OFF)
-
+option(DEV_MODE "Enable devel mode (aggressive checking of warnings ..). Default = ON." ON)
# Set python install mode:
# - user --> behave as 'python setup.py install --user'
# - standard --> install in python site-package (ie behave as python setup.py install)
@@ -75,25 +75,17 @@ if(NOT USE_MPI)
message(FATAL_ERROR "No-mpi version of hysop is broken, please enable mpi.")
endif()
+# Fortran interface is not used by default.
+set(USE_FORTRAN "OFF")
if(WITH_FFTW OR WITH_SCALES OR WITH_EXTRAS)
set(USE_FORTRAN "ON")
endif()
-if(NOT WITH_LIB_CXX)
+if(NOT USE_CXX)
set(WITH_MAIN_CXX "OFF")
set(WITH_GOOGLE_TESTS "OFF")
endif()
-# true if hysop used Fortran and/or c++ sources
-# We can not run scales or fftw without mpi ...
-if(USE_FORTRAN OR WITH_LIB_CXX)
- set(WITH_COMPILED_LIB "ON")
- #set(WITH_FFTW "ON")
-else()
- set(WITH_COMPILED_LIB "OFF")
- #set(WITH_FFTW "OFF")
-endif()
-
# Force a default build type if not provided by user
# CMAKE_BUILD_TYPE = empty, Debug, Release, RelWithDebInfo or MinSizeRel.
if(NOT CMAKE_BUILD_TYPE)
@@ -117,12 +109,14 @@ set(PROJECT_LIBRARY_NAME ${PROJECT_NAME})
# Note that because of OutOfSourceBuild, binary_dir and source_dir must be different.
set(LANGLIST)
-if(WITH_LIB_CXX)
+if(USE_CXX)
set(LANGLIST ${LANGLIST} C CXX)
endif()
+
if(USE_FORTRAN)
set(LANGLIST ${LANGLIST} Fortran)
endif()
+
include(HysopVersion)
project(${PROJECT_NAME} ${LANGLIST})
@@ -154,7 +148,7 @@ if(USE_MPI)
endif()
# --- Wheel, required for a proper build/install process ---
find_python_module(wheel REQUIRED)
-if(WITH_LIB_CXX)
+if(USE_CXX)
find_package(SWIG 3.0.2 REQUIRED)
# WARNING FP : for cmake < 3.0 UseSWIG.cmake
# does not work properly (bug for swig outdir)
@@ -165,7 +159,7 @@ if(WITH_LIB_CXX)
endif()
# Find python build dir name --> needed for tests and doc
-if(WITH_COMPILED_LIB)
+if(USE_CXX OR USE_FORTRAN)
execute_process(
COMMAND ${PYTHON_EXECUTABLE} -c "import distutils.util as ut ; import distutils.sysconfig as sy; print 'lib.'+ut.get_platform()+'-'+sy.get_python_version()"
OUTPUT_VARIABLE ${PROJECT_NAME}_PYTHON_BUILD_DIR)
@@ -179,16 +173,21 @@ endif()
# --- FFTW ---
if(WITH_FFTW)
- set(FIND_FFTW_VERBOSE VERBOSE_MODE)
- set(FIND_FFTW_DEBUG ON)
+ #set(FIND_FFTW_VERBOSE VERBOSE_MODE)
+ set(FIND_FFTW_VERBOSE OFF)
+ set(FIND_FFTW_DEBUG OFF)
compile_with(FFTW
- REQUIRED COMPONENTS Fftw3d Fftw3f Fftw3d-mpi Fftw3f-mpi
- OPTIONAL_COMPONENTS Fftw3l Fftw3l-mpi Fftw3q)
+ REQUIRED COMPONENTS Fftw3f Fftw3d
+ Fftw3f-mpi Fftw3d-mpi
+ OPTIONAL_COMPONENTS
+ Fftw3f-threads Fftw3d-threads
+ Fftw3l Fftw3l-mpi Fftw3l-threads
+ Fftw3q Fftw3q-threads)
set(dirlist)
foreach(_file ${FFTW_LIBRARIES})
get_filename_component(_name ${_file} DIRECTORY)
- list(FIND dirlist ${_name} isin)
+ list(FIND dirlist "${_name}" isin)
if(isin EQUAL -1)
list(APPEND dirlist ${_name})
endif()
@@ -197,9 +196,22 @@ if(WITH_FFTW)
add_definitions(${FFTW_DEFINES})
endif()
+if(USE_CXX)
+ compile_with(Boost REQUIRED)
+endif()
+
if(WITH_EXTRAS)
# Arnoldi solver needs zgeev, which means lapack
compile_with(LAPACK)
+ foreach(_file ${LAPACK_LIBRARY})
+ get_filename_component(_name ${_file} DIRECTORY)
+ list(FIND dirlist ${_name} isin)
+ if(isin EQUAL -1)
+ list(APPEND dirlist ${_name})
+ endif()
+ endforeach()
+ set(EXTRASLIB ${dirlist} CACHE PATH "extras libraries dir")
+
endif()
# ========= Check which opencl devices are available on the system =========
@@ -255,6 +267,7 @@ set_directory_properties(PROPERTIES ADDITIONAL_MAKE_CLEAN_FILES ${CMAKE_BINARY_D
set(PYTHON_SETUP "${CMAKE_CURRENT_BINARY_DIR}/setup.py")
if(USE_FORTRAN)
+ # if fortran is enabled, explicit setup of the compiler is required.
add_custom_target(wheel ALL
COMMAND ${PYTHON_EXECUTABLE} ${CMAKE_CURRENT_BINARY_DIR}/setup.py bdist_wheel build config_fc --f90exec=${CMAKE_Fortran_COMPILER}#-d ${CMAKE_BINARY_DIR}/wheel/
COMMENT "create wheel file for ${PACKAGE_NAME} package"
@@ -276,17 +289,74 @@ include(HySoPInstallSetup)
# Remark : this must be done before add_subdir below, since install process in src needs CMAKE_INSTALL_PREFIX
# to be properly set.
+# # ============= Extra setup =============
+# set precision for real numbers
+# used to generate precision.f95 file/module and constant.py
+if(DOUBLEPREC)
+ # -- Variables required in fortran files --
+ set(WORKING_PRECISION dp)
+ set(MPI_PRECISION MPI_DOUBLE_PRECISION)
+ # -- Variables required in python files --
+ set(PYTHON_PREC np.float64)
+ set(MPI_PYTHON_PREC MPI.DOUBLE)
+ # -- f2py stuff --
+ set(f2pymap_for_real double)
+else()
+ set(WORKING_PRECISION sp)
+ set(MPI_PRECISION MPI_FLOAT)
+ set(PYTHON_PREC np.float32)
+ set(MPI_PYTHON_PREC MPI.FLOAT)
+ set(f2pymap_for_real float)
+endif()
+
+# set data layout ('fortran' order or 'C' order) in python (numpy).
+if(FORTRAN_LAYOUT)
+ set(DATA_LAYOUT 'F')
+ set(MPI_DATA_LAYOUT MPI.ORDER_F)
+else()
+ set(DATA_LAYOUT 'C')
+ set(MPI_DATA_LAYOUT MPI.ORDER_C)
+endif()
+if(EXISTS ${CMAKE_SOURCE_DIR}/${PACKAGE_NAME}/constants.py.in)
+ message(STATUS "Generate constant.py file ...")
+ configure_file(${CMAKE_SOURCE_DIR}/${PACKAGE_NAME}/constants.py.in
+ ${CMAKE_SOURCE_DIR}/${PACKAGE_NAME}/constants.py)
+endif()
+
+
if(USE_FORTRAN)
- if(EXISTS ${CMAKE_SOURCE_DIR}/${PACKAGE_NAME}/.f2py_f2cmap)
+
+ # Path to fortran-related generated files (.pyf, precision ...)
+ set(GENERATED_FORTRAN_FILES_DIR ${CMAKE_BINARY_DIR}/generated_fortran/)
+
+
+ # --- copy sort_f90 file to build ---
+ # Required for setup.py to handle fortran files dependencies
+ configure_file(${CMAKE_SOURCE_DIR}/sort_f90.py ${CMAKE_BINARY_DIR}/sort_f90.py)
+
+ # --- Generate f2py_f2cmap file ---
+ if(EXISTS ${CMAKE_SOURCE_DIR}/f2py_f2cmap.in)
message(STATUS "Generate f2py map file ...")
- configure_file(${CMAKE_SOURCE_DIR}/${PACKAGE_NAME}/.f2py_f2cmap
+ configure_file(${CMAKE_SOURCE_DIR}/f2py_f2cmap.in
${CMAKE_BINARY_DIR}/.f2py_f2cmap)
endif()
+
+ # --- Create top-level pyf file ---
+ # -> depends on cmake config. This file
+ # includes the other required pyf files.
+ # For example, if WITH_FFTW is ON, then
+ # add a line 'include fftw2py.py'
+ set(F_2_HYSOP "f2hysop")
include(fortran_utils)
- # Create f2hysop.pyf file
- write_main_pyf_file(f2hysop)
+ write_main_pyf_file(${F_2_HYSOP})
+ # f2py failed with:
+ # real(kind=wp), dimension(:) :: tab
+ # whit wp = real64 or real32 from iso_fortran_env
+ # a const parameter defined in another module
+ # AND tab is an assumed shaped array, even when using a f2py_f2cmap file.
+ # The solution is to set directly real(kind=8) in pyf file.
- # ====== Create non-python (fortran) libraries (fftw and scales interfaces), if required =====
+ # --- fortran libraries setup ---
# Set module files directory (i.e. where .mod will be created)
set(CMAKE_Fortran_MODULE_DIRECTORY ${CMAKE_BINARY_DIR}/Modules)
@@ -304,34 +374,53 @@ if(USE_FORTRAN)
list(APPEND HYSOP_LINK_LIBRARIES ${MPI_Fortran_LIBRARIES} )
endif(USE_MPI)
- #set(Fortran_FLAGS ${CMAKE_Fortran_FLAGS})
- #append_flags(Fortran_FLAGS ${CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE}})
+ set(Fortran_FLAGS ${CMAKE_Fortran_FLAGS})
+ append_flags(Fortran_FLAGS ${CMAKE_Fortran_FLAGS_${CMAKE_BUILD_TYPE}})
+ # --- Generate precision.f95 and precision.pyf files ---
+ if(EXISTS ${CMAKE_SOURCE_DIR}/precision.conf.in)
+ message(STATUS "Generate precision.f95 file ...")
+ configure_file(${CMAKE_SOURCE_DIR}/precision.conf.in
+ ${GENERATED_FORTRAN_FILES_DIR}/precision.f95)
+ configure_file(${CMAKE_SOURCE_DIR}/precision.conf.in
+ ${GENERATED_FORTRAN_FILES_DIR}/precision.pyf)
+ endif()
endif()
-if(WITH_COMPILED_LIB)
+if(USE_FORTRAN)
add_subdirectory(src)
- #get_directory_property(FORTRAN_INCLUDE_DIRS
- #DIRECTORY ${CMAKE_SOURCE_DIR}/src
- #DEFINITION FORTRAN_INCLUDE_DIRS)
-endif()
-
-if(WITH_LIB_CXX)
- #C++ variables used by setup.py.in for swig
- set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -W -Wall -Wextra -Wno-unused-variable -Wno-unused-but-set-variable -Wno-unused-parameter ${FFTW_COMPILE_FLAGS} -fPIC -std=c++11")
- set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
- set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "${CMAKE_CXX_FLAGS_RELWITHDEBINFO}")
- set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}")
- set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS}")
-
- set(CXX_FLAGS "${CMAKE_CXX_FLAGS}")
- set(CXX_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS}")
- set(CXX_EXT_INCLUDES ${PYTHON_INCLUDE_DIR} ${FFTW_INCLUDE_DIRS})
- set(CXX_EXT_LIBS ${PYTHON_LIBRARIES} ${FFTW_LIBRARIES})
- set(CXX_EXT_LIB_DIRS ${FFTW_LIBRARY_DIRS})
- set(CXX_EXTRA_DEFINES ${FFTW_DEFINES} -DHAS_EXTERN_TEMPLATES)
+ set(FORTRAN_INCLUDE_DIRS ${FFTW_INCLUDE_DIRS})
+endif()
- #swig package name (lib name generated by swig)
- set(CPP_2_HYSOP "cpp2hysop")
+if(USE_CXX)
+ #C++ variables used by setup.py.in for swig
+ if(DEV_MODE)
+ if ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
+ set(CXX_WARNING_FLAGS "-W -Wall -Wextra -Wno-unused-variable -Wno-unused-parameter -Wno-unused-local-typedefs -Wno-missing-braces")
+ elseif ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "GNU")
+ set(CXX_WARNING_FLAGS "-W -Wall -Wextra -Wno-unused-variable -Wno-unused-but-set-variable -Wno-unused-parameter -Wno-unused-local-typedefs -Wno-deprecated-declarations")
+ #elseif ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "Intel")
+ #elseif ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "MSVC")
+ else()
+ set(CXX_WARNING_FLAGS "")
+ endif()
+ endif()
+
+ list(APPEND CMAKE_CXX_FLAGS "${CXX_WARNING_FLAGS} ${FFTW_COMPILE_FLAGS} -fPIC -std=c++11")
+ list(APPEND CMAKE_EXE_LINKER_FLAGS "-Wl,--no-as-needed -ldl -lutil")
+
+ set(CXX_FLAGS ${CMAKE_CXX_FLAGS})
+ set(CXX_LINKER_FLAGS ${CMAKE_EXE_LINKER_FLAGS})
+ set(CXX_EXTRA_DEFINES ${FFTW_DEFINES} "-DHAS_EXTERN_TEMPLATES")
+
+ set(CXX_EXT_INCLUDES ${Boost_INCLUDE_DIR} ${PYTHON_INCLUDE_DIR} ${FFTW_INCLUDE_DIRS})
+ set(CXX_EXT_LIBS ${Boost_LIBRARIES} ${PYTHON_LIBRARIES} ${FFTW_LIBRARIES})
+ set(CXX_EXT_LIB_DIR ${Boost_LIBRARY_DIRS} ${PYTHON_LIBRARY_DIRS} ${FFTW_LIBRARY_DIRS})
+
+ set(CMAKE_INCLUDE_SYSTEM_FLAG_C "-isystem ")
+ set(CMAKE_INCLUDE_SYSTEM_FLAG_CXX "-isystem ")
+
+ #swig package name (lib name generated by swig)
+ set(CPP_2_HYSOP "cpp2hysop")
endif()
# ====== Generates python files required for build/install process ======
@@ -351,12 +440,12 @@ endif()
if(EXISTS ${CMAKE_SOURCE_DIR}/hysop/mpi/__init__.py.in)
message(STATUS "Generate mpi/__init__.py file ...")
file(REMOVE ${CMAKE_SOURCE_DIR}/hysop/mpi/__init__.py)
- configure_file(hysop/mpi/__init__.py.in ${CMAKE_SOURCE_DIR}/hysop/mpi/__init__.py)
+configure_file(hysop/mpi/__init__.py.in ${CMAKE_SOURCE_DIR}/hysop/mpi/__init__.py)
endif()
# Hysop C++ library is generated in setup.py by swig
# --- C++ main and tests ---
-if(WITH_LIB_CXX)
+if(USE_CXX)
get_filename_component(CXX_DIR "${CMAKE_SOURCE_DIR}/src/hysop++" ABSOLUTE)
get_filename_component(CXX_MAIN_DIR "${CXX_DIR}/main" ABSOLUTE)
@@ -382,7 +471,7 @@ if(WITH_LIB_CXX)
set(HYSOP_CXX_LIBRARY_BUNDLE "${CMAKE_CURRENT_BINARY_DIR}/libcpp2hysop_bundle.so")
add_custom_target(cpp2hysop_bundle
DEPENDS wheel
- COMMAND cp `find ${CMAKE_CURRENT_BINARY_DIR}/build -name _${CPP_2_HYSOP}.so` ${HYSOP_CXX_LIBRARY_BUNDLE}
+ COMMAND cp `find ${CMAKE_CURRENT_BINARY_DIR}/build -name ${CPP_2_HYSOP}.so` ${HYSOP_CXX_LIBRARY_BUNDLE}
WORKING_DIRECTORY "${CMAKE_CURRENT_BINARY_DIR}"
COMMENT "Copy swig c++ library to link")
set(HYSOP_CXX_LIBRARY ${HYSOP_CXX_LIBRARY_BUNDLE})
@@ -484,7 +573,7 @@ if(WITH_TESTS)
if(NOT USE_MPI)
set(WITH_MPI_TESTS "OFF")
endif()
- include(HySoPTests)
+ include(hysop_tests)
endif(WITH_TESTS)
# ============= Documentation setup =============
@@ -505,12 +594,12 @@ if(VERBOSE_MODE)
if(USE_FORTRAN)
message(STATUS " Fortran compiler : ${CMAKE_Fortran_COMPILER}")
else()
- message(WARNING "You deactivate libhysop (fortran) generation. This will disable the fortran interface, including fftw and scales fonctionnalities.")
+ message(WARNING "You deactivate fortran to python interface generation. This will disable the fortran interface, including fftw and scales fonctionnalities.")
endif()
- if(WITH_LIB_CXX)
+ if(USE_CXX)
message(STATUS " CXX compiler : ${CMAKE_CXX_COMPILER}")
else()
- message(WARNING "You deactivate libhysop (cxx) generation. This will disable the Aitken-Schwarz Poisson solver.")
+ message(WARNING "You deactivate c++ to python interface generation. This will disable the Aitken-Schwarz Poisson solver.")
endif()
message(STATUS " Sources are in : ${CMAKE_SOURCE_DIR}")
message(STATUS " Project uses MPI : ${USE_MPI}")
@@ -520,6 +609,11 @@ if(VERBOSE_MODE)
message(STATUS " ${PROJECT_NAME} profile mode : ${PROFILE}")
message(STATUS " ${PROJECT_NAME} debug mode : ${DEBUG}")
message(STATUS " Enable -OO run? : ${OPTIM}")
+ if(DOUBLEPREC)
+ message(STATUS " Real numbers precision : double.")
+ else()
+ message(STATUS " Real numbers precision : simple.")
+ endif()
message(STATUS "====================== ======= ======================")
message(STATUS " ")
message(STATUS "Try :")
@@ -531,5 +625,5 @@ if(VERBOSE_MODE)
message(STATUS " 'make uninstall' to clean install directory. Dry-run (make -n uninstall) is advisable to check what will really be deleted.")
message(STATUS "\n\n/!\\ Warning /!\\ : depending on your python environment configuration, you may need to set PYTHONPATH.")
message("Try to run python -c 'import hysop'. If it fails, add ${HYSOP_PYTHON_INSTALL_DIR} to PYTHONPATH environment variable.")
- message("Example : \n export PYTHONPATH=${HYSOP_PYTHON_INSTALL_DIR}:\${PYTHONPATH}\n")
+ message("Example : \n export PYTHONPATH=${HYSOP_PYTHON_INSTALL_DIR}/:\${PYTHONPATH}\n")
endif()
diff --git a/ci/config.sh b/ci/config.sh
index 5605ed2e1e0b4f2a9be0d1554af8140a9cdc3095..fd983559c56973578bda07dfe710dd198f8b9fdd 100644
--- a/ci/config.sh
+++ b/ci/config.sh
@@ -2,4 +2,4 @@
mkdir build
cd build
export FC=mpif90 CC=mpicc CXX=mpic++ F77=mpif90
-cmake -DCMAKE_BUILD_TYPE=Debug -DWITH_LIB_CXX=OFF ..
+cmake -DCMAKE_BUILD_TYPE=Debug -DUSE_CXX=OFF ..
diff --git a/ci/run_tests.sh b/ci/run_tests.sh
index f60cd72261aafdb06567fca7e78a79cdee041964..fc5e1a792093993de07e64f5c5a8e850416e487e 100644
--- a/ci/run_tests.sh
+++ b/ci/run_tests.sh
@@ -2,6 +2,6 @@
mkdir build
cd build
export FC=mpif90 CC=mpicc CXX=mpic++
-cmake -D CMAKE_BUILD_TYPE=Debug -DWITH_LIB_CXX=OFF ..
+cmake -D CMAKE_BUILD_TYPE=Debug -DUSE_CXX=OFF ..
make
make test
diff --git a/cmake/FindFFTW.cmake b/cmake/FindFFTW.cmake
index ed244493e5ade01e0f708009fa0dd6a48b18b18b..15bca50d3bd1ed1c893974f91bc28dd0da96065f 100644
--- a/cmake/FindFFTW.cmake
+++ b/cmake/FindFFTW.cmake
@@ -26,23 +26,23 @@
# == Defined variables ==
#
# FFTW_FOUND - will be set to true if and only if all required components and their dependencies were found
-# FFTW_INCLUDE_DIRS - all FFTW include directories
-# FFTW_LIBRARY_DIRS - all FFTW library directories
-# FFTW_LIBRARIES - all FFTW libraries
-# FFTW_DEFINES - all FFTW defines
+# FFTW_INCLUDE_DIRS - all FFTW include directories
+# FFTW_LIBRARY_DIRS - all FFTW library directories
+# FFTW_LIBRARIES - all FFTW libraries
+# FFTW_DEFINES - all FFTW defines
# FTTW_COMPILE_FLAGS - all FFTW compile flags (currently only used for quadfloat fftw)
#
# For each required or optional component, this package defines:
# COMPONENT_FOUND - will be set to true the component and its dependencies were found, else false
# COMPONENT_DEFINES - all COMPONENT defines (-DFFTW_HAS_COMPONENT)
#
-# COMPONENT_INCLUDE_DIRS - COMPONENT and its dependancies include directories
-# COMPONENT_LIBRARY_DIRS - COMPONENT and its dependancies library directories
-# COMPONENT_LIBRARIES - COMPONENT and its dependancies libraries
+# COMPONENT_INCLUDE_DIRS - COMPONENT and its dependencies include directories
+# COMPONENT_LIBRARY_DIRS - COMPONENT and its dependencies library directories
+# COMPONENT_LIBRARIES - COMPONENT and its dependencies libraries
#
-# COMPONENT_INCLUDE_DIR - COMPONENT include directory
-# COMPONENT_LIBRARY_DIR - COMPONENT library directory
-# COMPONENT_LIBRARY - COMPONENT library
+# COMPONENT_INCLUDE_DIR - COMPONENT include directory
+# COMPONENT_LIBRARY_DIR - COMPONENT library directory
+# COMPONENT_LIBRARY - COMPONENT library
#
# where COMPONENT is equal to <input component name> transformed with the following rules:
# * uppercased
@@ -71,6 +71,13 @@ set(FFTW_VERSION_STRING ${FFTW_FIND_VERSION})
if(FIND_FFTW_VERBOSE)
message(STATUS "Entering FindFFTW.cmake in verbose mode:")
endif()
+
+# -- initialize empty lists
+list(APPEND FFTW_INCLUDE_DIRS "")
+list(APPEND FFTW_LIBRARY_DIRS "")
+list(APPEND FFTW_LIBRARIES "")
+list(APPEND FFTW_DEFINES "")
+list(APPEND FFTW_COMPILE_FLAGS "")
foreach(fftw_comp ${FFTW_FIND_COMPONENTS})
string(REPLACE "-" "_" fftw_comp_no_dash "${fftw_comp}")
@@ -81,6 +88,7 @@ foreach(fftw_comp ${FFTW_FIND_COMPONENTS})
if(${COMPONENT}_FOUND)
continue()
endif()
+
# -- find header name given the component name
string(REGEX REPLACE "_(omp|threads)" "" component_without_ext "${component}")
@@ -165,26 +173,30 @@ foreach(fftw_comp ${FFTW_FIND_COMPONENTS})
endif()
# -- find quadmath library if required
+ # -- only gcc >= 4.6 supports quadmaths
string(FIND ${component} "fftw3q" FFTWQ_POS)
if(FFTWQ_POS EQUAL 0)
- if(NOT "${CMAKE_CXX_COMPILER_ID}" STREQUAL "GNU")
- set(DEPENDENCIES_FOUND FALSE) # -- only gcc supports quadmaths
- else()
- find_library(QUADMATHLIB
+ if ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 4.5 )
+ find_library(QUADMATH_LIBRARY
NAMES quadmath
PATHS ENV LIBRARY_PATH
ENV LD_LIBRARY_PATH
- ENV DYLD_LIBRARY_PATH)
- if(${QUADMATHLIB} STREQUAL "QUADMATHLIB-NOTFOUND")
- set(DEPENDENCIES_FOUND FALSE)
- else()
- list(APPEND ${COMPONENT}_LIBRARIES ${QUADMATHLIB})
- list(APPEND ${COMPONENT}_DEFINES "-DHAS_QUADMATHS")
- list(APPEND FFTW_COMPILE_FLAGS "-fext-numeric-literals")
- set(DEPENDENCIES_FOUND TRUE)
- endif()
- endif()
- else()
+ ENV DYLD_LIBRARY_PATH
+ /usr/lib/x86_64-linux-gnu/
+ )
+
+ if(QUADMATH_LIBRARY STREQUAL "QUADMATH_LIBRARY-NOTFOUND")
+ set(DEPENDENCIES_FOUND FALSE)
+ else()
+ list(APPEND ${COMPONENT}_LIBRARIES "${QUADMATH_LIBRARY}")
+ list(APPEND ${COMPONENT}_DEFINES "-DHAS_QUADMATHS")
+ list(APPEND ${COMPONENT}_COMPILE_FLAGS "-fext-numeric-literals")
+ set(DEPENDENCIES_FOUND TRUE)
+ endif()
+ else()
+ set(DEPENDENCIES_FOUND FALSE)
+ endif()
+ else()
set(DEPENDENCIES_FOUND TRUE)
endif()
@@ -194,12 +206,13 @@ foreach(fftw_comp ${FFTW_FIND_COMPONENTS})
list(APPEND ${COMPONENT}_LIBRARY_DIRS ${${COMPONENT}_LIBRARY_DIR})
list(APPEND ${COMPONENT}_LIBRARIES ${${COMPONENT}_LIBRARY})
list(APPEND ${COMPONENT}_DEFINES "-DFFTW_HAS_${COMPONENT}")
-
- list(APPEND FFTW_INCLUDE_DIRS ${${COMPONENT}_INCLUDE_DIRS})
- list(APPEND FFTW_LIBRARY_DIRS ${${COMPONENT}_LIBRARY_DIRS})
- list(APPEND FFTW_LIBRARIES ${${COMPONENT}_LIBRARIES})
- list(APPEND FFTW_DEFINES ${${COMPONENT}_DEFINES})
-
+
+ list(APPEND FFTW_INCLUDE_DIRS ${${COMPONENT}_INCLUDE_DIRS})
+ list(APPEND FFTW_LIBRARY_DIRS ${${COMPONENT}_LIBRARY_DIRS})
+ list(APPEND FFTW_LIBRARIES ${${COMPONENT}_LIBRARIES})
+ list(APPEND FFTW_DEFINES ${${COMPONENT}_DEFINES})
+ list(APPEND FFTW_COMPILE_FLAGS ${${COMPONENT}_COMPILE_FLAGS})
+
if(FIND_FFTW_VERBOSE)
message("\tFound FFTW::${fftw_comp} with parameters '-I${${COMPONENT}_INCLUDE_DIR} -L${${COMPONENT}_LIBRARY_DIR} -l${${COMPONENT}_LIBRARY}'.")
endif()
@@ -226,9 +239,12 @@ foreach(fftw_comp ${FFTW_FIND_COMPONENTS})
unset(component)
unset(COMPONENT)
endforeach()
+
list(REMOVE_DUPLICATES FFTW_INCLUDE_DIRS)
list(REMOVE_DUPLICATES FFTW_LIBRARY_DIRS)
list(REMOVE_DUPLICATES FFTW_LIBRARIES)
+list(REMOVE_DUPLICATES FFTW_DEFINES)
+list(REMOVE_DUPLICATES FFTW_COMPILE_FLAGS)
# -- check required variables, version and set FFTW_FOUND to TRUE if ok
find_package_handle_standard_args(FFTW FOUND_VAR FFTW_FOUND
diff --git a/cmake/HySoPInstallSetup.cmake b/cmake/HySoPInstallSetup.cmake
index 537bea581b6bef0c7d1f33dae010278e951fe022..a21e4a94f82cfaaf3a9db2535b832c79dde2f76f 100755
--- a/cmake/HySoPInstallSetup.cmake
+++ b/cmake/HySoPInstallSetup.cmake
@@ -67,7 +67,6 @@ else()
COMMENT "build/install hysop package")
add_custom_target(uninstall
echo >> ${CMAKE_CURRENT_BINARY_DIR}/install_manifest.txt
- #COMMAND cat ${CMAKE_CURRENT_BINARY_DIR}/python_install_manifest.txt >> ${CMAKE_CURRENT_BINARY_DIR}/install_manifest.txt
COMMAND pip uninstall ${PACKAGE_NAME}
COMMAND ${CMAKE_COMMAND} -P ${CMAKE_CURRENT_BINARY_DIR}/cmake_uninstall.cmake)
endif()
diff --git a/cmake/PythonInstallSetup.cmake b/cmake/PythonInstallSetup.cmake
index 313f0b88f2d152e648db0a96f7839584c883ca94..c7b1ec86ce6b1e521c00b0ee254189ecdcc3f5ba 100755
--- a/cmake/PythonInstallSetup.cmake
+++ b/cmake/PythonInstallSetup.cmake
@@ -78,9 +78,9 @@ function(set_python_install_path)
# "import site; print(site.getsitepackages()[0])")
# --> this does not work properly: the order in resulting
# list depends on the OS, the python version ...
- configure_file(CMake/fake/setup.py tmp/setup.py)
- configure_file(CMake/fake/__init__.py tmp/fake/__init__.py)
- configure_file(CMake/find_python_install.py tmp/find_python_install.py)
+ configure_file(cmake/fake/setup.py tmp/setup.py)
+ configure_file(cmake/fake/__init__.py tmp/fake/__init__.py)
+ configure_file(cmake/find_python_install.py tmp/find_python_install.py)
execute_process(
COMMAND ${PYTHON_EXECUTABLE} find_python_install.py
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/tmp/
diff --git a/cmake/fortran_utils.cmake b/cmake/fortran_utils.cmake
index 79c56db9b7d9bd60d0d8a29c5724e4e43f4f4247..a86bb87cf00020013105bd6f24c4ff5ad026fab5 100644
--- a/cmake/fortran_utils.cmake
+++ b/cmake/fortran_utils.cmake
@@ -15,38 +15,42 @@
# --> create f2hysop.pyf that will be used to generate hysop.f2hysop module.
#
function(write_main_pyf_file filename)
- set(_file ${CMAKE_SOURCE_DIR}/${PACKAGE_NAME}/${filename}.pyf)
+
+ # First writes filename.pyf.in, according to cmake current config
+ # and then generate filename.pyf.
+ set(_file ${GENERATED_FORTRAN_FILES_DIR}/${filename}.pyf.in)
file(WRITE ${_file}
"! -*- f90 -*-\n
! Generated file - Do not edit.\n
! Note: the context of this file is case sensitive.\n
-python module f2hysop ! in\n
+python module ${F_2_HYSOP} ! in\n
interface\n")
file(APPEND ${_file}
" ! Example
- include '@CMAKE_SOURCE_DIR@/hysop/fortran/template.pyf'\n")
- file(APPEND ${_file}
- " ! precision
- include '@CMAKE_SOURCE_DIR@/hysop/f2py/parameters.pyf'\n")
- if(WITH_FFTW)
- file(APPEND ${_file}
+ include '@GENERATED_FORTRAN_FILES_DIR@/precision.pyf'\n")
+ file(APPEND ${_file}
+ " ! Example
+ include '@CMAKE_SOURCE_DIR@/hysop/common_f/template.pyf'\n")
+ if(WITH_FFTW)
+ file(APPEND ${_file}
" ! fftw
- include '@CMAKE_SOURCE_DIR@/hysop/f2py/fftw2py.pyf'\n")
+ include '@CMAKE_SOURCE_DIR@/hysop/numerics/fftw_f/fftw2py.pyf'\n")
endif()
if(WITH_SCALES)
file(APPEND ${_file}
" ! scales
- include '@CMAKE_SOURCE_DIR@/hysop/f2py/scales2py.pyf'\n")
+ include '@CMAKE_SOURCE_DIR@/hysop/scales_f/scales2py.pyf'\n")
endif()
if(WITH_EXTRAS)
file(APPEND ${_file}
" ! arnoldi
- include '@CMAKE_SOURCE_DIR@/hysop/fortran/arnoldi2py.pyf'\n")
+ include '@CMAKE_SOURCE_DIR@/hysop/numerics/extras_f/arnoldi.pyf'\n")
endif()
file(APPEND ${_file} " end interface\n
-end python module f2hysop")
+end python module ${F_2_HYSOP}")
-message(STATUS "Generate pyf file ...")
-configure_file(${_file} ${CMAKE_SOURCE_DIR}/${PACKAGE_NAME}/${filename}.pyf @ONLY)
+message(STATUS "Generate ${F_2_HYSOP}.pyf file ...")
+configure_file(${_file} ${GENERATED_FORTRAN_FILES_DIR}/${filename}.pyf @ONLY)
endfunction()
+
diff --git a/cmake/HySoPTests.cmake b/cmake/hysop_tests.cmake
similarity index 84%
rename from cmake/HySoPTests.cmake
rename to cmake/hysop_tests.cmake
index bf9948b98835380afc4f2e231d62c8e5fe77aef1..b32777bcaa0d58499bda318ecc272a82f8dbecfa 100755
--- a/cmake/HySoPTests.cmake
+++ b/cmake/hysop_tests.cmake
@@ -55,33 +55,32 @@ endif()
# === Set the list of all directories which may contain tests ===
set(py_src_dirs
+ core
+ backend
fields
domain
operator
numerics
- problem
tools
- mpi
)
# If GPU is on, we add test_XXX.py files of hysop/gpu directory
-if(WITH_GPU)
- list(APPEND py_src_dirs gpu)
-endif()
+#if(WITH_GPU)
+#endif()
# Copy the OpenCL sources files to build dir (required since only python files are copied by setup.py)
-set(clfiles)
-file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/[a-z]*.cl)
-set(clfiles ${clfiles} ${clfilestmp})
-file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/kernels/[a-z]*.cl)
-set(clfiles ${clfiles} ${clfilestmp})
-file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/advection/[a-z]*.cl)
-set(clfiles ${clfiles} ${clfilestmp})
-file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/remeshing/[a-z]*.cl)
-set(clfiles ${clfiles} ${clfilestmp})
-foreach(_F ${clfiles})
- configure_file(${_F} ${testDir}/${_F} COPYONLY)
-endforeach()
+#set(clfiles)
+#file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/[a-z]*.cl)
+#set(clfiles ${clfiles} ${clfilestmp})
+#file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/kernels/[a-z]*.cl)
+#set(clfiles ${clfiles} ${clfilestmp})
+#file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/advection/[a-z]*.cl)
+#set(clfiles ${clfiles} ${clfilestmp})
+#file(GLOB clfilestmp RELATIVE ${CMAKE_SOURCE_DIR} hysop/gpu/cl_src/remeshing/[a-z]*.cl)
+#set(clfiles ${clfiles} ${clfilestmp})
+#foreach(_F ${clfiles})
+ #configure_file(${_F} ${testDir}/${_F} COPYONLY)
+#endforeach()
# === Create the files list from all directories in py_src_dirs ===
@@ -101,7 +100,7 @@ endforeach()
# Doctest are run for every line which contains '>>>'
set(py_doctest_files)
foreach(testdir ${py_src_dirs})
- file(GLOB testfiles hysop/${testdir}/[a-zA-Z]*.py)
+ file(GLOB testfiles RELATIVE ${CMAKE_SOURCE_DIR} hysop/${testdir}/[a-zA-Z]*.py)
foreach(testfile ${testfiles})
file(STRINGS ${testfile} test_doctest REGEX ">>>")
if(NOT "${test_doctest}" STREQUAL "")
@@ -110,6 +109,7 @@ foreach(testdir ${py_src_dirs})
endforeach()
endforeach()
+
# === Create tests from py_test_files ===
foreach(testfile ${py_test_files})
get_filename_component(testName ${testfile} NAME_WE)
@@ -121,6 +121,7 @@ endforeach()
# Add files containing doctests
foreach(testfile ${py_doctest_files})
get_filename_component(testName ${testfile} NAME_WE)
- add_test("doctest_${testName}" py.test -v --doctest-modules ${testfile})
+ set(exename ${testDir}/${testfile})
+ add_test("doctest_${testName}" py.test -v --doctest-modules ${exename})
endforeach()
diff --git a/docs/CMakeLists.txt b/docs/CMakeLists.txt
index 26ba1cf23db6bebdd9bc7160535b4defbcad4ffb..97febbed0fda483e3b61ab5de6ba1dbb72f1eca6 100644
--- a/docs/CMakeLists.txt
+++ b/docs/CMakeLists.txt
@@ -14,12 +14,11 @@ if(WITH_DOCUMENTATION)
# --------------------- Doxygen setup ---------------------
find_package(Doxygen)
- find_file(DOXY name doxypy.py PATH ENV{PATH})
- if(DOXY-NOTFOUND)
- message(STATUS "Warning, doxypy seems to be missing on your system. You may not be able to properly generate the documentation.")
- endif()
+
# Output path for doxygen documentation
- set(DOXYGEN_OUTPUT ${DOC_ROOT_DIR}/doxygen)
+ if(NOT DOXYGEN_OUTPUT)
+ set(DOXYGEN_OUTPUT ${DOC_ROOT_DIR}/doxygen)
+ endif()
# doxygen tags are required for doxygen-sphinx link.
file(MAKE_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/build/tags)
file(MAKE_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/build/html)
@@ -43,7 +42,7 @@ if(WITH_DOCUMENTATION)
set(GENERATE_HTML YES)
set(GENERATE_XML YES)
- configure_file(${CMAKE_CURRENT_SOURCE_DIR}/config/hysop.doxyfile.in ${CMAKE_CURRENT_BINARY_DIR}/config/hysop.doxyfile)
+ configure_file(${CMAKE_CURRENT_SOURCE_DIR}/config/hysop.doxyfile.in ${DOXY_CONFIG})
# create a target to build doxygen documentation
# i.e. to run 'make doxygen'
@@ -149,4 +148,4 @@ if(WITH_DOCUMENTATION)
# add_dependencies(html doxygen)
# add_dependencies(html apidoc)
-endif()
\ No newline at end of file
+endif()
diff --git a/docs/config/hysop.doxyfile.in b/docs/config/hysop.doxyfile.in
index 78907963763fed73166db0e9e9b68f613fa52774..db08da3edde2751ff9b746d4988f570d7da9974f 100644
--- a/docs/config/hysop.doxyfile.in
+++ b/docs/config/hysop.doxyfile.in
@@ -1,11 +1,11 @@
-# Doxyfile 1.8.5
+# Doxyfile 1.8.11
# This file describes the settings to be used by the documentation system
# doxygen (www.doxygen.org) for a project.
-#
+#
# All text after a double hash (##) is considered a comment and is placed in
# front of the TAG it is preceding.
-#
+#
# All text after a single hash (#) is considered a comment and will be ignored.
# The format is:
# TAG = value [value, ...]
@@ -46,21 +46,21 @@ PROJECT_NUMBER = @PACKAGE_VERSION@
PROJECT_BRIEF = "Particle Methods simulation on hybrid architectures"
-# With the PROJECT_LOGO tag one can specify an logo or icon that is included in
-# the documentation. The maximum height of the logo should not exceed 55 pixels
-# and the maximum width should not exceed 200 pixels. Doxygen will copy the logo
-# to the output directory.
+# With the PROJECT_LOGO tag one can specify a logo or an icon that is included
+# in the documentation. The maximum height of the logo should not exceed 55
+# pixels and the maximum width should not exceed 200 pixels. Doxygen will copy
+# the logo to the output directory.
-PROJECT_LOGO =
+PROJECT_LOGO = @CMAKE_CURRENT_SOURCE_DIR@/sphinx/figures/logo_hysop_nb.png
# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute) path
# into which the generated documentation will be written. If a relative path is
# entered, it will be relative to the location where doxygen was started. If
# left blank the current directory will be used.
-OUTPUT_DIRECTORY = @CMAKE_BINARY_DIR@/DoxygenGeneratedDoc
+OUTPUT_DIRECTORY = @DOXYGEN_OUTPUT@
-# If the CREATE_SUBDIRS tag is set to YES, then doxygen will create 4096 sub-
+# If the CREATE_SUBDIRS tag is set to YES then doxygen will create 4096 sub-
# directories (in 2 levels) under the output directory of each output format and
# will distribute the generated files over these directories. Enabling this
# option can be useful when feeding doxygen a huge amount of source files, where
@@ -70,29 +70,39 @@ OUTPUT_DIRECTORY = @CMAKE_BINARY_DIR@/DoxygenGeneratedDoc
CREATE_SUBDIRS = YES
+# If the ALLOW_UNICODE_NAMES tag is set to YES, doxygen will allow non-ASCII
+# characters to appear in the names of generated files. If set to NO, non-ASCII
+# characters will be escaped, for example _xE3_x81_x84 will be used for Unicode
+# U+3044.
+# The default value is: NO.
+
+ALLOW_UNICODE_NAMES = NO
+
# The OUTPUT_LANGUAGE tag is used to specify the language in which all
# documentation generated by doxygen is written. Doxygen will use this
# information to generate all constant output in the proper language.
-# Possible values are: Afrikaans, Arabic, Brazilian, Catalan, Chinese, Chinese-
-# Traditional, Croatian, Czech, Danish, Dutch, English, Esperanto, Farsi,
-# Finnish, French, German, Greek, Hungarian, Italian, Japanese, Japanese-en,
-# Korean, Korean-en, Latvian, Norwegian, Macedonian, Persian, Polish,
-# Portuguese, Romanian, Russian, Serbian, Slovak, Slovene, Spanish, Swedish,
-# Turkish, Ukrainian and Vietnamese.
+# Possible values are: Afrikaans, Arabic, Armenian, Brazilian, Catalan, Chinese,
+# Chinese-Traditional, Croatian, Czech, Danish, Dutch, English (United States),
+# Esperanto, Farsi (Persian), Finnish, French, German, Greek, Hungarian,
+# Indonesian, Italian, Japanese, Japanese-en (Japanese with English messages),
+# Korean, Korean-en (Korean with English messages), Latvian, Lithuanian,
+# Macedonian, Norwegian, Persian (Farsi), Polish, Portuguese, Romanian, Russian,
+# Serbian, Serbian-Cyrillic, Slovak, Slovene, Spanish, Swedish, Turkish,
+# Ukrainian and Vietnamese.
# The default value is: English.
OUTPUT_LANGUAGE = English
-# If the BRIEF_MEMBER_DESC tag is set to YES doxygen will include brief member
+# If the BRIEF_MEMBER_DESC tag is set to YES, doxygen will include brief member
# descriptions after the members that are listed in the file and class
# documentation (similar to Javadoc). Set to NO to disable this.
# The default value is: YES.
BRIEF_MEMBER_DESC = YES
-# If the REPEAT_BRIEF tag is set to YES doxygen will prepend the brief
+# If the REPEAT_BRIEF tag is set to YES, doxygen will prepend the brief
# description of a member or function before the detailed description
-#
+#
# Note: If both HIDE_UNDOC_MEMBERS and BRIEF_MEMBER_DESC are set to NO, the
# brief descriptions will be completely suppressed.
# The default value is: YES.
@@ -108,7 +118,7 @@ REPEAT_BRIEF = YES
# the entity):The $name class, The $name widget, The $name file, is, provides,
# specifies, contains, represents, a, an and the.
-ABBREVIATE_BRIEF =
+ABBREVIATE_BRIEF =
# If the ALWAYS_DETAILED_SEC and REPEAT_BRIEF tags are both set to YES then
# doxygen will generate a detailed section even if there is only a brief
@@ -125,7 +135,7 @@ ALWAYS_DETAILED_SEC = NO
INLINE_INHERITED_MEMB = NO
-# If the FULL_PATH_NAMES tag is set to YES doxygen will prepend the full path
+# If the FULL_PATH_NAMES tag is set to YES, doxygen will prepend the full path
# before files name in the file list and in the header files. If set to NO the
# shortest path that makes the file name unique will be used
# The default value is: YES.
@@ -137,12 +147,12 @@ FULL_PATH_NAMES = NO
# part of the path. The tag can be used to show relative paths in the file list.
# If left blank the directory from which doxygen is run is used as the path to
# strip.
-#
+#
# Note that you can specify absolute paths here, but also relative paths, which
# will be relative from the directory where doxygen is started.
# This tag requires that the tag FULL_PATH_NAMES is set to YES.
-STRIP_FROM_PATH =
+STRIP_FROM_PATH = @CMAKE_SOURCE_DIR@
# The STRIP_FROM_INC_PATH tag can be used to strip a user-defined part of the
# path mentioned in the documentation of a class, which tells the reader which
@@ -151,7 +161,7 @@ STRIP_FROM_PATH =
# specify the list of include paths that are normally passed to the compiler
# using the -I flag.
-STRIP_FROM_INC_PATH =
+STRIP_FROM_INC_PATH =
# If the SHORT_NAMES tag is set to YES, doxygen will generate much shorter (but
# less readable) file names. This can be useful is your file systems doesn't
@@ -182,7 +192,7 @@ QT_AUTOBRIEF = NO
# a brief description. This used to be the default behavior. The new default is
# to treat a multi-line C++ comment block as a detailed description. Set this
# tag to YES if you prefer the old behavior instead.
-#
+#
# Note that setting this tag to YES also means that rational rose comments are
# not recognized any more.
# The default value is: NO.
@@ -195,9 +205,9 @@ MULTILINE_CPP_IS_BRIEF = NO
INHERIT_DOCS = YES
-# If the SEPARATE_MEMBER_PAGES tag is set to YES, then doxygen will produce a
-# new page for each member. If set to NO, the documentation of a member will be
-# part of the file/class/namespace that contains it.
+# If the SEPARATE_MEMBER_PAGES tag is set to YES then doxygen will produce a new
+# page for each member. If set to NO, the documentation of a member will be part
+# of the file/class/namespace that contains it.
# The default value is: NO.
SEPARATE_MEMBER_PAGES = NO
@@ -218,13 +228,13 @@ TAB_SIZE = 8
# "Side Effects:". You can put \n's in the value part of an alias to insert
# newlines.
-ALIASES =
+ALIASES =
# This tag can be used to specify a number of word-keyword mappings (TCL only).
# A mapping has the form "name=value". For example adding "class=itcl::class"
# will allow you to use the command class in the itcl::class meaning.
-TCL_SUBST =
+TCL_SUBST =
# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C sources
# only. Doxygen will then generate output that is more tailored for C. For
@@ -240,13 +250,13 @@ OPTIMIZE_OUTPUT_FOR_C = NO
# qualified scopes will look different, etc.
# The default value is: NO.
-OPTIMIZE_OUTPUT_JAVA = YES
+OPTIMIZE_OUTPUT_JAVA = NO
# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran
# sources. Doxygen will then generate output that is tailored for Fortran.
# The default value is: NO.
-OPTIMIZE_FOR_FORTRAN = NO
+OPTIMIZE_FOR_FORTRAN = YES
# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL
# sources. Doxygen will then generate output that is tailored for VHDL.
@@ -259,16 +269,19 @@ OPTIMIZE_OUTPUT_VHDL = NO
# extension. Doxygen has a built-in mapping, but you can override or extend it
# using this tag. The format is ext=language, where ext is a file extension, and
# language is one of the parsers supported by doxygen: IDL, Java, Javascript,
-# C#, C, C++, D, PHP, Objective-C, Python, Fortran, VHDL. For instance to make
-# doxygen treat .inc files as Fortran files (default is PHP), and .f files as C
-# (default is Fortran), use: inc=Fortran f=C.
-#
-# Note For files without extension you can use no_extension as a placeholder.
-#
+# C#, C, C++, D, PHP, Objective-C, Python, Fortran (fixed format Fortran:
+# FortranFixed, free formatted Fortran: FortranFree, unknown formatted Fortran:
+# Fortran. In the later case the parser tries to guess whether the code is fixed
+# or free formatted code, this is the default for Fortran type files), VHDL. For
+# instance to make doxygen treat .inc files as Fortran files (default is PHP),
+# and .f files as C (default is Fortran), use: inc=Fortran f=C.
+#
+# Note: For files without extension you can use no_extension as a placeholder.
+#
# Note that for custom extensions you also need to set FILE_PATTERNS otherwise
# the files are not read by doxygen.
-EXTENSION_MAPPING =
+EXTENSION_MAPPING =
# If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments
# according to the Markdown format, which allows for more readable
@@ -278,12 +291,12 @@ EXTENSION_MAPPING =
# case of backward compatibilities issues.
# The default value is: YES.
-MARKDOWN_SUPPORT = NO
+MARKDOWN_SUPPORT = YES
# When enabled doxygen tries to link words that correspond to documented
# classes, or namespaces to their corresponding documentation. Such a link can
-# be prevented in individual cases by by putting a % sign in front of the word
-# or globally by setting AUTOLINK_SUPPORT to NO.
+# be prevented in individual cases by putting a % sign in front of the word or
+# globally by setting AUTOLINK_SUPPORT to NO.
# The default value is: YES.
AUTOLINK_SUPPORT = YES
@@ -323,13 +336,20 @@ SIP_SUPPORT = NO
IDL_PROPERTY_SUPPORT = YES
# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC
-# tag is set to YES, then doxygen will reuse the documentation of the first
+# tag is set to YES then doxygen will reuse the documentation of the first
# member in the group (if any) for the other members of the group. By default
# all members of a group must be documented explicitly.
# The default value is: NO.
DISTRIBUTE_GROUP_DOC = NO
+# If one adds a struct or class to a group and this option is enabled, then also
+# any nested class or struct is added to the same group. By default this option
+# is disabled and one has to add nested compounds explicitly via \ingroup.
+# The default value is: NO.
+
+GROUP_NESTED_COMPOUNDS = NO
+
# Set the SUBGROUPING tag to YES to allow class member groups of the same type
# (for instance a group of public functions) to be put as a subgroup of that
# type (e.g. under the Public Functions section). Set it to NO to prevent
@@ -343,7 +363,7 @@ SUBGROUPING = YES
# are shown inside the group in which they are included (e.g. using \ingroup)
# instead of on a separate page (for HTML and Man pages) or section (for LaTeX
# and RTF).
-#
+#
# Note that this feature does not work in combination with
# SEPARATE_MEMBER_PAGES.
# The default value is: NO.
@@ -388,7 +408,7 @@ LOOKUP_CACHE_SIZE = 0
# Build related configuration options
#---------------------------------------------------------------------------
-# If the EXTRACT_ALL tag is set to YES doxygen will assume all entities in
+# If the EXTRACT_ALL tag is set to YES, doxygen will assume all entities in
# documentation are documented, even if no documentation was available. Private
# class members and static file members will be hidden unless the
# EXTRACT_PRIVATE respectively EXTRACT_STATIC tags are set to YES.
@@ -398,39 +418,39 @@ LOOKUP_CACHE_SIZE = 0
EXTRACT_ALL = NO
-# If the EXTRACT_PRIVATE tag is set to YES all private members of a class will
+# If the EXTRACT_PRIVATE tag is set to YES, all private members of a class will
# be included in the documentation.
# The default value is: NO.
EXTRACT_PRIVATE = NO
-# If the EXTRACT_PACKAGE tag is set to YES all members with package or internal
+# If the EXTRACT_PACKAGE tag is set to YES, all members with package or internal
# scope will be included in the documentation.
# The default value is: NO.
-EXTRACT_PACKAGE = YES
+EXTRACT_PACKAGE = NO
-# If the EXTRACT_STATIC tag is set to YES all static members of a file will be
+# If the EXTRACT_STATIC tag is set to YES, all static members of a file will be
# included in the documentation.
# The default value is: NO.
EXTRACT_STATIC = YES
-# If the EXTRACT_LOCAL_CLASSES tag is set to YES classes (and structs) defined
-# locally in source files will be included in the documentation. If set to NO
+# If the EXTRACT_LOCAL_CLASSES tag is set to YES, classes (and structs) defined
+# locally in source files will be included in the documentation. If set to NO,
# only classes defined in header files are included. Does not have any effect
# for Java sources.
# The default value is: YES.
EXTRACT_LOCAL_CLASSES = YES
-# This flag is only useful for Objective-C code. When set to YES local methods,
+# This flag is only useful for Objective-C code. If set to YES, local methods,
# which are defined in the implementation section but not in the interface are
-# included in the documentation. If set to NO only methods in the interface are
+# included in the documentation. If set to NO, only methods in the interface are
# included.
# The default value is: NO.
-EXTRACT_LOCAL_METHODS = YES
+EXTRACT_LOCAL_METHODS = NO
# If this flag is set to YES, the members of anonymous namespaces will be
# extracted and appear in the documentation as a namespace called
@@ -451,25 +471,25 @@ HIDE_UNDOC_MEMBERS = YES
# If the HIDE_UNDOC_CLASSES tag is set to YES, doxygen will hide all
# undocumented classes that are normally visible in the class hierarchy. If set
-# to NO these classes will be included in the various overviews. This option has
-# no effect if EXTRACT_ALL is enabled.
+# to NO, these classes will be included in the various overviews. This option
+# has no effect if EXTRACT_ALL is enabled.
# The default value is: NO.
HIDE_UNDOC_CLASSES = YES
# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, doxygen will hide all friend
-# (class|struct|union) declarations. If set to NO these declarations will be
+# (class|struct|union) declarations. If set to NO, these declarations will be
# included in the documentation.
# The default value is: NO.
HIDE_FRIEND_COMPOUNDS = NO
# If the HIDE_IN_BODY_DOCS tag is set to YES, doxygen will hide any
-# documentation blocks found inside the body of a function. If set to NO these
+# documentation blocks found inside the body of a function. If set to NO, these
# blocks will be appended to the function's detailed documentation block.
# The default value is: NO.
-HIDE_IN_BODY_DOCS = NO
+HIDE_IN_BODY_DOCS = YES
# The INTERNAL_DOCS tag determines if documentation that is typed after a
# \internal command is included. If the tag is set to NO then the documentation
@@ -479,27 +499,41 @@ HIDE_IN_BODY_DOCS = NO
INTERNAL_DOCS = NO
# If the CASE_SENSE_NAMES tag is set to NO then doxygen will only generate file
-# names in lower-case letters. If set to YES upper-case letters are also
+# names in lower-case letters. If set to YES, upper-case letters are also
# allowed. This is useful if you have classes or files whose names only differ
# in case and if your file system supports case sensitive file names. Windows
# and Mac users are advised to set this option to NO.
# The default value is: system dependent.
-CASE_SENSE_NAMES = NO
+CASE_SENSE_NAMES = YES
# If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with
-# their full class and namespace scopes in the documentation. If set to YES the
+# their full class and namespace scopes in the documentation. If set to YES, the
# scope will be hidden.
# The default value is: NO.
HIDE_SCOPE_NAMES = NO
+# If the HIDE_COMPOUND_REFERENCE tag is set to NO (default) then doxygen will
+# append additional text to a page's title, such as Class Reference. If set to
+# YES the compound reference will be hidden.
+# The default value is: NO.
+
+HIDE_COMPOUND_REFERENCE= NO
+
# If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of
# the files that are included by a file in the documentation of that file.
# The default value is: YES.
SHOW_INCLUDE_FILES = YES
+# If the SHOW_GROUPED_MEMB_INC tag is set to YES then Doxygen will add for each
+# grouped member an include statement to the documentation, telling the reader
+# which file to include in order to use the member.
+# The default value is: NO.
+
+SHOW_GROUPED_MEMB_INC = NO
+
# If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include
# files with double quotes in the documentation rather than with sharp brackets.
# The default value is: NO.
@@ -514,17 +548,18 @@ INLINE_INFO = YES
# If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the
# (detailed) documentation of file and class members alphabetically by member
-# name. If set to NO the members will appear in declaration order.
+# name. If set to NO, the members will appear in declaration order.
# The default value is: YES.
-SORT_MEMBER_DOCS = NO
+SORT_MEMBER_DOCS = YES
# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief
# descriptions of file, namespace and class members alphabetically by member
-# name. If set to NO the members will appear in declaration order.
+# name. If set to NO, the members will appear in declaration order. Note that
+# this will also influence the order of the classes in the class list.
# The default value is: NO.
-SORT_BRIEF_DOCS = NO
+SORT_BRIEF_DOCS = YES
# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the
# (brief and detailed) documentation of class members so that constructors and
@@ -553,7 +588,7 @@ SORT_GROUP_NAMES = NO
# list.
# The default value is: NO.
-SORT_BY_SCOPE_NAME = YES
+SORT_BY_SCOPE_NAME = NO
# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper
# type resolution of all parameters of a function it will reject a match between
@@ -565,27 +600,25 @@ SORT_BY_SCOPE_NAME = YES
STRICT_PROTO_MATCHING = NO
-# The GENERATE_TODOLIST tag can be used to enable ( YES) or disable ( NO) the
-# todo list. This list is created by putting \todo commands in the
-# documentation.
+# The GENERATE_TODOLIST tag can be used to enable (YES) or disable (NO) the todo
+# list. This list is created by putting \todo commands in the documentation.
# The default value is: YES.
GENERATE_TODOLIST = YES
-# The GENERATE_TESTLIST tag can be used to enable ( YES) or disable ( NO) the
-# test list. This list is created by putting \test commands in the
-# documentation.
+# The GENERATE_TESTLIST tag can be used to enable (YES) or disable (NO) the test
+# list. This list is created by putting \test commands in the documentation.
# The default value is: YES.
GENERATE_TESTLIST = YES
-# The GENERATE_BUGLIST tag can be used to enable ( YES) or disable ( NO) the bug
+# The GENERATE_BUGLIST tag can be used to enable (YES) or disable (NO) the bug
# list. This list is created by putting \bug commands in the documentation.
# The default value is: YES.
GENERATE_BUGLIST = YES
-# The GENERATE_DEPRECATEDLIST tag can be used to enable ( YES) or disable ( NO)
+# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or disable (NO)
# the deprecated list. This list is created by putting \deprecated commands in
# the documentation.
# The default value is: YES.
@@ -596,7 +629,7 @@ GENERATE_DEPRECATEDLIST= YES
# sections, marked by \if <section_label> ... \endif and \cond <section_label>
# ... \endcond blocks.
-ENABLED_SECTIONS =
+ENABLED_SECTIONS =
# The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the
# initial value of a variable or macro / define can have for it to appear in the
@@ -610,11 +643,11 @@ ENABLED_SECTIONS =
MAX_INITIALIZER_LINES = 29
# Set the SHOW_USED_FILES tag to NO to disable the list of files generated at
-# the bottom of the documentation of classes and structs. If set to YES the list
-# will mention the files that were used to generate the documentation.
+# the bottom of the documentation of classes and structs. If set to YES, the
+# list will mention the files that were used to generate the documentation.
# The default value is: YES.
-SHOW_USED_FILES = YES
+SHOW_USED_FILES = NO
# Set the SHOW_FILES tag to NO to disable the generation of the Files page. This
# will remove the Files entry from the Quick Index and from the Folder Tree View
@@ -628,7 +661,7 @@ SHOW_FILES = YES
# Folder Tree View (if specified).
# The default value is: YES.
-SHOW_NAMESPACES = NO
+SHOW_NAMESPACES = YES
# The FILE_VERSION_FILTER tag can be used to specify a program or script that
# doxygen should invoke to get the current version for each file (typically from
@@ -638,7 +671,7 @@ SHOW_NAMESPACES = NO
# by doxygen. Whatever the program writes to standard output is used as the file
# version. For an example see the documentation.
-FILE_VERSION_FILTER =
+FILE_VERSION_FILTER =
# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed
# by doxygen. The layout file controls the global structure of the generated
@@ -646,12 +679,12 @@ FILE_VERSION_FILTER =
# that represents doxygen's defaults, run doxygen with the -l option. You can
# optionally specify a file name after the option, if omitted DoxygenLayout.xml
# will be used as the name of the layout file.
-#
+#
# Note that if you run doxygen from a directory containing a file called
# DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE
# tag is left empty.
-LAYOUT_FILE =
+LAYOUT_FILE =
# The CITE_BIB_FILES tag can be used to specify one or more bib files containing
# the reference definitions. This must be a list of .bib files. The .bib
@@ -659,10 +692,9 @@ LAYOUT_FILE =
# to be installed. See also http://en.wikipedia.org/wiki/BibTeX for more info.
# For LaTeX the style of the bibliography can be controlled using
# LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the
-# search path. Do not use file names with spaces, bibtex cannot handle them. See
-# also \cite for info how to create references.
+# search path. See also \cite for info how to create references.
-CITE_BIB_FILES =
+CITE_BIB_FILES =
#---------------------------------------------------------------------------
# Configuration options related to warning and progress messages
@@ -673,23 +705,23 @@ CITE_BIB_FILES =
# messages are off.
# The default value is: NO.
-QUIET = NO
+QUIET = @DOXY_QUIET@
# The WARNINGS tag can be used to turn on/off the warning messages that are
-# generated to standard error ( stderr) by doxygen. If WARNINGS is set to YES
+# generated to standard error (stderr) by doxygen. If WARNINGS is set to YES
# this implies that the warnings are on.
-#
+#
# Tip: Turn warnings on while writing the documentation.
# The default value is: YES.
-WARNINGS = YES
+WARNINGS = @DOXY_WARNINGS@
-# If the WARN_IF_UNDOCUMENTED tag is set to YES, then doxygen will generate
+# If the WARN_IF_UNDOCUMENTED tag is set to YES then doxygen will generate
# warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag
# will automatically be disabled.
# The default value is: YES.
-WARN_IF_UNDOCUMENTED = YES
+WARN_IF_UNDOCUMENTED = @DOXY_WARNINGS@
# If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for
# potential errors in the documentation, such as not documenting some parameters
@@ -697,15 +729,15 @@ WARN_IF_UNDOCUMENTED = YES
# markup commands wrongly.
# The default value is: YES.
-WARN_IF_DOC_ERROR = YES
+WARN_IF_DOC_ERROR = @DOXY_WARNINGS@
# This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that
# are documented, but have no documentation for their parameters or return
-# value. If set to NO doxygen will only warn about wrong or incomplete parameter
-# documentation, but not about the absence of documentation.
+# value. If set to NO, doxygen will only warn about wrong or incomplete
+# parameter documentation, but not about the absence of documentation.
# The default value is: NO.
-WARN_NO_PARAMDOC = YES
+WARN_NO_PARAMDOC = @DOXY_WARNINGS@
# The WARN_FORMAT tag determines the format of the warning messages that doxygen
# can produce. The string should contain the $file, $line, and $text tags, which
@@ -721,7 +753,7 @@ WARN_FORMAT = "$file:$line: $text"
# messages should be written. If left blank the output is written to standard
# error (stderr).
-WARN_LOGFILE =
+WARN_LOGFILE =
#---------------------------------------------------------------------------
# Configuration options related to the input files
@@ -730,12 +762,10 @@ WARN_LOGFILE =
# The INPUT tag is used to specify the files and/or directories that contain
# documented source files. You may enter file names like myfile.cpp or
# directories like /usr/src/myproject. Separate the files or directories with
-# spaces.
+# spaces. See also FILE_PATTERNS and EXTENSION_MAPPING
# Note: If this tag is empty the current directory is searched.
-INPUT = @CMAKE_SOURCE_DIR@/hysop \
- @CMAKE_SOURCE_DIR@/DoxyConf/mainpage.doxygen \
- @CMAKE_SOURCE_DIR@/src/fftw
+INPUT =@DOXYGEN_INPUTS@
# This tag can be used to specify the character encoding of the source files
# that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses
@@ -748,17 +778,24 @@ INPUT_ENCODING = UTF-8
# If the value of the INPUT tag contains directories, you can use the
# FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and
-# *.h) to filter out the source-files in the directories. If left blank the
-# following patterns are tested:*.c, *.cc, *.cxx, *.cpp, *.c++, *.java, *.ii,
-# *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h, *.hh, *.hxx, *.hpp,
-# *.h++, *.cs, *.d, *.php, *.php4, *.php5, *.phtml, *.inc, *.m, *.markdown,
-# *.md, *.mm, *.dox, *.py, *.f90, *.f, *.for, *.tcl, *.vhd, *.vhdl, *.ucf,
-# *.qsf, *.as and *.js.
+# *.h) to filter out the source-files in the directories.
+#
+# Note that for custom extensions or not directly supported extensions you also
+# need to set EXTENSION_MAPPING for the extension otherwise the files are not
+# read by doxygen.
+#
+# If left blank the following patterns are tested:*.c, *.cc, *.cxx, *.cpp,
+# *.c++, *.java, *.ii, *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h,
+# *.hh, *.hxx, *.hpp, *.h++, *.cs, *.d, *.php, *.php4, *.php5, *.phtml, *.inc,
+# *.m, *.markdown, *.md, *.mm, *.dox, *.py, *.pyw, *.f90, *.f, *.for, *.tcl,
+# *.vhd, *.vhdl, *.ucf, *.qsf, *.as and *.js.
FILE_PATTERNS = *.doxygen \
- *.py \
*.cl \
- *.f90
+ *.f90 \
+ *.f95 \
+ *.F90 \
+ *.F95
# The RECURSIVE tag can be used to specify whether or not subdirectories should
# be searched for input files as well.
@@ -769,52 +806,51 @@ RECURSIVE = YES
# The EXCLUDE tag can be used to specify files and/or directories that should be
# excluded from the INPUT source files. This way you can easily exclude a
# subdirectory from a directory tree whose root is specified with the INPUT tag.
-#
+#
# Note that relative paths are relative to the directory from which doxygen is
# run.
-EXCLUDE =
+EXCLUDE = @EXCLUDE_DIRS@
# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
# directories that are symbolic links (a Unix file system feature) are excluded
# from the input.
# The default value is: NO.
-EXCLUDE_SYMLINKS = NO
+EXCLUDE_SYMLINKS = YES
# If the value of the INPUT tag contains directories, you can use the
# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude
# certain files from those directories.
-#
+#
# Note that the wildcards are matched against the file with absolute path, so to
# exclude all test directories for example use the pattern */test/*
-EXCLUDE_PATTERNS = */.svn/* \
- */tests/*
+EXCLUDE_PATTERNS = */tests/*
# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
# (namespaces, classes, functions, etc.) that should be excluded from the
# output. The symbol name can be a fully qualified name, a word, or if the
# wildcard * is used, a substring. Examples: ANamespace, AClass,
# AClass::ANamespace, ANamespace::*Test
-#
+#
# Note that the wildcards are matched against the file with absolute path, so to
# exclude all test directories use the pattern */test/*
-EXCLUDE_SYMBOLS =
+EXCLUDE_SYMBOLS =
# The EXAMPLE_PATH tag can be used to specify one or more files or directories
# that contain example code fragments that are included (see the \include
# command).
-EXAMPLE_PATH =
+EXAMPLE_PATH =
# If the value of the EXAMPLE_PATH tag contains directories, you can use the
# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and
# *.h) to filter out the source-files in the directories. If left blank all
# files are included.
-EXAMPLE_PATTERNS = *
+EXAMPLE_PATTERNS =
# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be
# searched for input files to be used with the \include or \dontinclude commands
@@ -827,24 +863,24 @@ EXAMPLE_RECURSIVE = NO
# that contain images that are to be included in the documentation (see the
# \image command).
-IMAGE_PATH =
+IMAGE_PATH =
# The INPUT_FILTER tag can be used to specify a program that doxygen should
# invoke to filter for each input file. Doxygen will invoke the filter program
# by executing (via popen()) the command:
-#
+#
# <filter> <input-file>
-#
+#
# where <filter> is the value of the INPUT_FILTER tag, and <input-file> is the
# name of an input file. Doxygen will then use the output that the filter
# program writes to standard output. If FILTER_PATTERNS is specified, this tag
# will be ignored.
-#
+#
# Note that the filter must not add or remove lines; it is applied before the
# code is scanned, but not when the output code is generated. If lines are added
# or removed, the anchors will not be placed correctly.
-INPUT_FILTER =
+INPUT_FILTER =
# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern
# basis. Doxygen will compare the file name with each pattern and apply the
@@ -853,10 +889,10 @@ INPUT_FILTER =
# filters are used. If the FILTER_PATTERNS tag is empty or if none of the
# patterns match the file name, INPUT_FILTER is applied.
-FILTER_PATTERNS = *.py=doxypy.py
+FILTER_PATTERNS =
# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using
-# INPUT_FILTER ) will also be used to filter the input files that are used for
+# INPUT_FILTER) will also be used to filter the input files that are used for
# producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES).
# The default value is: NO.
@@ -868,14 +904,14 @@ FILTER_SOURCE_FILES = YES
# *.ext= (so without naming a filter).
# This tag requires that the tag FILTER_SOURCE_FILES is set to YES.
-FILTER_SOURCE_PATTERNS =
+FILTER_SOURCE_PATTERNS =
# If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that
# is part of the input, its contents will be placed on the main page
# (index.html). This can be useful if you have a project on for instance GitHub
# and want to reuse the introduction page also for the doxygen output.
-USE_MDFILE_AS_MAINPAGE =
+USE_MDFILE_AS_MAINPAGE =
#---------------------------------------------------------------------------
# Configuration options related to source browsing
@@ -883,12 +919,12 @@ USE_MDFILE_AS_MAINPAGE =
# If the SOURCE_BROWSER tag is set to YES then a list of source files will be
# generated. Documented entities will be cross-referenced with these sources.
-#
+#
# Note: To get rid of all source code in the generated output, make sure that
# also VERBATIM_HEADERS is set to NO.
# The default value is: NO.
-SOURCE_BROWSER = NO
+SOURCE_BROWSER = YES
# Setting the INLINE_SOURCES tag to YES will include the body of functions,
# classes and enums directly into the documentation.
@@ -907,16 +943,16 @@ STRIP_CODE_COMMENTS = YES
# function all documented functions referencing it will be listed.
# The default value is: NO.
-REFERENCED_BY_RELATION = NO
+REFERENCED_BY_RELATION = YES
# If the REFERENCES_RELATION tag is set to YES then for each documented function
# all documented entities called/used by that function will be listed.
# The default value is: NO.
-REFERENCES_RELATION = NO
+REFERENCES_RELATION = YES
# If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set
-# to YES, then the hyperlinks from functions in REFERENCES_RELATION and
+# to YES then the hyperlinks from functions in REFERENCES_RELATION and
# REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will
# link to the documentation.
# The default value is: YES.
@@ -938,16 +974,16 @@ SOURCE_TOOLTIPS = YES
# source browser. The htags tool is part of GNU's global source tagging system
# (see http://www.gnu.org/software/global/global.html). You will need version
# 4.8.6 or higher.
-#
+#
# To use it do the following:
# - Install the latest version of global
# - Enable SOURCE_BROWSER and USE_HTAGS in the config file
# - Make sure the INPUT points to the root of the source tree
# - Run doxygen as normal
-#
+#
# Doxygen will invoke htags (and that will in turn invoke gtags), so these
# tools must be available from the command line (i.e. in the search path).
-#
+#
# The result: instead of the source browser generated by doxygen, the links to
# source code will now point to the output of htags.
# The default value is: NO.
@@ -963,25 +999,6 @@ USE_HTAGS = NO
VERBATIM_HEADERS = YES
-# If the CLANG_ASSISTED_PARSING tag is set to YES, then doxygen will use the
-# clang parser (see: http://clang.llvm.org/) for more acurate parsing at the
-# cost of reduced performance. This can be particularly helpful with template
-# rich C++ code for which doxygen's built-in parser lacks the necessary type
-# information.
-# Note: The availability of this option depends on whether or not doxygen was
-# compiled with the --with-libclang option.
-# The default value is: NO.
-
-CLANG_ASSISTED_PARSING = NO
-
-# If clang assisted parsing is enabled you can provide the compiler with command
-# line options that you would normally use when invoking the compiler. Note that
-# the include paths will already be set by doxygen for the files and directories
-# specified with INPUT and INCLUDE_PATH.
-# This tag requires that the tag CLANG_ASSISTED_PARSING is set to YES.
-
-CLANG_OPTIONS =
-
#---------------------------------------------------------------------------
# Configuration options related to the alphabetical class index
#---------------------------------------------------------------------------
@@ -1006,16 +1023,16 @@ COLS_IN_ALPHA_INDEX = 5
# while generating the index headers.
# This tag requires that the tag ALPHABETICAL_INDEX is set to YES.
-IGNORE_PREFIX =
+IGNORE_PREFIX =
#---------------------------------------------------------------------------
# Configuration options related to the HTML output
#---------------------------------------------------------------------------
-# If the GENERATE_HTML tag is set to YES doxygen will generate HTML output
+# If the GENERATE_HTML tag is set to YES, doxygen will generate HTML output
# The default value is: YES.
-GENERATE_HTML = YES
+GENERATE_HTML = @GENERATE_HTML@
# The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
@@ -1035,7 +1052,7 @@ HTML_FILE_EXTENSION = .html
# The HTML_HEADER tag can be used to specify a user-defined HTML header file for
# each generated HTML page. If the tag is left blank doxygen will generate a
# standard header.
-#
+#
# To get valid HTML the header file that includes any scripts and style sheets
# that doxygen needs, which is dependent on the configuration options used (e.g.
# the setting GENERATE_TREEVIEW). It is highly recommended to start with a
@@ -1050,7 +1067,7 @@ HTML_FILE_EXTENSION = .html
# of the possible markers and block names see the documentation.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_HEADER =
+HTML_HEADER = @CMAKE_SOURCE_DIR@/docs/doxygen_layout/header.html
# The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each
# generated HTML page. If the tag is left blank doxygen will generate a standard
@@ -1060,7 +1077,7 @@ HTML_HEADER =
# that doxygen normally uses.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_FOOTER =
+HTML_FOOTER = @CMAKE_SOURCE_DIR@/docs/doxygen_layout/footer.html
# The HTML_STYLESHEET tag can be used to specify a user-defined cascading style
# sheet that is used by each HTML page. It can be used to fine-tune the look of
@@ -1072,18 +1089,20 @@ HTML_FOOTER =
# obsolete.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_STYLESHEET =
+HTML_STYLESHEET =
-# The HTML_EXTRA_STYLESHEET tag can be used to specify an additional user-
-# defined cascading style sheet that is included after the standard style sheets
+# The HTML_EXTRA_STYLESHEET tag can be used to specify additional user-defined
+# cascading style sheets that are included after the standard style sheets
# created by doxygen. Using this option one can overrule certain style aspects.
# This is preferred over using HTML_STYLESHEET since it does not replace the
-# standard style sheet and is therefor more robust against future updates.
-# Doxygen will copy the style sheet file to the output directory. For an example
-# see the documentation.
+# standard style sheet and is therefore more robust against future updates.
+# Doxygen will copy the style sheet files to the output directory.
+# Note: The order of the extra style sheet files is of importance (e.g. the last
+# style sheet in the list overrules the setting of the previous ones in the
+# list). For an example see the documentation.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_EXTRA_STYLESHEET =
+HTML_EXTRA_STYLESHEET =
# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or
# other source files which should be copied to the HTML output directory. Note
@@ -1093,10 +1112,10 @@ HTML_EXTRA_STYLESHEET =
# files will be copied as-is; there are no commands or markers available.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_EXTRA_FILES =
+HTML_EXTRA_FILES =
# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen
-# will adjust the colors in the stylesheet and background images according to
+# will adjust the colors in the style sheet and background images according to
# this color. Hue is specified as an angle on a colorwheel, see
# http://en.wikipedia.org/wiki/Hue for more information. For instance the value
# 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300
@@ -1104,7 +1123,7 @@ HTML_EXTRA_FILES =
# Minimum value: 0, maximum value: 359, default value: 220.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_COLORSTYLE_HUE = 115
+HTML_COLORSTYLE_HUE = 192
# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors
# in the HTML output. For a value of 0 the output will use grayscales only. A
@@ -1112,7 +1131,7 @@ HTML_COLORSTYLE_HUE = 115
# Minimum value: 0, maximum value: 255, default value: 100.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_COLORSTYLE_SAT = 115
+HTML_COLORSTYLE_SAT = 30
# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the
# luminance component of the colors in the HTML output. Values below 100
@@ -1123,12 +1142,13 @@ HTML_COLORSTYLE_SAT = 115
# Minimum value: 40, maximum value: 240, default value: 80.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_COLORSTYLE_GAMMA = 124
+HTML_COLORSTYLE_GAMMA = 67
# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML
# page will contain the date and time when the page was generated. Setting this
-# to NO can help when comparing the output of multiple runs.
-# The default value is: YES.
+# to YES can help to show when doxygen was last run and thus if the
+# documentation is up to date.
+# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
HTML_TIMESTAMP = YES
@@ -1139,7 +1159,7 @@ HTML_TIMESTAMP = YES
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
-HTML_DYNAMIC_SECTIONS = NO
+HTML_DYNAMIC_SECTIONS = @GENERATE_HTML@
# With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries
# shown in the various tree structured indices initially; the user can expand
@@ -1203,7 +1223,7 @@ DOCSET_PUBLISHER_NAME = Publisher
# index.hhp is a project file that can be read by Microsoft's HTML Help Workshop
# (see: http://www.microsoft.com/en-us/download/details.aspx?id=21138) on
# Windows.
-#
+#
# The HTML Help Workshop contains a compiler that can convert all HTML output
# generated by doxygen into a single compiled HTML file (.chm). Compiled HTML
# files are now used as the Windows 98 help format, and will replace the old
@@ -1221,31 +1241,32 @@ GENERATE_HTMLHELP = NO
# written to the html output directory.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
-CHM_FILE =
+CHM_FILE =
# The HHC_LOCATION tag can be used to specify the location (absolute path
-# including file name) of the HTML help compiler ( hhc.exe). If non-empty
+# including file name) of the HTML help compiler (hhc.exe). If non-empty,
# doxygen will try to run the HTML help compiler on the generated index.hhp.
# The file has to be specified with full path.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
-HHC_LOCATION =
+HHC_LOCATION =
-# The GENERATE_CHI flag controls if a separate .chi index file is generated (
-# YES) or that it should be included in the master .chm file ( NO).
+# The GENERATE_CHI flag controls if a separate .chi index file is generated
+# (YES) or that it should be included in the master .chm file (NO).
# The default value is: NO.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
GENERATE_CHI = NO
-# The CHM_INDEX_ENCODING is used to encode HtmlHelp index ( hhk), content ( hhc)
+# The CHM_INDEX_ENCODING is used to encode HtmlHelp index (hhk), content (hhc)
# and project file content.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
-CHM_INDEX_ENCODING =
+CHM_INDEX_ENCODING =
-# The BINARY_TOC flag controls whether a binary table of contents is generated (
-# YES) or a normal table of contents ( NO) in the .chm file.
+# The BINARY_TOC flag controls whether a binary table of contents is generated
+# (YES) or a normal table of contents (NO) in the .chm file. Furthermore it
+# enables the Previous and Next buttons.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
@@ -1272,7 +1293,7 @@ GENERATE_QHP = NO
# the HTML output folder.
# This tag requires that the tag GENERATE_QHP is set to YES.
-QCH_FILE =
+QCH_FILE =
# The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help
# Project output. For more information please see Qt Help Project / Namespace
@@ -1297,7 +1318,7 @@ QHP_VIRTUAL_FOLDER = doc
# filters).
# This tag requires that the tag GENERATE_QHP is set to YES.
-QHP_CUST_FILTER_NAME =
+QHP_CUST_FILTER_NAME =
# The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the
# custom filter to add. For more information please see Qt Help Project / Custom
@@ -1305,21 +1326,21 @@ QHP_CUST_FILTER_NAME =
# filters).
# This tag requires that the tag GENERATE_QHP is set to YES.
-QHP_CUST_FILTER_ATTRS =
+QHP_CUST_FILTER_ATTRS =
# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this
# project's filter section matches. Qt Help Project / Filter Attributes (see:
# http://qt-project.org/doc/qt-4.8/qthelpproject.html#filter-attributes).
# This tag requires that the tag GENERATE_QHP is set to YES.
-QHP_SECT_FILTER_ATTRS =
+QHP_SECT_FILTER_ATTRS =
# The QHG_LOCATION tag can be used to specify the location of Qt's
# qhelpgenerator. If non-empty doxygen will try to run qhelpgenerator on the
# generated .qhp file.
# This tag requires that the tag GENERATE_QHP is set to YES.
-QHG_LOCATION =
+QHG_LOCATION =
# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be
# generated, together with the HTML files, they form an Eclipse help plugin. To
@@ -1358,7 +1379,7 @@ DISABLE_INDEX = NO
# index structure (just like the one that is generated for HTML Help). For this
# to work a browser that supports JavaScript, DHTML, CSS and frames is required
# (i.e. any modern browser). Windows users are probably better off using the
-# HTML help feature. Via custom stylesheets (see HTML_EXTRA_STYLESHEET) one can
+# HTML help feature. Via custom style sheets (see HTML_EXTRA_STYLESHEET) one can
# further fine-tune the look of the index. As an example, the default style
# sheet generated by doxygen has an example that shows how to put an image at
# the root of the tree instead of the PROJECT_NAME. Since the tree basically has
@@ -1371,7 +1392,7 @@ GENERATE_TREEVIEW = NO
# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that
# doxygen will group on one line in the generated HTML documentation.
-#
+#
# Note that a value of 0 will completely suppress the enum values from appearing
# in the overview section.
# Minimum value: 0, maximum value: 20, default value: 4.
@@ -1386,7 +1407,7 @@ ENUM_VALUES_PER_LINE = 4
TREEVIEW_WIDTH = 250
-# When the EXT_LINKS_IN_WINDOW option is set to YES doxygen will open links to
+# If the EXT_LINKS_IN_WINDOW option is set to YES, doxygen will open links to
# external symbols imported via tag files in a separate window.
# The default value is: NO.
# This tag requires that the tag GENERATE_HTML is set to YES.
@@ -1405,7 +1426,7 @@ FORMULA_FONTSIZE = 10
# Use the FORMULA_TRANPARENT tag to determine whether or not the images
# generated for formulas are transparent PNGs. Transparent PNGs are not
# supported properly for IE 6.0, but are supported on all modern browsers.
-#
+#
# Note that when changing this option you need to delete any form_*.png files in
# the HTML output directory before the changes have effect.
# The default value is: YES.
@@ -1415,7 +1436,7 @@ FORMULA_TRANSPARENT = YES
# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see
# http://www.mathjax.org) which uses client side Javascript for the rendering
-# instead of using prerendered bitmaps. Use this if you do not have LaTeX
+# instead of using pre-rendered bitmaps. Use this if you do not have LaTeX
# installed or if you want to formulas look prettier in the HTML output. When
# enabled you may also need to install MathJax separately and configure the path
# to it using the MATHJAX_RELPATH option.
@@ -1445,14 +1466,14 @@ MATHJAX_FORMAT = HTML-CSS
# The default value is: http://cdn.mathjax.org/mathjax/latest.
# This tag requires that the tag USE_MATHJAX is set to YES.
-MATHJAX_RELPATH = http://www.mathjax.org/mathjax
+MATHJAX_RELPATH = http://cdn.mathjax.org/mathjax/latest
# The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax
# extension names that should be enabled during MathJax rendering. For example
# MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols
# This tag requires that the tag USE_MATHJAX is set to YES.
-MATHJAX_EXTENSIONS =
+MATHJAX_EXTENSIONS =
# The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces
# of code that will be used on startup of the MathJax code. See the MathJax site
@@ -1460,7 +1481,7 @@ MATHJAX_EXTENSIONS =
# example see the documentation.
# This tag requires that the tag USE_MATHJAX is set to YES.
-MATHJAX_CODEFILE =
+MATHJAX_CODEFILE =
# When the SEARCHENGINE tag is enabled doxygen will generate a search box for
# the HTML output. The underlying search engine uses javascript and DHTML and
@@ -1481,15 +1502,15 @@ MATHJAX_CODEFILE =
# The default value is: YES.
# This tag requires that the tag GENERATE_HTML is set to YES.
-SEARCHENGINE = YES
+SEARCHENGINE = NO
# When the SERVER_BASED_SEARCH tag is enabled the search engine will be
# implemented using a web server instead of a web client using Javascript. There
-# are two flavours of web server based searching depending on the
-# EXTERNAL_SEARCH setting. When disabled, doxygen will generate a PHP script for
-# searching and an index file used by the script. When EXTERNAL_SEARCH is
-# enabled the indexing and searching needs to be provided by external tools. See
-# the section "External Indexing and Searching" for details.
+# are two flavors of web server based searching depending on the EXTERNAL_SEARCH
+# setting. When disabled, doxygen will generate a PHP script for searching and
+# an index file used by the script. When EXTERNAL_SEARCH is enabled the indexing
+# and searching needs to be provided by external tools. See the section
+# "External Indexing and Searching" for details.
# The default value is: NO.
# This tag requires that the tag SEARCHENGINE is set to YES.
@@ -1500,11 +1521,11 @@ SERVER_BASED_SEARCH = NO
# which needs to be processed by an external indexer. Doxygen will invoke an
# external search engine pointed to by the SEARCHENGINE_URL option to obtain the
# search results.
-#
-# Doxygen ships with an example indexer ( doxyindexer) and search engine
+#
+# Doxygen ships with an example indexer (doxyindexer) and search engine
# (doxysearch.cgi) which are based on the open source search engine library
# Xapian (see: http://xapian.org/).
-#
+#
# See the section "External Indexing and Searching" for details.
# The default value is: NO.
# This tag requires that the tag SEARCHENGINE is set to YES.
@@ -1513,14 +1534,14 @@ EXTERNAL_SEARCH = NO
# The SEARCHENGINE_URL should point to a search engine hosted by a web server
# which will return the search results when EXTERNAL_SEARCH is enabled.
-#
-# Doxygen ships with an example indexer ( doxyindexer) and search engine
+#
+# Doxygen ships with an example indexer (doxyindexer) and search engine
# (doxysearch.cgi) which are based on the open source search engine library
# Xapian (see: http://xapian.org/). See the section "External Indexing and
# Searching" for details.
# This tag requires that the tag SEARCHENGINE is set to YES.
-SEARCHENGINE_URL =
+SEARCHENGINE_URL =
# When SERVER_BASED_SEARCH and EXTERNAL_SEARCH are both enabled the unindexed
# search data is written to a file for indexing by an external tool. With the
@@ -1536,7 +1557,7 @@ SEARCHDATA_FILE = searchdata.xml
# projects and redirect the results back to the right project.
# This tag requires that the tag SEARCHENGINE is set to YES.
-EXTERNAL_SEARCH_ID =
+EXTERNAL_SEARCH_ID =
# The EXTRA_SEARCH_MAPPINGS tag can be used to enable searching through doxygen
# projects other than the one defined by this configuration file, but that are
@@ -1546,13 +1567,13 @@ EXTERNAL_SEARCH_ID =
# EXTRA_SEARCH_MAPPINGS = tagname1=loc1 tagname2=loc2 ...
# This tag requires that the tag SEARCHENGINE is set to YES.
-EXTRA_SEARCH_MAPPINGS =
+EXTRA_SEARCH_MAPPINGS =
#---------------------------------------------------------------------------
# Configuration options related to the LaTeX output
#---------------------------------------------------------------------------
-# If the GENERATE_LATEX tag is set to YES doxygen will generate LaTeX output.
+# If the GENERATE_LATEX tag is set to YES, doxygen will generate LaTeX output.
# The default value is: YES.
GENERATE_LATEX = NO
@@ -1567,7 +1588,7 @@ LATEX_OUTPUT = latex
# The LATEX_CMD_NAME tag can be used to specify the LaTeX command name to be
# invoked.
-#
+#
# Note that when enabling USE_PDFLATEX this option is only used for generating
# bitmaps for formulas in the HTML output, but not in the Makefile that is
# written to the output directory.
@@ -1583,13 +1604,13 @@ LATEX_CMD_NAME = latex
MAKEINDEX_CMD_NAME = makeindex
-# If the COMPACT_LATEX tag is set to YES doxygen generates more compact LaTeX
+# If the COMPACT_LATEX tag is set to YES, doxygen generates more compact LaTeX
# documents. This may be useful for small projects and may help to save some
# trees in general.
# The default value is: NO.
# This tag requires that the tag GENERATE_LATEX is set to YES.
-COMPACT_LATEX = YES
+COMPACT_LATEX = NO
# The PAPER_TYPE tag can be used to set the paper type that is used by the
# printer.
@@ -1598,41 +1619,57 @@ COMPACT_LATEX = YES
# The default value is: a4.
# This tag requires that the tag GENERATE_LATEX is set to YES.
-PAPER_TYPE = a4
+PAPER_TYPE = a4wide
# The EXTRA_PACKAGES tag can be used to specify one or more LaTeX package names
-# that should be included in the LaTeX output. To get the times font for
-# instance you can specify
-# EXTRA_PACKAGES=times
+# that should be included in the LaTeX output. The package can be specified just
+# by its name or with the correct syntax as to be used with the LaTeX
+# \usepackage command. To get the times font for instance you can specify :
+# EXTRA_PACKAGES=times or EXTRA_PACKAGES={times}
+# To use the option intlimits with the amsmath package you can specify:
+# EXTRA_PACKAGES=[intlimits]{amsmath}
# If left blank no extra packages will be included.
# This tag requires that the tag GENERATE_LATEX is set to YES.
-EXTRA_PACKAGES =
+EXTRA_PACKAGES = amsmath
# The LATEX_HEADER tag can be used to specify a personal LaTeX header for the
# generated LaTeX document. The header should contain everything until the first
# chapter. If it is left blank doxygen will generate a standard header. See
# section "Doxygen usage" for information on how to let doxygen write the
# default header to a separate file.
-#
+#
# Note: Only use a user-defined header if you know what you are doing! The
# following commands have a special meaning inside the header: $title,
-# $datetime, $date, $doxygenversion, $projectname, $projectnumber. Doxygen will
-# replace them by respectively the title of the page, the current date and time,
-# only the current date, the version number of doxygen, the project name (see
-# PROJECT_NAME), or the project number (see PROJECT_NUMBER).
+# $datetime, $date, $doxygenversion, $projectname, $projectnumber,
+# $projectbrief, $projectlogo. Doxygen will replace $title with the empty
+# string, for the replacement values of the other commands the user is referred
+# to HTML_HEADER.
# This tag requires that the tag GENERATE_LATEX is set to YES.
-LATEX_HEADER =
+LATEX_HEADER =
# The LATEX_FOOTER tag can be used to specify a personal LaTeX footer for the
# generated LaTeX document. The footer should contain everything after the last
-# chapter. If it is left blank doxygen will generate a standard footer.
-#
+# chapter. If it is left blank doxygen will generate a standard footer. See
+# LATEX_HEADER for more information on how to generate a default footer and what
+# special commands can be used inside the footer.
+#
# Note: Only use a user-defined footer if you know what you are doing!
# This tag requires that the tag GENERATE_LATEX is set to YES.
-LATEX_FOOTER =
+LATEX_FOOTER =
+
+# The LATEX_EXTRA_STYLESHEET tag can be used to specify additional user-defined
+# LaTeX style sheets that are included after the standard style sheets created
+# by doxygen. Using this option one can overrule certain style aspects. Doxygen
+# will copy the style sheet files to the output directory.
+# Note: The order of the extra style sheet files is of importance (e.g. the last
+# style sheet in the list overrules the setting of the previous ones in the
+# list).
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_EXTRA_STYLESHEET =
# The LATEX_EXTRA_FILES tag can be used to specify one or more extra images or
# other source files which should be copied to the LATEX_OUTPUT output
@@ -1640,7 +1677,7 @@ LATEX_FOOTER =
# markers available.
# This tag requires that the tag GENERATE_LATEX is set to YES.
-LATEX_EXTRA_FILES =
+LATEX_EXTRA_FILES =
# If the PDF_HYPERLINKS tag is set to YES, the LaTeX that is generated is
# prepared for conversion to PDF (using ps2pdf or pdflatex). The PDF file will
@@ -1651,8 +1688,8 @@ LATEX_EXTRA_FILES =
PDF_HYPERLINKS = YES
-# If the LATEX_PDFLATEX tag is set to YES, doxygen will use pdflatex to generate
-# the PDF file directly from the LaTeX files. Set this option to YES to get a
+# If the USE_PDFLATEX tag is set to YES, doxygen will use pdflatex to generate
+# the PDF file directly from the LaTeX files. Set this option to YES, to get a
# higher quality PDF documentation.
# The default value is: YES.
# This tag requires that the tag GENERATE_LATEX is set to YES.
@@ -1677,7 +1714,7 @@ LATEX_HIDE_INDICES = NO
# If the LATEX_SOURCE_CODE tag is set to YES then doxygen will include source
# code with syntax highlighting in the LaTeX output.
-#
+#
# Note that which sources are shown also depends on other settings such as
# SOURCE_BROWSER.
# The default value is: NO.
@@ -1697,7 +1734,7 @@ LATEX_BIB_STYLE = plain
# Configuration options related to the RTF output
#---------------------------------------------------------------------------
-# If the GENERATE_RTF tag is set to YES doxygen will generate RTF output. The
+# If the GENERATE_RTF tag is set to YES, doxygen will generate RTF output. The
# RTF output is optimized for Word 97 and may not look too pretty with other RTF
# readers/editors.
# The default value is: NO.
@@ -1712,7 +1749,7 @@ GENERATE_RTF = NO
RTF_OUTPUT = rtf
-# If the COMPACT_RTF tag is set to YES doxygen generates more compact RTF
+# If the COMPACT_RTF tag is set to YES, doxygen generates more compact RTF
# documents. This may be useful for small projects and may help to save some
# trees in general.
# The default value is: NO.
@@ -1725,7 +1762,7 @@ COMPACT_RTF = NO
# output) instead of page references. This makes the output suitable for online
# browsing using Word or some other Word compatible readers that support those
# fields.
-#
+#
# Note: WordPad (write) and others do not support links.
# The default value is: NO.
# This tag requires that the tag GENERATE_RTF is set to YES.
@@ -1735,25 +1772,35 @@ RTF_HYPERLINKS = NO
# Load stylesheet definitions from file. Syntax is similar to doxygen's config
# file, i.e. a series of assignments. You only have to provide replacements,
# missing definitions are set to their default value.
-#
+#
# See also section "Doxygen usage" for information on how to generate the
# default style sheet that doxygen normally uses.
# This tag requires that the tag GENERATE_RTF is set to YES.
-RTF_STYLESHEET_FILE =
+RTF_STYLESHEET_FILE =
# Set optional variables used in the generation of an RTF document. Syntax is
# similar to doxygen's config file. A template extensions file can be generated
# using doxygen -e rtf extensionFile.
# This tag requires that the tag GENERATE_RTF is set to YES.
-RTF_EXTENSIONS_FILE =
+RTF_EXTENSIONS_FILE =
+
+# If the RTF_SOURCE_CODE tag is set to YES then doxygen will include source code
+# with syntax highlighting in the RTF output.
+#
+# Note that which sources are shown also depends on other settings such as
+# SOURCE_BROWSER.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_RTF is set to YES.
+
+RTF_SOURCE_CODE = NO
#---------------------------------------------------------------------------
# Configuration options related to the man page output
#---------------------------------------------------------------------------
-# If the GENERATE_MAN tag is set to YES doxygen will generate man pages for
+# If the GENERATE_MAN tag is set to YES, doxygen will generate man pages for
# classes and files.
# The default value is: NO.
@@ -1777,6 +1824,13 @@ MAN_OUTPUT = man
MAN_EXTENSION = .3
+# The MAN_SUBDIR tag determines the name of the directory created within
+# MAN_OUTPUT in which the man pages are placed. If defaults to man followed by
+# MAN_EXTENSION with the initial . removed.
+# This tag requires that the tag GENERATE_MAN is set to YES.
+
+MAN_SUBDIR =
+
# If the MAN_LINKS tag is set to YES and doxygen generates man output, then it
# will generate one additional man file for each entity documented in the real
# man page(s). These additional files only source the real man page, but without
@@ -1790,11 +1844,11 @@ MAN_LINKS = NO
# Configuration options related to the XML output
#---------------------------------------------------------------------------
-# If the GENERATE_XML tag is set to YES doxygen will generate an XML file that
+# If the GENERATE_XML tag is set to YES, doxygen will generate an XML file that
# captures the structure of the code including all documentation.
# The default value is: NO.
-GENERATE_XML = NO
+GENERATE_XML = @GENERATE_XML@
# The XML_OUTPUT tag is used to specify where the XML pages will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
@@ -1804,19 +1858,7 @@ GENERATE_XML = NO
XML_OUTPUT = xml
-# The XML_SCHEMA tag can be used to specify a XML schema, which can be used by a
-# validating XML parser to check the syntax of the XML files.
-# This tag requires that the tag GENERATE_XML is set to YES.
-
-XML_SCHEMA =
-
-# The XML_DTD tag can be used to specify a XML DTD, which can be used by a
-# validating XML parser to check the syntax of the XML files.
-# This tag requires that the tag GENERATE_XML is set to YES.
-
-XML_DTD =
-
-# If the XML_PROGRAMLISTING tag is set to YES doxygen will dump the program
+# If the XML_PROGRAMLISTING tag is set to YES, doxygen will dump the program
# listings (including syntax highlighting and cross-referencing information) to
# the XML output. Note that enabling this will significantly increase the size
# of the XML output.
@@ -1829,7 +1871,7 @@ XML_PROGRAMLISTING = YES
# Configuration options related to the DOCBOOK output
#---------------------------------------------------------------------------
-# If the GENERATE_DOCBOOK tag is set to YES doxygen will generate Docbook files
+# If the GENERATE_DOCBOOK tag is set to YES, doxygen will generate Docbook files
# that can be used to generate PDF.
# The default value is: NO.
@@ -1843,14 +1885,23 @@ GENERATE_DOCBOOK = NO
DOCBOOK_OUTPUT = docbook
+# If the DOCBOOK_PROGRAMLISTING tag is set to YES, doxygen will include the
+# program listings (including syntax highlighting and cross-referencing
+# information) to the DOCBOOK output. Note that enabling this will significantly
+# increase the size of the DOCBOOK output.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_DOCBOOK is set to YES.
+
+DOCBOOK_PROGRAMLISTING = NO
+
#---------------------------------------------------------------------------
# Configuration options for the AutoGen Definitions output
#---------------------------------------------------------------------------
-# If the GENERATE_AUTOGEN_DEF tag is set to YES doxygen will generate an AutoGen
-# Definitions (see http://autogen.sf.net) file that captures the structure of
-# the code including all documentation. Note that this feature is still
-# experimental and incomplete at the moment.
+# If the GENERATE_AUTOGEN_DEF tag is set to YES, doxygen will generate an
+# AutoGen Definitions (see http://autogen.sf.net) file that captures the
+# structure of the code including all documentation. Note that this feature is
+# still experimental and incomplete at the moment.
# The default value is: NO.
GENERATE_AUTOGEN_DEF = NO
@@ -1859,15 +1910,15 @@ GENERATE_AUTOGEN_DEF = NO
# Configuration options related to the Perl module output
#---------------------------------------------------------------------------
-# If the GENERATE_PERLMOD tag is set to YES doxygen will generate a Perl module
+# If the GENERATE_PERLMOD tag is set to YES, doxygen will generate a Perl module
# file that captures the structure of the code including all documentation.
-#
+#
# Note that this feature is still experimental and incomplete at the moment.
# The default value is: NO.
GENERATE_PERLMOD = NO
-# If the PERLMOD_LATEX tag is set to YES doxygen will generate the necessary
+# If the PERLMOD_LATEX tag is set to YES, doxygen will generate the necessary
# Makefile rules, Perl scripts and LaTeX code to be able to generate PDF and DVI
# output from the Perl module output.
# The default value is: NO.
@@ -1875,9 +1926,9 @@ GENERATE_PERLMOD = NO
PERLMOD_LATEX = NO
-# If the PERLMOD_PRETTY tag is set to YES the Perl module output will be nicely
+# If the PERLMOD_PRETTY tag is set to YES, the Perl module output will be nicely
# formatted so it can be parsed by a human reader. This is useful if you want to
-# understand what is going on. On the other hand, if this tag is set to NO the
+# understand what is going on. On the other hand, if this tag is set to NO, the
# size of the Perl module output will be much smaller and Perl will parse it
# just the same.
# The default value is: YES.
@@ -1891,20 +1942,20 @@ PERLMOD_PRETTY = YES
# overwrite each other's variables.
# This tag requires that the tag GENERATE_PERLMOD is set to YES.
-PERLMOD_MAKEVAR_PREFIX =
+PERLMOD_MAKEVAR_PREFIX =
#---------------------------------------------------------------------------
# Configuration options related to the preprocessor
#---------------------------------------------------------------------------
-# If the ENABLE_PREPROCESSING tag is set to YES doxygen will evaluate all
+# If the ENABLE_PREPROCESSING tag is set to YES, doxygen will evaluate all
# C-preprocessor directives found in the sources and include files.
# The default value is: YES.
ENABLE_PREPROCESSING = YES
-# If the MACRO_EXPANSION tag is set to YES doxygen will expand all macro names
-# in the source code. If set to NO only conditional compilation will be
+# If the MACRO_EXPANSION tag is set to YES, doxygen will expand all macro names
+# in the source code. If set to NO, only conditional compilation will be
# performed. Macro expansion can be done in a controlled way by setting
# EXPAND_ONLY_PREDEF to YES.
# The default value is: NO.
@@ -1920,7 +1971,7 @@ MACRO_EXPANSION = NO
EXPAND_ONLY_PREDEF = NO
-# If the SEARCH_INCLUDES tag is set to YES the includes files in the
+# If the SEARCH_INCLUDES tag is set to YES, the include files in the
# INCLUDE_PATH will be searched if a #include is found.
# The default value is: YES.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
@@ -1932,7 +1983,7 @@ SEARCH_INCLUDES = YES
# preprocessor.
# This tag requires that the tag SEARCH_INCLUDES is set to YES.
-INCLUDE_PATH =
+INCLUDE_PATH =
# You can use the INCLUDE_FILE_PATTERNS tag to specify one or more wildcard
# patterns (like *.h and *.hpp) to filter out the header-files in the
@@ -1940,7 +1991,7 @@ INCLUDE_PATH =
# used.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
-INCLUDE_FILE_PATTERNS =
+INCLUDE_FILE_PATTERNS =
# The PREDEFINED tag can be used to specify one or more macro names that are
# defined before the preprocessor is started (similar to the -D option of e.g.
@@ -1950,7 +2001,7 @@ INCLUDE_FILE_PATTERNS =
# recursively expanded use the := operator instead of the = operator.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
-PREDEFINED =
+PREDEFINED =
# If the MACRO_EXPANSION and EXPAND_ONLY_PREDEF tags are set to YES then this
# tag can be used to specify a list of macro names that should be expanded. The
@@ -1959,12 +2010,12 @@ PREDEFINED =
# definition found in the source code.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
-EXPAND_AS_DEFINED =
+EXPAND_AS_DEFINED =
# If the SKIP_FUNCTION_MACROS tag is set to YES then doxygen's preprocessor will
-# remove all refrences to function-like macros that are alone on a line, have an
-# all uppercase name, and do not end with a semicolon. Such function macros are
-# typically used for boiler-plate code, and will confuse the parser if not
+# remove all references to function-like macros that are alone on a line, have
+# an all uppercase name, and do not end with a semicolon. Such function macros
+# are typically used for boiler-plate code, and will confuse the parser if not
# removed.
# The default value is: YES.
# This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
@@ -1984,32 +2035,33 @@ SKIP_FUNCTION_MACROS = YES
# where loc1 and loc2 can be relative or absolute paths or URLs. See the
# section "Linking to external documentation" for more information about the use
# of tag files.
-# Note: Each tag file must have an unique name (where the name does NOT include
+# Note: Each tag file must have a unique name (where the name does NOT include
# the path). If a tag file is not located in the directory in which doxygen is
# run, you must also specify the path to the tagfile here.
-TAGFILES =
+TAGFILES =
# When a file name is specified after GENERATE_TAGFILE, doxygen will create a
# tag file that is based on the input files it reads. See section "Linking to
# external documentation" for more information about the usage of tag files.
-GENERATE_TAGFILE =
+GENERATE_TAGFILE = @CMAKE_BINARY_DIR@/docs/build/tags/@PROJECT_NAME@.tag
-# If the ALLEXTERNALS tag is set to YES all external class will be listed in the
-# class index. If set to NO only the inherited external classes will be listed.
+# If the ALLEXTERNALS tag is set to YES, all external class will be listed in
+# the class index. If set to NO, only the inherited external classes will be
+# listed.
# The default value is: NO.
ALLEXTERNALS = NO
-# If the EXTERNAL_GROUPS tag is set to YES all external groups will be listed in
-# the modules index. If set to NO, only the current project's groups will be
+# If the EXTERNAL_GROUPS tag is set to YES, all external groups will be listed
+# in the modules index. If set to NO, only the current project's groups will be
# listed.
# The default value is: YES.
EXTERNAL_GROUPS = YES
-# If the EXTERNAL_PAGES tag is set to YES all external pages will be listed in
+# If the EXTERNAL_PAGES tag is set to YES, all external pages will be listed in
# the related pages index. If set to NO, only the current project's pages will
# be listed.
# The default value is: YES.
@@ -2026,7 +2078,7 @@ PERL_PATH = /usr/bin/perl
# Configuration options related to the dot tool
#---------------------------------------------------------------------------
-# If the CLASS_DIAGRAMS tag is set to YES doxygen will generate a class diagram
+# If the CLASS_DIAGRAMS tag is set to YES, doxygen will generate a class diagram
# (in HTML and LaTeX) for classes with base or super classes. Setting the tag to
# NO turns the diagrams off. Note that this option also works with HAVE_DOT
# disabled, but it is recommended to install and use dot, since it yields more
@@ -2042,9 +2094,16 @@ CLASS_DIAGRAMS = YES
# the mscgen tool resides. If left empty the tool is assumed to be found in the
# default search path.
-MSCGEN_PATH =
+MSCGEN_PATH =
-# If set to YES, the inheritance and collaboration graphs will hide inheritance
+# You can include diagrams made with dia in doxygen documentation. Doxygen will
+# then run dia to produce the diagram and insert it in the documentation. The
+# DIA_PATH tag allows you to specify the directory where the dia binary resides.
+# If left empty dia is assumed to be found in the default search path.
+
+DIA_PATH =
+
+# If set to YES the inheritance and collaboration graphs will hide inheritance
# and usage relations if the target is undocumented or is not a class.
# The default value is: YES.
@@ -2069,7 +2128,7 @@ HAVE_DOT = YES
DOT_NUM_THREADS = 0
-# When you want a differently looking font n the dot files that doxygen
+# When you want a differently looking font in the dot files that doxygen
# generates you can specify the font name using DOT_FONTNAME. You need to make
# sure dot is able to find the font, which can be done by putting it in a
# standard location or by setting the DOTFONTPATH environment variable or by
@@ -2091,7 +2150,7 @@ DOT_FONTSIZE = 10
# the path where dot can find it using this tag.
# This tag requires that the tag HAVE_DOT is set to YES.
-DOT_FONTPATH =
+DOT_FONTPATH =
# If the CLASS_GRAPH tag is set to YES then doxygen will generate a graph for
# each documented class showing the direct and indirect inheritance relations.
@@ -2117,7 +2176,7 @@ COLLABORATION_GRAPH = YES
GROUP_GRAPHS = YES
-# If the UML_LOOK tag is set to YES doxygen will generate inheritance and
+# If the UML_LOOK tag is set to YES, doxygen will generate inheritance and
# collaboration diagrams in a style similar to the OMG's Unified Modeling
# Language.
# The default value is: NO.
@@ -2166,10 +2225,11 @@ INCLUDED_BY_GRAPH = YES
# If the CALL_GRAPH tag is set to YES then doxygen will generate a call
# dependency graph for every global function or class method.
-#
+#
# Note that enabling this option will significantly increase the time of a run.
# So in most cases it will be better to enable call graphs for selected
-# functions only using the \callgraph command.
+# functions only using the \callgraph command. Disabling a call graph can be
+# accomplished by means of the command \hidecallgraph.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
@@ -2177,10 +2237,11 @@ CALL_GRAPH = YES
# If the CALLER_GRAPH tag is set to YES then doxygen will generate a caller
# dependency graph for every global function or class method.
-#
+#
# Note that enabling this option will significantly increase the time of a run.
# So in most cases it will be better to enable caller graphs for selected
-# functions only using the \callergraph command.
+# functions only using the \callergraph command. Disabling a caller graph can be
+# accomplished by means of the command \hidecallergraph.
# The default value is: NO.
# This tag requires that the tag HAVE_DOT is set to YES.
@@ -2203,11 +2264,15 @@ GRAPHICAL_HIERARCHY = YES
DIRECTORY_GRAPH = YES
# The DOT_IMAGE_FORMAT tag can be used to set the image format of the images
-# generated by dot.
+# generated by dot. For an explanation of the image formats see the section
+# output formats in the documentation of the dot tool (Graphviz (see:
+# http://www.graphviz.org/)).
# Note: If you choose svg you need to set HTML_FILE_EXTENSION to xhtml in order
# to make the SVG files visible in IE 9+ (other browsers do not have this
# requirement).
-# Possible values are: png, jpg, gif and svg.
+# Possible values are: png, jpg, gif, svg, png:gd, png:gd:gd, png:cairo,
+# png:cairo:gd, png:cairo:cairo, png:cairo:gdiplus, png:gdiplus and
+# png:gdiplus:gdiplus.
# The default value is: png.
# This tag requires that the tag HAVE_DOT is set to YES.
@@ -2215,7 +2280,7 @@ DOT_IMAGE_FORMAT = png
# If DOT_IMAGE_FORMAT is set to svg, then this option can be set to YES to
# enable generation of interactive SVG images that allow zooming and panning.
-#
+#
# Note that this requires a modern browser other than Internet Explorer. Tested
# and working are Firefox, Chrome, Safari, and Opera.
# Note: For IE 9+ you need to set HTML_FILE_EXTENSION to xhtml in order to make
@@ -2236,13 +2301,32 @@ DOT_PATH = @DOXYGEN_DOT_PATH@
# command).
# This tag requires that the tag HAVE_DOT is set to YES.
-DOTFILE_DIRS =
+DOTFILE_DIRS =
# The MSCFILE_DIRS tag can be used to specify one or more directories that
# contain msc files that are included in the documentation (see the \mscfile
# command).
-MSCFILE_DIRS =
+MSCFILE_DIRS =
+
+# The DIAFILE_DIRS tag can be used to specify one or more directories that
+# contain dia files that are included in the documentation (see the \diafile
+# command).
+
+DIAFILE_DIRS =
+
+# When using plantuml, the PLANTUML_JAR_PATH tag should be used to specify the
+# path where java can find the plantuml.jar file. If left blank, it is assumed
+# PlantUML is not used or called during a preprocessing step. Doxygen will
+# generate a warning when it encounters a \startuml command in this case and
+# will not generate output for the diagram.
+
+PLANTUML_JAR_PATH =
+
+# When using plantuml, the specified paths are searched for files specified by
+# the !include statement in a plantuml block.
+
+PLANTUML_INCLUDE_PATH =
# The DOT_GRAPH_MAX_NODES tag can be used to set the maximum number of nodes
# that will be shown in the graph. If the number of nodes in a graph becomes
@@ -2271,7 +2355,7 @@ MAX_DOT_GRAPH_DEPTH = 0
# Set the DOT_TRANSPARENT tag to YES to generate images with a transparent
# background. This is disabled by default, because dot on Windows does not seem
# to support this out of the box.
-#
+#
# Warning: Depending on the platform used, enabling this option may lead to
# badly anti-aliased labels on the edges of a graph (i.e. they become hard to
# read).
@@ -2280,7 +2364,7 @@ MAX_DOT_GRAPH_DEPTH = 0
DOT_TRANSPARENT = NO
-# Set the DOT_MULTI_TARGETS tag to YES allow dot to generate multiple output
+# Set the DOT_MULTI_TARGETS tag to YES to allow dot to generate multiple output
# files in one run (i.e. multiple -o and -T options on the command line). This
# makes dot run faster, but since only newer versions of dot (>1.8.10) support
# this, this feature is disabled by default.
@@ -2297,7 +2381,7 @@ DOT_MULTI_TARGETS = NO
GENERATE_LEGEND = YES
-# If the DOT_CLEANUP tag is set to YES doxygen will remove the intermediate dot
+# If the DOT_CLEANUP tag is set to YES, doxygen will remove the intermediate dot
# files that are used to generate the various graphs.
# The default value is: YES.
# This tag requires that the tag HAVE_DOT is set to YES.
diff --git a/docs/sphinx/_static/logo_hysop_favicon.ico b/docs/sphinx/_static/logo_hysop_favicon.ico
deleted file mode 100644
index fa0e8afe56caabc5865839ce84f7d726f99163cb..0000000000000000000000000000000000000000
Binary files a/docs/sphinx/_static/logo_hysop_favicon.ico and /dev/null differ
diff --git a/docs/sphinx/conf.py.in b/docs/sphinx/conf.py.in
index c6d9070893cec0f914d4809afb3758b7325d9e76..8399b4a984cfc674a93c06e90e22f278927f4e77 100644
--- a/docs/sphinx/conf.py.in
+++ b/docs/sphinx/conf.py.in
@@ -26,6 +26,8 @@
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
import sys
+import sphinx_bootstrap_theme
+
extensions = [
'sphinx.ext.autodoc',
'sphinx.ext.autosummary',
@@ -138,29 +140,12 @@ html_theme = 'bootstrap'
# Add any paths that contain custom themes here, relative to this directory.
html_theme_path = ['@CMAKE_CURRENT_SOURCE_DIR@/sphinx/themes']
-import sphinx_bootstrap_theme
html_theme_path += sphinx_bootstrap_theme.get_html_theme_path()
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
html_theme_options = {'bootswatch_theme': "sandstone", }
-# Activate the bootstrap theme if it's available
-#try:
-# import sphinx_bootstrap_theme
-# html_theme = 'bootstrap'
-# html_theme_path += sphinx_bootstrap_theme.get_html_theme_path()
-# print "ooooooooooooooooooooo ", html_theme_path
-# html_theme_options = {
-# 'bootswatch_theme': "superhero",
-# }
-#except:
-# print("""Warning: Module sphinx_bootstrap_theme not found, continuing
-#anyway using old theme. To get the new theme, use,#
-#
-# pip install sphinx_bootstrap_theme""")
-
-
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
# html_title = None
@@ -196,10 +181,14 @@ html_static_path = ['_static']
# html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
-html_sidebars = {
- '**': ['menu.html',],# 'searchbox.html'],
- 'using/windows': ['windowssidebar.html', 'searchbox.html'],
-}
+#html_sidebars = {
+# '**': ['menu.html',],# 'searchbox.html'],
+# 'using/windows': ['windowssidebar.html', 'searchbox.html'],
+#}
+# html_sidebars = {
+# '**': ['menu.html', ],# 'searchbox.html'],
+# 'using/windows': ['windowssidebar.html', 'searchbox.html'],
+# }
# Additional templates that should be rendered to pages, maps page names to
# template names.
diff --git a/docs/sphinx/devel/fortran2python.rst b/docs/sphinx/devel/fortran2python.rst
new file mode 100644
index 0000000000000000000000000000000000000000..a20e7d93a1fc13c28a1a7d86d1e97934e79ba2bc
--- /dev/null
+++ b/docs/sphinx/devel/fortran2python.rst
@@ -0,0 +1,35 @@
+.. _fortran2python:
+
+Fortran to python interface
+===========================
+
+This page propose a tutorial to call some fortran subroutines in python within hysop.
+
+
+Sources:
+
+ * some fortran files which contain some subroutines inside some modules
+ * a pyf file
+
+
+
+ TO BE DONE !!!
+
+
+
+
+
+Kind values
+-----------
+
+According to f2py doc: "Currently, F2PY can handle only <type spec>(kind=<kindselector>) declarations where <kindselector> is a numeric integer (e.g. 1, 2, 4,...) but not a function call KIND(..) or any other expression. F2PY needs to know what would be the corresponding C type and a general solution for that would be too complicated to implement."
+
+To overcome this, a .f2py_f2cmap is generated during the build, from hysop/f2py_f2cmap.in.
+It contains all the required mappings defined as a dictionnary, like::
+
+ {'integer':{'c_int':'int'}, 'real':{'real64':'double', 'wp':'double'}}
+
+In that example, a fortran :code:'real(kind=wp)' will be mapped into a double-precision real in python.
+
+
+
diff --git a/docs/sphinx/figures/logo_hysop_couleur.eps b/docs/sphinx/figures/logo_hysop_couleur.eps
new file mode 100644
index 0000000000000000000000000000000000000000..cb76de857bad3e5b699cbfb72444177558b8bc94
--- /dev/null
+++ b/docs/sphinx/figures/logo_hysop_couleur.eps
@@ -0,0 +1,8563 @@
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+%%Creator: cairo 1.12.2 (http://cairographics.org)
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+%%Pages: 1
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+%%LanguageLevel: 3
+%%BoundingBox: 0 -1 343 135
+%%EndComments
+%%BeginProlog
+save
+50 dict begin
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+/c { curveto } bind def
+/h { closepath } bind def
+/re { exch dup neg 3 1 roll 5 3 roll moveto 0 rlineto
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+/S { stroke } bind def
+/f { fill } bind def
+/f* { eofill } bind def
+/n { newpath } bind def
+/W { clip } bind def
+/W* { eoclip } bind def
+/BT { } bind def
+/ET { } bind def
+/pdfmark where { pop globaldict /?pdfmark /exec load put }
+ { globaldict begin /?pdfmark /pop load def /pdfmark
+ /cleartomark load def end } ifelse
+/BDC { mark 3 1 roll /BDC pdfmark } bind def
+/EMC { mark /EMC pdfmark } bind def
+/cairo_store_point { /cairo_point_y exch def /cairo_point_x exch def } def
+/Tj { show currentpoint cairo_store_point } bind def
+/TJ {
+ {
+ dup
+ type /stringtype eq
+ { show } { -0.001 mul 0 cairo_font_matrix dtransform rmoveto } ifelse
+ } forall
+ currentpoint cairo_store_point
+} bind def
+/cairo_selectfont { cairo_font_matrix aload pop pop pop 0 0 6 array astore
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+/Tf { pop /cairo_font exch def /cairo_font_matrix where
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+/Td { matrix translate cairo_font_matrix matrix concatmatrix dup
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+ &=LCP?A_STWoIU-"C'+>9X%*Z2Jrr]mo6am~>
+Q
+Q Q
+showpage
+%%Trailer
+end restore
+%%EOF
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diff --git a/docs/sphinx/getting_started/index.rst b/docs/sphinx/getting_started/index.rst
new file mode 100644
index 0000000000000000000000000000000000000000..98de687efe4acece6a0a8d34cce5aeb53f0f74d1
--- /dev/null
+++ b/docs/sphinx/getting_started/index.rst
@@ -0,0 +1,136 @@
+.. _getting_started:
+
+
+############################
+Getting Started With HySoP
+############################
+
+Basics : running a simulation with HySoP
+========================================
+
+The problem to be solved must be described using Python language either interactively or in a python script.
+If you are not at ease with this language, we strongly encourage you to check one of the numerous python tutorials available on the web. Try for example https://docs.python.org/2/tutorial/. A basic understanding of numpy may also be useful : http://www.numpy.org.
+Numpy is the python package for scientific computing on which HySoP relies, especially for arrays handling.
+
+
+Some, python references:
+
+* https://www.python.org/about/gettingstarted/, for beginners with python
+* https://docs.python.org/2/, python official documentation, including tutorials
+* http://www.numpy.org, numpy, scipy documentation
+* http://hplgit.github.io/homepage/books.html
+
+Interactive session
+-------------------
+
+For an interactive use, we recommend ipython or even ipython notebook. Start the interpreter and then import hysop and/or its
+submodules. For example, try in a terminal window::
+
+ ipython
+
+and
+
+ >>> from hysop import Box
+ >>> from hysop.operator.poisson import Poisson
+ >>> dom = Box()
+
+Use script
+----------
+
+Interactive session is very useful for tests, basic understanding of hysop functionnalities but real simulation must
+be executed by using a script.
+
+To do so, write a python script 'myscript.py' which contains all python commands required to describe and solve your problem (see next part or user guide) and run in a terminal window::
+
+ python myscript.py
+
+for sequential run, or::
+
+ mpirun -np 4 python myscript.py
+
+for parallel run on 4 mpi processes.
+
+The best way to begin with HySoP is to try one of the numerous examples available in the distribution.
+
+
+Basics : describe a problem in HySoP
+====================================
+
+This short introduction presents the basic objects to know to describe and solve properly a problem with HySoP.
+
+HySoP provides a framework for flow simulation, based on particular methods. The workflow for such a simulation will be:
+
+* define a physical domain : geometry and boundary conditions,
+* define some scalar or vector fields on this domain, the unknowns,
+* describe which equations are applied on these unknowns, thanks to a sequence of operators,
+* configure these operators (space discretization, numerical methods ...),
+* define a time discretisation and initialize the operators and fields,
+* run the simulation : execute the sequence of operators at each time step,
+* post-process the results.
+
+Here is a short glossary of the objects which form a simulation process within HySoP:
+
+**Domain**: a physical domain, defined by its origin, its size and some types of boundary conditions. Different space discretisations and data distributions can be associated with a domain. See details in :ref:`domains`.
+
+**Fields**: the unknowns of your problem, the 'classical' mathematical vector or scalar fields, i.e. a function which associates a scalar or a vector to each point of the space.
+Fields obviously depends on time and space.
+
+**Operator**: a set of equations (most of the time ode), defined on a domain, with some fields as unknowns.
+
+**Problem**: a sequence of operators associated with a simulation.
+
+All of the objects defined above are high-level continuous objects, only descriptions indeed.
+In particular, none of them depends on the type of execution (parallel or sequential) and on the number of mpi processes involved.
+Indeed, to proceed with the simulation, it is necessary to define space and time discretization, to choose some numerical methods to solve each operator, in some words to configure and discretize the whole process. Thus, we need to introduce the following objects:
+
+**Discretization** : space discretization of the global domain (grid resolution, space step size ...).
+
+**Topology** : description of how data are distributed among mpi processes and of the space discretisation (global and local to each process)
+
+For details about discretisation and data distribution, check :ref:`topologies`.
+
+**Simulation**: description of the time discretisation (start and end time, time step ...)
+
+Consider for example the following advection problem,
+
+.. math::
+
+ \frac{\partial \rho(x,y,t)}{\partial t} + v(x,y,t).\nabla\rho(x,y,t) &=& 0
+
+
+where :math:`\rho`, a scalar field, and v, a vector field, are the unknowns, defined on a box-shaped domain with some given values on the boundaries
+and initial values at time :math:`t=t_0`.
+
+Then, in HySoP, you will have to define two *Fields*, representing :math:`\rho` and :math:`v`, a 2d domain, an operator 'advection' and a problem including only one operator. Such a process may look like::
+
+
+ from hysop import Box, Field, Discretization, Simulation
+ from hysop.operators import Advection
+
+ # A box-shaped 2d domain
+ dom = Box(length=[1., 1.], origin=[0., 0.])
+ # Choose a global space discretisation/grid resolution
+ d2d = Discretization([65, 65])
+ # Define some continuous fields
+ v = Field(domain=dom, name='velocity', is_vector=True)
+ rho = Field(domain=dom, name='rho')
+ # Define a continuous operator, that will be discretized
+ # according to d2d
+ adv = Advection(v, rho, discretization=d2d)
+ # Time discretization
+ simu = Simulation(nb_iter=100)
+
+ # ... some stuff to initialize fields values ...
+
+ # discretize operator and distribute data
+ adv.discretize()
+ adv.setup()
+
+ # solve advection for the current time
+ adv.apply(simu)
+
+ # ... post process ...
+
+
+Notice that you don't need a deep understanding about 'parallel' things, mpi or gpu, to use HySoP, at least for a basic usage.
+As you can see in the example above, we try to hide as much as possible those parallel stuff from the high-level user interface. Just keep in mind that your programm may run on several processes and that data may be distributed accross different memory areas.
diff --git a/docs/sphinx/hysop.bib b/docs/sphinx/hysop.bib
index 5ba5c1351f9b04a32d262f71e1ef471f682db7a9..63a5a0eae611353ecdb131dcf8a714f378faf3d6 100644
--- a/docs/sphinx/hysop.bib
+++ b/docs/sphinx/hysop.bib
@@ -42,3 +42,10 @@
Title = {A comparison of methods for evaluating time-dependent fluid dynamic forces on bodies, using only velocity fields and their derivatives},
Volume = {13},
Year = {1999}}
+
+@misc{cottet2000vortex,
+ title={Vortex methods: theory and practice},
+ author={Cottet, Georges-Henri and Koumoutsakos, Petros D},
+ year={2000},
+ publisher={Cambridge University Press}
+}
\ No newline at end of file
diff --git a/docs/sphinx/index.rst.in b/docs/sphinx/index.rst.in
index 1f86f101d59afb2a504e5898a9270a0cdbfc4127..a70e47b6ef165447fb4be63b39982cb68c75616d 100644
--- a/docs/sphinx/index.rst.in
+++ b/docs/sphinx/index.rst.in
@@ -13,7 +13,7 @@ HySoP software: hybrid simulation with particles
getting_started/index
users_guide/index
examples/index
-
+ reference/index
license
contacts
diff --git a/docs/sphinx/install_guide/index.rst b/docs/sphinx/install_guide/index.rst
new file mode 100644
index 0000000000000000000000000000000000000000..4e6ed9939f2779d0577feba7632894921c216f82
--- /dev/null
+++ b/docs/sphinx/install_guide/index.rst
@@ -0,0 +1,80 @@
+.. hysop_install_guide:
+
+HySoP installation guide
+========================
+
+
+HySoP is written in Python (main user interface and high level functionnalities) and Fortran.
+
+Quick start and install
+-----------------------
+
+::
+
+ cd path_to_build
+ cmake path_to_sources
+ make -j N
+ make install
+
+Note:
+
+* -jN for make command runs the build process on N processes. Choose a value of N that fits with your machine.
+* depending on your system you may need to set PYTHONPATH to where hysop has been installed::
+
+ export PYTHONPATH=hysop_install_path:${PYTHONPATH}
+
+ Check the end of cmake output, where the proper command will be indicated.
+
+
+
+
+Then just run python interactively and ::
+
+
+ >>> import hysop
+ >>> dir(hysop)
+
+
+or run python on an hysop example file::
+
+
+ mpirun -np 4 python your_file.py
+
+
+.. _hysop_config:
+
+Configuration options
+---------------------
+
+cmake configuration may be customized by user, using::
+
+ cmake -DOPTION_NAME=option_value path_to_source
+
+'OPTION_NAME' being one of the options described below.
+
+* FFTW_DIR : where to find fftw if it's not in a "standard" place.
+* WITH_SCALES=ON/OFF : to compile an HySoP version including scales (default = on)
+* WITH_TESTS=ON/OFF: enable testing (i.e. prepare target "make test", default = off)
+
+
+.. _hysop_dependencies:
+
+Dependencies
+------------
+
+* python > 2.7
+* a proper mpi implementation including a fortran compiler
+* fftw
+* cmake > 2.8
+* numpy, mpi4py, h5py
+
+
+.. _hysop_install:
+
+What will be installed
+----------------------
+
+* python package in PREFIX/lib/pythonX.Y/site-packages/hysop/
+* library in PREFIX/lib/pythonX.Y/site-packages/hysop/lib
+* fortran modules in PREFIX/lib/pythonX.Y/site-packages/hysop/include/Modules
+* CMake configuration files in PREFIX/lib/pythonX.Y/site-packages/hysop/share/CMake
diff --git a/docs/sphinx/reference/fortran_api.rst b/docs/sphinx/reference/fortran_api.rst
new file mode 100644
index 0000000000000000000000000000000000000000..deb94a0ec5990b238a3e138f90b65fa41b25b809
--- /dev/null
+++ b/docs/sphinx/reference/fortran_api.rst
@@ -0,0 +1,13 @@
+.. _fortran_api:
+
+Fortran, C/C++ API
+==================
+
+Documentation for functions and classes written in other languages than python is generated thanks
+to doxygen.
+
+This includes fftw and scales' interfaces.
+
+See `Fortran API <../../../DoxygenGeneratedDoc/html/index.html>`_.
+
+
diff --git a/docs/sphinx/users_guide/absorption_bc.rst b/docs/sphinx/users_guide/absorption_bc.rst
new file mode 100644
index 0000000000000000000000000000000000000000..1f16a5490d04810b789d19757ff1a67c2d593ebf
--- /dev/null
+++ b/docs/sphinx/users_guide/absorption_bc.rst
@@ -0,0 +1,91 @@
+.. _absorption_bc:
+
+
+Smooth solenoidal vorticity absorption at the outlet
+====================================================
+
+For sake of efficiency when solving the diffusion and the Poisson equation with FFTW library, periodic boundary conditions are prescribed at the
+domain walls in each direction. Then, one needs to apply a specific treatment on the flow fields in order to discard, in the downstream region,
+the eddies coming periodically from the outlet. This is done through an outlet absorption of the vorticity field.
+Let us first define the expression of the corrected velocity u ̃ allowing to recover a uniform flow field at the inlet :
+
+.. math::
+
+ \tilde u = f(x) u_{periodic} + (1 - f(x))u_{\infty},
+
+where f is the smoothing function defined as follows :
+
+.. math::
+
+ f(x) = \begin{cases}
+ 1, \text{ if } x < x_b\\
+ \frac{tanh(\epsilon(x - x_c)) - tanh(\epsilon(x_e - x_c))}{tanh(\epsilon(x_b - x_c)) - tanh(\epsilon(x_e - x_c))}, \text{ if } x_b < x < x_e \\
+ 0 \text{ if } x > x_e
+ \end{cases}
+
+
+with :math:`x_c = \frac{x_b + x_e}{2}` (we refer to the figure below for a schematic description of the absorption process).
+
+
+.. figure:: /figures/vorticity_absorption.*
+ :scale: 50 %
+
+One can notice that this velocity correction is only performed in the x-direction, that is to say in the
+flow direction: the periodicity is indeed maintained in the y and z directions.
+
+Then, the absorbed vorticity is given by :
+
+.. math::
+
+ \omega_{absorbed} &=& \ \nabla \times \tilde u \\
+ &=& \ f(x)\omega_{periodic} + \nabla f(x) \times u_{periodic} + \nabla(1 - f(x))\times u_{\infty}\\
+ &=&\left[\begin{array}{c}
+ \omega_xf(x) \\
+ \omega_yf(x) + f'(x)(u_\infty - u_z)\\
+ \omega_zf(x) - f'(x)(u_\infty - u_y)\\
+ \end{array}\right]
+
+
+Let us mention here that this absorption conserves the solenoidal property of the vorticity field, which is
+not the case when the vorticity is absorbed as follows :
+
+.. math::
+
+ \omega_{absorbed} = f(x) \omega_{periodic}
+
+Indeed, defining the absorbed vorticity as the curl of the absorbed velocity to project the vorticity in the space of divergence free vector fields
+(see :ref:`vorticity_projection`). In practice, vorticity absorption based on equation 6 is responsible for reflexion effects and produces spurious oscillations (see drag plots for instance).
+From an algorithmic point of view, the vorticity absorption is applied before solving the Poisson equation.
+
+
+The corresponding operator is :class:AbsorptionBC`, build with the standard parameters of all operators, plus:
+
+* a float, req_flow_rate, to set required value of the flow rate at the outlet.
+* a 'x_range' vector, to set the coordinates delimitating the absorption domain, x_range=[xb, xe]
+* an optional 'filter_func' parameter, list of two python functions, used to set the filter function and its derivative
+
+
+Example::
+
+ d3d = Discretization([33, 33, 33])
+ dom = Box([1., ] * dim)
+ v = Field(dom, name='velo', is_vector=True)
+ w = Field(dom, name='vorti', is_vector=True)
+ # -- Build and apply absorption operator on w --
+ # set flowrate
+ flowrate = VariableParameter(data=10.)
+ # set layer size
+ x_range = [0.9, 1.]
+ op = AbsorptionBC(v, w, flowrate, x_range,
+ discretization=d3d)
+ op.discretize()
+ op.setup()
+
+ simu = Simulation(nb_iter=100)
+ simu.initialize()
+
+ op.apply(simu)
+
+
+One may also choose user-defined functions to apply in the absorption area (in place of the tanh-like function shown above).
+See the example in test_absorption_bc.py file.
diff --git a/docs/sphinx/users_guide/adaptive_time_step.rst b/docs/sphinx/users_guide/adaptive_time_step.rst
new file mode 100644
index 0000000000000000000000000000000000000000..fc1ee3f587ce9c9713ceaef814fcfe7194e09452
--- /dev/null
+++ b/docs/sphinx/users_guide/adaptive_time_step.rst
@@ -0,0 +1,120 @@
+.. _adaptive_time_step:
+
+.. currentmodule:: hysop.operator
+
+Adaptive Time Step
+------------------
+
+The class :class:`~adapt_timestep.AdaptiveTimeStep` is used to compute a new time-step
+depending on some predifined criteria.
+
+Several criteria are available, depending on which is the stability condition of interest. All cases
+are listed below.
+
+:math:`u` and :math:`\omega` denote respectively the velocity and vorticity fields, while :math:`x_i` represents the space coordinates, d being the dimension of the space.
+
+Details on the different formulations and criteria can be found in :cite:`Chloe-thesis`.
+
+Stability condition for the advection scheme
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+In particle methods, the non-linear stability of the convection/remeshing scheme is ensured under the following condition on the time step:
+
+.. math::
+
+ dt_{adv} \leq\frac{LCFL}{\lVert \nabla u \rVert_\infty}
+
+where LCFL (the Lagrangian CFL) must satisfy :math:`LCFL \leq 1`
+
+Based or derived from this condition, the three following criteria are implemented in HySoP:
+
+* 'gradU' :
+
+ .. math::
+
+ dt \leq \frac{LCFL}{\max\limits_{0 \leq i < d} \ \left|\frac{\partial u_i}{\partial x_i}\right|}
+
+* 'vort' :
+
+ .. math::
+
+ dt \leq \frac{LCFL}{\max\limits_{0 \leq i < d} \left|\omega_i\right|}
+
+* 'strain' :
+
+ .. math::
+
+ dt \leq \frac{LCFL}{\max\limits_{0 \leq i < d} \ \sum\limits_{j=0}^{d-1} \left|\epsilon_{i,j}\right|}
+
+ where :math:`\epsilon = 0.5(\nabla u + \nabla u^T)` is the strain tensor.
+
+ .. math::
+
+ \epsilon_{i,j} = \frac{1}{2}(\frac{\partial u_i}{\partial x_j} + \frac{\partial u_j}{\partial x_i})
+
+Stability condition for the stretching scheme
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+* 'stretch' :
+
+ .. math::
+
+ dt \leq \frac{c_s}{\max\limits_{0 \leq i < d} \ \sum\limits_{j=0}^{d-1} \left|\frac{\partial u_i}{\partial x_j}\right|}
+
+where :math:`c_s` being a constant depending on the time integration scheme used to discretize the stretching equation. The following table gives the values of C for different time integration schemes :
+
+============= ===== ===========
+Scheme order :math:`c_s`
+============= ===== ===========
+Euler 1 2
+Runge-Kutta 2 2 2
+Runge-Kutta 3 3 2.5127
+Runge-Kutta 4 4 2.7853
+============= ===== ===========
+
+CFL-like stability condition
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The 'classical' CFL condition.
+
+* 'cfl' :
+
+ .. math::
+
+ dt \leq \frac{CFL\times h_0}{\max\limits_{0 \leq i < d} \left|u_i\right|}
+
+
+ :math:`h_0` is the space step in the first direction.
+
+
+
+When several criteria are chosen, the final time step will be set with the minimum value among
+all criteria.
+
+
+Usage
++++++
+
+.. code::
+
+ # Build and init
+ op = AdaptiveTimeStep(velocity, vorticity, simulation, lcfl, cfl, chosen_criteria, time_range, maxdt, ...)
+ op.discretize()
+ op.setup(rwork)
+
+ # Compute criteria AND update simulation time step
+ op.apply()
+ op.wait()
+
+* lcfl and cfl are optional with lcfl=0.125 and cfl=0.5 as default
+* chosen\_criteria (optional) is the list of the criteria to be applied. For example,
+ ['vort', 'gradU']. By default, 'vort' criterion is used.
+* time\_range (optional) may be use to define a range where the operator is applied.
+ This range is given in 'iteration number'. For example time\_range = [3, 20] means
+ the time step will be updated between iteration number 3 and 20.
+* maxdt (optional, default = 9999) may be used to set a maximum value allowed for the time
+ step, whatever the results of criteria computation are.
+* finite differences are used to compute the velocity derivatives which means that for some
+ criteria the topology must have ghost points.
+* wait call is very important and compulsory, since time-step may be shared between several
+ mpi inter-communicators (tasks).
+* see operators/tests/test_adapative_time_step.py for complete examples on the way to use this operator.
diff --git a/docs/sphinx/users_guide/advection.rst b/docs/sphinx/users_guide/advection.rst
new file mode 100644
index 0000000000000000000000000000000000000000..a2f80bb2e97b87c4524705d7359bbf07dd7c9758
--- /dev/null
+++ b/docs/sphinx/users_guide/advection.rst
@@ -0,0 +1,57 @@
+.. _advection:
+
+
+Advection operator
+==================
+
+Advection of one or more fields, i.e. find field X which solves
+
+.. math::
+
+ \frac{\partial{X}}{\partial{t}} + velocity.\nabla X = 0
+
+for a given velocity field and assuming incompressible flow.
+
+
+Multi-CPU (scales) advection
+----------------------------
+
+Scales :
+
+* Fortran routines
+* 3D only
+
+Available solvers:
+^^^^^^^^^^^^^^^^^^
+* 'p_O2' : order 4 method, corrected to allow large CFL number,
+ untagged particles
+* 'p_O4' : order 4 method, corrected to allow large CFL number,
+ untagged particles
+* 'p_L2' : limited and corrected lambda 2
+* 'p_M4' : Lambda_2,1 (=M'4) 4 point formula
+* 'p_M6' (default) : Lambda_4,2 (=M'6) 6 point formula
+* 'p_M8' : M8prime formula
+* 'p_44' : Lambda_4,4 formula
+* 'p_64' : Lambda_6,4 formula
+* 'p_66' : Lambda_6,6 formula
+* 'p_84' : Lambda_8,4 formula
+
+
+
+Splitting
+^^^^^^^^^
+
+Computations are performed with a dimensional splitting as follows:
+
+* 'strang' (2nd order):
+
+ * X-dir, half time step
+ * Y-dir, half time step
+ * Z-dir, full time step
+ * Y-dir, half time step
+ * X-dir, half time step
+
+* 'classic' (1st order):
+ * X-dir, full time step
+ * Y-dir, full time step
+ * Z-dir, full time step
diff --git a/docs/sphinx/users_guide/custom.rst b/docs/sphinx/users_guide/custom.rst
new file mode 100644
index 0000000000000000000000000000000000000000..74499c519d2aa96d0e3463d3b909efcf0746b926
--- /dev/null
+++ b/docs/sphinx/users_guide/custom.rst
@@ -0,0 +1,44 @@
+.. _custom:
+
+User-defined operator
+=====================
+
+A specific operator class, :class:`~hysop.operator.custom.Custom` is available in hysop to allow users to
+define their own operator.apply, thanks to a python function.
+
+
+.. code::
+
+ # v1, v2, v3 some continuous fields
+ iop = IOParams('somefile.dat', fileformat=IO.ASCII)
+ my_op = Custom(function=my_function, in_fields=[v1, v2], out_fields=[v3],
+ diagnostics_shape=(1,2), io_params=iop, ...)
+ my_op.discretize()
+ my_op.setup()
+
+ simu = Simulation(nb_iter=10)
+ my_op.apply(simu)
+
+
+A call to my_op.apply(simu) will run 'my_func(simu, [v1, v2], [v3], buffer)'
+and write 'buffer' into a file (defined as usual with iop).
+
+* my_func arguments list MUST match the following::
+
+ def my_func(sim, in_fields, out_fields=None, diagnostics=None):
+ # optionally compute out_fields depending on in_fields
+ out_fields[0].data[1] = 2 * in_fields[0].data[0]
+ # optionally compute some diagnostics
+ diagnostics[0,0] = sim.time
+ diagnostics[0,1] = out_fields[0].data[0].max()
+
+* diagnostics_shape arg must corresponds to the shape of the buffer written in the function
+ and buffer must be a 2D array (i.e. diagnostics_shape a tuple like (nx, ny)).
+
+* if diagnostics_shape is None, no file output will be done and obviously in that case,
+ diagnostics must not be filled in my_func
+
+* as usual real use-case are available in operator/test/test_custom.py
+
+
+
diff --git a/docs/sphinx/users_guide/diffusion.rst b/docs/sphinx/users_guide/diffusion.rst
new file mode 100644
index 0000000000000000000000000000000000000000..2356fbe5658dabb1360407471fae7e8982b6c1ca
--- /dev/null
+++ b/docs/sphinx/users_guide/diffusion.rst
@@ -0,0 +1,43 @@
+.. _diffusion:
+.. currentmodule:: hysop.operator.diffusion
+
+Diffusion Operator
+------------------
+
+
+The class :class:`Diffusion` is used to model and solve the following problem :
+
+.. math::
+
+ \frac{\partial \omega}{\partial t} &=& \nu\Delta\omega
+
+for the unknown vector field :math:`\omega` and a given constant viscosity value :math:`\nu`,
+
+with
+
+.. math::
+ \omega = \nabla \times velocity \\
+ \nabla . velocity = 0
+
+
+
+Examples
+^^^^^^^^
+
+
+::
+
+ from hysop.operator.diffusion import Diffusion
+ dom = Box()
+ d3d = Discretization([33, 33, 33])
+ topo = dom.create_topology(d3d)
+ om = Field(name='vorticity', is_vector=True, domain=dom)
+ om.randomize(topo)
+ op = Diffusion(vorticity=om, viscosity=0.3, discretization=topo)
+ op.discretize()
+ op.setup()
+ sim = Simulation(nb_iter=10)
+ sim.initialize()
+ while not sim.is_over:
+ op.apply(sim)
+ sim.advance()
diff --git a/docs/sphinx/users_guide/energy_enstrophy.rst b/docs/sphinx/users_guide/energy_enstrophy.rst
new file mode 100644
index 0000000000000000000000000000000000000000..a07a0b64b593c72b1f15a6da2cea89b5d59d4969
--- /dev/null
+++ b/docs/sphinx/users_guide/energy_enstrophy.rst
@@ -0,0 +1,49 @@
+.. _energy_enstrophy:
+
+
+Kinetic energy and enstrophy computation
+========================================
+
+
+For :math:`v(x, t), \omega(x,t)` some velocity and vorticity fields, the kinetic energy is defined as :
+
+.. math::
+
+ E_c = 0.5V_{\Omega}\int_\Omega v^2 d\Omega
+
+and the enstrophy as :
+
+.. math::
+
+ S = V_{\Omega}\int_\Omega \omega^2 d\Omega
+
+
+* Default value for :math:`V_{\Omega}` is :math:`\frac{1.}{||\Omega||}` with :math:`||\Omega||` the volume of the domain of definition of the fields, but it can be set to 1. by setting is_normalized parameter to False in the operator definition.
+* By default, the output file name is energy_enstrophy.
+
+Energy and enstrophy can be computed thanks to :class:`hysop.operator.energy_enstrophy.EnergyEnstrophy` operator
+as shown in the example below.
+
+
+::
+
+ from hysop.operators import EnergyEnstrophy
+ from hysop import Field, Box, Simulation, Discretization
+ d3d = Discretization([65, 65, 65])
+ box = Box()
+ velocity = Field(domain=box, name='velo', is_vector=True)
+ vorticity = Field(domain=box, name='vorti', is_vector=True)
+ op = EnergyEnstrophy(velocity, vorticity, discretization=d3d)
+ # Or
+ # op = EnergyEnstrophy(velocity, vorticity, discretization=d3d
+ # is_normalized=False)
+ op.discretize()
+ op.setup()
+ simu = Simulation(nb_iter=100)
+ # do some stuff on velocity and vorticity ...
+
+ op.apply(simu)
+ # --> compute energy and enstrophy for velocity and vorticity
+ # values at time simu.time
+ print op.energy
+ print op.enstrophy
diff --git a/docs/sphinx/users_guide/finite_differences.rst b/docs/sphinx/users_guide/finite_differences.rst
index 81d277931d12716dff1f41adee43ac36cf2b6e3f..24671a8cc6e2c3a7e89594fcb795aaf8e8dc0631 100644
--- a/docs/sphinx/users_guide/finite_differences.rst
+++ b/docs/sphinx/users_guide/finite_differences.rst
@@ -5,17 +5,17 @@
Finite differences schemes
--------------------------
-Differentiate some fields in one direction using finite differences.
+To differentiate some field(s) in one direction using finite differences.
-So, to compute
+If tab is a numpy array representing the discrete values of a scalar field :math:`\rho`
+on a grid, then to compute
.. math::
\begin{eqnarray}
result &=& \frac{\partial \rho}{\partial y}
\end{eqnarray}
-if tab is a numpy array representing the discrete values of the scalar field :math:`\rho`
-on a grid, then the basic usage of such schemes is :
+the basic usage of such schemes is :
.. code::
@@ -25,10 +25,10 @@ on a grid, then the basic usage of such schemes is :
dir = 1 # y direction
result = scheme(tab, dir, result)
-This will compute :
+with :
-result = diff(tab[indices], dir), diff depending on
-the chosen scheme.
+result[iout] = diff(tab[indices], dir), diff depending on
+the chosen scheme. See examples below to understand properly indices and iout.
Available schemes
@@ -42,75 +42,96 @@ Available schemes
A few important remarks
^^^^^^^^^^^^^^^^^^^^^^^
+* Mind that 'tab' arg is a numpy array not a field. Usually,
+ you will have to use some_field.data[i] as tab, some_field being a :class:`~hysop.fields.discrete.DiscreteField` and i the component number.
* step is the space discretization step size in each direction, i.e. a list or numpy array
- with d values, d being the dimension of the domain. A common case is :code::
+ with d values, d being the dimension of the domain. A common case is code::
step = topo.mesh.space_step
* indices represent the set of points on which the scheme must be applied. This is usually
- a list of slices, for example, :code::
+ a list of slices, for example, code::
- indices = topo.mesh.iCompute
+ indices = topo.mesh.compute_index
* result must be a predefined numpy array of the 'right' size, here the same size/shape as tab.
* To optimize memory usage and computational time, it's possible to reduce the size of
- the output and/or to apply the scheme on a subset of the domain. All available possibilities
- are summarized through the examples below.
-
-* the size of the ghost layer depends on the scheme but is not checked! You must ensure
- that topo.ghosts() >= scheme.minimal_ghost_layer.
+ the output and/or to apply the scheme on a subset of the domain.
+ scheme.indices represents the indices (in topo.mesh) of points for which the derivative will be computed.
+ scheme.output_indices are positions in result where the resulting derivative will be saved.
+ All available possibilities are summarized through the examples below.
+
+* The size of the ghost layer depends on the scheme but is not checked! You must ensure
+ that topo.ghosts() >= scheme.ghosts_layer_size.
-* for some schemes a work array may be provided during call. It must be a numpy array of
- the same size of the result. It's shape is not really important, since during call
+* For some schemes a work array may be provided during call. If so, it must be a numpy array of
+ the same size as result. It's shape is not really important, since during call
work will be reshaped to be of the same shape as result. This allows us to provide 1D array
that may be shared between different operators/methods whatever the internal required shapes are.
* Notice that most of the time, finite-differences are defined as internal methods of operators and work arrays management, indices list or ghosts layers are set/checked internally.
+
Default case : apply scheme on all the domain with a full-size result
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+This is the standard case where result and input tab have the same shape.
+Computation is performed on all grid points, excluding ghosts.
+
.. code::
from hysop.numerics.finite_differences import FDC2
+ # --- Domain, discretization and topology ---
box = Box(length=[1., 1.])
d2d = Discretization([33, 33], [1, 1])
topo = box.create_topology(d2d)
+ # --- Scalar field on the domain ---
rho = Field(box, name='rho')
# discretize and initialize rho
rd = rho.randomize(topo)
+ # --- Grid parameters required for FD scheme ---
# Get 'computational' points, i.e. grid points excluding ghosts
- ic = topo.mesh.iCompute
+ ic = topo.mesh.compute_index
# space step
step = topo.mesh.space_step
# field resolution on the grid defined by topo
shape = topo.mesh.resolution
+ # create a new array to save results
result = npw.zeros(shape)
+ # --- Create FD scheme ---
scheme = FDC2(step, ic)
- assert (topo.ghosts() >= scheme.minimal_ghost_layer).all()
+ assert (topo.ghosts() >= scheme.ghosts_layer_size).all()
+ # --- Apply FD scheme ---
+ # compute first derivative of scal on all points (except ghosts)
+ # of the 'topo' discretization of the domain
result = scheme(rd.data[0], 1, result)
In that case:
* result.shape = (34, 34)
-* scheme.indices = [slice(1,33), slice(1,33)]
-* scheme.output_indices = [slice(0,32), slice(0,32)]
+* scheme.indices = [slice(1,33), slice(1,33)] = topo.mesh.compute_index
+* scheme.output_indices = scheme.indices
+Notice that ghost points of result are not updated!
Apply scheme on all the domain with a reduced result
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-If you do not want to allocate ghosts points for the result, then use:
+Suppose that you want to compute a derivative on all the domain but
+use non-standard shape array to save the result. This may be useful
+if you do not want to allocate memory for ghost points in result.
.. code::
-
+
+ # Create a 'reduced-shape' result
+ # result shape == shape of topo.mesh without ghosts
shape = np.asarray(topo.mesh.resolution).copy()
shape -= 2 * topo.ghosts()
shape = tuple(shape)
result = npw.zeros(shape)
- scheme = FDC2(step, ic, indices_out=True)
- assert (topo.ghosts() >= scheme.minimal_ghost_layer).all()
+ # build and apply the scheme
+ scheme = FDC2(step, ic, output_indices=True)
result = scheme(rd.data[0], 1, result)
In that case:
@@ -120,8 +141,8 @@ In that case:
* scheme.output_indices = [slice(0,32), slice(0,32)]
-Apply scheme on a subset of the domain with a full-size result
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Apply scheme on a subset of the domain
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.. code::
@@ -131,14 +152,18 @@ Apply scheme on a subset of the domain with a full-size result
sl = topo.domain.length * 0.5
orig = topo.domain.origin + 0.1 * topo.domain.length
subbox = SubBox(parent=topo.domain, origin=orig, length=sl)
+ # then we get indices of points inside this subdomain, for
+ # the discretization 'topo'
indices = subbox.discretize(topo)[0]
+ # and build a FD scheme for this set of indices
scheme = FDC2(step, indices)
result = npw.zeros_like(rd.data[0])
result = scheme(rd.data[0], 1, result)
-In that case:
+In that case derivative is computed only inside subdomain and
+only the corresponding subpart of result is updated:
-* result.shape = (34,34)
+* result.shape = (34,34), i.e. same shape as the complete mesh of topo.
* scheme.indices = [slice(4,21), slice(4,21)]
* scheme.output_indices = scheme.indices
@@ -146,6 +171,9 @@ In that case:
Apply scheme on a subset of the domain with a reduced-size result
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Same as above but to limit memory print, a reduced-shape result
+is used
+
.. code::
# We define a subset of the domain,
@@ -155,7 +183,9 @@ Apply scheme on a subset of the domain with a reduced-size result
orig = topo.domain.origin + 0.1 * topo.domain.length
subbox = SubBox(parent=topo.domain, origin=orig, length=sl)
indices = subbox.discretize(topo)[0]
- scheme = FDC2(step, indices, indices_out=True)
+ # build and apply a FD scheme, notice the output_indices arg!
+ scheme = FDC2(step, indices, output_indices=True)
+ # result shape is computed using discretized subdomain shape
shape = subbox.mesh[topo].resolution
result = npw.zeros(shape)
result = scheme(rd.data[0], 1, result)
@@ -164,7 +194,7 @@ In that case:
* result.shape = (17,17)
* scheme.indices = [slice(4,21), slice(4,21)]
-* scheme.output_indices = [slice(0,17), slice(0,17)]scheme.indices
+* scheme.output_indices = [slice(0,17), slice(0,17)]
Apply scheme on a subset of the domain with a predifined-size result
@@ -183,17 +213,18 @@ the values of the computed derivative.
subbox = SubBox(parent=topo.domain, origin=orig, length=sl)
indices = subbox.discretize(topo)[0]
shape = subbox.mesh[topo].resolution
- result = npw.zeros_like(rd.data[0)
+ result = npw.zeros_like(rd.data[0])
+ # output_indices are explicitely given
iout = [slice(2, 19), slice(3, 20)]
- scheme = FDC2(step, indices, indices_out=iout)
+ scheme = FDC2(step, indices, output_indices=iout)
result = scheme(rd.data[0], 1, result)
In that case:
* result.shape = (17,17)
* scheme.indices = [slice(4,21), slice(4,21)]
-* scheme.output_indices = iout
+* scheme.output_indices = iout = [slice(2, 19), slice(3, 20)]
-This option is usefull when input tab is a work array, with a size different
+This option is useful when input tab is a work array, with a size different
from the topology resolution, and the result a field defined on the whole grid.
diff --git a/docs/sphinx/users_guide/finite_differences.rst.orig b/docs/sphinx/users_guide/finite_differences.rst.orig
new file mode 100644
index 0000000000000000000000000000000000000000..a40d96f71287ca95ca7715cf452eb7469e6913fc
--- /dev/null
+++ b/docs/sphinx/users_guide/finite_differences.rst.orig
@@ -0,0 +1,235 @@
+.. _finite_differences:
+
+.. currentmodule:: hysop.numerics.finite_differences
+
+Finite differences schemes
+--------------------------
+
+Differentiate some fields in one direction using finite differences.
+
+So, to compute
+
+.. math::
+ \begin{eqnarray}
+ result &=& \frac{\partial \rho}{\partial y}
+ \end{eqnarray}
+
+<<<<<<< HEAD
+if tab is a numpy array representing the discrete values of the scalar field `:math: \rho`
+on a grid, then the basic usage of such schemes is :
+
+.. code::
+
+=======
+if tab is a numpy array representing the discrete values of the scalar field :math:`\rho`
+on a grid, then the basic usage of such schemes is :
+
+.. code::
+
+>>>>>>> master
+ # Build/declare the scheme for a given space discretization
+ scheme = FDC2(step, indices)
+ # Apply scheme on the array
+ dir = 1 # y direction
+ result = scheme(tab, dir, result)
+
+This will compute :
+
+<<<<<<< HEAD
+result[scheme.output_indices] = diff(tab[indices], dir), diff depending on
+the chosen scheme.
+
+A few important remarks:
+
+* step is the space discretization step size in each direction, i.e. a list of numpy array
+ with d values, d being the dimension of the domain.
+* indices represent the set of points on which the scheme must be applied.
+* result must be a predefined numpy array of the 'right' size, here the same size/shape as tab.
+* In the previous default case, output_indices and input_indices are the same.
+* To optimize memory usage and computational time, it's possible to reduce the size of
+ the output and/or to apply the scheme on a subset of the domain. All available possibilities
+ are summarized through the examples below.
+* the size of the ghost layer depends on the scheme but is not checked! You must ensure
+ that topo.ghosts() >= scheme.minimal_ghost_layer
+=======
+result = diff(tab[indices], dir), diff depending on
+the chosen scheme.
+
+
+Available schemes
+^^^^^^^^^^^^^^^^^
+
+* :class:`~FDC2` : first derivative, 2nd order centered scheme
+* :class:`~FD2C2`: second derivative, 2nd order centered scheme
+* :class:`~FDC4`: first derivative, 4th order centered scheme
+
+
+A few important remarks
+^^^^^^^^^^^^^^^^^^^^^^^
+
+* step is the space discretization step size in each direction, i.e. a list or numpy array
+ with d values, d being the dimension of the domain. A common case is :code::
+
+ step = topo.mesh.space_step
+
+* indices represent the set of points on which the scheme must be applied. This is usually
+ a list of slices, for example, :code::
+
+ indices = topo.mesh.iCompute
+
+* result must be a predefined numpy array of the 'right' size, here the same size/shape as tab.
+
+* To optimize memory usage and computational time, it's possible to reduce the size of
+ the output and/or to apply the scheme on a subset of the domain. All available possibilities
+ are summarized through the examples below.
+
+* the size of the ghost layer depends on the scheme but is not checked! You must ensure
+ that topo.ghosts() >= scheme.minimal_ghost_layer.
+
+* for some schemes a work array may be provided during call. It must be a numpy array of
+ the same size of the result. It's shape is not really important, since during call
+ work will be reshaped to be of the same shape as result. This allows us to provide 1D array
+ that may be shared between different operators/methods whatever the internal required shapes are.
+
+* Notice that most of the time, finite-differences are defined as internal methods of operators and work arrays management, indices list or ghosts layers are set/checked internally.
+>>>>>>> master
+
+Default case : apply scheme on all the domain with a full-size result
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code::
+
+ from hysop.numerics.finite_differences import FDC2
+ box = Box(length=[1., 1.])
+ d2d = Discretization([33, 33], [1, 1])
+ topo = box.create_topology(d2d)
+ rho = Field(box, name='rho')
+ # discretize and initialize rho
+ rd = rho.randomize(topo)
+ # Get 'computational' points, i.e. grid points excluding ghosts
+ ic = topo.mesh.iCompute
+ # space step
+ step = topo.mesh.space_step
+ # field resolution on the grid defined by topo
+ shape = topo.mesh.resolution
+ result = npw.zeros(shape)
+ scheme = FDC2(step, ic)
+ assert (topo.ghosts() >= scheme.minimal_ghost_layer).all()
+ result = scheme(rd.data[0], 1, result)
+
+In that case:
+
+* result.shape = (34, 34)
+* scheme.indices = [slice(1,33), slice(1,33)]
+* scheme.output_indices = [slice(0,32), slice(0,32)]
+
+
+Apply scheme on all the domain with a reduced result
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+If you do not want to allocate ghosts points for the result, then use:
+
+.. code::
+
+ shape = np.asarray(topo.mesh.resolution).copy()
+ shape -= 2 * topo.ghosts()
+ shape = tuple(shape)
+ result = npw.zeros(shape)
+ scheme = FDC2(step, ic, indices_out=True)
+ assert (topo.ghosts() >= scheme.minimal_ghost_layer).all()
+ result = scheme(rd.data[0], 1, result)
+
+In that case:
+
+* result.shape = (32,32)
+* scheme.indices = [slice(1,33), slice(1,33)]
+* scheme.output_indices = [slice(0,32), slice(0,32)]
+
+
+Apply scheme on a subset of the domain with a full-size result
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code::
+
+ # We define a subset of the domain,
+ # a box of size half of the domain size.
+ from hysop.domain.subsets import SubBox
+ sl = topo.domain.length * 0.5
+ orig = topo.domain.origin + 0.1 * topo.domain.length
+ subbox = SubBox(parent=topo.domain, origin=orig, length=sl)
+ indices = subbox.discretize(topo)[0]
+ scheme = FDC2(step, indices)
+ result = npw.zeros_like(rd.data[0])
+ result = scheme(rd.data[0], 1, result)
+
+In that case:
+
+* result.shape = (34,34)
+* scheme.indices = [slice(4,21), slice(4,21)]
+* scheme.output_indices = scheme.indices
+
+
+Apply scheme on a subset of the domain with a reduced-size result
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code::
+
+ # We define a subset of the domain,
+ # a box of size half of the domain size.
+ from hysop.domain.subsets import SubBox
+ sl = topo.domain.length * 0.5
+ orig = topo.domain.origin + 0.1 * topo.domain.length
+ subbox = SubBox(parent=topo.domain, origin=orig, length=sl)
+ indices = subbox.discretize(topo)[0]
+ scheme = FDC2(step, indices, indices_out=True)
+ shape = subbox.mesh[topo].resolution
+ result = npw.zeros(shape)
+ result = scheme(rd.data[0], 1, result)
+
+In that case:
+
+* result.shape = (17,17)
+* scheme.indices = [slice(4,21), slice(4,21)]
+* scheme.output_indices = [slice(0,17), slice(0,17)]scheme.indices
+
+
+Apply scheme on a subset of the domain with a predifined-size result
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Here you can choose explicitely where in result you want to put
+the values of the computed derivative.
+
+
+.. code::
+
+ # We define a subset of the domain,
+ # a box of size half of the domain size.
+ from hysop.domain.subsets import SubBox
+ sl = topo.domain.length * 0.5
+ orig = topo.domain.origin + 0.1 * topo.domain.length
+ subbox = SubBox(parent=topo.domain, origin=orig, length=sl)
+ indices = subbox.discretize(topo)[0]
+ shape = subbox.mesh[topo].resolution
+ result = npw.zeros_like(rd.data[0)
+ iout = [slice(2, 19), slice(3, 20)]
+ scheme = FDC2(step, indices, indices_out=iout)
+ result = scheme(rd.data[0], 1, result)
+
+In that case:
+
+* result.shape = (17,17)
+* scheme.indices = [slice(4,21), slice(4,21)]
+* scheme.output_indices = iout
+
+This option is usefull when input tab is a work array, with a size different
+from the topology resolution, and the result a field defined on the whole grid.
+
+<<<<<<< HEAD
+
+Available schemes
+^^^^^^^^^^^^^^^^^
+
+* :class:`~FDC2` : first derivative, 2nd order centered scheme
+* :class:`~FD2C2`: second derivative, 2nd order centered scheme
+* :class:`~FDC4`: first derivative, 4th order centered scheme
+=======
+>>>>>>> master
diff --git a/docs/sphinx/users_guide/forces.rst b/docs/sphinx/users_guide/forces.rst
index 2b6c6c93e506ca941881ad4bcd5c14d1572cdad7..bc96aa9970f33968e60c0d51ae2efbd30593d2aa 100644
--- a/docs/sphinx/users_guide/forces.rst
+++ b/docs/sphinx/users_guide/forces.rst
@@ -6,24 +6,27 @@ Drag and lift computation
.. currentmodule:: hysop.operator.drag_and_lift
Two operators are dedicated to drag and lift computation: :class:`MomentumForces` and :class:`NocaForces`.
+Both formulations are detailed below.
+SHOULD BE REVIEWED
+
Momentum formula
-----------------
-Reference?
+See :cite:`Chloe-thesis` for more details.
The :class:`Momentum` may be used to compute Drag and lift forces as :
.. math::
- Forces = \int_O (\tilde v - v_k) dt
+ Forces = Coeff * \frac{d}{dt}\int_O (u_k - \tilde u) dt
-O is the obstacle inside the flow and :math:`\tilde v` is the penalised velocity, such that :
+O is the obstacle inside the flow and :math:`\tilde u` is the velocity inside the obstacle (i.e. the penalised velocity), such that :
.. math::
- \tilde v = -\chi_O\frac{v_k}{1 + \lambda dt}
+ \tilde v = \chi_O\frac{v_k}{1 + \lambda dt}
where :math:`v_k` is the current velocity, dt the time step, :math:`\lambda` a penalisation coefficient, with :math:`\chi` the indicator function of the obstacle:
@@ -35,7 +38,6 @@ where :math:`v_k` is the current velocity, dt the time step, :math:`\lambda` a p
0 & \ if x \notin O
\end{align}\right. \ \forall x \in \Omega
-
Notice that this formula depends only on the velocity and on the obstacle but requires a penalisation.
The velocity is not impacted by this operator, a temporary buffer is used for all penalisation operations.
@@ -45,30 +47,47 @@ Noca's formula
See :cite:`Noca-1999` or even :cite:`Noca-thesis` for the whole details about Noca's formulation.
+All Noca's formula are implemented in HySoP as
+
+ * :class:`NocaI` for the "impulse equation"
+ * :class:`NocaII` for the "momentum equation"
+ * :class:`NocaIII` for the "flux equation"
+
+
+
+Usage
+-----
+
+.. code::
-About buffers
--------------
+ # Build and init
+ force_1 = MomentumForces(velocity=velo, discretization=topo,
+ obstacles=obst, penalisation_coeff=[1e8],
+ io_params=IOParams('Momentum'),
+ normalization=some_coeff)
+ # Noca : choose formulation = 1, 2 or 3
+ force_2 = MomentumForces(velocity=velo, vorticity=vorti, discretization=topo,
+ nu=0.3, obstacles=obst, formulation=1,
+ normalization=some_coeff)
+ force_1.discretize()
+ force_2.discretize()
+ force_1.setup()
+ force_2.setup()
-Depending on the formula used, some buffers are required to compute time derivatives of velocity, inside the control box or on its surfaces.
+ # Compute drag and lift ...
+ force1.apply(simu)
+ force2.apply(simu)
-D is the domain dimension.
-Faces are sorted in this order : [xmin, xmax, ymin, ymax ...], index gives s_id.
-For each face, i_n is the normal direction, i_t the tangential directions.
-self._previous_velo is a list of D * D * 2 components.
-with self_previous_velo[s_id * D + j] corresponding to velocity, component j on face
-s_id.
-
-Noca I :
- * buffer for integral on the volume : a D dim vector, save the sum over points inside
- the control box
- *
+ print force1.forces()
+ print force2.drag()
+ print force1.lift()
-Noca II:
- * buffer on for integral on the volume, same as Noca I.
- * for each face, we need time derivative of velocity components of index i_t --> 2 buffers for each face.
-Noca III:
- * for each face, we need time derivative of all velocity components
- --> 3 buffers for each face.
- *
+Notes :
+ * A penalisation coefficient is required for MomentumForces.
+ * obstacle must be a list of :class:`~hysop.domain.subsets.Subset` but is
+ optional for Noca formulations.
+ * For Noca, a volume of control may be provided to define the domain used to compute
+ the forces. By default a box of about 90% of the size of the domain is used.
+ * As usual some examples may be found in operator/tests/test_drag_and_lift.py
diff --git a/docs/sphinx/users_guide/odesolvers.rst b/docs/sphinx/users_guide/odesolvers.rst
index 5408afcb89936ef81d24eb3e1af033ba7e780af9..13909c7b213cb6817462bde64ef9f5112095660d 100644
--- a/docs/sphinx/users_guide/odesolvers.rst
+++ b/docs/sphinx/users_guide/odesolvers.rst
@@ -13,7 +13,7 @@ Consider the following problem:
y(x, t_0) &=& y_0
-with y and rhs some vector fields.
+with y and rhs some vector fields defined on a 1,2 or 3D domain.
The following time integrators are implemented in hysop:
@@ -25,10 +25,11 @@ Usage
::
- # Build
- ti = Euler(nb_components=2, topo=topo, f=func)
+ # Build the system with 'some_func' as right-hand side
+ ti = Euler(nb_components=2, topo=topo, f=some_func)
- # Solve
+ # integrate between t and t+dt, with y representing y(x,t) on topo,
+ # save y(x,t+dt) in result:
result = ti(t, y, dt, result)
@@ -36,16 +37,15 @@ Usage
To build a time integrator, it is necessary to define a python function to compute the right-hand side.
This function must be of the following form::
- def some_name(t, y, work):
+ def some_func(t, y, work):
work[0][...] = ...
work[1][...] = ...
...
return work
-with y and work some lists of numpy arrays of length nb_components, nb_components being the number of
-components of the right-hand side. y must not be modified by the function and work must contain the result of the computation. t is the time.
-
-
-
-to set the number of components of the rhs
+* nb_components being the number of components of the right-hand side.
+* y and work some lists of numpy arrays of length nb_components
+* t is the time
+* y must not be modified by the function
+* work must contain the result of the computation
diff --git a/docs/sphinx/users_guide/operators.rst b/docs/sphinx/users_guide/operators.rst
index 985a67bbef2a8f164425228d23541a061b11929a..6da590e093373149080aa6c1f478faf1c04ff01c 100644
--- a/docs/sphinx/users_guide/operators.rst
+++ b/docs/sphinx/users_guide/operators.rst
@@ -1,35 +1,62 @@
.. _operators:
-Operators
-==========
+Operators in HySoP, basic ideas
+================================
+This is an introduction about all kinds of operators available in HySoP with the basic ideas
+and common tools shared between all operators. You should read this whole section before any attempt
+to use a specific operator.
-An operator is an abstract object that handles a set of continuous variables
-and has an 'apply' function that modifies some of these variables.
+Continuous operators
+--------------------
-Available operators:
+A **continuous operator** is an object that handles a set of continuous fields, depending on time and space,
+with an 'apply' function that may modify some of these variables.
-.. toctree::
+For example, consider the advection of a scalar :math:`\rho` at velocity v, as defined in the following system
- poisson
- stretching
- advection
- forces
- penalisation
+.. math::
-Examples
----------
+ \frac{\partial{\rho(x, t}}{\partial{t}} + v(x,t).\nabla \rho(x,t) = 0
-To define and apply the advection of a scalar rho at velocity v Code::
+To simulate this problem, an advection operator must be defined as Code::
+ # v and rho some pre-defined continuous fields
advec = hysop.operator.advection(v, rho, ...)
+ advec.discretize()
advec.setup()
...
advec.apply()
+Obviously, many other parameters are required, such as which methods will be used for the space discretisation, the time integration and so on. This depends on each operator and will be detailed later.
+
+An operator is determined by
+
+* its name which sets the 'type' of problem it handles,
+* a list of variables, the continuous fields, defined on one and only one domain,
+* an mpi-task,
+* some i/o parameters.
+
+.. toctree::
+ :maxdepth: 2
+
+
+Variables
+^^^^^^^^^
+
+Each operator is associated with a set of continuous fields splitted into 'input' (read only) and
+'output' (read and write) variables.
+
+.. toctree::
+ :maxdepth: 2
+discrete_op
+ operators_io
+
+Computational operators
+-----------------------
-About 'method' arg in operator init
------------------------------------
+Methods
+^^^^^^^
Method argument must be a dictionnary with some of the following keys/values:
@@ -39,50 +66,55 @@ preset dictionnaries.
Keys in methods dict are given in hysop.method_keys.
+Discretisation and setup
+^^^^^^^^^^^^^^^^^^^^^^^^
-Internal work arrays management
--------------------------------
-.. currentmodule:: hysop.operator.computational
-
-Internal temporary buffers may be required by computational operators (buffers for Runge-Kutta scheme for example). By default, each operator handles its own work arrays and manage their memory.
+Each computational operator has a 'discretize' method, which:
-But, to improve performance and limit the required memory amount, user can provide some external
-storage for those arrays, for example to share them between several operators.
+* check if each continuous field of the operator (in variables) is associated with either a :class:`~hysop.tools.parameters.Discretization` or a :class:`~hysop.mpi.topology.Cartesian`
+* discretize, if needed, each continuous field,
-Each operator has a :py:meth:`~Computational.get_work_properties` function, returning information on the required memory for internal stuff.
-This function returns a dictionnary with the following keys:
- * 'rwork' : parameters for internal real arrays
- * 'iwork' : parameters for internal integer arrays
+and a 'setup' function which creates a discrete operator and ensure that the operator is ready for simulation. This function handles also internal work arrays management (see below).
-To each key corresponds a value which may be either 'None' if no internal memory is required
-or a list of tuples, each tuple being the shape of the required array.
+So, the correct and required sequence for each computational operator is::
-For example:
-
- >>> op = ...
- >>> op.discretize()
- >>> work_params = op.get_work_properties()
- >>> print work_params
- {'rwork': [(12, 12), (45, 12, 33)], 'iwork': None}
-
+ # build
+ op = Operator(...)
+ # discretize
+ op.discretize()
+ # make it ready for apply
+ op.setup(rwork=..., iwork=...)
-means that op requires two real arrays, of shape (12,12) and (45, 12, 33) while no
-integer arrays is needed.
+.. toctree::
+ :maxdepth: 2
-Note that this function must be called after discretization, else the operator may lack some
-information about local resolution and data distribution.
+ work_arrays
-Then, if needed, one may set internal arrays for the operator with setup optional parameters, as in the example below:
- >>> myrwork = []
- >> for shape in work.params['rwork']
- ... myrwork.append(npw.zeros(shape))
+Data-distribution operators
+---------------------------
- >>> op.setup(rwork=myrwork)
- >>> # And this work may be used by another operator
- >>> op2.setup(rwork=myrwork
+Discrete operators
+------------------
+A **discrete operator** is the representation of the space discretisation of a continuous operator, i.e.
+a discrete object which applies on some discrete fields. Such an object is associated with at least one
+topology (but maybe several for multi-resolution operators).
-Warning: obviously, data in work arrays may ne modified at any time by the operator.
-
+Review
+------
+
+.. toctree::
+ :maxdepth: 2
+
+ absorption_bc
+ poisson
+ diffusion
+ forces
+ penalisation
+ adaptive_time_step
+ advection
+ stretching
+ energy_enstrophy
+ custom
diff --git a/docs/sphinx/users_guide/operators_io.rst b/docs/sphinx/users_guide/operators_io.rst
new file mode 100644
index 0000000000000000000000000000000000000000..c87976a8083baf1ef63940eda41460326eb7b05b
--- /dev/null
+++ b/docs/sphinx/users_guide/operators_io.rst
@@ -0,0 +1,8 @@
+.. _operators_io:
+
+
+Setting I/O for operators
+=========================
+
+
+Todo : explain how to set I/O for operators using Writer class ...
diff --git a/docs/sphinx/users_guide/poisson.rst b/docs/sphinx/users_guide/poisson.rst
index 7a40e71364d238a55cce24bfbd987308f7eac617..edba19f18f365ddb1892755faeab3e3e1e12a7f9 100644
--- a/docs/sphinx/users_guide/poisson.rst
+++ b/docs/sphinx/users_guide/poisson.rst
@@ -10,7 +10,7 @@ Poisson Operator
The class :class:`Poisson` is used to model and solve the following problem :
.. math::
- \nabla \psi = -\omega \\
+ \Delta \psi = -\omega \\
v = \nabla \times \psi
with
@@ -21,8 +21,8 @@ with
-Examples:
----------
+Examples
+^^^^^^^^
Code::
diff --git a/docs/sphinx/users_guide/remeshing_and_interpolation.rst b/docs/sphinx/users_guide/remeshing_and_interpolation.rst
new file mode 100644
index 0000000000000000000000000000000000000000..a5d69e721a8901b367dded4e11d4d3c5a9dc3398
--- /dev/null
+++ b/docs/sphinx/users_guide/remeshing_and_interpolation.rst
@@ -0,0 +1,60 @@
+.. _remesh_and_interpolate:
+
+
+Interpolation and remeshing methods
+===================================
+
+Interpolation
+-------------
+
+Use :class:`~hysop.numerics.interpolation.Linear to interpolate a field (scalar or vector)
+from one mesh to another.
+
+
+:class:`~hysop.numerics.interpolation.Interpolation
+
+**What**: interpolation of a field, defined as a numpy array from one "grid" to another.
+
+To interpolate a field, the following inputs are required:
+
+* a 'source' grid, provided as a :class:`~hysop.mpi.topology.Cartesian`
+* a 'target' grid, i.e. the coordinates of the points on which the field will be interpolated.
+ May be defined with a :class:`~hysop.mpi.topology.Cartesian` or with the shape of a mesh.
+
+
+
+
+* requirements for position parameter
+
+ * :math:`shape[d] == topo_target.mesh.resolution[d] \forall d \neq idir` where idir is the interpolation direction.
+ * :math:`shape[idir] \leq topo_target.mesh.compute_resolution[d]`
+
+
+
+Devel notes
+-----------
+
+topo_source :
+
+* used to compute/get the 'left points' coordinates
+* ghost points layer size must fit with interpolation scheme
+* used to compute/get space step size
+* used to compute/get domain origin
+
+
+topo_target :
+
+* used to compute work arrays shape
+* must be included into topo_source domain
+* used to compute/get list of indices of interpolated points
+
+We must take into account the three cases below:
+
+* interpolate from one grid to another, grid defined as topology. Easy case, we know both topo/
+* interpolate from one grid to 'particles', when particles are initialized everywhere on a grid.
+ We also know both topo so, it works.
+* interpolate from one grid to 'particles' when a threshold is used to initialize particles.
+ In that case, the set of indices of particles must be provided to the interpolation caller since
+ topo_target is not known (not defined indeed). This to set the variable ic in __call__.
+ THIS REMAINS TO BE DONE/TEST PROPERLY
+
diff --git a/docs/sphinx/users_guide/space.rst b/docs/sphinx/users_guide/space.rst
new file mode 100644
index 0000000000000000000000000000000000000000..fde0556b2ef06721130f2531bf716431edda7604
--- /dev/null
+++ b/docs/sphinx/users_guide/space.rst
@@ -0,0 +1,14 @@
+.. _toc_dom:
+
+Domains, data distribution and space discretisation
+===================================================
+
+
+Roughly speaking, building a problem in HySoP consists in describing some fields (vectors and/or scalars), defined on physical domains, then some operators are applied to compute the behavior of those fields in time and space. This part of the manual describes fields, domains and the way data are discretized and distributed in space.
+
+.. toctree::
+ :maxdepth: 2
+
+ domains
+ subsets
+ redistribute
diff --git a/docs/sphinx/users_guide/stretching.rst b/docs/sphinx/users_guide/stretching.rst
new file mode 100644
index 0000000000000000000000000000000000000000..c8a37b0e951aa5177e595d804734a51f00e21a25
--- /dev/null
+++ b/docs/sphinx/users_guide/stretching.rst
@@ -0,0 +1,93 @@
+.. _stretching:
+
+Stretching
+==========
+
+.. currentmodule:: hysop.operator.stretching
+
+The stretching equation, :math:`\frac{\partial\omega}{\partial t} = (\omega.\nabla)u`
+which models the lengthening of vortices in a three-dimensional flow,
+may be given under several formulations :cite:`Cottet2000vortex`:
+
+
+.. math::
+
+ \frac{\partial\omega}{\partial t} &=& [\nabla u] . \omega \\
+ &=& [\nabla u]^T . \omega \\
+ &=& \nabla.(\omega:u)
+
+
+
+
+Solve
+
+Two formulations are proposed :
+
+* operator :class:`Conservative`, which corresponds to the resolution of the conservative form:
+
+ .. math::
+
+ \frac{\partial \omega}{\partial t} = div(\omega : u)
+
+* operator :class:`GradUW`, which corresponds to the resolution of:
+
+ .. math::
+
+ \frac{\partial \omega}{\partial t} = [\nabla u]^T . \omega
+
+
+The default is 'conservative'.
+
+Usage
+-----
+
+
+TO BE REVIEWED
+.. code::
+
+ m_guv = {Formulation:'GradUW', TimeIntegrator='RK3', SpaceDiscretisation='FDC4'}
+ stretch_graduv = Stretching(velocity=v, vorticity=w, discretisation=some_topo, method=m_guv
+ m_cons = {Formulation:'GradUW', TimeIntegrator='RK3', SpaceDiscretisation='FDC4'}
+ stretch_conservative = Stretching(velocity=v, vorticity=w, discretisation=some_topo, method=m_cons)
+
+
+ stretch = Conservative(velocity=v, vorticity=w, discretisation=some_topo,
+ method={Formulation:'GradUW', TimeIntegrator='RK3', SpaceDiscretisation='FDC4')
+
+
+
+Linearized Stretching
+---------------------
+
+In the context of a global linear stability study of the Navier-Stokes equation, one may have to formulate and solve
+a "linearized stretching". See details in :ref:`global_linear_stability`.
+
+Let us decompose the vorticity and the velocity fields into the sum of the steady state solution, :math:`(.)_b`, and a perturbation,
+:math:`(.)'`:
+
+.. math::
+
+ (\omega,u) = (\omega' + \omega_b, u' + u_b)
+
+then the stretching part of the governing equations writes:
+
+.. math::
+
+ \frac{\partial\omega'}{\partial t} = \underbrace{(\omega'\cdot\nabla)u_b}_{A} + \underbrace{(\omega_b\cdot\nabla)u'}_{B}
+
+
+The corresponding operator is :class:`StretchingLinearized`, built with the same parameters as for the standard stretching
+plus two fields corresponding to the steady state part of the velocity and the vorticity ('BF' below stands for 'Base Flow'):
+
+
+.. code::
+
+ stretch_lin = StretchingLinearized(velocity_BF=v_b, vorticity_BF=w_b,
+ velocity=v, vorticity=w, ...)
+
+
+Notice that time-integrator for part A of the equation above is user-defined but set to Euler scheme for part B.
+
+
+
+
diff --git a/docs/sphinx/users_guide/vorticity_projection.rst b/docs/sphinx/users_guide/vorticity_projection.rst
new file mode 100644
index 0000000000000000000000000000000000000000..7c346f1cca9ddf1fb4d8d7763d2a4e6335dd8bd9
--- /dev/null
+++ b/docs/sphinx/users_guide/vorticity_projection.rst
@@ -0,0 +1,10 @@
+.. _vorticity_projection:
+
+
+Vorticity solenoidal projection using 3D Helmholtz decomposition
+================================================================
+
+
+To be done ...
+See french doc in latex
+
diff --git a/examples/.gitignore b/examples/.gitignore
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..47d84e5623e3321f0b342c09b39f7f428f877038 100644
--- a/examples/.gitignore
+++ b/examples/.gitignore
@@ -0,0 +1 @@
+advection_gpu/
diff --git a/examples/advection_gpu.py b/examples/advection_gpu.py
new file mode 100644
index 0000000000000000000000000000000000000000..1dac067c5450fd9d676aa78ef1404368858158c5
--- /dev/null
+++ b/examples/advection_gpu.py
@@ -0,0 +1,138 @@
+
+from hysop.constants import np
+from hysop.methods_keys import TimeIntegrator, Remesh, ExtraArgs, \
+ Splitting, MultiScale, Interpolation, Precision, \
+ StretchingFormulation, BoundaryCondition, Backend
+
+from hysop.gpu.kernel_autotuner import AutotunerConfig, AutotunerFlags
+
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.problem.simulation import Simulation
+from hysop.mpi.topology import Cartesian
+from hysop.tools.parameters import Discretization
+from hysop.operator.advection import Advection
+
+from hysop.numerics.odesolvers import Euler, RK2, RK3, RK4, ExplicitRungeKutta
+from hysop.numerics.interpolation import Linear
+
+from hysop.numerics.remeshing import L2_1, L2_2, L2_3, L2_4
+from hysop.numerics.remeshing import L4_2, L4_3, L4_4
+from hysop.numerics.remeshing import L6_3, L6_4, L6_5, L6_6
+from hysop.numerics.remeshing import L8_4
+
+from hysop.constants import callback_profiler
+
+if __name__=='__main__':
+
+ GHOSTS = 0
+ NSCALARS = 1
+
+ # DIM = 3
+ # f_resolution = (33,33,33)[:DIM]
+ # f_resolution = (65,65,65)[:DIM]
+ f_resolution = (129,129,129)[:DIM]
+ # f_resolution = (257,257,257)[:DIM]
+ # f_resolution = (513,513,257)[:DIM]
+
+ #DIM = 2
+ #f_resolution = (8193,8193,8193)[:DIM]
+ #f_resolution = (2049,2049,2049)[:DIM]
+ #f_resolution = (4097,4097,4097)[:DIM]
+
+ v_resolution = f_resolution
+ ghosts = (GHOSTS,)*DIM
+
+ def initVel(res, *args):
+ res[0][...] = 0.
+ if DIM>1:
+ res[1][...] = 0.
+ if DIM>2:
+ res[2][...] = 0.
+ return res
+ def initVort(res, *args):
+ res[0][...] = args[0]
+ if DIM>1:
+ res[1][...] = args[0]*args[0]
+ if DIM>2:
+ res[2][...] = args[0]*args[0]*args[0]
+ return res
+
+ def initScalar(i):
+ def init(res,*args):
+ res[0][...] = i+1
+ return res
+ return init
+
+
+ d3d = Discretization(resolution=f_resolution, ghosts=ghosts)
+ d3dv = Discretization(resolution=v_resolution, ghosts=ghosts)
+
+ box = Box(length=[1.0]*DIM, origin=[0.0]*DIM)
+
+ velo = Field(domain=box, formula=initVel,
+ name='Velocity', is_vector=True)
+ vorti = Field(domain=box, formula=initVort,
+ name='Vorticity', is_vector=True)
+ scalars = [ Field(domain=box, formula=initScalar(i),
+ name='Scalar_{}'.format(i),
+ is_vector=False)
+ for i in xrange(NSCALARS) ]
+
+ f_topo = Cartesian(box,d3d,DIM)
+ v_topo = Cartesian(box,d3dv,DIM)
+
+ dvelo = velo.discretize(v_topo)
+ dvorti = vorti.discretize(f_topo)
+ dscalars = []
+ for s in scalars:
+ dscalars.append(s.discretize(f_topo))
+
+ autotuner_config = AutotunerConfig(autotuner_flag=AutotunerFlags.PATIENT, prune_threshold=1.20, override_cache=False)
+ rk_scheme = ExplicitRungeKutta('Euler')
+
+ method = {
+ Backend: Backend.OPENCL,
+ TimeIntegrator: rk_scheme,
+ Remesh: L2_1,
+ ExtraArgs: {
+ 'autotuner_config':autotuner_config,
+ 'use_builtin_copy':True,
+ }
+ }
+
+ if DIM==3:
+ method[ExtraArgs]['stretching'] = \
+ {
+ 'rk_scheme': rk_scheme,
+ 'formulation': StretchingFormulation.CONSERVATIVE,
+ 'boundary': BoundaryCondition.PERIODIC,
+ 'order':4
+ }
+
+ advected_fields = [vorti]+scalars
+ variables = dict(zip(advected_fields, [f_topo]*len(advected_fields)))
+
+ A = Advection(velo, v_topo, variables=variables, method=method)
+ A.discretize()
+ A.setup()
+
+ velo.initialize()
+ vorti.initialize()
+ for s in scalars:
+ s.initialize()
+
+ simu = Simulation(start=0.0, end=1.0, time_step=0.01)
+ simu.initialize()
+
+ i=0
+ while not simu.is_over:
+ print
+ simu.print_state()
+
+ A.apply(simu)
+ simu.advance()
+ i+=1
+
+ print callback_profiler.report()
+
diff --git a/examples/taylor_green/TaylorGreen3D.py.old b/examples/taylor_green/TaylorGreen3D.py.old
new file mode 100755
index 0000000000000000000000000000000000000000..93684a350cff22237d9be777b37c5476fbf48a52
--- /dev/null
+++ b/examples/taylor_green/TaylorGreen3D.py.old
@@ -0,0 +1,260 @@
+#!/usr/bin/python
+
+"""
+Taylor Green 3D : see paper van Rees 2011.
+
+All parameters are set and defined in python module dataTG.
+
+"""
+
+import parmepy as pp
+from parmepy.f2py import fftw2py
+import numpy as np
+from parmepy.fields.continuous import Field
+from parmepy.fields.variable_parameter import VariableParameter
+from parmepy.mpi.topology import Cartesian
+from parmepy.operator.advection import Advection
+from parmepy.operator.stretching import Stretching
+from parmepy.operator.poisson import Poisson
+from parmepy.operator.diffusion import Diffusion
+from parmepy.operator.adapt_timestep import AdaptTimeStep
+from parmepy.operator.redistribute import Redistribute
+from parmepy.problem.navier_stokes import NSProblem
+from parmepy.operator.monitors.printer import Printer
+from parmepy.operator.monitors.energy_enstrophy import Energy_enstrophy
+from parmepy.operator.monitors.reprojection_criterion import Reprojection_criterion
+from parmepy.problem.simulation import Simulation
+from parmepy.constants import VTK, HDF5
+from parmepy.methods_keys import Scales, TimeIntegrator, Interpolation,\
+ Remesh, Support, Splitting, dtCrit, SpaceDiscretisation
+from parmepy.numerics.integrators.runge_kutta2 import RK2 as RK2
+from parmepy.numerics.integrators.runge_kutta3 import RK3 as RK3
+from parmepy.numerics.integrators.runge_kutta4 import RK4 as RK4
+from parmepy.numerics.finite_differences import FD_C_4, FD_C_2
+from parmepy.numerics.interpolation import Linear
+from parmepy.numerics.remeshing import L6_4 as rmsh
+
+## ----------- A 3d problem -----------
+print " ========= Start Navier-Stokes 3D (Taylor Green benchmark) ========="
+## pi constant
+pi = np.pi
+cos = np.cos
+sin = np.sin
+
+## constants
+VISCOSITY = 1. / 1600.
+
+## Domain
+dim = 3
+box = pp.Box(dim, length=[2.0 * pi, 2.0 * pi, 2.0 * pi])
+
+## Global resolution
+nb = 33
+nbElem = [nb] * dim
+
+## Function to compute TG velocity
+def computeVel(res, x, y, z, t):
+ res[0][...] = sin(x) * cos(y) * cos(z)
+ res[1][...] = - cos(x) * sin(y) * cos(z)
+ res[2][...] = 0.
+ return res
+
+
+## Function to compute reference vorticity
+def computeVort(res, x, y, z, t):
+ res[0][...] = - cos(x) * sin(y) * sin(z)
+ res[1][...] = - sin(x) * cos(y) * sin(z)
+ res[2][...] = 2. * sin(x) * sin(y) * cos(z)
+ return res
+
+## Fields
+velo = Field(domain=box, formula=computeVel,
+ name='Velocity', is_vector=True)
+vorti = Field(domain=box, formula=computeVort,
+ name='Vorticity', is_vector=True)
+
+## Parameter Variable (adaptative timestep)
+data = {'dt': 0.01}
+dt_adapt = VariableParameter(data)
+
+## Usual Cartesian topology definition
+# At the moment we use two (or three?) topologies :
+# - "topo" for Stretching and all operators based on finite differences.
+# --> ghost layer = 2
+# - topo from Advection operator for all the other operators.
+# --> no ghost layer
+# - topo from fftw for Poisson and Diffusion.
+# Todo : check compat between scales and fft operators topologies.
+NBGHOSTS = 2
+ghosts = [NBGHOSTS] * box.dimension
+topo = Cartesian(box, box.dimension, nbElem, ghosts=ghosts)
+
+## Tools Operators
+# Adaptative timestep method : dt = min(values(dtCrit))
+# where dtCrit is a list of criterions on which the computation
+# of the adaptative time step is based
+# ex : dtCrit = ['gradU', 'cfl', 'stretch'], means :
+# dt = min (dtAdv, dtCfl, dtStretch), where dtAdv is equal to LCFL / |gradU|
+# For dtAdv, the possible choices are the following:
+# 'vort' (infinite norm of vorticity) : dtAdv = LCFL / |vort|
+# 'gradU' (infinite norm of velocity gradient), dtAdv = LCFL / |gradU|
+# 'deform' (infinite norm of deformation tensor), dtAdv = LCFL / (0.5(gradU + gradU^T))
+dtAdapt = AdaptTimeStep(velo, vorti,
+ resolutions={velo: nbElem,
+ vorti: nbElem},
+ dt_adapt=dt_adapt,
+ method={TimeIntegrator: RK3,
+ SpaceDiscretisation: FD_C_4,
+ dtCrit: ['deform', 'cfl', 'stretch']},
+ topo=topo,
+ io_params={},
+ lcfl=0.125,
+ cfl=0.5)
+
+## Navier Stokes Operators
+advec = Advection(velo, vorti,
+ resolutions={velo: nbElem,
+ vorti: nbElem},
+ method={Scales: 'p_M6', Splitting: 'classic'} # Scales advection
+# method={TimeIntegrator: RK2,
+# Interpolation: Linear,
+# Remesh: rmsh,
+# Support: '',
+# Splitting: 'o2_FullHalf'} # pure Python advection
+ )
+
+stretch = Stretching(velo, vorti,
+ resolutions={velo: nbElem,
+ vorti: nbElem},
+ topo=topo
+ )
+
+diffusion = Diffusion(vorti,
+ resolution=nbElem,
+ viscosity=VISCOSITY
+ )
+
+poisson = Poisson(velo, vorti,
+ resolutions={velo: nbElem,
+ vorti: nbElem}
+ )
+
+#-----------------------------
+# Topology without ghost points
+poisson.discretize()
+topofft = poisson.discreteFields[poisson.vorticity].topology
+#-----------------------------
+
+# Bridges between the different topologies in order to
+# redistribute data.
+# 1 -Advection to stretching
+distrAdvStr_vorti = Redistribute([vorti], advec, stretch)
+distrPoiStr_velo = Redistribute([velo], poisson, stretch)
+# 2 - Stretching to Poisson/Diffusion
+distrStrDiff = Redistribute([vorti], stretch, diffusion)
+# 3 - Poisson to TimeStep
+distrPoissTimeStep = Redistribute([velo, vorti], poisson, dtAdapt)
+
+## Simulation
+simu = Simulation(start=0.0,
+ end=10.0,
+ time_step=dt_adapt['dt'],
+ max_iter=1000000)
+
+# Define the problem to solve
+## With adaptative time step
+pb = NSProblem(operators=[distrPoiStr_velo,
+ advec,
+ distrAdvStr_vorti,
+ stretch,
+ distrStrDiff,
+ diffusion,
+ poisson,
+ distrPoissTimeStep,
+ dtAdapt],
+ simulation=simu, dumpFreq=-1)
+
+## With fixed time step
+#pb = NSProblem(operators=[distrPoiStr_velo,
+# advec,
+# distrAdvStr_vorti,
+# stretch,
+# distrStrDiff,
+# diffusion,
+# poisson],
+# simulation=simu, dumpFreq=-1)
+
+## Diagnostics related to the problem
+printer = Printer(variables=[velo, vorti],
+ topo=topofft,
+ frequency=100,
+ formattype=HDF5,
+ prefix='TG_io',
+ xmfalways=True)
+
+energy = Energy_enstrophy(velo, vorti,
+ viscosity=VISCOSITY,
+ isNormalized=True ,
+ topo=topofft,
+ io_params={})
+
+reproj = Reprojection_criterion(vorti,
+ reproj_cst=0.04,
+ reprojRate=1,
+ topo=topofft,
+ checkCriterion=False,
+ io_params={})
+
+## Add the reprojection of vorticity field (i.e div(vort)=0) for poisson operator
+poisson.activateProjection(reproj)
+
+## Setting solver to Problem (only operators for computational tasks)
+pb.pre_setUp()
+
+## Initializations on required topos + add monitors to problem + setUp
+vorti.setTopoInit(topofft)
+velo.setTopoInit(topofft)
+pb.addMonitors([energy, printer])
+pb.setUp()
+
+printer.apply(simu)
+## Time loop
+def run():
+# =====Automatic problem launch=====
+ pb.solve()
+# =====Manually problem launch=====
+# print "\n\n Start solving ..."
+# simu.initialize()
+# while not simu.isOver:
+# distrPoiStr_velo.apply(simu)
+# subSimu = Simulation(start=simu.tk, end=10., time_step=simu.time_step/2.0,
+# max_iter=2)
+# subSimu.initialize()
+# print '=============='
+# simu.printState()
+# while not subSimu.isOver:
+# subSimu.printState()
+# advec.apply(subSimu)
+# poisson.apply(subSimu)
+# subSimu.advance()
+# distrAdvStr_vorti.apply(simu)
+# stretch.apply(simu)
+# distrStrDiff.apply(simu)
+# diffusion.apply(simu)
+# poisson.apply(simu)
+# distrPoissTimeStep.apply(simu)
+# dtAdapt.apply(simu)
+# energy.apply(simu)
+## reproj.apply(simu)
+# simu.advance()
+
+## Solve problem
+from parmepy.mpi import MPI
+print "Start computation ..."
+time = MPI.Wtime()
+run()
+pb.finalize()
+print 'total time (rank):', MPI.Wtime() - time, '(', topo.rank, ')'
+
+## Clean memory buffers
+#fftw2py.clean_fftw_solver(box.dimension)
diff --git a/examples/taylor_green/taylor_green_monoscale.py b/examples/taylor_green/taylor_green_monoscale.py
new file mode 100644
index 0000000000000000000000000000000000000000..08b51e05daa0e03aaba12b5a70041c6967dde227
--- /dev/null
+++ b/examples/taylor_green/taylor_green_monoscale.py
@@ -0,0 +1,94 @@
+
+from hysop import Domain, Field, Cartesian, Box, Discretization, \
+ Cartesian, Simulation, Problem
+from hysop.backend.device.kernel_autotuner import AutotunerConfig, AutotunerFlags
+from hysop.backend.device.kernel_config import KernelConfig
+from hysop.constants import Backend
+from hysop.numerics.splitting.strang import StrangSplitting
+from hysop.operators import DirectionalAdvection, DirectionalStretching,\
+ Poisson, Diffusion
+from hysop.methods import StrangOrder, SpaceDiscretization, Remesh
+from hysop.deps import np
+
+pi = np.pi
+cos = np.cos
+sin = np.sin
+
+## Function to compute Taylor-Green velocity
+def init_velocity(res, x, y, z, t):
+ res[0][...] = + sin(x) * cos(y) * cos(z)
+ res[1][...] = - cos(x) * sin(y) * cos(z)
+ res[2][...] = 0.
+ return res
+
+
+## Function to compute reference vorticity
+def init_vorticity(res, x, y, z, t):
+ res[0][...] = - cos(x) * sin(y) * sin(z)
+ res[1][...] = - sin(x) * cos(y) * sin(z)
+ res[2][...] = 2. * sin(x) * sin(y) * cos(z)
+ return res
+
+def do_solve(npts, viscosity=1./1600., lcfl=0.125, cfl=0.50):
+ autotuner_config = AutotunerConfig(autotuner_flag=AutotunerFlags.EXHAUSTIVE,
+ prune_threshold=1.2, override_cache=True, verbose=2)
+ kernel_config = KernelConfig(autotuner_config=autotuner_config)
+
+ dim = 3
+ ghosts = 2
+
+ box = Box(length=(2*pi,)*dim)
+
+ resolution = (npts,)*dim
+ ghosts = (ghosts,)*dim
+
+ velo = Field(domain=box, formula=init_velocity,
+ name='V', is_vector=True)
+ vorti = Field(domain=box, formula=init_vorticity,
+ name='W', is_vector=True)
+
+ d3d = Discretization(resolution=resolution)
+
+ simu = Simulation(start=0.0, end=10.0, time_step=5)
+
+ advec = DirectionalAdvection(
+ name='advec',
+ velocity = velo,
+ advected_fields = (vorti,),
+ velocity_cfl = cfl,
+ variables = {velo: d3d, vorti: d3d},
+ method = {Remesh: Remesh.L8_4}
+ )
+ stretch = DirectionalStretching(
+ name='stretch',
+ velocity = velo,
+ vorticity = vorti,
+ variables = {velo: d3d, vorti: d3d},
+ method = {SpaceDiscretization: SpaceDiscretization.FDC4}
+ )
+
+ poisson = Poisson(name='poisson', velocity=velo, vorticity=vorti,
+ variables={velo:d3d, vorti: d3d})
+ diffusion = Diffusion(name='diffusion', input_field=vorti, viscosity=viscosity,
+ variables={vorti: d3d})
+
+ splitting = StrangSplitting(splitting_dim=dim, order=StrangOrder.STRANG_SECOND_ORDER,
+ method={KernelConfig: kernel_config})
+ # splitting.push_operators(advec, stretch)
+ splitting.push_operators(advec)
+
+ problem = Problem()
+ problem.insert(splitting)
+ # problem.insert(diffusion)
+ # problem.insert(poisson)
+
+ problem.build()
+ # problem.display()
+
+ problem.solve(simu)
+ problem.finalize()
+
+if __name__=='__main__':
+ N = 257
+ do_solve(N)
+
diff --git a/examples/taylor_green/taylor_green_multiscale.py b/examples/taylor_green/taylor_green_multiscale.py
new file mode 100644
index 0000000000000000000000000000000000000000..d1a17bdb9ccdfaf68a4e0eb002a62d160bbcf6d9
--- /dev/null
+++ b/examples/taylor_green/taylor_green_multiscale.py
@@ -0,0 +1,85 @@
+
+from hysop import Domain, Field, Cartesian, Box, Discretization, \
+ Cartesian, Simulation, Problem
+from hysop.splitting.strang import StrangSplitting
+from hysop.operators import DirectionalAdvection, \
+ Poisson
+from hysop.methods import StrangOrder
+from hysop.deps import np
+
+pi = np.pi
+cos = np.cos
+sin = np.sin
+
+## Function to compute Taylor-Green velocity
+def init_velocity(res, x, y, z, t):
+ res[0][...] = + sin(x) * cos(y) * cos(z)
+ res[1][...] = - cos(x) * sin(y) * cos(z)
+ res[2][...] = 0.
+ return res
+
+
+## Function to compute reference vorticity
+def init_vorticity(res, x, y, z, t):
+ res[0][...] = - cos(x) * sin(y) * sin(z)
+ res[1][...] = - sin(x) * cos(y) * sin(z)
+ res[2][...] = 2. * sin(x) * sin(y) * cos(z)
+ return res
+
+def do_solve(npts, viscosity=1./1600., lcfl=0.125, cfl=0.50):
+ #autotuner_config = AutotunerConfig(autotuner_flag=AutotunerFlags.PATIENT, prune_threshold=1.20, override_cache=False)
+ #print callback_profiler.report()
+
+ dim = 3
+ ghosts = 2
+
+ box = Box(length=(2*pi,)*dim)
+
+ v_resolution = (npts,)*dim
+ w_resolution = (npts,)*dim
+ ghosts = (ghosts,)*dim
+
+ velo = Field(domain=box, formula=init_velocity,
+ name='V', is_vector=True)
+ vorti = Field(domain=box, formula=init_vorticity,
+ name='W', is_vector=True)
+
+ d3dw = Discretization(resolution=w_resolution, ghosts=None)
+ d3dv = Discretization(resolution=v_resolution, ghosts=None)
+ d3dwg = Discretization(resolution=w_resolution, ghosts=ghosts)
+ d3dvg = Discretization(resolution=v_resolution, ghosts=ghosts)
+
+ w_topo_fft = Cartesian(box,d3dw,dim)
+ v_topo_fft = Cartesian(box,d3dv,dim)
+ w_topo_ghosts = Cartesian(box,d3dwg,dim)
+ v_topo_ghosts = Cartesian(box,d3dvg,dim)
+
+ simu = Simulation(start=0.0, end=10.0, time_step=5)
+
+ advec = DirectionalAdvection(
+ name='advec',
+ velocity = velo,
+ advected_fields = (vorti,),
+ variables = {velo: v_topo_ghosts, vorti: w_topo_ghosts},
+ )
+
+ poisson = Poisson(name='poisson',
+ velocity=velo, vorticity=vorti, topology=v_topo_fft)
+
+ splitting = StrangSplitting(dim=dim, order=StrangOrder.STRANG_FIRST_ORDER)
+ splitting.push_operator(advec)
+
+ problem = Problem()
+ problem.insert(splitting)
+ problem.insert(poisson)
+
+ problem.build()
+ problem.display()
+
+ problem.solve(simu)
+ problem.finalize()
+
+if __name__=='__main__':
+ N = 65
+ do_solve(N)
+
diff --git a/f2py_f2cmap.in b/f2py_f2cmap.in
new file mode 100644
index 0000000000000000000000000000000000000000..ab94da543fa5de74594a278abe2d31425af19c1c
--- /dev/null
+++ b/f2py_f2cmap.in
@@ -0,0 +1,3 @@
+{'integer':{'ip':'int'}, 'real':{'real64':'double', 'real32':'float', 'wp':'@f2pymap_for_real@'}}
+
+
diff --git a/hysop/.f2py_f2cmap b/hysop/.f2py_f2cmap
deleted file mode 100644
index 99f5f3517caf6260a22a9851a15f66443a1045d4..0000000000000000000000000000000000000000
--- a/hysop/.f2py_f2cmap
+++ /dev/null
@@ -1,3 +0,0 @@
-{'integer':{'c_int':'int'}, 'real':{'real64':'double', 'wp':'double'}}
-
-
diff --git a/hysop/__init__.py b/hysop/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..0c4f302de021568a896d3fa83ccac3c91f98d9c7
--- /dev/null
+++ b/hysop/__init__.py
@@ -0,0 +1,105 @@
+"""Python package dedicated to flow simulation using particular methods
+on hybrid architectures (MPI-GPU)
+
+"""
+from functools import wraps
+from hysop.deps import __builtin__, print_function, os, sys
+
+# HySoP
+package_name = "hysop"
+version = "2.0.0"
+
+# Compilation flags
+__MPI_ENABLED__ = "ON" is "ON"
+__GPU_ENABLED__ = "ON" is "ON"
+__FFTW_ENABLED__ = "ON" is "ON"
+__SCALES_ENABLED__ = "ON" is "ON"
+__OPTIMIZE__ = "OFF" is "ON"
+
+__VERBOSE__ = "ON" in ["1", "3"]
+__DEBUG__ = "ON" in ["2", "3"]
+__TRACE__ = "ON" in ["5"]
+__KERNEL_DEBUG__ = "ON" in ["4", "3"]
+__PROFILE__ = "OFF" in ["0", "1"]
+
+__ENABLE_LONG_TESTS__ = "OFF" is "ON"
+
+# OpenCL
+__DEFAULT_PLATFORM_ID__ = 0
+__DEFAULT_DEVICE_ID__ = 0
+
+
+
+if __MPI_ENABLED__:
+ from hysop.core.mpi import MPI, main_rank, main_size, \
+ host_rank, interhost_size, \
+ shm_rank, intershm_size
+
+# define printing functions
+def print(*args, **kargs):
+ """Wrap print function (because of python 3)"""
+ __builtin__.print(*args, **kargs)
+
+def vprint(*args, **kargs):
+ """prints only if __VERBOSE__ has been set"""
+ if __VERBOSE__:
+ print(*args, **kargs)
+def dprint(*args, **kargs):
+ """prints only if __DEBUG__ has been set"""
+ if __DEBUG__:
+ print(*args, **kargs)
+
+def mprint(*args, **kargs):
+ """prints only on world master rank 0"""
+ if (main_rank==0):
+ vprint(*args, **kargs)
+def hprint(*args, **kargs):
+ """prints only host master rank 0"""
+ if (host_rank==0):
+ vprint(*args, **kargs)
+def sprint(*args, **kargs):
+ """prints only shared memory master rank 0"""
+ if (shm_rank==0):
+ vprint(*args, **kargs)
+
+if __TRACE__:
+ def __trace(frame, event, arg):
+ print('{} {}:{}'.format(event, frame.f_code.co_filename, frame.f_lineno))
+ sys.settrace(__trace)
+
+from hysop.domain.domain import Domain
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology import Topology, Cartesian
+from hysop.core.mpi.topology_descriptor import TopologyDescriptor
+from hysop.tools.parameters import Discretization
+from hysop.simulation import Simulation
+from hysop.problem import Problem
+from hysop.tools.io_utils import IO, IOParams
+__all__ = ['Box', 'Field', 'Cartesian', 'Domain', 'Discretization', 'Simulation',
+ 'Problem', 'IO', 'IOParams', 'Topology', 'Cartesian', 'TopologyDescriptor']
+if __MPI_ENABLED__:
+ __all__ += ['MPI', 'main_rank', 'main_size']
+
+from hysop.tools.sys_utils import SysUtils
+if SysUtils.is_interactive():
+ # Set i/o default path to current directory
+ # for interactive sessions
+ # i.e. python interactive session or any call of ipython.
+ defpath = os.path.join(os.getcwd(), 'interactive')
+ IO.set_default_path(defpath)
+
+
+msg_start = '\nStarting {} version {}'.format(package_name, version)
+if __MPI_ENABLED__:
+ msg_start += (' with {} mpi process(es) on {} host(s) '+
+ 'providing {} shared memory node(s).').format(main_size,interhost_size,intershm_size)
+vprint(msg_start)
+
+default_path = IO.default_path()
+cache_path = IO.default_cache_path()
+msg_io = '\n*Default path for all i/o is \'{}\'.'.format(default_path)
+msg_io += '\n*Default path for caching is \'{}\'.'.format(cache_path)
+msg_io += '\n'
+vprint(msg_io)
+
diff --git a/hysop/__init__.py.in b/hysop/__init__.py.in
old mode 100755
new mode 100644
index 657ce52951e693bca786297df6b8562809a1c67e..8b9ab0ff4f8aa3665b36d23d43a083586354f542
--- a/hysop/__init__.py.in
+++ b/hysop/__init__.py.in
@@ -1,45 +1,86 @@
"""Python package dedicated to flow simulation using particular methods
on hybrid architectures (MPI-GPU)
-
"""
+from functools import wraps
+from hysop.deps import __builtin__, print_function, os, sys
+
+# HySoP
+package_name = "@PACKAGE_NAME@"
+version = "@HYSOP_VERSION@"
+
# Compilation flags
-__MPI_ENABLED__ = "@USE_MPI@" is "ON"
-__GPU_ENABLED__ = "@WITH_GPU@" is "ON"
-__FFTW_ENABLED__ = "@WITH_FFTW@" is "ON"
+__MPI_ENABLED__ = "@USE_MPI@" is "ON"
+__GPU_ENABLED__ = "@WITH_GPU@" is "ON"
+__FFTW_ENABLED__ = "@WITH_FFTW@" is "ON"
__SCALES_ENABLED__ = "@WITH_SCALES@" is "ON"
-__VERBOSE__ = "@DEBUG@" in ["1", "3"]
-__DEBUG__ = "@DEBUG@" in ["2", "3"]
-__PROFILE__ = "@PROFILE@" in ["0", "1"]
-__OPTIMIZE__ = "@OPTIM@" is "ON"
+__OPTIMIZE__ = "@OPTIM@" is "ON"
-import os
-from hysop.tools.sys_utils import SysUtils
-# Box-type physical domain
-from hysop.domain.box import Box
-# Fields
-from hysop.fields.continuous import Field
-# Variable parameters
-from hysop.fields.variable_parameter import VariableParameter
-# Simulation parameters
-from hysop.problem.simulation import Simulation
-# Tools (io, mpi ...)
-from hysop.tools.io_utils import IO, IOParams
-from hysop.tools.parameters import MPIParams, Discretization
-import hysop.mpi
-# Problem
-from hysop.problem.problem import Problem
-# Solver
-# import particular_solvers.basic
-# ## #import particular_solvers.gpu
-# ParticleSolver = particular_solvers.basic.ParticleSolver
-# ## #GPUParticleSolver = particular_solvers.gpu.GPUParticleSolver
-## from tools.explore_hardware import explore
-
-
-__all__ = ['Box', 'Field', 'Discretization',
- 'IOParams', 'Simulation', 'MPIParams', 'Problem', 'IO']
+__VERBOSE__ = "@DEBUG@" in ["1", "3"]
+__DEBUG__ = "@DEBUG@" in ["2", "3"]
+__TRACE__ = "@DEBUG@" in ["5"]
+__KERNEL_DEBUG__ = "@DEBUG@" in ["4", "3"]
+__PROFILE__ = "@PROFILE@" in ["0", "1"]
+
+__ENABLE_LONG_TESTS__ = "@ENABLE_LONG_TESTS@" is "ON"
+
+# OpenCL
+__DEFAULT_PLATFORM_ID__ = @OPENCL_DEFAULT_OPENCL_PLATFORM_ID@
+__DEFAULT_DEVICE_ID__ = @OPENCL_DEFAULT_OPENCL_DEVICE_ID@
+
+
+if __MPI_ENABLED__:
+ from hysop.core.mpi import MPI, main_rank, main_size, \
+ host_rank, interhost_size, \
+ shm_rank, intershm_size
+# define printing functions
+def print(*args, **kargs):
+ """Wrap print function (because of python 3)"""
+ __builtin__.print(*args, **kargs)
+
+def vprint(*args, **kargs):
+ """prints only if __VERBOSE__ has been set"""
+ if __VERBOSE__:
+ print(*args, **kargs)
+def dprint(*args, **kargs):
+ """prints only if __DEBUG__ has been set"""
+ if __DEBUG__:
+ print(*args, **kargs)
+
+def mprint(*args, **kargs):
+ """prints only on world master rank 0"""
+ if (main_rank==0):
+ vprint(*args, **kargs)
+def hprint(*args, **kargs):
+ """prints only host master rank 0"""
+ if (host_rank==0):
+ vprint(*args, **kargs)
+def sprint(*args, **kargs):
+ """prints only shared memory master rank 0"""
+ if (shm_rank==0):
+ vprint(*args, **kargs)
+
+if __TRACE__:
+ def __trace(frame, event, arg):
+ print('{} {}:{}'.format(event, frame.f_code.co_filename, frame.f_lineno))
+ sys.settrace(__trace)
+
+from hysop.domain.domain import Domain
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology import Topology, Cartesian
+from hysop.core.mpi.topology_descriptor import TopologyDescriptor
+from hysop.tools.parameters import Discretization
+from hysop.simulation import Simulation
+from hysop.problem import Problem
+from hysop.tools.io_utils import IO, IOParams
+__all__ = ['Box', 'Field', 'Cartesian', 'Domain', 'Discretization', 'Simulation',
+ 'Problem', 'IO', 'IOParams', 'Topology', 'Cartesian', 'TopologyDescriptor']
+if __MPI_ENABLED__:
+ __all__ += ['MPI', 'main_rank', 'main_size']
+
+from hysop.tools.sys_utils import SysUtils
if SysUtils.is_interactive():
# Set i/o default path to current directory
# for interactive sessions
@@ -47,26 +88,17 @@ if SysUtils.is_interactive():
defpath = os.path.join(os.getcwd(), 'interactive')
IO.set_default_path(defpath)
-default_path = IO.default_path()
-msg_start = '\nStarting @PACKAGE_NAME@ version '
-msg_start += str("@HYSOP_VERSION@")
-msg_io = '\nWarning : default path for all i/o is ' + default_path + '.\n'
-msg_io += 'If you want to change this, use io.set_default_path function.\n'
-
-if __VERBOSE__:
- if __MPI_ENABLED__:
- if mpi.main_rank == 0:
- msg_start += ' with ' + str(mpi.main_size) + ' mpi process(es).'
- print msg_start
- print msg_io
-
- else:
- print msg_start
- print msg_io
-# OpenCL
-__DEFAULT_PLATFORM_ID__ = @OPENCL_DEFAULT_OPENCL_PLATFORM_ID@
-__DEFAULT_DEVICE_ID__ = @OPENCL_DEFAULT_OPENCL_DEVICE_ID@
+msg_start = '\nStarting {} version {}'.format(package_name, version)
+if __MPI_ENABLED__:
+ msg_start += (' with {} mpi process(es) on {} host(s) '+
+ 'providing {} shared memory node(s).').format(main_size,interhost_size,intershm_size)
+vprint(msg_start)
-version = "@HYSOP_VERSION"
+default_path = IO.default_path()
+cache_path = IO.default_cache_path()
+msg_io = '\n*Default path for all i/o is \'{}\'.'.format(default_path)
+msg_io += '\n*Default path for caching is \'{}\'.'.format(cache_path)
+msg_io += '\n'
+vprint(msg_io)
diff --git a/hysop/backend/__init__.py b/hysop/backend/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b884af398253e0298c83dcc89e5d3b049719fe5
--- /dev/null
+++ b/hysop/backend/__init__.py
@@ -0,0 +1,13 @@
+try:
+ import pyopencl as cl
+ __HAS_OPENCL_BACKEND__ = True
+except:
+ __HAS_OPENCL_BACKEND__ = False
+
+try:
+ import pycuda as cuda
+ __HAS_CUDA_BACKEND__ = True
+except:
+ __HAS_CUDA_BACKEND__ = False
+
+__HAS_DEVICE_BACKEND__ = (__HAS_OPENCL_BACKEND__ or __HAS_CUDA_BACKEND__)
diff --git a/hysop/codegen/__init__.py b/hysop/backend/device/__init__.py
similarity index 100%
rename from hysop/codegen/__init__.py
rename to hysop/backend/device/__init__.py
diff --git a/hysop/codegen/base/__init__.py b/hysop/backend/device/codegen/__init__.py
similarity index 100%
rename from hysop/codegen/base/__init__.py
rename to hysop/backend/device/codegen/__init__.py
diff --git a/hysop/codegen/functions/__init__.py b/hysop/backend/device/codegen/base/__init__.py
similarity index 100%
rename from hysop/codegen/functions/__init__.py
rename to hysop/backend/device/codegen/base/__init__.py
diff --git a/hysop/backend/device/codegen/base/cl_extensions.py b/hysop/backend/device/codegen/base/cl_extensions.py
new file mode 100644
index 0000000000000000000000000000000000000000..826d24c7220c54fb333906a82df981c2f4dbb2c4
--- /dev/null
+++ b/hysop/backend/device/codegen/base/cl_extensions.py
@@ -0,0 +1,48 @@
+
+
+_cl_khr_fp64_code = '''
+#if __OPENCL_VERSION__ < 120
+ #if defined(cl_khr_fp64)
+ #pragma OPENCL EXTENSION cl_khr_fp64 : enable
+ #elif defined(cl_amd_fp64)
+ #pragma OPENCL EXTENSION cl_amd_fp64 : enable
+ #else
+ #error Your OpenCL device is missing double precision extension!
+ #endif
+#endif
+'''
+
+_cl_extension_custom_declarations = {
+ 'cl_khr_fp64': _cl_khr_fp64_code
+}
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.test import _test_typegen
+
+class ClExtCodeGen(OpenClCodeGenerator):
+ def __init__(self,ext_name):
+ super(ClExtCodeGen,self).__init__(name=ext_name,
+ typegen=OpenClTypeGen.devicelessTypegen(), declare_cl_exts=False)
+ self._generate_cl_extension(ext_name)
+
+ def _generate_cl_extension(self, ext_name):
+ with self._codeblock_('pragma_extensions'):
+ if ext_name not in _cl_extension_custom_declarations.keys():
+ with self._align_() as al:
+ base = \
+'''
+#if defined({ext})
+ #pragma OPENCL EXTENSION {ext}$ : enable
+#else
+ #error your opencl device is missing the {ext} extension!
+#endif
+'''
+ base = \
+'''
+#pragma OPENCL EXTENSION {ext}$ : enable
+'''
+ al.append(base.format(ext=ext_name))
+ else:
+ self.append(_cl_extension_custom_declarations[ext_name]);
+
diff --git a/hysop/codegen/base/codegen.py b/hysop/backend/device/codegen/base/codegen.py
similarity index 80%
rename from hysop/codegen/base/codegen.py
rename to hysop/backend/device/codegen/base/codegen.py
index 9df83fa7fc75953a3aa47cc445a8e45a714b1104..69d7531a93c2f5adbe5101bbaed200ab089bb901 100644
--- a/hysop/codegen/base/codegen.py
+++ b/hysop/backend/device/codegen/base/codegen.py
@@ -2,12 +2,11 @@
from contextlib import contextmanager
from subprocess import call
-import sys, os, string, tempfile, operator
-import itertools as it
-
-import pyopencl as cl
-
-from hysop.codegen.base.utils import WriteOnceDict, VarDict
+from hysop.tools.types import check_instance
+from hysop.deps import it, sys, os, string, tempfile, operator
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, VarDict
+from hysop.backend.device.codegen.base.variables import CodegenVariable
class CodeGenerator(object):
@@ -20,15 +19,17 @@ class CodeGenerator(object):
'inline': 'inline',
}
default_block_priorities = {
- 'pragma_extensions' : -1000,
+ 'pragma_extensions' : -10000,
- 'enum_definitions' : -800,
- 'struct_prototypes' : -700,
- 'function_prototypes': -600,
- 'kernel_prototypes' : -500,
+ 'enum_definitions' : -1000,
+ 'union_prototypes' : -900,
+ 'struct_prototypes' : -800,
+ 'function_prototypes': -700,
+ 'kernel_prototypes' : -600,
+ 'union_declarations' : -500,
'struct_declarations' : -400,
- 'global_scope_constants' : -300,
+ 'global_scope_constants' : -300,
'function_declarations' : -200,
'kernel_declarations' : -100
}
@@ -118,8 +119,6 @@ class CodeGenerator(object):
pass
return self
-
-
def to_file(self,folder,filename):
dst_file = folder + '/' + filename
if not os.path.exists(folder):
@@ -184,7 +183,6 @@ class CodeGenerator(object):
if k>0:
self.code = self.code[:k]
return self
-
def _noop(self):
@@ -204,9 +202,9 @@ class CodeGenerator(object):
def define(self,what,prepend=True):
code = '#define {}'.format(what)
self.append(code,simple=True)
- def include(self,*kargs):
+ def include(self,*args):
code = []
- for k in kargs:
+ for k in args:
code.append('#include {}'.format(k))
return self.append(code)
@@ -250,24 +248,35 @@ class CodeGenerator(object):
else:
self.append(code)
- def decl_vars(self,_type,_varnames,_inits=None,comment=None,cv_qualifier=None):
- if not isinstance(_varnames,list):
- _varnames = [_varnames]
- if _inits is not None and not isinstance(_inits,list):
- _inits = [_inits]
-
- declvar = ''
- if cv_qualifier:
- declvar+=cv_qualifier+' '
- declvar += '{} '.format(_type)
- if _inits:
- declvar += ','.join(['{}={}'.format(v,i) for v,i in zip(_varnames,_inits)])
+ def decl_vars(self, *variables, **kargs):
+ codegen = kargs.pop('codegen', None)
+ align = kargs.pop('align', False)
+ assert len(set(var.base_ctype() for var in variables))==1
+ base= variables[0].base_ctype()
+ svars=[]
+ for var in variables:
+ check_instance(var, CodegenVariable)
+ svars.append(var.declare(multidecl=True, **kargs))
+ decl = '{} ${};'.format(base, ', '.join(svars))
+ if not align:
+ decl = decl.replace('$','')
+ if (codegen is None):
+ self.append(decl)
else:
- declvar += ','.join(_varnames)
- declvar += ';'
- if comment is not None:
- declvar += ' /* {} */'.format(comment)
- self.append(declvar)
+ codegen.append(decl)
+
+ def decl_aligned_vars(self, *variables, **kargs):
+ assert len(variables)>0
+ jmp = kargs.pop('jmp', True)
+ try:
+ with self._align_() as al:
+ for var in variables:
+ check_instance(var, CodegenVariable)
+ var.declare(codegen=al, align=True, **kargs)
+ if jmp:
+ al.jumpline()
+ except:
+ raise
class VarBlock(object):
@@ -314,10 +323,8 @@ class CodeGenerator(object):
@contextmanager
def _var_block_(self):
vb = self.VarBlock()
- try:
- yield vb
- finally:
- self.append(vb.code())
+ yield vb
+ self.append(vb.code())
class AlignBlock(object):
@@ -327,7 +334,7 @@ class CodeGenerator(object):
self._parts_count = None
def jumpline(self,count=1):
- lines = '\n'*count
+ lines = ''+'\n'*(count-1)
self.append(lines)
return self
@@ -349,12 +356,18 @@ class CodeGenerator(object):
def code(self):
if self._parts_count is None:
- raise RuntimeError('Call at least one append() before closing an _align_!')
+ msg='Call at least one append() before closing an _align_!'
+ msg+='\n got: {}'.format(self._lines)
+ raise RuntimeError(msg)
maxlen = lambda i: max([len(line[i]) for line in self._lines if len(line)>1])
line_str = ''
for i in xrange(self._parts_count):
- line_str+='{:'+str(maxlen(i))+'}'
+ ml = maxlen(i)
+ if ml==0:
+ line_str+='{}'
+ else:
+ line_str+='{:'+str(ml)+'}'
code = []
for line in self._lines:
if len(line)>1:
@@ -366,11 +379,8 @@ class CodeGenerator(object):
@contextmanager
def _align_(self,sep='$'):
ab = self.AlignBlock(sep=sep)
- try:
- yield ab
- finally:
- self.append(ab.code())
-
+ yield ab
+ self.append(ab.code())
def declare_codeblocks(self,names,initial_code=None,priorities=None,comments=None):
if not isinstance(names,list):
@@ -410,16 +420,14 @@ class CodeGenerator(object):
elif priority is not None and self.blocks[blockname][0] != priority:
raise ValueError('Priority mismatch!')
- try:
- code = self.code
- indent = self.indent_level
- self.indent_level = self.initial_indent_level
- self.code = self.blocks[blockname][1]
- yield
- finally:
- self.blocks[blockname][1] = self.code
- self.code = code
- self.indent_level = indent
+ code = self.code
+ indent = self.indent_level
+ self.indent_level = self.initial_indent_level
+ self.code = self.blocks[blockname][1]
+ yield
+ self.blocks[blockname][1] = self.code
+ self.code = code
+ self.indent_level = indent
def block_exists(self,name):
return (name in self.blocks)
@@ -449,42 +457,39 @@ class CodeGenerator(object):
def _block_(self,header_prefix='',header_postfix='',footer_postfix='',compact=False):
count = 1-int(compact)
newline = not compact
- try:
- header = header_prefix + '{' + header_postfix
- self.append(header,newline).indent(count)
- yield
- finally:
- if compact:
- self.supress_newline()
- self.code += ' '
- footer = '}' + footer_postfix
- self.dedent(count).append(footer)
+
+ header = header_prefix + '{' + header_postfix
+ self.append(header,newline).indent(count)
+ yield
+ if compact:
+ self.supress_newline()
+ self.code += ' '
+ footer = '}' + footer_postfix
+ self.dedent(count).append(footer)
#conditional facilities
@contextmanager
def _if_(self,cond,compact=False,force_spaces=False):
- try:
- if cond=='true':
- yield
- elif cond=='false':
- code = self.code
- indent = self.indent_level
- self.code = ''
- yield
- else:
- sep = self.space() if force_spaces else self.empty()
- header_prefix = 'if (' + sep + cond + sep + ') '
- with self._block_(header_prefix=header_prefix,compact=compact) as b:
- yield b
- finally:
- if cond=='false':
- self.code = code
- self.indent_level = indent
+ if cond=='true':
+ yield
+ elif cond=='false':
+ code = self.code
+ indent = self.indent_level
+ self.code = ''
+ yield
+ else:
+ sep = self.space() if force_spaces else self.empty()
+ header_prefix = 'if ({}{}{}) '.format(sep,cond,sep)
+ with self._block_(header_prefix=header_prefix,compact=compact) as b:
+ yield b
+ if cond=='false':
+ self.code = code
+ self.indent_level = indent
@contextmanager
- def _elif_(self,cond,compact=False,force_spaces=True):
+ def _elif_(self,cond,compact=False,force_spaces=False):
sep = self.space() if force_spaces else self.empty()
- header_prefix = 'else if (' + sep + cond + sep + ') '
+ header_prefix = 'else if ({}{}{}) '.format(sep,cond,sep)
with self._block_(header_prefix=header_prefix,compact=compact) as b:
yield b
@contextmanager
@@ -508,7 +513,29 @@ class CodeGenerator(object):
self.declare_prototype(declaration, 'struct')
with self._codeblock_('struct_declarations'):
- with self._block_(header_prefix=header_prefix+' ',footer_postfix=';',compact=False) as b:
+ with self._block_(header_prefix=header_prefix+' ',
+ footer_postfix=';',compact=False) as b:
+ if variables is not None:
+ for v in variables:
+ self.append(v+';')
+ yield b
+
+ # union facilities
+ @contextmanager
+ def _union_(self,name,variables=None,typedef=None):
+ if name == '' and typedef is None:
+ raise ValueError('Cannot define a non typedefed anonymous struct!')
+
+ header_prefix = 'union ' + name
+ if typedef:
+ declaration = 'typedef ' + header_prefix + ' ' + typedef + ';'
+ else:
+ declaration = header_prefix + ';'
+ self.declare_prototype(declaration, 'union')
+
+ with self._codeblock_('union_declarations'):
+ with self._block_(header_prefix=header_prefix+' ',
+ footer_postfix=';',compact=False) as b:
if variables is not None:
for v in variables:
self.append(v+';')
@@ -534,24 +561,26 @@ class CodeGenerator(object):
#function facilities
@contextmanager
- def _function_(self,name,output,args=[],arg_spaces=True,inline=False,compact=False,add_impl_const=[]):
- if not args:
- args = ['']
+ def _function_(self,name,output,args=[],args_impl=None,arg_spaces=True,inline=False,compact=False):
+
+ def filter_args(_args):
+ if not args:
+ newargs = ['']
+ else:
+ newargs = []
+ for i,arg in enumerate(_args):
+ newl=(arg[-1] == self.newl())
+ arg = arg[:-1] if newl else arg
+ newargs.append(arg)
+ if newl and i != len(_args)-1:
+ newargs.append(self.newl())
+ return newargs
+
+ args = filter_args(args)
+ if not args_impl:
+ args_impl = args
else:
- newargs = []
- i=0
- for ii,arg in enumerate(args):
- newl=(arg[-1] == self.newl())
- arg = arg[:-1] if newl else arg
- newargs.append(arg)
- i+=1
- if newl and ii != len(args)-1:
- for j,id in enumerate(add_impl_const):
- if id>=i:
- add_impl_const[j] += 1
- newargs.append(self.newl())
- i+=1
- args = newargs
+ args_impl = filter_args(args_impl)
if arg_spaces:
comma = ', '
@@ -562,6 +591,7 @@ class CodeGenerator(object):
sfun = '{prefix}({args})'
inline = self.keywords['inline']+' ' if inline else ''
+
prefix = sprefix.format(inline=inline,output=output,name=name)
indent = len(self.current_indent() + prefix)*' ' + ' '
if args:
@@ -571,13 +601,11 @@ class CodeGenerator(object):
prototype = sfun.format(prefix=prefix,args=''.join(pargs))
prototype += ';'
- for i in add_impl_const:
- args[i] = 'const '+args[i]
prefix = sprefix.format(inline='',output=output,name=name)
indent = len(self.current_indent() + prefix)*' ' + ' '
- if args:
- dargs = [arg+comma if arg!=self.newl() else arg+indent for arg in args[:-1]]+[args[-1]]
+ if args_impl:
+ dargs = [arg+comma if arg!=self.newl() else arg+indent for arg in args_impl[:-1]]+[args_impl[-1]]
else:
dargs = []
definition = sfun.format(prefix=prefix,args=''.join(dargs))
@@ -587,6 +615,8 @@ class CodeGenerator(object):
with self._codeblock_('function_declarations'):
with self._block_(header_prefix=definition+' ',compact=compact) as b:
yield b
+ if not compact:
+ self.jumpline()
diff --git a/hysop/codegen/base/enum_codegen.py b/hysop/backend/device/codegen/base/enum_codegen.py
similarity index 74%
rename from hysop/codegen/base/enum_codegen.py
rename to hysop/backend/device/codegen/base/enum_codegen.py
index 0ec54fd42efdeb96758e33bb05ef99b50af8c047..8701ee23396b504004fc36c79509a53b80163de4 100644
--- a/hysop/codegen/base/enum_codegen.py
+++ b/hysop/backend/device/codegen/base/enum_codegen.py
@@ -1,23 +1,22 @@
import numpy as np
import pyopencl as cl
-from hysop.codegen.base.codegen import CodeGenerator
-from hysop.codegen.base.types import TypeGen
+from hysop.backend.device.codegen.base.codegen import CodeGenerator
+from hysop.backend.device.opencl.opencl_types import TypeGen
from hysop.tools.enum import EnumFactory
-from hysop.codegen.base.variables import register_ctype_dtype
+from hysop.backend.device.codegen.base.variables import register_ctype_dtype
class EnumCodeGenerator(CodeGenerator):
- def __init__(self,enum,ext='.c',
+ def __init__(self, enum, comments=None, ext='.c',
initial_indent_level=0,escape_seqs=None,keywords=None):
super(EnumCodeGenerator,self).__init__(name=enum.name,typegen=TypeGen('float'),
ext=ext,initial_indent_level=initial_indent_level,
escape_seqs=escape_seqs,keywords=keywords)
-
- if not isinstance(enum, EnumFactory.StaticMetaEnum):
- raise ValueError('Input enum should be generated with hysop.tools.enum.EnumFactory !')
+ if not isinstance(enum, EnumFactory.MetaEnum):
+ raise ValueError('Input enum should be generated with hysop.tools.enum.EnumFactory.')
self.enum = enum
@@ -28,15 +27,18 @@ class EnumCodeGenerator(CodeGenerator):
for k,v in self.fields().iteritems():
setattr(self,k,v)
- self.ctype = 'enum ' + self.enum.name
+ self.ctype = 'enum ' + self.enum.name
register_ctype_dtype(self.ctype,self.dtype)
- self.gencode()
+ self.gencode(comments)
- def gencode(self):
+ def gencode(self, comments):
with self._codeblock_('enum_definitions'):
+ if comments is not None:
+ self.jumpline()
+ self.comment(comments)
if self.dtype != np.int32:
- prefix = 'enum {} : {} '.format(self.name, self.ctype(np.int32))
+ prefix = 'enum {} : {} '.format(self.name, self.ctype(self.dtype))
else:
prefix = 'enum {} '.format(self.name)
with self._block_(header_prefix=prefix,footer_postfix=';'):
@@ -65,7 +67,7 @@ if __name__ == '__main__':
days = ['MONDAY','TUESDAY']
enum = EnumFactory.create('Days',days)
- scg = EnumCodeGenerator(enum)
+ scg = EnumCodeGenerator(enum, comments='Days enumeration')
scg.edit()
diff --git a/hysop/codegen/base/function_codegen.py b/hysop/backend/device/codegen/base/function_codegen.py
similarity index 66%
rename from hysop/codegen/base/function_codegen.py
rename to hysop/backend/device/codegen/base/function_codegen.py
index 52e8a2c644bc3626129e6176bd62b3a9768954ce..d9ec1f53718e25747b6059ca0ef7d5b94ca81f6e 100644
--- a/hysop/codegen/base/function_codegen.py
+++ b/hysop/backend/device/codegen/base/function_codegen.py
@@ -2,11 +2,12 @@
import pyopencl as cl
from contextlib import contextmanager
-from hysop.codegen.base.codegen import CodeGenerator
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.utils import ArgDict
-from hysop.codegen.base.types import TypeGen, OpenClTypeGen
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenVectorClBuiltinFunc
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.codegen import CodeGenerator
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.utils import ArgDict
+from hysop.backend.device.opencl.opencl_types import TypeGen, OpenClTypeGen
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenVectorClBuiltinFunc
class FunctionBase(object):
@@ -17,7 +18,8 @@ class FunctionBase(object):
super(FunctionBase,self).__init__(typegen=typegen,**kargs)
known_args = ArgDict() if (known_args is None) else known_args
- assert isinstance(fargs, ArgDict)
+ output = 'void' if (output is None) else output
+ check_instance(fargs,ArgDict)
fargs.release()
for varname, varval in known_args.iteritems():
@@ -59,27 +61,40 @@ class FunctionBase(object):
elif argname in kvars:
var = kvars[argname]
else:
- raise RuntimeError('Could not match argument {} from vars={} and kvars={}.'.format(argname, vars,kvars))
+ svars = ''.join(['\n\t{}'.format(var) for var in sorted(vars)])
+ skvars = ''.join(['\n\t{} -> {}'.format(kname,kvars[kname]) for kname in sorted(kvars.keys())])
+ if len(svars)!=0:
+ svars +='\n '
+ if len(skvars)!=0:
+ skvars+='\n '
+ msg = \
+'''Could not match function argument '{}' of type '{}' while calling function '{}' from:
+ vars = [{}]
+ kvars = {}{}{}
+'''.format(argname, arg.ctype, self.fname, svars, '{', skvars, '}')
+ raise RuntimeError(msg)
if isinstance(var, str):
sargs.append(var)
- elif isinstance(var,arg.__class__):
+ elif isinstance(var,arg.__class__) \
+ or (arg.__class__==CodegenVectorClBuiltin and arg.dim==1 \
+ and isinstance(var, CodegenVariable)):
sargs.append(var.name)
else:
msg = 'Matched variable \'{}\' with argument \'{}\' but there was a type mismatch(\'{}\' is not an instance of \'{}\')!'.format(var.name, arg.name, var.__class__, arg.__class__)
raise RuntimeError(msg)
- return ','.join(sargs)
+ return ', '.join(sargs)
class FunctionCodeGenerator(FunctionBase, CodeGenerator):
def __init__(self,basename,typegen,output,
args=None,known_args=None,inline=False,ext='.tmp'):
- assert isinstance(typegen, TypeGen)
+ check_instance(typegen,TypeGen)
name = basename
fname = basename
if args is not None:
- assert isinstance(args, ArgDict)
+ check_instance(args,ArgDict)
fname += args.function_name_suffix(output)
name += args.codegen_name_suffix(output)
@@ -92,9 +107,10 @@ class FunctionCodeGenerator(FunctionBase, CodeGenerator):
def _function_(self):
name=self.fname
output=self.output
- fargs,cargs,add_impl_const = self.args.build_args()
+ fargs,fargs_impl,cargs = self.args.build_args()
with super(FunctionCodeGenerator,self)._function_(name=name,output=output,
- args=fargs,add_impl_const=add_impl_const,inline=self.inline) as f:
+ args=fargs,args_impl=fargs_impl,
+ inline=self.inline) as f:
for c in cargs:
self.append(c)
yield f
@@ -103,11 +119,11 @@ class OpenClFunctionCodeGenerator(FunctionBase, OpenClCodeGenerator):
def __init__(self,basename,typegen,output,
args=None,known_args=None,inline=False,ext='.cl'):
- assert isinstance(typegen, OpenClTypeGen)
+ check_instance(typegen,OpenClTypeGen)
name = basename
fname = basename
if args is not None:
- assert isinstance(args, ArgDict)
+ check_instance(args,ArgDict)
fname += args.function_name_suffix(output)
name += args.codegen_name_suffix(output)
@@ -120,9 +136,10 @@ class OpenClFunctionCodeGenerator(FunctionBase, OpenClCodeGenerator):
def _function_(self):
name=self.fname
output=self.output
- fargs,cargs,add_impl_const = self.args.build_args()
+ fargs,fargs_impl,cargs = self.args.build_args()
with super(OpenClFunctionCodeGenerator,self)._function_(name=name,output=output,
- args=fargs,add_impl_const=add_impl_const,inline=self.inline) as f:
+ args=fargs,args_impl=fargs_impl,
+ inline=self.inline) as f:
for c in cargs:
c.declare(self)
yield f
diff --git a/hysop/codegen/base/kernel_codegen.py b/hysop/backend/device/codegen/base/kernel_codegen.py
similarity index 58%
rename from hysop/codegen/base/kernel_codegen.py
rename to hysop/backend/device/codegen/base/kernel_codegen.py
index 499ecbd0230213bed2568c276cd20a7f10765bd4..41224982a6a1022d4413c24f6b9ae11a5ebfd3df 100644
--- a/hysop/codegen/base/kernel_codegen.py
+++ b/hysop/backend/device/codegen/base/kernel_codegen.py
@@ -1,12 +1,13 @@
from contextlib import contextmanager
-import pyopencl as cl
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.function_codegen import FunctionBase
-from hysop.codegen.base.utils import VarDict, ArgDict, WriteOnceDict
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenVectorClBuiltinFunc
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import FunctionBase
+from hysop.backend.device.codegen.base.utils import VarDict, ArgDict, WriteOnceDict
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, \
+ CodegenVectorClBuiltinFunc
class KernelBase(FunctionBase):
def __init__(self, kname, vec_type_hint=None,
@@ -22,19 +23,24 @@ class KernelCodeGenerator(KernelBase, OpenClCodeGenerator):
def __init__(self,name,typegen,work_dim,symbolic_mode=True,
kernel_args=None, known_vars=None,
- vec_type_hint=None, device=None, context=None):
+ vec_type_hint=None):
kernel_args = ArgDict() if (kernel_args is None) else kernel_args
known_vars = WriteOnceDict() if (known_vars is None) else known_vars
-
- assert isinstance(typegen, OpenClTypeGen)
- assert isinstance(kernel_args, ArgDict)
+
+ check_instance(typegen,OpenClTypeGen)
+ check_instance(kernel_args,ArgDict)
assert work_dim>0 and work_dim<=3
- vec_type_hint = None if (vec_type_hint is None) else vec_type_hint
+ if (vec_type_hint is not None):
+ if (vec_type_hint not in typegen.builtin_types):
+ msg = 'Invalid vec_type_hint \'{}\'.'.format(vec_type_hint)
+ raise ValueError(msg)
+ if typegen.components(vec_type_hint) == 1:
+ vec_type_hint = None
- self.work_dim = work_dim
self.vec_type_hint = vec_type_hint
+ self.work_dim = work_dim
if 'work_dim' not in known_vars.keys():
known_vars['work_dim'] = work_dim
@@ -48,31 +54,50 @@ class KernelCodeGenerator(KernelBase, OpenClCodeGenerator):
typegen=typegen,
symbolic_mode=symbolic_mode,
kernel_args=kernel_args, known_args=known_args,
- known_vars=known_vars,
- device=device, context=context)
+ known_vars=known_vars)
self.inject_vars(kernel_args)
+ self.symbolic_mode=symbolic_mode
self.gen_kernel_variables()
self.gen_kernel_attributes()
- def required_workgroup_cache_size(self):
- return (0,0) # static & dynamic cache
+ #return global_work_size from effective work_size and given local_work_size
+ # /!\ it should be garanted that global_work_size is a multiple of local_work_size
+ def get_global_work_size(self, work_size, local_work_size):
+ work_size = np.asarray(work_size)
+ local_work_size = np.asarray(local_work_size)
+ return ((work_size+local_work_size-1)/local_work_size) * local_work_size
+
+ def min_ghosts(self):
+ ghosts = (0,)*self.work_dim
+ return np.asarray(ghosts)
+
+ #return a tuple of required (static,dynamic) cache bytes per workgroup
+ def required_workgroup_cache_size(self, local_work_size):
+ return (0,0)
def gen_kernel_variables(self):
tg = self.typegen
work_dim = self.work_dim
+ sm = self.symbolic_mode
kvars = VarDict()
- kvars['work_dim'] = CodegenVariable('work_dim','uint', tg)
+ kvars['work_dim'] = CodegenVariable('work_dim','uint', tg, symbolic_mode=sm)
kvars['global_index'] = CodegenVariable('GID', 'int', tg)
kvars['local_index'] = CodegenVariable('LID', 'int', tg)
- kvars['global_size'] = CodegenVectorClBuiltinFunc('global_size', 'G', 'int',work_dim,tg)
- kvars['local_size'] = CodegenVectorClBuiltinFunc('local_size', 'L', 'int',work_dim,tg)
- kvars['global_id'] = CodegenVectorClBuiltinFunc('global_id', 'gid', 'int',work_dim,tg)
- kvars['local_id'] = CodegenVectorClBuiltinFunc('local_id', 'lid', 'int',work_dim,tg)
- kvars['num_groups'] = CodegenVectorClBuiltinFunc('num_groups', 'ngroups', 'int',work_dim,tg)
- kvars['group_id'] = CodegenVectorClBuiltinFunc('group_id', 'group_id','int',work_dim,tg)
+ kvars['global_size'] = CodegenVectorClBuiltinFunc('global_size', 'G',
+ 'int',work_dim,tg,symbolic_mode=sm)
+ kvars['local_size'] = CodegenVectorClBuiltinFunc('local_size', 'L',
+ 'int',work_dim,tg,symbolic_mode=sm)
+ kvars['global_id'] = CodegenVectorClBuiltinFunc('global_id', 'gid',
+ 'int',work_dim,tg)
+ kvars['local_id'] = CodegenVectorClBuiltinFunc('local_id', 'lid',
+ 'int',work_dim,tg)
+ kvars['num_groups'] = CodegenVectorClBuiltinFunc('num_groups', 'ngroups',
+ 'int',work_dim,tg,symbolic_mode=sm)
+ kvars['group_id'] = CodegenVectorClBuiltinFunc('group_id', 'group_id',
+ 'int',work_dim,tg)
self.update_vars(kvars)
@@ -83,17 +108,18 @@ class KernelCodeGenerator(KernelBase, OpenClCodeGenerator):
if (local_work_size is not None):
lws = tuple(local_work_size) + (1,)*(3-len(local_work_size))
- kernel_attributes['reqd_work_group_size'] = 'reqd_work_group_size({},{},{})'.format(lws[0],lws[1],lws[2])
- if (vec_type_hint is not None):
- kernel_attributes['vec_type_hint'] = 'vec_type_hint({})'.format(vec_type_hint)
+ kernel_attributes['reqd_work_group_size'] = 'reqd_work_group_size({},{},{})'.format(
+ lws[0],lws[1],lws[2])
+ #if (vec_type_hint is not None):
+ #kernel_attributes['vec_type_hint'] = 'vec_type_hint({})'.format(vec_type_hint)
self.kernel_attributes = kernel_attributes
def check_workitem_bounds(self,varname,compact=True):
gid = self.vars['global_id']
if isinstance(varname,str):
- N = self.vars[varname]
+ N = self.vars[varname]
elif isinstance(varname,CodegenVariable):
- N = varname
+ N = varname
else:
raise TypeError('varname')
conditions = ['({}>={})'.format(gid[i],N[i]) for i in xrange(self.work_dim)]
@@ -105,7 +131,7 @@ class KernelCodeGenerator(KernelBase, OpenClCodeGenerator):
def _kernel_(self):
name=self.fname
output=self.output
- fargs,cargs,add_impl_const = self.args.build_args()
+ fargs,fargs_impl,cargs = self.args.build_args()
with self._codeblock_('global_scope_constants'):
for carg in cargs:
@@ -113,8 +139,7 @@ class KernelCodeGenerator(KernelBase, OpenClCodeGenerator):
carg.storage='__constant'
carg.declare(self)
- with super(KernelCodeGenerator,self)._kernel_(name=name,args=fargs,
- add_impl_const=add_impl_const, attributes=self.kernel_attributes) as k:
+ with super(KernelCodeGenerator,self)._kernel_(name=name,args=fargs, args_impl=fargs_impl,
+ attributes=self.kernel_attributes) as k:
yield k
-
diff --git a/hysop/backend/device/codegen/base/opencl_codegen.py b/hysop/backend/device/codegen/base/opencl_codegen.py
new file mode 100644
index 0000000000000000000000000000000000000000..03643281477b4ed75346c4a4ab20463d4f97909b
--- /dev/null
+++ b/hysop/backend/device/codegen/base/opencl_codegen.py
@@ -0,0 +1,224 @@
+
+import pyopencl as cl
+from contextlib import contextmanager
+
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.codegen import CodeGenerator
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import VarDict
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenVectorClBuiltinFunc
+
+class OpenClCodeGenerator(CodeGenerator):
+ default_keywords = {
+ 'global' : '__global',
+ 'local' : '__local',
+ 'constant' : '__constant',
+ 'private' : '__private',
+
+ 'read_only' : '__read_only',
+ 'write_only' : '__write_only',
+ 'read_write' : '__read_write',
+
+ 'inline' : 'inline',
+ 'kernel' : '__kernel'
+ }
+ default_escape_seqs = {
+ '\t': ' '*4,
+ '\n': '\n',
+ ' ': ' '
+ }
+
+ _global, _local = '__global', '__local'
+
+ def __init__(self,name,typegen,ext='.cl',
+ known_vars=None, declare_cl_exts=True,
+ **kargs):
+
+ check_instance(typegen,OpenClTypeGen)
+ super(OpenClCodeGenerator,self).__init__(name=name,typegen=typegen, ext=ext,
+ known_vars=known_vars, keywords=self.default_keywords,
+ escape_seqs=self.default_escape_seqs, **kargs)
+
+
+ self.device = typegen.device
+ self.context = typegen.context
+ self.platform = typegen.platform
+
+ if declare_cl_exts:
+ for cl_ext in typegen.cl_requirements():
+ if cl_ext is not None:
+ self.declare_cl_extension(cl_ext)
+
+
+ def test_compile(self, contexts=None):
+ print 'Test build on device {}: '.format(self.device.name),
+ src=self.__str__()
+ prg = cl.Program(self.context,src)
+ prg.build()
+ print 'OK'
+
+
+ @staticmethod
+ def _mem_flags(_local, _global):
+ if _local and _global:
+ return 'CLK_LOCAL_MEM_FENCE | CLK_GLOBAL_MEM_FENCE'
+ elif _local:
+ return 'CLK_LOCAL_MEM_FENCE'
+ elif _global:
+ return 'CLK_GLOBAL_MEM_FENCE'
+ else:
+ return None
+
+ def barrier(self,_local=False, _global=False):
+ if not _local and not _global:
+ raise ValueError('Bad barrier configuration!')
+ code = 'barrier({});'.format(self._mem_flags(_local,_global))
+ self.append(code)
+
+ def mem_fence(self,read=False,write=False, _local=False, _global=False):
+ if (not read and not write) or (not _local and not _global):
+ raise ValueError('Bad memfence configuration!')
+
+ #opencl 1.0 has only the barrier function
+ self.append('#if __OPENCL_VERSION__ < 110')
+ self.indent()
+ self.barrier(_local=_local, _global=_global)
+ self.dedent()
+ self.append('#else')
+ self.indent()
+ if read and write:
+ mem_fun = 'mem_fence'
+ elif read:
+ mem_fun = 'read_mem_fence'
+ else:
+ mem_fun = 'write_mem_fence'
+ mem_flags = self._mem_flags(_local,_global)
+ code = '{}({});'.format(mem_fun,mem_flags)
+ self.append(code)
+ self.dedent()
+ self.append('#endif')
+
+
+ def declare_cl_extension(self,extname):
+ from hysop.backend.device.codegen.base.cl_extensions import ClExtCodeGen
+ self.require(extname, ClExtCodeGen(extname))
+ return self
+
+ @contextmanager
+ def _kernel_(self,name,args=None,args_impl=None,arg_spaces=True,attributes=None):
+
+ def filter_args(_args):
+ if not args:
+ newargs = ['']
+ else:
+ newargs = []
+ for i,arg in enumerate(_args):
+ newl=(arg[-1] == self.newl())
+ arg = arg[:-1] if newl else arg
+ newargs.append(arg)
+ if newl and i != len(_args)-1:
+ newargs.append(self.newl())
+ return newargs
+
+ args = filter_args(args)
+ if not args_impl:
+ args_impl = args
+ else:
+ args_impl = filter_args(args_impl)
+
+ if arg_spaces:
+ comma = ', '
+ else:
+ comma = ','
+
+ kernel_kwd = self.keywords['kernel']
+
+ prefix = '{kernel} void {name}('.format(kernel=kernel_kwd,name=name)
+ indent_proto = len(prefix)*' '
+ if attributes:
+ attr = ['{} __attribute__(({}))'.format(len(kernel_kwd)*' ',at)
+ for at in attributes.values()]
+ attr[0] = attr[0][len(kernel_kwd)+1:]
+ attr = '\n'.join(attr)
+ proto_prefix = '{kernel} {attr}\nvoid {name}('.format(
+ kernel=kernel_kwd,attr=attr,name=name)
+ indent_proto = len('void {name}('.format(name=name))*' '
+ else:
+ proto_prefix = prefix
+ suffix = '{args})'
+ indent = len(self.current_indent() + prefix)*' '
+
+ pargs = [arg+comma if arg!=self.newl() else arg+indent_proto
+ for arg in args[:-1]]+[args[-1]]
+ prototype = proto_prefix + suffix.format(args=''.join(pargs)) + ';'
+
+ dargs = [arg+comma if arg!=self.newl() else arg+indent
+ for arg in args_impl[:-1]]+[args_impl[-1]]
+ definition = prefix + suffix.format(args=''.join(dargs)) + ' '
+
+ self.declare_prototype(prototype, 'kernel')
+ with self._codeblock_('kernel_declarations'):
+ with self._block_(header_prefix=definition) as b:
+ yield b
+
+ def vstore(self, n, ptr, offset, data,
+ offset_is_ftype=True, align=False,
+ jmp=False, suppress_semicolon=False):
+ assert n in [1,2,4,8,16]
+ if offset_is_ftype:
+ if n>1:
+ shift = 0
+ _n=n
+ while _n>1:
+ _n>>=1
+ shift+=1
+ _offset = '({}) $>> {}'.format(offset, shift)
+ address = '{} $+ (({}) $& 0x{:02x})'.format(ptr, offset, ((1<<shift)-1))
+ code = 'vstore{}({},\n ${}, ${});'.format(n, data, _offset, address)
+ else:
+ code ='{} $= {};'.format(ptr[offset], data)
+ else:
+ if n>1:
+ code = 'vstore{}({},\n ${}, ${});'.format(n, data, offset, ptr)
+ else:
+ code = '{} $= {};'.format(
+ ptr['{}*{}'.format(nparticles,offset)],
+ data)
+ if not align:
+ code = code.replace('$','')
+ if not jmp:
+ code = code.replace('\n','')
+ if suppress_semicolon:
+ code = code.replace(';','')
+ return code
+
+
+ def vload(self, n, ptr, offset,
+ offset_is_ftype=True, align=False, jmp=False):
+ assert n in [1,2,4,8,16]
+ if offset_is_ftype:
+ if n>1:
+ shift = 0
+ _n=n
+ while _n>1:
+ _n>>=1
+ shift+=1
+ _offset = '({}) $>> {}'.format(offset, shift)
+ address = '{} $+ (({}) $& 0x{:02x})'.format(ptr, offset, ((1<<shift)-1))
+ code = 'vload{}({},\n ${})'.format(n, _offset, address)
+ else:
+ code = ptr[offset]
+ else:
+ if n>1:
+ address = ptr
+ code = 'vload{}({},\n ${})'.format(n, offset, address)
+ else:
+ code = ptr['{}*{}'.format(n,offset)]
+
+ if not align:
+ code = code.replace('$','')
+ if not jmp:
+ code = code.replace('\n','')
+ return code
+
+
diff --git a/hysop/backend/device/codegen/base/statistics.py b/hysop/backend/device/codegen/base/statistics.py
new file mode 100644
index 0000000000000000000000000000000000000000..716015254a7a80ac0ea95c364b2bb0b52df7dc66
--- /dev/null
+++ b/hysop/backend/device/codegen/base/statistics.py
@@ -0,0 +1,178 @@
+
+import copy
+import numpy as np
+
+from hysop.tools.types import check_instance
+from hysop.tools.units import bytes2str
+from hysop.backend.device.opencl.opencl_types import vsizes, signed_base_types, unsigned_base_types, float_base_types
+
+dtype_ops = {
+ np.int8: (0.25, 'IOPS'),
+ np.int16: (0.50, 'IOPS'),
+ np.int32: (1.00, 'IOPS'),
+ np.int64: (2.00, 'IOPS'),
+
+ np.uint8: (0.25, 'IOPS'),
+ np.uint16: (0.50, 'IOPS'),
+ np.uint32: (1.00, 'IOPS'),
+ np.uint64: (2.00, 'IOPS'),
+
+ np.float16: (0.50, 'FLOPS'),
+ np.float32: (1.00, 'FLOPS'),
+ np.float64: (2.00, 'FLOPS'),
+
+ np.complex64: (2.00, 'FLOPS'),
+ np.complex128: (4.00, 'FLOPS')
+}
+
+def _fill_dtype_ops():
+ integer_base_types = [signed_base_types, unsigned_base_types]
+ ibytes = [1,2,4,8]
+ for int_base_types in integer_base_types:
+ for itype,size in zip(int_base_types,ibytes):
+ for vsize in vsizes:
+ typename = itype + ('' if vsize==1 else str(vsize))
+ dtype_ops[typename] = (vsize*float(size)/4, 'IOPS')
+ fbytes = [2,4,8]
+ for ftype,size in zip(float_base_types,fbytes):
+ for vsize in vsizes:
+ typename = ftype + ('' if vsize==1 else str(vsize))
+ dtype_ops[typename] = (vsize*float(size)/4, 'FLOPS')
+
+_fill_dtype_ops()
+
+
+class WorkStatistics(object):
+ def __init__(self, stat=None):
+ if (stat is not None):
+ check_instance(stat,WorkStatistics)
+ self.global_mem_byte_reads = stat.global_mem_byte_reads
+ self.global_mem_byte_writes = stat.global_mem_byte_writes
+ self.local_mem_byte_reads = stat.local_mem_byte_reads
+ self.local_mem_byte_writes = stat.local_mem_byte_writes
+ self.ops_per_type = copy.deepcopy(stat.ops_per_type)
+ else:
+ self.global_mem_byte_reads = 0
+ self.global_mem_byte_writes = 0
+ self.local_mem_byte_reads = 0
+ self.local_mem_byte_writes = 0
+ self.ops_per_type = {}
+
+ def compute_timed_statistics(self, duration):
+ return TimedWorkStatistics(self,duration)
+
+ def global_mem_transactions(self):
+ return self.global_mem_byte_writes + self.global_mem_byte_reads
+ def global_mem_rw_ratio(self):
+ return float(self.global_mem_byte_writes)/self.global_mem_transactions()
+ def global_mem_read_ratio(self):
+ return float(self.global_mem_byte_reads)/self.global_mem_transactions()
+
+ def local_mem_transactions(self):
+ return self.local_mem_byte_writes + self.local_mem_byte_reads
+ def local_mem_rw_ratio(self):
+ return float(self.local_mem_byte_writes)/self.local_mem_transactions()
+ def local_mem_read_ratio(self):
+ return float(self.local_mem_byte_reads)/self.local_mem_transactions()
+
+ def total_mem_transactions(self):
+ return self.local_mem_transactions() + self.global_mem_transactions()
+
+ def has_local_mem_transactions(self):
+ return (self.local_mem_transactions() > 0)
+ def has_global_mem_transactions(self):
+ return (self.global_mem_transactions() > 0)
+
+ def __add__(self, rhs):
+ check_instance(rhs,WorkStatistics)
+ stats = copy.deepcopy(self)
+ stats.global_mem_byte_reads += rhs.global_mem_byte_reads
+ stats.global_mem_byte_writes += rhs.global_mem_byte_writes
+ stats.local_mem_byte_reads += rhs.local_mem_byte_reads
+ stats.local_mem_byte_writes += rhs.local_mem_byte_writes
+
+ for (k,v) in rhs.ops_per_type.iteritems():
+ if k not in stats.ops_per_type:
+ stats.ops_per_type[k] = v
+ else:
+ stats.ops_per_type[k] += v
+ return stats
+
+ def __mul__(self, rhs):
+ check_instance(rhs,int)
+ stats = copy.deepcopy(self)
+ stats.global_mem_byte_reads *= rhs
+ stats.global_mem_byte_writes *= rhs
+ stats.local_mem_byte_reads *= rhs
+ stats.local_mem_byte_writes *= rhs
+ for k in stats.ops_per_type.keys():
+ stats.ops_per_type[k] *= rhs
+ return stats
+
+ def __rmul__(self, lhs):
+ check_instance(lhs,int)
+ return self.__mul__(lhs)
+
+ def __str__(self):
+ op_count = [''] + ['{}: {}'.format(k,v) for (k,v) in self.ops_per_type.iteritems() ]
+ op_count = '\n '.join(op_count)
+
+ ss = ':: Work Statistics ::'
+
+ if self.has_global_mem_transactions():
+ ss += '\n Global memory: load={} store={} total={} rw_ratio={}'.format(
+ bytes2str(self.global_mem_byte_reads),
+ bytes2str(self.global_mem_byte_writes),
+ bytes2str(self.global_mem_transactions()),
+ round(self.global_mem_rw_ratio(),2))
+
+ if self.has_local_mem_transactions():
+ ss += '\n Local memory: load={} store={} total={} rw_ratio={}'.format(
+ bytes2str(self.local_mem_byte_reads),
+ bytes2str(self.local_mem_byte_writes),
+ bytes2str(self.local_mem_transactions()),
+ round(self.local_mem_rw_ratio(),2))
+
+ ss += '\n Operations count: {}'.format(op_count)
+
+ return ss
+
+class TimedWorkStatistics(WorkStatistics):
+ def __init__(self, workstat, duration):
+ super(TimedWorkStatistics,self).__init__(workstat)
+ self.duration = duration
+
+ self._init()
+
+ def ops_per_second(self):
+ return self._ops_per_second
+ def ops_per_category(self):
+ return self._ops_per_category
+
+ def global_mem_throughput(self):
+ return self.global_mem_transactions()/self.duration
+ def local_mem_throughput(self):
+ return self.local_mem_transactions()/self.duration
+ def total_mem_throughput(self):
+ return self.total_mem_transactions()/self.duration
+
+ def _init(self):
+ for dtype in self.ops_per_type:
+ if dtype not in dtype_ops.keys():
+ msg = 'unknown type {}, valed types are:\n\t{}.'.format(dtype, dtype_ops.keys())
+ raise ValueError(msg)
+
+ ops_count = {}
+ for (dtype, N) in self.ops_per_type.iteritems():
+ (multiplier,op_category) = dtype_ops[dtype]
+ if op_category not in ops_count:
+ ops_count[op_category] = 0.0
+ ops_count[op_category] += multiplier*N
+
+ ops_per_second = {}
+ for (op_category, op_count) in ops_count.iteritems():
+ ops_per_second[op_category] = op_count/self.duration
+
+ self._ops_per_category = ops_count
+ self._ops_per_second = ops_per_second
+
diff --git a/hysop/backend/device/codegen/base/struct_codegen.py b/hysop/backend/device/codegen/base/struct_codegen.py
new file mode 100644
index 0000000000000000000000000000000000000000..39e316e1db33beaf4787a4fac240f3272371dec7
--- /dev/null
+++ b/hysop/backend/device/codegen/base/struct_codegen.py
@@ -0,0 +1,78 @@
+
+import pyopencl as cl
+import pyopencl.tools
+
+import numpy as np
+import re
+
+from hysop.backend.device.opencl.opencl_types import np_dtype
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.variables import VarDict, CodegenVariable, CodegenVector, CodegenStruct, CodegenVectorClBuiltin
+from hysop.backend.device.codegen.base.variables import register_ctype_dtype
+
+class StructCodeGenerator(OpenClCodeGenerator):
+ def __init__(self,name,dtype,typegen,
+ typedef=None,comments=None,
+ ctype_overrides=None,
+ custom_types={}):
+
+ super(StructCodeGenerator,self).__init__(name=name,typegen=typegen)
+
+ self.typedef = typedef
+ self.dtype = np.dtype(dtype)
+ self.ctype = self.typedef if self.typedef else 'struct {}'.format(self.name)
+
+ cl.tools.get_or_register_dtype(self.ctype,self.dtype)
+ register_ctype_dtype(self.ctype,self.dtype)
+
+ for _ctype,_dtype in custom_types.iteritems():
+ cl.tools.get_or_register_dtype(_ctype,dtype=_dtype)
+
+ self.gencode(comments, ctype_overrides)
+
+ def fields(self):
+ return self.dtype.fields
+
+ def c_decl(self):
+ dtype,cdecl = cl.tools.match_dtype_to_c_struct( \
+ self.device,self.ctype.replace('struct',''),self.dtype,self.context)
+ return cdecl
+
+ def gencode(self, comments, ctype_overrides):
+ struct_vars = re.compile('\s+((?:struct\s+)?\w+)\s+((?:\s*\**(?:\w+)(?:\[\d+\])*[,;])+)')
+ lines = self.c_decl().split('\n')
+
+ with self._struct_(name=self.name,typedef=self.typedef):
+ with self._var_block_() as vb:
+ i=0
+ for l in lines:
+ match = struct_vars.match(l)
+ if match:
+ ctype = match.group(1)
+ variables = match.group(2).replace(';','').split(',')
+ if (ctype_overrides is not None) and (i in ctype_overrides.keys()):
+ ctype = ctype_overrides[i]
+ if comments is not None:
+ vb.decl_var(ctype,','.join(variables), comment=comments[i])
+ else:
+ vb.decl_var(ctype,','.join(variables))
+ i+=1
+
+ def build_codegen_variable(self, name, **kargs):
+ return CodegenStruct(name=name, struct=self, **kargs)
+
+if __name__ == '__main__':
+
+ from hysop.backend.device.codegen.base.test import _test_typegen
+ tg = _test_typegen()
+
+ dtype = []
+ dtype.append( ('f0', np.float32 ) )
+ dtype.append( ('d0', np.float64) )
+ dtype.append( ('v0', np_dtype('float4')) )
+ dtype.append( ('v1', np_dtype('int16')) )
+
+ scg = StructCodeGenerator('TestStruct',dtype,typedef=None,typegen=tg)
+ scg.edit()
+
+
diff --git a/hysop/backend/device/codegen/base/test.py b/hysop/backend/device/codegen/base/test.py
new file mode 100644
index 0000000000000000000000000000000000000000..fabc0f0dae832d8afcd595ac2c11a00570c8730b
--- /dev/null
+++ b/hysop/backend/device/codegen/base/test.py
@@ -0,0 +1,95 @@
+
+from hysop.constants import np, BoundaryCondition
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+
+## Quickly get a default opencl typegen **ONLY** for testing or debugging purpose
+## => do not use in production code
+def _test_typegen(fbtype='float',float_dump_mode='dec'):
+ from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+ env = get_or_create_opencl_env()
+ return OpenClTypeGen(
+ context=env.context, device=env.device, platform=env.platform,
+ fbtype=fbtype,float_dump_mode=float_dump_mode)
+
+def _test_mesh_info(name, typegen,dim,ghosts,resolution,**kargs):
+ ghosts = [ghosts]*dim if np.isscalar(ghosts) else ghosts
+ ghosts = np.asarray(ghosts)[:dim]
+
+ resolution = [resolution]*dim if np.isscalar(resolution) else resolution
+ resolution = np.asarray(resolution)[:dim]
+
+ lboundary = [BoundaryCondition.PERIODIC]*dim
+ rboundary = [BoundaryCondition.PERIODIC]*dim
+ boundaries = (lboundary, rboundary)
+
+ compute_resolution = resolution-2*ghosts
+
+ xmin = np.zeros((dim,))
+ xmax = np.ones((dim,))
+ size = xmax-xmin
+ dx = size / compute_resolution
+
+ start = ghosts
+ stop = resolution-ghosts
+
+ mbs = MeshBaseStruct(typegen, typedef='MeshBase_s')
+ mis = MeshInfoStruct(typegen, typedef='MeshInfo_s', mbs_typedef=mbs.typedef)
+
+ # create a local numpy and a codegen MeshInfoStruct variable
+ global_mesh = mbs.create(name='global',
+ resolution=resolution, compute_resolution=compute_resolution,
+ xmin=xmin, xmax=xmax,
+ boundaries=boundaries,
+ size=size,
+ **kargs)
+ local_mesh = mbs.create(name='local',
+ resolution=resolution, compute_resolution=compute_resolution,
+ xmin=xmin, xmax=xmax,
+ boundaries=boundaries,
+ size=size,
+ **kargs)
+
+ (np_mis, cg_mis) = mis.create(name=name,
+ dim=dim,
+ start=start, stop=stop,
+ ghosts=ghosts,
+ dx=dx,
+ local_mesh=local_mesh, global_mesh=global_mesh,
+ **kargs)
+
+ return (np_mis, cg_mis)
+
+def make_slice_views(compute_grid_size,
+ lghosts=None, rghosts=None, step=None):
+ compute_grid_size = np.asarray(compute_grid_size)
+ dim = compute_grid_size.size
+
+ if (lghosts is None):
+ lghosts = (0,)*dim
+ elif np.isscalar(lghosts):
+ lghosts = (lghosts,)*dim
+ lghosts = np.asarray(lghosts)
+
+ if (rghosts is None):
+ rghosts = (0,)*dim
+ elif np.isscalar(rghosts):
+ rghosts = (rghosts,)*dim
+ rghosts = np.asarray(rghosts)
+
+ if (step is None):
+ step = (1,)*dim
+ elif np.isscalar(step):
+ step = (step,)*dim
+ step = np.asarray(step)
+
+ view = [slice(lg, gs+lg) for lg, gs in zip(lghosts, compute_grid_size)]
+
+ grid_size = compute_grid_size + lghosts + rghosts
+ grid_shape = grid_size[::-1]
+
+ return view[::-1], grid_size, grid_shape, lghosts, rghosts, step
+
+
+
diff --git a/hysop/backend/device/codegen/base/union_codegen.py b/hysop/backend/device/codegen/base/union_codegen.py
new file mode 100644
index 0000000000000000000000000000000000000000..98fb708ecc4c7b7edb063b5db912d395c236a51d
--- /dev/null
+++ b/hysop/backend/device/codegen/base/union_codegen.py
@@ -0,0 +1,76 @@
+
+import pyopencl as cl
+import pyopencl.tools
+
+import numpy as np
+import re
+
+from hysop.backend.device.opencl.opencl_types import np_dtype
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.variables import VarDict, CodegenVariable, CodegenVector, CodegenStruct, CodegenVectorClBuiltin
+from hysop.backend.device.codegen.base.variables import register_ctype_dtype
+
+class UnionCodeGenerator(OpenClCodeGenerator):
+ def __init__(self,name,dtype,typegen,
+ typedef=None,comments=None,
+ ctype_overrides=None,
+ custom_types={}):
+
+ super(UnionCodeGenerator,self).__init__(name=name,typegen=typegen)
+
+ self.typedef = typedef
+ self.dtype = np.dtype(dtype)
+ self.ctype = self.typedef if (self.typedef is not None) else 'union {}'.format(self.name)
+
+ cl.tools.get_or_register_dtype(self.ctype,self.dtype)
+ register_ctype_dtype(self.ctype,self.dtype)
+
+ self.gencode(comments, ctype_overrides)
+
+ def c_decl(self):
+ dtype,cdecl = cl.tools.match_dtype_to_c_struct( \
+ self.device,self.ctype.replace('union',''),self.dtype,self.context)
+ return cdecl
+
+ def fields(self):
+ return self.dtype.fields
+
+ def gencode(self, comments, ctype_overrides):
+ union_vars = re.compile('\s+((?:struct\s+)?\w+)\s+((?:\s*\**(?:\w+)(?:\[\d+\])*[,;])+)')
+ lines = self.c_decl().split('\n')
+
+ with self._union_(name=self.name,typedef=self.typedef):
+ with self._var_block_() as vb:
+ i=0
+ for l in lines:
+ match = union_vars.match(l)
+ if match:
+ ctype = match.group(1)
+ variables = match.group(2).replace(';','').split(',')
+ if (ctype_overrides is not None) and (i in ctype_overrides.keys()):
+ ctype = ctype_overrides[i]
+ if comments is not None:
+ vb.decl_var(ctype,','.join(variables), comment=comments[i])
+ else:
+ vb.decl_var(ctype,','.join(variables))
+ i+=1
+
+ def build_codegen_variable(self, name, **kargs):
+ return CodegenStruct(name=name, struct=self, **kargs)
+
+if __name__ == '__main__':
+
+ from hysop.backend.device.codegen.base.test import _test_typegen
+
+ dtype = []
+ dtype.append( ('f0', np.float32 ) )
+ dtype.append( ('d0', np.int32) )
+ dtype.append( ('v0', np_dtype('float4')) )
+ dtype.append( ('v1', np_dtype('int16')) )
+
+ scg = UnionCodeGenerator('TestUnion',dtype,typedef='TestUnion_s',
+ typegen=_test_typegen())
+ scg.edit()
+ scg.test_compile()
+
+
diff --git a/hysop/codegen/base/utils.py b/hysop/backend/device/codegen/base/utils.py
similarity index 78%
rename from hysop/codegen/base/utils.py
rename to hysop/backend/device/codegen/base/utils.py
index 89fb57db9c8ed9c9e3dae9bcafeb0ae45644cab9..50c08aa80daa0407294a8ea24d42a27d5fae2276 100644
--- a/hysop/codegen/base/utils.py
+++ b/hysop/backend/device/codegen/base/utils.py
@@ -33,7 +33,7 @@ class ReadDefaultWriteOnceDict(WriteOnceDict):
class VarDict(WriteOnceDict):
def __setitem__(self,key,val):
- from hysop.codegen.base.variables import CodegenVariable
+ from hysop.backend.device.codegen.base.variables import CodegenVariable
if not isinstance(key,str):
raise TypeError('VarDict key should be a string!')
elif not isinstance(val,CodegenVariable):
@@ -47,7 +47,7 @@ class ArgDict(WriteOnceDict):
self.arg_order = []
self.overloading_allowed = overloading_allowed
def __setitem__(self,key,val):
- from hysop.codegen.base.variables import CodegenVariable
+ from hysop.backend.device.codegen.base.variables import CodegenVariable
if not isinstance(key,str):
raise TypeError('ArgDict key should be a string!')
elif not isinstance(val,CodegenVariable):
@@ -61,9 +61,12 @@ class ArgDict(WriteOnceDict):
if append:
self.arg_order.append(key)
+ def iteritems(self):
+ return iter([(argname, self.__getitem__(argname)) for argname in self.arg_order])
+
def build_args(self):
- function_args = []
- add_impl_const = []
+ function_proto_args = []
+ function_impl_args = []
constant_args = []
i=0
for varname in self.arg_order:
@@ -71,13 +74,18 @@ class ArgDict(WriteOnceDict):
if var.symbolic_mode and var.known():
constant_args.append(var)
elif var.is_symbolic():
- function_args.append(var.argument())
- if var.add_impl_const:
- add_impl_const.append(i)
+ prototype_arg = var.argument(impl=False)
+ implementation_arg = var.argument(impl=True)
+ function_proto_args.append(prototype_arg)
+ function_impl_args.append(implementation_arg)
i+=1
- if function_args[-1][-1]=='\n':
- function_args[-1] = function_args[-1][:-1]
- return function_args, constant_args, add_impl_const
+
+ if len(function_impl_args) and len(function_proto_args[-1]):
+ if function_proto_args[-1][-1]=='\n':
+ function_proto_args[-1] = function_proto_args[-1][:-1]
+ if function_impl_args[-1][-1]=='\n':
+ function_impl_args[-1] = function_impl_args[-1][:-1]
+ return function_proto_args, function_impl_args, constant_args
def function_name_suffix(self, return_type):
if not self.overloading_allowed:
diff --git a/hysop/codegen/base/variables.py b/hysop/backend/device/codegen/base/variables.py
similarity index 51%
rename from hysop/codegen/base/variables.py
rename to hysop/backend/device/codegen/base/variables.py
index 9017aa43e9335307c3797f643c3ec1eb8d94b041..943a08fab9253ea63499512c5dd2c13d46a567af 100644
--- a/hysop/codegen/base/variables.py
+++ b/hysop/backend/device/codegen/base/variables.py
@@ -1,13 +1,13 @@
-import re
-import hysop.codegen.base.types
+from hysop.deps import np, re, copy
+from hysop.tools.types import to_list, check_instance
+import hysop.backend.device.opencl.opencl_types
-from hysop.constants import np
-from hysop.codegen.base.utils import VarDict
-from hysop.codegen.base.types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import VarDict
+from hysop.backend.device.opencl.opencl_types import TypeGen, OpenClTypeGen
# opencl extras
-from hysop.codegen.base.types import cl_type_to_dtype
+from hysop.backend.device.opencl.opencl_types import cl_type_to_dtype
_ctype_to_dtype = {
'bool': np.bool_,
@@ -21,13 +21,13 @@ _ctype_to_dtype = {
'signed char': np.int8,
'signed short': np.int16,
'signed int': np.int32,
- 'signed long int': np.int32,
+ 'signed long int': np.int64,
'signed long long int': np.int64,
'unsigned char': np.uint8,
'unsigned short': np.uint16,
'unsigned int': np.uint32,
- 'unsigned long int': np.uint32,
+ 'unsigned long int': np.uint64,
'unsigned long long int': np.uint64,
'size_t': np.uint64, # warning: host and/or device can be 32bits
@@ -36,6 +36,7 @@ _ctype_to_dtype = {
'half': np.float16,
'float' : np.float32,
'double': np.float64,
+ 'long double': np.longdouble,
}
@@ -60,18 +61,72 @@ def register_ctype_dtype(ctype,dtype):
_ctype_to_dtype[ctype] = dtype
class CodegenVariable(object):
- def __init__(self,name,ctype,typegen,
- value=None, svalue=None,
- const=False, add_impl_const=False,
- storage=None, nl=None,
- ptr=False, restrict=False,
- init=None,
- symbolic_mode=False,struct_var=None):
+ def __init__(self, name, ctype, typegen,
+ storage=None, const=False, volatile=False,
+ add_impl_const=False, nl=None,
+ ptr=False, ptr_restrict=None, ptr_volatile=None, ptr_const=None,
+ value=None, svalue=None, init=None,
+ symbolic_mode=False, struct_var=None):
+
+ check_instance(typegen, TypeGen)
+
+ check_instance(name, str)
+ check_instance(ctype, str)
+ check_instance(storage, str, allow_none=True)
+ assert len(name)>0
+ assert len(ctype)>0
+ assert (storage is None) or len(ctype)>0
+
+ check_instance(const, bool)
+ check_instance(volatile, bool)
+ check_instance(add_impl_const, bool)
+ check_instance(nl, bool, allow_none=True)
+
+ self.name = name
+ self.ctype = ctype
+ self.typegen = typegen
+ self.const = const
+ self.volatile = volatile
+ self.add_impl_const = add_impl_const
+ self.storage = storage
- self.name = name
- self.ctype = ctype
- self.typegen = typegen
+ self.nl = nl if (nl is not None) else (storage is not None)
+ self.struct_var = struct_var
+ self.symbolic_mode = symbolic_mode
+
+ # pointer
+ if isinstance(ptr,bool):
+ is_ptr = ptr
+ ptr_level = int(ptr)
+ else:
+ check_instance(ptr, (int, long))
+ is_ptr = True
+ ptr_level = ptr
+ del ptr
+
+ if is_ptr:
+ ptr_restrict = to_list(ptr_restrict)
+ ptr_const = to_list(ptr_const)
+ ptr_volatile = to_list(ptr_volatile)
+ _len = max(len(ptr_restrict), len(ptr_const), len(ptr_volatile))
+ assert _len <= ptr_level
+
+ ptr_restrict = np.asarray(ptr_restrict + [False]*(ptr_level-len(ptr_restrict)))
+ ptr_volatile = np.asarray(ptr_volatile + [False]*(ptr_level-len(ptr_volatile)))
+ ptr_const = np.asarray(ptr_const + [False]*(ptr_level-len(ptr_const)))
+ else:
+ assert ptr_restrict is None
+ assert ptr_volatile is None
+ assert ptr_const is None
+
+ self.is_ptr = is_ptr
+ self.ptr_level = ptr_level
+ self.ptr_restrict = ptr_restrict
+ self.ptr_const = ptr_const
+ self.ptr_volatile = ptr_volatile
+
+ # value and svalue
if value is None:
value = None
elif np.isscalar(value):
@@ -94,39 +149,157 @@ class CodegenVariable(object):
value = value.copy()
else:
pass
-
+
self.value = value
self.svalue = svalue
-
- self.storage = storage
- self.nl = nl if (nl is not None) else (storage is not None)
- self.ptr = ptr
- self.struct_var = struct_var
- self.symbolic_mode = symbolic_mode
self.init=init
- const = [const] if isinstance(const,bool) else const
- add_impl_const = [add_impl_const] if isinstance(add_impl_const,bool) else add_impl_const
- restrict = [restrict] if isinstance(restrict,bool) else restrict
- const = np.asarray(const,dtype=bool)
- add_impl_const = np.asarray(add_impl_const,dtype=bool)
- restrict = np.asarray(restrict,dtype=bool)
- if (const.size != add_impl_const.size) or (const.size != restrict.size):
- raise ValueError('const, add_impl_const, restrict size mismatch!')
- if not ptr and restrict.any():
- raise ValueError('Non pointer types cannot be aliased!')
- if not ptr and (const.size>1 or add_impl_const.size>1):
- raise ValueError('Non pointer types cannot have multiple const qualifiers!')
- if np.logical_and(const, add_impl_const).any():
- raise ValueError('Variable {} is const and add_impl_const has been specified!'.format(name))
- #if (struct_var is not None) and (struct_var.const) and (not const[0]):
- #raise ValueError('Variable {} declared in const struct {} is not const!'.format(name,struct_var.name))
- self.const = const
- self.add_impl_const = add_impl_const
- self.restrict = restrict
+ # check
+ if add_impl_const:
+ if (not is_ptr):
+ if const:
+ msg='Variable {} is const and add_impl_const has been specified!'
+ msg=msg.format(name)
+ raise ValueError(msg)
+ elif len(ptr_const)>0:
+ if ptr_const[-1]:
+ msg='Variable {} has ptr_const[-1]=True and add_impl_const has been specified!'
+ msg=msg.format(name)
+ raise ValueError(msg)
+
+
+ def newvar(self, name, nl=False, typegen=None,
+ storage=None, value=None, svalue=None, init=None,
+ ctype=None, const=None, volatile=None, add_impl_const=None,
+ ptr=None, ptr_restrict=None, ptr_volatile=None, ptr_const=None):
+
+ ctype = self.ctype if (ctype is None) else ctype
+ const = self.const if (const is None) else const
+ volatile = self.volatile if (volatile is None) else volatile
+ add_impl_const = self.add_impl_const if (add_impl_const is None) else add_impl_const
+ storage = self.storage if (storage is None) else storage
+ typegen = self.typegen if (typegen is None) else typegen
+
+ if ptr is None:
+ ptr = self.ptr_level if (ptr is None) else ptr
+ ptr_const = self.ptr_const if (ptr_const is None) else ptr_const
+ ptr_volatile = self.ptr_volatile if (ptr_volatile is None) else ptr_volatile
+ ptr_restrict = self.ptr_restrict if (ptr_restrict is None) else ptr_restrict
+
+ return CodegenVariable(name=name, nl=nl,
+ value=value, svalue=svalue, init=init,
+ ctype=ctype, storage=storage,
+ const=const, volatile=volatile,
+ add_impl_const=add_impl_const,
+ ptr=ptr, ptr_restrict=ptr_restrict,
+ ptr_volatile=ptr_volatile, ptr_const=ptr_const,
+ typegen=typegen)
+
+ def pointer_alias(self, name, ctype, **kargs):
+ handle = self.newvar(name=name, ctype=ctype,
+ init='({})({})'.format(
+ self.full_ctype(cast=True,ctype=ctype), self),
+ **kargs)
+ return handle
+
+ def pointer(self, name, ptr_level,
+ ptr_const=None, ptr_volatile=None, ptr_restrict=None,
+ add_impl_const=False, with_init=True, **kargs):
+ ptr_const = [False]*ptr_level if (ptr_const is None) else to_list(ptr_const)
+ ptr_volatile = [False]*ptr_level if (ptr_volatile is None) else to_list(ptr_volatile)
+ ptr_restrict = [False]*ptr_level if (ptr_restrict is None) else to_list(ptr_restrict)
+ assert ptr_level>0
+ assert len(ptr_const) == ptr_level
+ assert len(ptr_volatile) == ptr_level
+ assert len(ptr_restrict) == ptr_level
+ if self.is_ptr:
+ ptr_level = self.ptr_level + ptr_level
+ ptr_const = self.ptr_const + ptr_const
+ ptr_volatile = self.ptr_volatile + ptr_volatile
+ ptr_restrict = self.ptr_restrict + ptr_restrict
+ if with_init:
+ init = '&{}'.format(self.name)
+ else:
+ init = None
+ return self.newvar(name=name, ptr=ptr_level,
+ ptr_const=ptr_const, ptr_volatile=ptr_volatile,
+ ptr_restrict=ptr_restrict, init=init,
+ add_impl_const=add_impl_const, **kargs)
+
+
+ def base_ctype(self, storage=None, ctype=None,
+ const=None, volatile=None,
+ impl=True, align=False,
+ add_impl_const=None):
+ storage = self.storage if (storage is None) else storage
+ ctype = self.ctype if (ctype is None) else ctype
+ volatile = self.volatile if (volatile is None) else volatile
+
+ if (const is None):
+ const = self.const
+ if impl and (not self.is_ptr) and (not const):
+ const = self.add_impl_const if (add_impl_const is None) else add_impl_const
+
+ base_ctype = '{storage}${const}${volatile}${ctype}'.format(
+ storage='{} '.format(storage) if (storage is not None) else '',
+ const='const ' if const else '',
+ volatile='volatile ' if volatile else '',
+ ctype=ctype+' ')
+ if not align:
+ base_ctype = base_ctype.replace('$','')
+ return base_ctype.strip()
+
+
+ def ptr_ctype(self, impl=True, add_impl_const=None, cast=False):
+ if self.is_ptr:
+ ptrs=[]
+ add_impl_const = self.add_impl_const if (add_impl_const is None) else add_impl_const
+ for i, (c,v,r) in enumerate(zip(self.ptr_const, self.ptr_volatile, self.ptr_restrict)):
+ if i==self.ptr_level-1:
+ c = c or (impl and add_impl_const)
+ ptr=' $*{const}${volatile}${restrict}'.format(
+ const = 'const ' if (c and not cast) else '',
+ volatile = 'volatile ' if (v and not cast) else '',
+ restrict = 'restrict ' if (r and not cast) else '')
+ ptrs.append(ptr)
+ ptr_ctype = ''.join(ptrs)
+ else:
+ ptr_ctype=''
+ return ptr_ctype
+ def full_ctype(self, storage=None, ctype=None, const=None, volatile=None,
+ impl=True, multidecl=False, align=False, cast=False,
+ add_impl_const=None):
+
+ if multidecl:
+ base_ctype = ''
+ else:
+ base_ctype = self.base_ctype(storage,ctype,const,volatile,impl,align,
+ add_impl_const=add_impl_const)
+ if len(base_ctype)==0:
+ msg= 'Failed to get base ctype in {}.'.format(self.__class__)
+ raise RuntimeError(msg)
+ ptr_ctype = self.ptr_ctype(impl=impl, add_impl_const=add_impl_const, cast=cast)
+
+ full_ctype = '{}{}'.format(base_ctype, ptr_ctype)
+ if not align:
+ full_ctype = full_ctype.replace('$', '')
+ else:
+ full_ctype = full_ctype.replace('$ ', '$')
+
+ return full_ctype.strip()
+ def argument(self,impl,
+ nl=None, name=None,
+ **kargs):
+ name = self.name if (name is None) else name
+ nl = self.nl if (nl is None) else nl
+ return '{} {name}{nl}'.format(
+ self.full_ctype(impl=impl, **kargs),
+ name=name,
+ nl='\n' if self.nl else '')
+
def is_symbolic(self):
return (self.value is None) or self.symbolic_mode
def in_struct(self):
@@ -142,8 +315,9 @@ class CodegenVariable(object):
assert not self.known(), 'Value was already set in variable {}!'.format(self.name)
self.value = val
- def sval(self):
- if self.is_symbolic():
+ def sval(self, symbolic=None):
+ symbolic = self.is_symbolic() if (symbolic is None) else symbolic
+ if symbolic:
return self.access_prefix(access=False)
else:
if self.svalue is not None:
@@ -153,7 +327,8 @@ class CodegenVariable(object):
elif self.value is not None:
return self.typegen.dump(self.value)
else:
- raise NotImplementedError()
+ msg='value and svalue are not defined.'
+ raise RuntimeError(msg)
def access_prefix(self,access):
acc = ''
@@ -161,197 +336,194 @@ class CodegenVariable(object):
acc += self.struct_var.access_prefix(access=True)
acc += self.name
if access:
- acc += '->' if self.ptr else '.'
+ acc += '->' if self.is_ptr else '.'
return acc
- def declare(self,codegen=None,align=False,
- const=None,restrict=None,
- storage=None,init=None):
-
- storage = storage if (storage is not None) else self.storage
- storage = '{} '.format(storage) if (storage is not None) else ''
-
- if const is not None:
- self.const = np.asarray(self.const,bool)
- const = (const,)+(False,)*(self.const.size-1) if isinstance(const,bool) else const
- const = np.asarray(const,dtype=bool)
- const = np.logical_or(const, self.const)
- else:
- const = self.const
+ def decl_name(self):
+ return self.name
+
+ def declare(self, codegen=None, align=False,
+ multidecl=False, const=None, init=None,
+ compact=False):
+ # const means add_impl_const, ie. declare current variable as constant (not pointed types)
+ ctype = self.full_ctype(align=align,multidecl=multidecl,add_impl_const=const)
+ if (not multidecl) and len(ctype)==0:
+ msg= 'Failed to get full ctype in {}.'.format(self.__class__)
+ raise RuntimeError(msg)
- if restrict is not None:
- restrict = (restrict,)+(False,)*(self.restrict.size-1) if isinstance(restrict,bool) else restrict
- restrict = np.asarray(restrict,dtype=bool)
- restrict = np.logical_or(restrict, self.restrict)
- else:
- restrict = self.restrict
+ # static array ctype needs to be split
+ name = self.decl_name()
- if self.ptr:
- if hasattr(self, 'sshape'):
- sshape = self.sshape
- qualifiers = ['[{}{}{}]'.format(
- s,
- (' const' if c else ''),
- (' restrict' if r else '' ))
- for (s,c,r) in zip(sshape,const,restrict)]
- array_qualifiers = ''.join(qualifiers)
- else:
- qualifiers = [(' const' if c else '') + (' restrict' if r else '' ) for (c,r) in zip(const,restrict)]
- array_qualifiers = '*'+'*'.join(qualifiers)
- ctype = '{}{}'.format(self.ctype, array_qualifiers)
- modifiers = storage
+ if init==False:
+ msg='Const variable should be initialized at declaration.'
+ assert (not self.const) or (not self.add_impl_const), msg
+ init=None
else:
- ctype = self.ctype
- modifiers = '{}{}'.format(storage,'' if not const else 'const ')
-
- init = init if (init is not None) else self.init
-
- code = '{}{} ${}'.format(modifiers, ctype, self.name)
+ init = init if (init is not None) else self.init
+ if (len(ctype)>0) and ctype[-1]=='*':
+ code = '{}${}'.format(ctype, name)
+ else:
+ code = '{} ${}'.format(ctype, name)
+
if (init is not None):
- code = '{} $= {}'.format(code,init)
+ if compact:
+ code = '{}={}'.format(code,init)
+ else:
+ code = '{} $= {}'.format(code,init)
elif self.known():
self.force_symbolic(False)
sval = self.sval()
- code = '{} $= {}'.format(code,sval)
- else:
- pass
- code+=';'
+ if compact:
+ code = '{}={}'.format(code,sval)
+ else:
+ code = '{} $= {}'.format(code,sval)
+
+ if not multidecl:
+ code+=';'
+
self.force_symbolic()
+ if not align:
+ code = code.replace('$','')
+ if codegen is not None:
+ codegen.append(code)
+ return code.strip()
+
+ def affect(self, codegen=None, align=False, init=None,
+ compact=False, i=None):
+ msg='Cannot affect a const variable.'
+ assert (not self.const) or (not self.add_impl_const), msg
+ init = self.init if (init is None) else init
+ if compact:
+ code = '{}$={};'
+ else:
+ code = '{} $= {};'
+ if i is None:
+ var = self
+ else:
+ var = self[i]
+ code = code.format(var, init)
if not align:
code = code.replace('$','')
if codegen is not None:
codegen.append(code)
return code
- def argument(self,const=None):
- if const is None:
- const = self.const
- storage = self.storage+' ' if self.storage else ''
- const = 'const ' if const else ''
- ctype = self.ctype
- ctype = self.ctype+'*' if self.ptr else self.ctype
- restrict = ' restrict' if self.restrict else ''
- name = self.name
- nl = '\n' if self.nl else ''
-
- return '{storage}{const}{ctype}{restrict} {name}{nl}'.format(storage=storage,restrict=restrict,const=const,ctype=ctype,name=name,nl=nl)
-
- def __call__(self):
- return self.sval()
def __getitem__(self,ss):
- if self.ptr:
+ if self.is_ptr:
return '{}[{}]'.format(self.name,ss)
elif ss==0:
return self.__call__()
else:
- assert self.ptr, '{} is not a pointer!'.format(self.name)
- def __str__(self):
+ assert self.is_ptr, '{} is not a pointer!'.format(self.name)
+
+ def __repr__(self):
if self.is_symbolic():
return '{}({})'.format(self.name,self.ctype)
else:
return '{}({},{})'.format(self.name,self.ctype,self.value)
+
+ def __call__(self):
+ return self.sval()
+ def __str__(self):
+ return self.sval()
class CodegenArray(CodegenVariable):
@staticmethod
- def initialize_rec(name,dim,
- ctype, typegen,
- shape,sshape,value,svalue,
- const, add_impl_const, restrict,
- symbolic_mode):
+ def _initialize_rec(name, typegen,
+ storage, ctype, const, volatile,
+ shape, sshape, value, svalue,
+ ptr_level, ptr_restrict, ptr_const, ptr_volatile,
+ symbolic_mode):
if (value is None):
return value, svalue
s0 = shape[0]
- if dim==1:
- _name = name
- _value = value
+
+ if ptr_level==1:
+ _name = name
+ _value = value
if (svalue is not None):
_svalue = '{ ' + ', '.join(svalue) + ' }'
else:
- _const = const[1:]
- _add_impl_const= add_impl_const[1:]
- _restrict=restrict[1:]
_shape = shape[1:]
_sshape = sshape[1:]
+ _ptr_level = ptr_level - 1
+ _ptr_const = ptr_const[:-1]
+ _ptr_restrict = ptr_restrict[:-1]
+ _ptr_volatile = ptr_volatile[:-1]
+
_value = [None]*s0
_svalue = [None]*s0
for d in xrange(s0):
- _name = name+'_{}'.format(d)
- val, sval = CodegenArray.initialize_rec(_name,
- dim-1, ctype, typegen,
- _shape, _sshape, value[d], svalue[d],
- _const, _add_impl_const, _restrict,
+ _name = '{}_{}'.format(name, d)
+ _value = value[d]
+ _svalue = svalue[d]
+ val, sval = CodegenArray.initialize_rec(_name, typegen,
+ storage, ctype, const, volatile,
+ _shape, _sshape, _value, _svalue,
+ _ptr_level, _ptr_restrict, _ptr_const, _ptr_volatile,
symbolic_mode)
- var = CodegenArray(name=_name,
- ctype=ctype, typegen=typegen,
- dim=dim-1,
- shape=_shape, sshape=_sshape,
- value=val, svalue=sval,
- symbolic_mode=False, struct_var=None,direct_init=True)
+ var = CodegenArray(name=_name, typegen=typegen,
+ storage=storage, ctype=ctype, const=const, volatile=volatile,
+ shape=_shape, sshape=_sshape, value=val, svalue=sval,
+ dim=_ptr_level, ptr_const=_ptr_const,
+ ptr_volatile=_ptr_volatile, ptr_restrict=_ptr_restrict,
+ add_impl_const=False,
+ symbolic_mode=False,
+ struct_var=None,
+ _direct_init=True)
_value[d] = var
_svalue[d] = '\n\t'.join(sval.split('\n'))
- if svalue is not None:
- _svalue = '{\n\t'+',\n\t'.join(_svalue)+'\n}'
- else:
+
+ if svalue is None:
_svalue=None
+ else:
+ _svalue = '{\n\t'+',\n\t'.join(_svalue)+'\n}'
return _value, _svalue
- def __init__(self, name, ctype, typegen,
- dim=1,
- shape=None, sshape=None,
+ def __init__(self, name, ctype, typegen,
+ storage=None, volatile=False, const=False, add_impl_const = False,
+ dim=1, ptr_const=None, ptr_volatile=None, ptr_restrict=None,
+ shape=None, sshape=None,
value=None, svalue=None,
- const=None, add_impl_const=None,
- restrict=None,
symbolic_mode=False, struct_var=None,
- direct_init=False):
+ _direct_init=False):
+
+ ptr_level = dim
+ del dim
- if direct_init:
+ if _direct_init:
_value, _svalue = value, svalue
else:
- if const is None:
- const = (False,)*dim
- elif const in [True,False]:
- const = (const,)*dim
- elif len(const)!= dim:
- raise ValueError('const dim mismatch!')
- const = np.asarray(const)
-
- if add_impl_const is None:
- add_impl_const = (False,)*dim
- elif add_impl_const in [True,False]:
- add_impl_const = (add_impl_const,)*dim
- elif len(add_impl_const)!= dim:
- raise ValueError('add_impl_const dim mismatch!')
- add_impl_const = np.asarray(add_impl_const)
-
- if restrict is None:
- restrict = (False,)*dim
- elif restrict in [True,False]:
- restrict = (restrict,)*dim
- elif len(restrict)!= dim:
- raise ValueError('restrict dim mismatch!')
- restrict = np.asarray(restrict)
+ ptr_const = [] if (ptr_const is None) else to_list(ptr_const)
+ ptr_volatile = [] if (ptr_volatile is None) else to_list(ptr_volatile)
+ ptr_restrict = [] if (ptr_restrict is None) else to_list(ptr_restrict)
+ ptr_const += [False]*(ptr_level-len(ptr_const))
+ ptr_volatile += [False]*(ptr_level-len(ptr_volatile))
+ ptr_restrict += [False]*(ptr_level-len(ptr_restrict))
if (value is not None):
value = np.asarray(value)
- if value.ndim != dim:
- raise ValueError('value array dim mismatch!')
+ if value.ndim != ptr_level:
+ raise ValueError('value array dim mismatch.')
if shape is None:
shape = value.shape
+ else:
+ assert value.shape == shape, 'shape mismatch.'
if (svalue is not None):
svalue = np.asarray(svalue)
if value is None:
raise ValueError('value cannot be None when svalue is not None.')
- if svalue.ndim != dim:
+ if svalue.ndim != ptr_level:
raise ValueError('svalue input array dimension mismatch!')
if svalue.shape != value.shape:
raise ValueError('Input array shape mismatch between value and svalue.')
- elif value is not None:
+ elif (value is not None):
svalue = np.zeros_like(value,dtype=object)
dtype = ctype_to_dtype(ctype)
sview = svalue.flat
@@ -359,47 +531,89 @@ class CodegenArray(CodegenVariable):
sview[i] = typegen.dump(v)
if (shape is not None):
- if len(shape)!=dim:
+ if len(shape)!=ptr_level:
raise ValueError('shape dim mismatch!')
else:
- shape = (None,)*dim
+ shape = (None,)*ptr_level
shape = np.asarray(shape)
if (sshape is None) and (shape[0] != None):
- sshape = [s.__str__() for s in shape]
+ sshape = [str(s) for s in shape]
elif (sshape is not None) and len(sshape)!=dim:
raise ValueError('sshape dim mismatch!')
else:
- sshape = (None,)*dim
+ sshape = (None,)*ptr_level
sshape = np.asarray(sshape)
- _value, _svalue = CodegenArray.initialize_rec(name,dim,
- ctype, typegen, shape, sshape, value, svalue,
- const, add_impl_const, restrict,
+ _value, _svalue = CodegenArray._initialize_rec(name, typegen,
+ storage, ctype, const, volatile,
+ shape, sshape, value, svalue,
+ ptr_level, ptr_restrict, ptr_const, ptr_volatile,
symbolic_mode)
-
- super(self.__class__, self).__init__(name=name,
- ctype=ctype, typegen=typegen,
+
+ super(CodegenArray, self).__init__(name=name,
+ storage=storage, ctype=ctype, typegen=typegen,
value=_value, svalue=_svalue,
- const=const, add_impl_const=add_impl_const,
- ptr=True,restrict=restrict,
+ const=const, add_impl_const=add_impl_const, volatile=volatile,
+ ptr=ptr_level, ptr_restrict=ptr_restrict, ptr_const=ptr_const, ptr_volatile=ptr_volatile,
symbolic_mode=symbolic_mode, struct_var=struct_var)
self.shape = shape
self.sshape = sshape
-
+
+ def decl_name(self):
+ if self.shape:
+ static_array = ['[{}]'.format(val) for val in self.shape]
+ elif self.shape:
+ static_array = ['[{}]'.format(val) for val in self.sshape]
+ else:
+ static_array = []
+ return '{}{}'.format(self.name, ''.join(static_array))
+
+ def array_dim(self):
+ if (self.shape is not None):
+ return self.shape.size
+ if (self.sshape is not None):
+ return self.sshape.size
+ msg='unknown array dim.'
+ raise RuntimeError(msg)
+
+ def ptr_ctype(self, impl=True, add_impl_const=None, cast=False):
+ if self.is_ptr:
+ add_impl_const = self.add_impl_const if (add_impl_const is None) else add_impl_const
+
+ dim = self.array_dim()
+ ptr_const = self.ptr_const[dim:]
+ ptr_volatile = self.ptr_volatile[dim:]
+ ptr_restrict = self.ptr_restrict[dim:]
+
+ ptrs=[]
+ for i, (c,v,r) in enumerate(zip(ptr_const, ptr_volatile, ptr_restrict)):
+ if i==self.ptr_level-1:
+ c = c or (impl and add_impl_const)
+ ptr=' $*{const}${volatile}${restrict}'.format(
+ const = 'const ' if (c and not cast) else '',
+ volatile = 'volatile ' if (v and not cast) else '',
+ restrict = 'restrict ' if (r and not cast) else '')
+ ptrs.append(ptr)
+ ptr_ctype = ''.join(ptrs)
+ else:
+ ptr_ctype=''
+ return ptr_ctype
+
class CodegenVector(CodegenVariable):
- def __init__(self,name,ctype,dim,typegen,
+ def __init__(self, name, ctype, dim, typegen,
value=None,svalue=None,
- const=False, add_impl_const=False,
- storage=None, nl=None,
- ptr=False, restrict=False,
+ storage=None, const=False, volatile=False,
+ ptr=False, ptr_const=None, ptr_volatile=None, ptr_restrict=None,
+ add_impl_const=False, nl=None,
symbolic_mode=False, struct_var=None,
init=None):
super(CodegenVector,self).__init__(name=name,ctype=ctype,value=value,typegen=typegen,
- const=const, add_impl_const=add_impl_const,
- storage=storage, nl=nl, ptr=ptr, restrict=restrict,
+ const=const, volatile=volatile, add_impl_const=add_impl_const,
+ storage=storage, nl=nl,
+ ptr=ptr, ptr_const=ptr_const, ptr_volatile=ptr_volatile, ptr_restrict=ptr_restrict,
symbolic_mode=symbolic_mode,struct_var=struct_var,init=init)
self.value = value
@@ -428,7 +642,7 @@ class CodegenVector(CodegenVariable):
def __getitem__(self,i):
return self.sval(i)
- def __str__(self):
+ def __repr__(self):
if self.is_symbolic():
return '{}({})'.format(self.name,self.ctype)
else:
@@ -509,7 +723,6 @@ class CodegenVectorClBuiltin(CodegenVector):
else:
self.svalue = [self.typegen.dump(f) for f in value]
-
def sval(self,i=None):
if self.is_symbolic():
if self.dim==1:
@@ -548,13 +761,24 @@ class CodegenVectorClBuiltin(CodegenVector):
return self.sval(key)
else:
raise TypeError, 'Invalid key type!'
+
+ def declare(self, codegen=None, init=None, **kargs):
+ if isinstance(init,int):
+ init = ','.join([self.typegen.dump(init) for _ in xrange(self.dim)])
+ init = '({})({})'.format(self.ctype,init)
+ elif init.__class__ in [list,tuple,np.ndarray]:
+ init = ','.join([self.typegen.dump(init[i]) for i in xrange(self.dim)])
+ init = '({})({})'.format(self.ctype,init)
+ return super(CodegenVectorClBuiltin,self).declare(init=init, codegen=codegen, **kargs)
+
class CodegenVectorClBuiltinFunc(CodegenVectorClBuiltin):
def __init__(self,fname,name,btype,dim,typegen,
value=None,access_mode='pos',
+ symbolic_mode=False,
const=False):
super(CodegenVectorClBuiltinFunc,self).__init__(name=name,btype=btype,dim=dim,typegen=typegen,
- value=value,access_mode=access_mode,const=const)
+ value=value,access_mode=access_mode,const=const,symbolic_mode=symbolic_mode)
self.fname = fname
def fval(self,i=None):
@@ -565,36 +789,37 @@ class CodegenVectorClBuiltinFunc(CodegenVectorClBuiltin):
assert i<self.dim
return 'get_{}({})'.format(self.fname,i)
- def declare(self,codegen=None,align=False,const=None,storage=None):
- init = self.fval() if not self.known() else None
- return super(CodegenVectorClBuiltinFunc,self).declare(codegen=codegen,align=align,const=const,storage=storage,init=init)
+ def declare(self, codegen=None, init=None, **kargs):
+ if init is False:
+ init = None
+ else:
+ init = self.fval() if not self.known() else init
+ return super(CodegenVectorClBuiltinFunc,self).declare(init=init, codegen=codegen, **kargs)
class CodegenStruct(CodegenVariable):
- def __init__(self,varname,struct,
- ptr=False, restrict=False,
- const=False, add_impl_const=False,
- storage=None, nl=None,
+ def __init__(self, name, struct,
+ storage=None, const=False, volatile=False,
+ ptr=False, ptr_const=None, ptr_volatile=None, ptr_restrict=None,
+ add_impl_const=False, nl=None,
symbolic_mode=False,
struct_var=None,
value=None,
var_overrides=None):
super(CodegenStruct,self).__init__(
- name=varname,
+ name=name,
ctype=struct.ctype,
typegen=struct.typegen,
+ storage=storage, const=const, volatile=volatile,
+ ptr=ptr, ptr_const=ptr_const,
+ ptr_volatile=ptr_volatile, ptr_restrict=ptr_restrict,
+ add_impl_const=add_impl_const, nl=nl,
value=value,
- const=const,
- add_impl_const=add_impl_const,
- storage=storage,
- nl=nl,
- ptr=ptr,
- restrict=restrict,
symbolic_mode=symbolic_mode,
struct_var=struct_var)
self.genvars(struct,var_overrides)
-
+
def force_symbolic(self, force=True):
if force is None:
return
@@ -606,7 +831,15 @@ class CodegenStruct(CodegenVariable):
if key in self.vars:
return self.vars[key]
else:
- raise KeyError('Unknown field {} in struct {}.\nAvailable fields are: {}'.format(key,self.name,self.vars.keys()))
+ msg='Unknown field {} in struct {}.\nAvailable fields are: {}'
+ msg=msg.format(key,self.name,self.vars.keys())
+ raise KeyError(msg)
+
+ def __getattr__(self, name):
+ if name in self.vars:
+ return self.__getitem__(name)
+ else:
+ raise AttributeError
def genvars(self,struct,var_overrides):
if var_overrides is None:
@@ -631,7 +864,8 @@ class CodegenStruct(CodegenVariable):
array = match.group(3)
nptrs = len(ptrs) if ptrs else 0
- narray = [int(x) for x in array[:-1].replace('[','').split(']')] if array else None
+ narray = [int(x) for x in array[:-1].replace('[','').split(']')] \
+ if array else None
is_struct = (struct.fields()[fieldname][0].fields is not None)
if nptrs>0:
@@ -653,7 +887,7 @@ class CodegenStruct(CodegenVariable):
var = var_overrides[fieldname]
var.struct_var = self
var.const = self.const
- elif is_struct and (ctype in hysop.codegen.base.types.builtin_types):
+ elif is_struct and (ctype in hysop.backend.device.opencl.opencl_types.builtin_types):
tg=struct.typegen
btype = tg.basetype(ctype)
dim = tg.components(ctype)
@@ -690,9 +924,8 @@ class CodegenStruct(CodegenVariable):
if __name__ == '__main__':
-
- tg = OpenClTypeGen('float')
-
+ from hysop.backend.device.codegen.base.test import test_typegen
+ tg = test_typegen('float')
print':: ARRAYS ::'
#var = CodegenArray(name='A0',ctype='float',shape=(3,),value=[1,2,3],typegen=tg)
@@ -708,9 +941,6 @@ if __name__ == '__main__':
[16,17,18]
]],typegen=tg)
print var.declare()
-
- import sys
- sys.exit(1)
# runtime known variable
print ':: SYMBOLIC VECTOR ::'
@@ -765,7 +995,7 @@ if __name__ == '__main__':
# hexadecimal deciml float dumper
print ':: HEXADECIMAL FLOAT DUMPER ::'
var = CodegenVectorClBuiltin('size_hex','float',4, value=(1.0,2.0,4.0,8.0),
- typegen=OpenClTypeGen('float',float_dump_mode='hex'))
+ typegen=test_typegen('float',float_dump_mode='hex'))
print var()
for i in xrange(var.dim):
print var[i]
diff --git a/hysop/codegen/kernels/__init__.py b/hysop/backend/device/codegen/functions/__init__.py
similarity index 100%
rename from hysop/codegen/kernels/__init__.py
rename to hysop/backend/device/codegen/functions/__init__.py
diff --git a/hysop/backend/device/codegen/functions/advection_rhs.py b/hysop/backend/device/codegen/functions/advection_rhs.py
new file mode 100644
index 0000000000000000000000000000000000000000..23cc392a3c2baa0fab0266fc71e1abe10bce8a7a
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/advection_rhs.py
@@ -0,0 +1,166 @@
+
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+from hysop.constants import BoundaryCondition
+
+from hysop.backend.device.codegen.functions.apply_stencil import ApplyStencilFunction
+
+from hysop.numerics.stencil.stencil import Stencil
+
+# compute alpha*grad(u).w + (1-alpha)*grad(u)^T.w
+# where u may be is_cached and w is private
+# with finite difference centred stencil of given order
+class DirectionalAdvectionRhsFunction(OpenClFunctionCodeGenerator):
+
+ def __init__(self, typegen, ftype, work_dim, nparticles, is_cached, boundary,
+ ptr_restrict=True,
+ itype='int',
+ known_args=None):
+
+ assert work_dim>=1 and work_dim<=3
+ check_instance(boundary,BoundaryCondition)
+ assert nparticles in [1,2,4,8,16]
+
+ is_periodic = (boundary==BoundaryCondition.PERIODIC)
+
+ if is_cached:
+ storage='__local'
+ else:
+ storage='__global'
+
+ vtype = typegen.vtype(ftype,nparticles)
+
+ (args,basename) = self.build_prototype(typegen,work_dim,itype,ftype,vtype,
+ nparticles,ptr_restrict,storage,is_cached, is_periodic)
+
+ reqs = self.build_requirements(typegen,work_dim,itype,ftype,vtype,
+ nparticles,ptr_restrict,storage,is_cached, is_periodic)
+
+ super(DirectionalAdvectionRhsFunction,self).__init__(basename=basename,
+ output=vtype,typegen=typegen,inline=True,
+ args=args, known_args=known_args)
+
+ self.update_requirements(reqs)
+
+ self.work_dim = work_dim
+
+ self.itype = itype
+ self.ftype = ftype
+
+ self.storage = storage
+ self.boundary = boundary
+ self.nparticles = nparticles
+ self.is_cached = is_cached
+ self.is_periodic = is_periodic
+
+ self.gencode()
+
+ def build_prototype(self,typegen,work_dim,itype,ftype,vtype,
+ nparticles,ptr_restrict,storage,is_cached, is_periodic):
+
+ args = ArgDict()
+
+ args['line_velocity'] = CodegenVariable('line_velocity', ftype, typegen, const=True, add_impl_const=True,
+ storage=storage, ptr=True, ptr_restrict=ptr_restrict, nl=True)
+ args['X'] = CodegenVectorClBuiltin('X', ftype, nparticles, typegen, add_impl_const=True, nl=True)
+
+ if is_periodic and (not is_cached):
+ args['line_width'] = CodegenVariable('line_width', itype, typegen, add_impl_const=True)
+ args['line_offset'] = CodegenVariable('line_offset', itype, typegen, add_impl_const=True,nl=True)
+
+ args['rk_step'] = CodegenVariable('rk_step', itype, typegen)
+ args['inv_dx'] = CodegenVariable('inv_dx', ftype, typegen, add_impl_const=True, nl=True)
+ # args['active'] = CodegenVariable('active','bool',typegen, add_impl_const=True)
+
+ cached = 'cached_' if is_cached else ''
+ basename = 'advection_rhs_{}{}{}p'.format(cached, ftype[0], nparticles)
+
+ return (args,basename)
+
+ def build_requirements(self,typegen,work_dim,itype,ftype,vtype,
+ nparticles,ptr_restrict,storage,is_cached, is_periodic):
+ reqs = WriteOnceDict()
+ return reqs
+
+ def gencode(self):
+ s = self
+ tg = self.typegen
+ work_dim = s.work_dim
+
+ nparticles = s.nparticles
+
+ is_cached = s.is_cached
+ is_periodic = s.is_periodic
+
+ itype = s.itype
+ ftype = s.ftype
+
+ position = s.args['X']
+ velocity = s.args['line_velocity']
+
+ line_offset = s.args['line_offset']
+ if not is_cached and is_periodic:
+ line_width = s.args['line_width']
+
+ inv_dx = s.args['inv_dx']
+ rk_step = s.args['rk_step']
+
+ dX_dt = CodegenVectorClBuiltin('dX_dt', ftype, nparticles, tg)
+
+ pos = CodegenVectorClBuiltin('pos', ftype, nparticles, tg)
+ lidx = CodegenVectorClBuiltin('lidx', itype, nparticles, tg)
+ idx = CodegenVectorClBuiltin('idx', itype, nparticles, tg)
+ alpha = CodegenVectorClBuiltin('alpha', ftype, nparticles, tg)
+
+ Vl = CodegenVectorClBuiltin('Vl', ftype, nparticles, tg)
+ Vr = CodegenVectorClBuiltin('Vr', ftype, nparticles, tg)
+
+ part_ftype = Vl.ctype
+ part_itype = lidx.ctype
+
+ with s._function_():
+ s.jumpline()
+
+ dX_dt.declare(s,init=0)
+ with s._align_() as al:
+ pos.declare(al, init='{}*{}'.format(position(), inv_dx()),align=True)
+ lidx.declare(al, init='convert_{}_rtn({})'.format(part_itype, pos()),align=True)
+ alpha.declare(al, init='{} - convert_{}({})'.format(pos(),part_ftype,lidx()),align=True)
+ idx.declare(s)
+ s.jumpline()
+
+ with s._if_('{} == 0'.format(rk_step())):
+ s.append('{} = {}-{};'.format(idx(), lidx(), line_offset()))
+ reads = [velocity[idx[i] ] for i in xrange(nparticles)]
+ init = '({})({})'.format(part_ftype,', '.join(reads))
+ s.append('{} = {};'.format(dX_dt(), init))
+ with s._else_():
+ if is_periodic and not is_cached:
+ s.append('{lidx} = ({lidx}+{size})%{size};'.format(lidx=lidx(),size=line_width()))
+ s.append('{} = {}-{};'.format(idx(), lidx(), line_offset()))
+ reads = [velocity[idx[i] ] for i in xrange(nparticles)]
+ init = '({})({})'.format(part_ftype,', '.join(reads))
+ Vl.declare(s,init=init)
+ if is_periodic and not is_cached:
+ s.append('{lidx} = ({lidx}+1)%{size};'.format(lidx=lidx(),size=line_width()))
+ s.append('{} = {}-{};'.format(idx(), lidx(), line_offset()))
+ else:
+ s.append('{} += 1;'.format(idx()))
+ Vr.declare(s,init=init)
+ s.append('{} = mix({},{},{});'.format(dX_dt(), Vl(), Vr(), alpha()))
+
+ s.append('return {};'.format(dX_dt()))
+
+if __name__ == '__main__':
+
+ from hysop.backend.device.codegen.base.test import _test_typegen
+
+ tg = _test_typegen('float')
+ asf = DirectionalAdvectionRhsFunction(tg, 'float', 3, 4, False,
+ BoundaryCondition.PERIODIC)
+ asf.edit()
diff --git a/hysop/backend/device/codegen/functions/apply_stencil.py b/hysop/backend/device/codegen/functions/apply_stencil.py
new file mode 100644
index 0000000000000000000000000000000000000000..1fdd04e1f4d1112bc231503801efc25212b7b081
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/apply_stencil.py
@@ -0,0 +1,222 @@
+
+from hysop.deps import sm
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+from hysop.numerics.stencil.stencil import Stencil
+
+class ApplyStencilFunction(OpenClFunctionCodeGenerator):
+
+ def __init__(self,typegen,stencil,ftype,
+ symbol2vars=None,
+ components=1, vectorize=True,
+ extra_inputs=[],
+ scalar_inputs=[],
+ vector_inputs=['data'],
+ op='{vinput0}[id]',
+ custom_id=None,
+ vector_suffixes=None,
+ data_storage='__local', ptr_restrict=True,
+ multipliers={},
+ itype='int',
+ known_args=None):
+
+ check_instance(stencil,Stencil)
+ check_instance(symbol2vars, dict, keys=sm.Symbol, values=CodegenVariable, allow_none=True)
+ assert set(symbol2vars.keys())==stencil.variables()
+
+ extra_inputs = set(extra_inputs + symbol2vars.values())
+ scalar_inputs = set(scalar_inputs)
+ vector_inputs = set(vector_inputs)
+
+ dim = stencil.dim
+
+ vtype = typegen.vtype(ftype,components)
+
+ if (vector_suffixes is None):
+ vector_suffixes = range(components)
+
+ has_custom_id = (custom_id is not None)
+
+ args = ArgDict()
+ for iname in vector_inputs:
+ if vectorize:
+ name = iname
+ args[name] = CodegenVariable(name, vtype, typegen, const=True,
+ add_impl_const=True, storage=data_storage, ptr=True, ptr_restrict=ptr_restrict)
+ else:
+ for i in xrange(components):
+ name = '{}{}'.format(iname,vector_suffixes[i])
+ args[name] = CodegenVariable(name, ftype, typegen,
+ const=True, add_impl_const=True, storage=data_storage,
+ ptr=True, ptr_restrict=ptr_restrict)
+ for iname in scalar_inputs:
+ name = iname
+ args[name] = CodegenVariable(name, ftype, typegen, const=True,
+ add_impl_const=True, storage=data_storage, ptr=True, ptr_restrict=ptr_restrict)
+ for arg in extra_inputs:
+ args[arg.name] = arg
+
+ if not has_custom_id:
+ args['offset'] = CodegenVariable('offset', itype, typegen, add_impl_const=True)
+ args['stride'] = CodegenVectorClBuiltin('stride', itype, dim, typegen,
+ add_impl_const=True,nl=True)
+ for varname,vartype in multipliers.iteritems():
+ if vartype=='ftype':
+ vartype=ftype
+ elif vartype=='vtype':
+ vartype=vtype
+ args[varname] = CodegenVariable(varname, vartype, typegen, add_impl_const=True)
+
+ _type = '{}{}'.format(ftype[0],components)
+ if vectorize:
+ _type+='v'
+ basename = 'apply_stencil_{}_{}'.format(_type,stencil.hash())
+ super(ApplyStencilFunction,self).__init__(basename=basename,
+ output=vtype,typegen=typegen,inline=True,
+ args=args, known_args=known_args)
+
+ self.dim = dim
+ self.itype = itype
+ self.ftype = ftype
+ self.vtype = vtype
+ self.vectorized = vectorize
+ self.components = components
+ self.data_storage = data_storage
+ self.multipliers = multipliers
+ self.stencil = stencil
+ self.vector_inputs = vector_inputs
+ self.vector_suffixes = vector_suffixes
+ self.scalar_inputs = scalar_inputs
+ self.has_custom_id = has_custom_id
+ self.custom_id = custom_id
+ self.op = op
+ self.symbol2vars = symbol2vars
+
+ self.gencode()
+
+ def is_cached(self):
+ if self.data_storage == '__local':
+ return True
+ elif self.data_storage == '__global':
+ return False
+ else:
+ raise NotImplemented()
+
+ def per_work_statistics(self):
+ tg = self.typegen
+ itype = self.itype
+ ftype = self.ftype
+ components = self.components
+ known_args = self.known_args
+ cached = self.is_cached()
+
+ ncoeffs = self.stencil.non_zero_coefficients()
+ nmul = len(self.multipliers)+int(self.stencil.has_factor())
+
+ stats = WorkStatistics()
+
+ # Reads
+ size = tg.FLT_BYTES[ftype]
+ byte_reads = components*ncoeffs*size
+ if cached:
+ stats.local_mem_byte_reads += byte_reads
+ else:
+ stats.global_mem_byte_reads += byte_reads
+
+ # Ops
+ ops = {}
+ ops[ftype] = (2*ncoeffs + nmul)*components
+ ops[itype] = 2*ncoeffs
+ stats.ops_per_type = ops
+
+ return stats
+
+ def gencode(self):
+ s = self
+ dim = s.dim
+ tg = self.typegen
+
+ components = s.components
+ vectorized = s.vectorized
+
+ has_custom_id = s.has_custom_id
+
+ vector_suffixes = s.vector_suffixes
+
+ ftype = s.ftype
+ vtype = s.vtype
+ stencil = s.stencil
+
+ res = CodegenVectorClBuiltin('res',ftype,components,tg)
+
+ with s._function_():
+ s.append(res.declare(init=0))
+ with s._block_():
+ with s._align_() as al:
+ for i in xrange(components):
+ if i>0:
+ al.jumpline()
+ operands = {}
+ if s.vectorized:
+ vector_varnames = s.vector_inputs
+ _res = res()
+ else:
+ vector_varnames = ['{}{}'.format(varname,vector_suffixes[i])
+ for varname in s.vector_inputs]
+ _res = res[i]
+ for j,vn in enumerate(vector_varnames):
+ operands['vinput{}'.format(j)] = s.vars[vn]()
+ for j,vn in enumerate(s.scalar_inputs):
+ operands['sinput{}'.format(j)] = s.vars[vn]()
+ for (off,coeff) in stencil.iteritems(include_factor=False):
+ if coeff=='0':
+ continue
+ if not has_custom_id:
+ offset = s.vars['offset']
+ stride = s.vars['stride']
+ strided=''
+ for i in xrange(dim):
+ if stride.known() and stride.value[0] == 1:
+ strided+='{}'.format(tg.dump(off[i]))
+ else:
+ strided+='{}*{}'.format(tg.dump(off[i]),stride[i])
+ operands['id'] = '{}+{}'.format(offset(),strided)
+ else:
+ operands['id'] = s.custom_id.format(offset=tg.dump(off[0]))
+ code = '{} += {} $* {};'.format(_res,tg.dump_expr(coeff,symbol2vars=s.symbol2vars),
+ s.op.format(**operands))
+ al.append(code)
+ if vectorized:
+ break
+
+ mul = ''
+ for mult in s.multipliers:
+ mul+='{}*'.format(s.vars[mult]())
+ if stencil.has_factor():
+ mul+='{}*'.format(tg.dump_expr(stencil.factor, symbol2vars=s.symbol2vars))
+
+ ret = 'return {}{};'.format(mul,res())
+ s.append(ret)
+
+
+if __name__ == '__main__':
+
+ from hysop.backend.device.codegen.base.test import _test_typegen
+
+ stencil = Stencil([2.0,1.0,0.0,-1.0,-2.0], origin=2, order=2)
+
+ tg = _test_typegen('double', float_dump_mode='hex')
+ asf = ApplyStencilFunction(tg,stencil,ftype=tg.fbtype,
+ components=3, vectorize=False, data_storage='__local',
+ scalar_inputs = ['S'], vector_inputs=['A','B'], vector_suffixes=['x','y','z'],
+ op='{sinput0}[{id}] * ({vinput0}[{id}] + {vinput1}[{id}])',
+ multipliers={'a':'int','b':'float','c':'ftype','d':'vtype'})
+ print asf.per_work_statistics()
+ asf.edit()
+
diff --git a/hysop/backend/device/codegen/functions/cache_load.py b/hysop/backend/device/codegen/functions/cache_load.py
new file mode 100644
index 0000000000000000000000000000000000000000..852d8eb2847264a3756cc103c8968629e9bfe4c0
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/cache_load.py
@@ -0,0 +1,250 @@
+
+import contextlib
+from contextlib import contextmanager
+
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+from hysop.backend.device.codegen.functions.compute_index import ComputeIndexFunction
+from hysop.constants import BoundaryCondition
+
+class CacheLoadFunction(OpenClFunctionCodeGenerator):
+
+ arguments = {
+ 'src':'source data',
+ 'dst':'destination buffer',
+ 'global_id:':'global thread_id',
+ 'local_id':'local thread_id',
+ 'local_size':'size of a workgroup',
+ 'data_size':'size of source data'
+ }
+
+ def __init__(self, typegen, ftype, work_dim, boundary,
+ components=1, src_vectorize=True, dst_vectorize=True,
+ itype='int',
+ with_gid_ghost_offset=True,
+ with_gid_bound_check=True,
+ known_args=None,force_symbolic=False):
+
+ assert work_dim>0
+
+ check_instance(boundary,BoundaryCondition)
+ if boundary not in [BoundaryCondition.NONE, BoundaryCondition.PERIODIC]:
+ raise NotImplemented('Boundary \'{}\' not implemented yet!'.format(str(boundary).lower()))
+
+ tg = typegen
+ fs = force_symbolic
+ vtype = tg.vtype(ftype,components)
+ name = 'cache_load_{}d'.format(work_dim)
+ if boundary != BoundaryCondition.NONE:
+ name+='_{}'.format(str(boundary).lower())
+ output = 'void'
+
+ args = ArgDict()
+ if src_vectorize:
+ args['src'] = CodegenVariable('src', vtype, typegen=tg, ptr=True, const=True,
+ storage='__global', nl=True, ptr_restrict=True)
+ else:
+ for i in xrange(components):
+ src = 'src{}'.format(i)
+ args[src] = CodegenVariable(src, ftype, typegen=tg, ptr=True, const=True,
+ storage='__global', nl=True, ptr_restrict=True)
+ if dst_vectorize:
+ args['dst'] = CodegenVariable('dst', vtype, typegen=tg, ptr=True, const=False,
+ storage='__local' , nl=True, ptr_restrict=True)
+ else:
+ for i in xrange(components):
+ dst = 'dst{}'.format(i)
+ args[dst] = CodegenVariable(dst, ftype, typegen=tg, ptr=True, const=False,
+ storage='__local' , nl=True, ptr_restrict=True)
+
+ args['global_id'] = CodegenVectorClBuiltin('gid',itype,work_dim,typegen,
+ add_impl_const=False)
+ args['local_id'] = CodegenVectorClBuiltin('lid',itype,work_dim,typegen,
+ add_impl_const=False, nl=True)
+
+ args['local_size'] = CodegenVectorClBuiltin('L',itype,work_dim,tg,
+ add_impl_const=True, symbolic_mode=fs)
+ args['src_size'] = CodegenVectorClBuiltin('N',itype,work_dim,tg,
+ add_impl_const=True, symbolic_mode=fs, nl=True)
+
+ args['multiplier'] = CodegenVectorClBuiltin('multiplier',itype,work_dim,tg,
+ add_impl_const=True, symbolic_mode=fs)
+ args['lghosts'] = CodegenVectorClBuiltin('lghosts',itype,work_dim,tg,
+ add_impl_const=True, symbolic_mode=fs)
+ args['rghosts'] = CodegenVectorClBuiltin('rghosts',itype,work_dim,tg,
+ add_impl_const=True, symbolic_mode=fs)
+
+ super(CacheLoadFunction,self).__init__(basename=name, output=output,
+ args=args,known_args=known_args,
+ typegen=tg,inline=True)
+
+ self.itype = itype
+ self.ftype = ftype
+ self.vtype = vtype
+ self.work_dim = work_dim
+ self.components = components
+ self.src_vectorize = src_vectorize
+ self.dst_vectorize = dst_vectorize
+
+ self.with_gid_ghost_offset = with_gid_ghost_offset
+ self.with_gid_bound_check = with_gid_bound_check
+
+ self.boundary = boundary
+ self.declare_code()
+
+ def declare_code(self):
+ s = self
+ tg = s.typegen
+ work_dim = s.work_dim
+ itype = s.itype
+ ftype = s.ftype
+ vtype = s.vtype
+ components = s.components
+ src_vectorize = s.src_vectorize
+ dst_vectorize = s.dst_vectorize
+ boundary=s.boundary
+
+ with_gid_ghost_offset = self.with_gid_ghost_offset
+ with_gid_bound_check = self.with_gid_bound_check
+
+ global_id = s.args['global_id'];
+ local_id = s.args['local_id'];
+
+ local_size = s.args['local_size'];
+ src_size = s.args['src_size'];
+
+ lghosts = s.args['lghosts'];
+ rghosts = s.args['rghosts'];
+ multiplier = s.args['multiplier'];
+
+ cache_size = CodegenVectorClBuiltin('S' ,itype,work_dim,tg,const=True)
+ local_pos = CodegenVectorClBuiltin('lidx',itype,work_dim,tg)
+ global_pos = CodegenVectorClBuiltin('gidx',itype,work_dim,tg)
+
+ LID = CodegenVariable('LID',itype, tg)
+ GID = CodegenVariable('GID',itype, tg)
+
+ tmp = CodegenVectorClBuiltin('tmp', ftype, components, tg)
+
+ compute_index = ComputeIndexFunction(tg,work_dim,wrap=False)
+ s.require('compute_index',compute_index)
+
+ with s._function_():
+ s.jumpline()
+ s.append(cache_size.declare(init='{}+{}*{}+{}'.format(lghosts(),multiplier(),
+ local_size(),rghosts())))
+ s.jumpline()
+ s.append(global_pos.declare())
+ s.append(local_pos.declare())
+ s.jumpline()
+
+ if boundary == BoundaryCondition.PERIODIC:
+ if with_gid_ghost_offset:
+ s.append('{} += {}-{};'.format(global_id(),src_size(),lghosts()))
+ else:
+ s.append('{} += {};'.format(global_id(),src_size()))
+ s.append('{} %= {};'.format(global_id(), src_size()))
+
+ @contextmanager
+ def _cache_iterate_(i):
+ try:
+ if (local_size.known() and lghosts.known() and rghosts.known()):
+ s.pragma('unroll')
+ else:
+ s.pragma('unroll 8')
+ with s._for_('{} k{i}=0; k{i}<({}+{L}-1)/{L}; k{i}++'.format(
+ itype,cache_size[i],i=i,L=local_size[i])) as ctx:
+ s.append('{} = {}+k{i}*{};'.format(local_pos[i],local_id[i],
+ local_size[i],i=i));
+ s.append('{} = {}+k{i}*{};'.format(global_pos[i],global_id[i],
+ local_size[i],i=i));
+ cond = '({}>={})'.format(local_pos[i],cache_size[i])
+ if with_gid_bound_check:
+ if boundary != BoundaryCondition.PERIODIC:
+ cond += ' || ({}>={}+{})'.format(global_pos[i],src_size[i],rghosts[i])
+ s.append('if ({}) continue;'.format(cond))
+
+ if boundary==BoundaryCondition.PERIODIC:
+ s.append('{} %= {};'.format(global_pos[i],src_size[i]));
+ yield ctx
+ except:
+ pass
+
+ s.barrier(_local=True)
+ with s._block_():
+ nested_loops = [_cache_iterate_(i) for i in xrange(work_dim-1,-1,-1)]
+ with contextlib.nested(*nested_loops):
+ with s._block_():
+ s.append(LID.declare(const=True,init=compute_index(idx=local_pos,
+ size=cache_size[:work_dim])))
+ s.append(GID.declare(const=True,init=compute_index(idx=global_pos,
+ size=src_size[:work_dim])))
+
+ if src_vectorize:
+ load=s.vars['src'][GID()]
+ else:
+ load = ','.join([s.vars['src{}'.format(i)][GID()] \
+ for i in xrange(components)])
+ load = '({})({})'.format(vtype,load)
+ tmp.declare(s,init=load,const=True)
+ if dst_vectorize:
+ store='{} = {};'.format(s.vars['dst'][LID()], tmp())
+ s.append(store)
+ else:
+ for i in xrange(components):
+ store='{} = {};'.format(s.vars['dst{}'.format(i)][LID()], tmp[i])
+ s.append(store)
+
+
+ s.barrier(_local=True)
+
+
+ def per_work_statistics(self):
+ typegen = self.typegen
+ itype = self.itype
+ ftype = self.ftype
+ work_dim = self.work_dim
+ components = self.components
+
+ size = typegen.FLT_BYTES[ftype]
+ reads = components*size
+ writes = reads
+
+ ops = {}
+ ops[itype] = 2*work_dim
+ ops[itype] += 10*work_dim
+
+ stats = WorkStatistics()
+ stats.ops_per_type = ops
+ stats.global_mem_byte_reads += reads
+ stats.local_mem_byte_writes += writes
+
+ stats += 2*self.reqs['compute_index'].per_work_statistics()
+
+ return stats
+
+
+
+
+if __name__ == '__main__':
+ from hysop.backend.device.codegen.base.test import _test_typegen
+
+ tg = _test_typegen('float')
+ cg = OpenClCodeGenerator(name='base', typegen=tg)
+
+ cache_load0 = CacheLoadFunction(typegen=tg,ftype=tg.fbtype,work_dim=3,
+ components=4, src_vectorize=False, dst_vectorize=True)
+ print cache_load0.per_work_statistics()
+
+ cg.require('cl0',cache_load0)
+
+ cg.edit()
+ cg.test_compile()
+
+
diff --git a/hysop/codegen/functions/compute_index.py b/hysop/backend/device/codegen/functions/compute_index.py
similarity index 54%
rename from hysop/codegen/functions/compute_index.py
rename to hysop/backend/device/codegen/functions/compute_index.py
index 3047d60646ecc765252b527f5655aaf14b1adf6e..2208ac3219d8126f4cb8f5fcbfa14e20165ce5c7 100644
--- a/hysop/codegen/functions/compute_index.py
+++ b/hysop/backend/device/codegen/functions/compute_index.py
@@ -1,17 +1,18 @@
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.function_codegen import OpenClFunctionCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
class ComputeIndexFunction(OpenClFunctionCodeGenerator):
def __init__(self,typegen,dim,wrap=None,itype='int'):
assert dim>0
args = ArgDict()
- args['idx'] = CodegenVectorClBuiltin('idx', 'int', dim, typegen, add_impl_const=(wrap==False))
+ args['idx'] = CodegenVectorClBuiltin('idx', 'int', dim, typegen, add_impl_const=bool(wrap==False))
args['size'] = CodegenVectorClBuiltin('size', itype, dim, typegen, add_impl_const=True)
args['wrap'] = CodegenVariable('wrap', 'bool',typegen, add_impl_const=True, value=wrap)
@@ -20,6 +21,8 @@ class ComputeIndexFunction(OpenClFunctionCodeGenerator):
basename += '_' + ('' if wrap else 'no') + 'wrap'
super(ComputeIndexFunction,self).__init__(basename=basename,ext='.c', output=itype,args=args,typegen=typegen,inline=True)
self.dim = dim
+ self.wrap = wrap
+ self.itype = itype
self.gencode()
@@ -31,30 +34,39 @@ class ComputeIndexFunction(OpenClFunctionCodeGenerator):
wrap = s.args['wrap']
with s._function_():
with s._if_(wrap()):
- self.append('{idx} = ({idx}+{size}) % {size};'.format(idx=idx(),size=size()))
+ self.append('{idx} = ({idx}+{size}) % {size};'.format(idx=idx(),size=size))
ss = '{}'.format(idx[dim-1])
for i in xrange(dim-2,-1,-1):
ss = '({}*{}+{})'.format(ss,size[i],idx[i])
ret = 'return {};'.format(ss)
self.append(ret)
+ def per_work_statistics(self):
+ dim = self.dim
+ wrap = self.wrap
+ itype = self.itype
+
+ ops = {}
+ ops[itype] = int(wrap)*2*dim + 2*(dim-1)*dim
+
+ stats = WorkStatistics()
+ stats.ops_per_type = ops
+
+ return stats
+
if __name__ == '__main__':
- cg = OpenClCodeGenerator('main',OpenClTypeGen('float'))
+ from hysop.backend.device.codegen.base.test import test_typegen
+ tg = test_typegen('float')
+ cg = OpenClCodeGenerator('main',tg)
+
+ ci0 = ComputeIndexFunction(tg,3,wrap=None)
+ ci1 = ComputeIndexFunction(tg,3,wrap=True)
+ ci2 = ComputeIndexFunction(tg,3,wrap=False)
- ci0 = ComputeIndexFunction(cg.typegen,3,wrap=None)
- ci1 = ComputeIndexFunction(cg.typegen,3,wrap=True)
- ci2 = ComputeIndexFunction(cg.typegen,3,wrap=False)
cg.require(ci0.name, ci0)
cg.require(ci1.name, ci1)
cg.require(ci2.name, ci2)
-
- #ciu0 = ComputeIndexFunction(cg.typegen,wrap=None, itype='uint')
- #ciu1 = ComputeIndexFunction(cg.typegen,wrap=True, itype='uint')
- #ciu2 = ComputeIndexFunction(cg.typegen,wrap=False, itype='uint')
- #cg.require(ciu0.name, ciu0)
- #cg.require(ciu1.name, ciu1)
- #cg.require(ciu2.name, ciu2)
cg.edit()
diff --git a/hysop/backend/device/codegen/functions/custom_atomics.py b/hysop/backend/device/codegen/functions/custom_atomics.py
new file mode 100644
index 0000000000000000000000000000000000000000..7f09b26b102061c94a73ede81ba17644252fdf73
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/custom_atomics.py
@@ -0,0 +1,111 @@
+
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+
+class CustomAtomicFunction(OpenClFunctionCodeGenerator):
+
+ def __init__(self,typegen,ftype,op,
+ storage='__global',
+ opname=None):
+
+ reqs,union = self.build_union(ftype,typegen)
+
+ args = ArgDict()
+ args['p'] = CodegenVariable('p',ftype,add_impl_const=False,typegen=typegen,
+ ptr=True, volatile=True, storage=storage)
+ args['val'] = CodegenVariable('val',ftype,add_impl_const=True,typegen=typegen)
+
+ fname = 'custom_atomic_{}'.format(
+ 'op{}'.format(hex(hash(op))[2:6]) if (opname is None)
+ else opname)
+ super(CustomAtomicFunction,self).__init__(basename=fname,
+ output=ftype,args=args,typegen=typegen)
+
+ self.op = op
+ self.ftype=ftype
+ self.storage=storage
+
+ if typegen.opencl_version_greater(1,0):
+ if ftype=='float':
+ atomic_cmpxchg='atomic_cmpxchg({ptr},{intcmp},{val});'
+ elif ftype=='double':
+ self.declare_cl_extension('cl_khr_int64_base_atomics')
+ atomic_cmpxchg='atom_cmpxchg({ptr},{intcmp},{val});'
+ else:
+ raise NotImplementedError('Unknown ftype {}.'.format(ftype))
+ else:
+ if ftype=='float':
+ if storage=='__global':
+ self.declare_cl_extension('cl_khr_global_int32_base_atomics')
+ elif storage=='__local':
+ self.declare_cl_extension('cl_khr_local_int32_base_atomics')
+ else:
+ raise NotImplementedError('Unknown storage {}.'.format(storage))
+ elif ftype=='double':
+ self.declare_cl_extension('cl_khr_int64_base_atomics')
+ else:
+ raise NotImplementedError('Unknown ftype {}.'.format(ftype))
+ atomic_cmpxchg='atom_cmpxchg({ptr},{intcmp},{val});'
+
+ self.update_requirements(reqs)
+ self.gencode(atomic_cmpxchg)
+
+ def build_union(self, ftype, tg):
+ from hysop.backend.device.codegen.unions.float_int import FloatIntegerUnion
+ reqs = WriteOnceDict()
+ union = FloatIntegerUnion(ftype, tg)
+ reqs['union'] = union
+ return reqs, union
+
+ def gencode(self, atomic_cmpxchg):
+ s = self
+ tg = s.typegen
+ op = s.op
+
+ p = s.args['p']
+ val = s.args['val']
+
+ union = self.reqs['union']
+ old_val = union.build_codegen_variable('old_val')
+ new_val = union.build_codegen_variable('new_val')
+ ret_val = union.build_codegen_variable('ret_val')
+ alias = p.pointer_alias(name='ip', ctype=old_val.intval.ctype)
+ with s._function_():
+ old_val.declare(s)
+ new_val.declare(s)
+ ret_val.declare(s)
+ s.jumpline()
+ alias.declare(s)
+ with s._do_while_('{} != {}'.format(ret_val.intval, old_val.intval)):
+ load='{} = *{};'.format(old_val.floatval, p)
+ op='{} = {};'.format(new_val.floatval, op.format(old_val.floatval, val))
+ cmpxchg = '{} = {}'.format(ret_val.intval,
+ atomic_cmpxchg.format(ptr=alias, intcmp=old_val.intval,
+ val=new_val.intval))
+ s.append(load)
+ s.append(op)
+ s.append(cmpxchg)
+ s.jumpline()
+ s.append('return {};'.format(ret_val.floatval))
+
+
+
+
+if __name__ == '__main__':
+ from hysop.backend.device.codegen.base.test import _test_typegen
+ tg = _test_typegen('double')
+ cg = OpenClCodeGenerator('main',tg)
+
+ h = CustomAtomicFunction(tg, 'float', '{} + {}', '__global' )
+ f = CustomAtomicFunction(tg, 'double', '{} + {}', '__local' )
+ cg.require(h.name,f)
+ cg.require(f.name,f)
+
+ cg.edit()
+
+ cg.test_compile()
+
diff --git a/hysop/backend/device/codegen/functions/directional_remesh.py b/hysop/backend/device/codegen/functions/directional_remesh.py
new file mode 100644
index 0000000000000000000000000000000000000000..051fdd6207050abd4720128dcbdb0ebbd41b291d
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/directional_remesh.py
@@ -0,0 +1,366 @@
+
+from hysop.deps import sm, np, contextlib
+from hysop.tools.types import check_instance
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+from hysop.backend.device.codegen.functions.polynomial import PolynomialFunction
+from hysop.backend.device.codegen.functions.custom_atomics import CustomAtomicFunction
+
+from hysop.constants import BoundaryCondition
+from hysop.numerics.remesh.remesh import RemeshKernel
+
+from hysop.numerics.stencil.stencil_generator import StencilGenerator
+
+class DirectionalRemeshFunction(OpenClFunctionCodeGenerator):
+
+ def __init__(self, typegen, work_dim, itype, ftype,
+ nparticles, nscalars,
+ sboundary, remesh_kernel,
+ use_atomics, remesh_criteria_eps,
+ known_args=None,
+ debug_mode=False):
+
+ check_instance(sboundary,tuple,values=BoundaryCondition)
+ check_instance(remesh_kernel, RemeshKernel)
+ assert remesh_kernel.n % 2 == 0
+ assert remesh_kernel.n > 0
+
+ is_periodic = (sboundary[0]==BoundaryCondition.PERIODIC) and \
+ (sboundary[1]==BoundaryCondition.PERIODIC)
+
+ ivtype = typegen.vtype(itype, nparticles)
+ fvtype = typegen.vtype(ftype, nparticles)
+
+ reqs = self.build_requirements(typegen, work_dim, itype, ftype,
+ ivtype, fvtype, nparticles, nscalars, sboundary, remesh_kernel,
+ use_atomics, remesh_criteria_eps)
+
+ (args,basename) = self.build_prototype(reqs, typegen, work_dim, itype, ftype,
+ ivtype, fvtype, nparticles, nscalars, sboundary, remesh_kernel,
+ use_atomics, remesh_criteria_eps, is_periodic)
+
+ super(DirectionalRemeshFunction,self).__init__(basename=basename,
+ output=None, typegen=typegen, inline=True,
+ args=args, known_args=known_args)
+
+ self.update_requirements(reqs)
+
+ self.work_dim = work_dim
+ self.itype = itype
+ self.ftype = ftype
+ self.ivtype = ivtype
+ self.fvtype = fvtype
+
+ self.nparticles = nparticles
+ self.nscalars = nscalars
+ self.sboundary = sboundary
+ self.kernel = remesh_kernel
+ self.use_atomics = use_atomics
+ self.remesh_criteria_eps = remesh_criteria_eps
+ self.is_periodic = is_periodic
+ self.debug_mode = debug_mode
+
+ self.gencode()
+
+ @staticmethod
+ def _printv(ncomponents):
+ assert ncomponents in [1,2,4,8,16]
+ if ncomponents==1:
+ return ''
+ else:
+ return 'v{}'.format(ncomponents)
+
+
+ def build_prototype(self, reqs, typegen, work_dim, itype, ftype,
+ ivtype, fvtype, nparticles, nscalars, sboundary, remesh_kernel,
+ use_atomics, remesh_criteria_eps, is_periodic):
+
+ args = ArgDict()
+
+ atomic = 'atomic_' if use_atomics else ''
+ criteria = '{}eps__'.format(remesh_criteria_eps) if (remesh_criteria_eps is not None) else 'full'
+
+ basename = '__{}remesh_{}d__lambda_{}_{}__{}__{}p__{}s__{}'.format(
+ atomic, work_dim,
+ remesh_kernel.n, remesh_kernel.r, ftype,
+ nparticles, nscalars,
+ criteria)
+
+ args['p'] = CodegenVectorClBuiltin(name='p', btype=ftype, dim=nparticles, typegen=typegen,
+ add_impl_const=True, nl=True)
+
+ scalars = []
+ for i in xrange(nscalars):
+ Si = CodegenVectorClBuiltin(name='s{}'.format(i), btype=ftype, dim=nparticles, typegen=typegen,
+ add_impl_const=True, nl=(i==nscalars-1))
+ scalars.append(Si)
+ args[Si.name] = Si
+
+ args['dx'] = CodegenVariable(name='dx', ctype=ftype, typegen=typegen,
+ add_impl_const=True)
+ args['inv_dx'] = CodegenVariable(name='inv_dx', ctype=ftype, typegen=typegen,
+ add_impl_const=True, nl=True)
+
+ if is_periodic:
+ args['grid_size'] = CodegenVariable(name='grid_size', ctype=itype, typegen=typegen,
+ add_impl_const=True)
+ args['line_offset'] = CodegenVariable(name='line_offset', ctype=itype, typegen=typegen,
+ add_impl_const=True)
+ args['cache_ghosts'] = CodegenVariable(name='cache_ghosts', ctype=itype, typegen=typegen,
+ add_impl_const=True)
+ args['active'] = CodegenVariable(name='active', ctype='bool', typegen=typegen,
+ add_impl_const=True, nl=True)
+
+
+ cached_scalars = []
+ for i in xrange(nscalars):
+ Si = CodegenVariable(name='S{}'.format(i), ctype=ftype, typegen=typegen,
+ ptr_restrict=True, ptr=True, storage=self._local,
+ ptr_const=False, add_impl_const=True, nl=True)
+ cached_scalars.append(Si)
+ args[Si.name] = Si
+
+ self.scalars = scalars
+ self.cached_scalars = cached_scalars
+
+ return (args,basename)
+
+
+ def build_requirements(self, typegen, work_dim, itype, ftype,
+ ivtype, fvtype, nparticles, nscalars, sboundary, remesh_kernel,
+ use_atomics, remesh_criteria_eps):
+
+ reqs = WriteOnceDict()
+
+ P = []
+ kernel = remesh_kernel
+ if kernel.poly_splitted:
+ self.poly_splitted = True
+ name='lambda_{}_{}__{}'.format(kernel.n, kernel.r, '{}_{}')
+ for i, _ in enumerate(kernel.Pt_l):
+ ilname = name.format(i,'left')
+ irname = name.format(i,'right')
+ Pil = PolynomialFunction(typegen, ftype, nparticles,
+ kernel.Cl[:,i], ilname, use_fma=True, var='y')
+ Pir = PolynomialFunction(typegen, ftype, nparticles,
+ kernel.Cr[:,i], irname, use_fma=True, var='y')
+ P.append((Pil,Pir))
+ reqs[ilname] = Pil
+ reqs[irname] = Pir
+ else:
+ self.poly_splitted = False
+ name='lambda_{}_{}__{}'.format(kernel.n, kernel.r, '{}')
+ for i, _ in enumerate(kernel.Pt):
+ iname = name.format(i)
+ Pi = PolynomialFunction(typegen, ftype, nparticles,
+ kernel.C[:,i], iname, use_fma=True, var='y')
+ P.append((Pi,))
+ reqs[iname] = Pi
+ self.polynomials = P
+
+ if use_atomics:
+ reqs['atomic_add'] = CustomAtomicFunction(typegen, ftype, '{} + {}', self._local, 'add')
+
+ return reqs
+
+ def gencode(self):
+ s = self
+ dim = s.work_dim
+ tg = self.typegen
+
+ itype = s.itype
+ ftype = s.ftype
+ ivtype = s.ivtype
+ fvtype = s.fvtype
+
+ work_dim = s.work_dim
+ itype = s.itype
+ ftype = s.ftype
+ ivtype = s.ivtype
+ fvtype = s.fvtype
+
+ nparticles = s.nparticles
+ nscalars = s.nscalars
+ sboundary = s.sboundary
+ use_atomics = s.use_atomics
+ remesh_criteria_eps = s.remesh_criteria_eps
+ debug_mode = s.debug_mode
+
+ is_periodic = s.is_periodic
+
+ scalars = s.scalars
+ cached_scalars = s.cached_scalars
+
+ pos = s.vars['p']
+
+ dx = s.vars['dx']
+ inv_dx = s.vars['inv_dx']
+
+ active = s.vars['active']
+ line_offset = s.vars['line_offset']
+ cache_ghosts = s.vars['cache_ghosts']
+
+ poly_splitted = s.poly_splitted
+
+ vnf = '[%2.2{}f]'.format(self._printv(nparticles))
+ vni = '[%{}i]'.format(self._printv(nparticles))
+
+ @contextlib.contextmanager
+ def if_thread_active():
+ with s._if_('{}'.format(active)):
+ yield
+
+ if is_periodic:
+ grid_size = s.vars['grid_size']
+
+ dtype = tg.np_dtype(ftype)
+
+ P = CodegenVariable(name='P', ctype=itype, typegen=tg,
+ const=True, value=1+(self.kernel.n/2))
+ eps = CodegenVariable(name='eps', ctype=ftype, typegen=tg,
+ const=True, value=np.finfo(dtype).eps)
+
+ y = CodegenVectorClBuiltin(name='y', btype=ftype, dim=nparticles, typegen=tg)
+ ind = CodegenVectorClBuiltin(name='ind', btype=itype, dim=nparticles, typegen=tg)
+ find = CodegenVectorClBuiltin(name='find', btype=ftype, dim=nparticles, typegen=tg)
+
+ if poly_splitted:
+ wl = CodegenVectorClBuiltin(name='Wl', btype=ftype, dim=nparticles, typegen=tg)
+ wr = CodegenVectorClBuiltin(name='Wr', btype=ftype, dim=nparticles, typegen=tg)
+ w = CodegenVectorClBuiltin(name='W', btype=ftype, dim=nparticles, typegen=tg)
+ weights = (wl,wr,w)
+ else:
+ w = CodegenVectorClBuiltin(name='W', btype=ftype, dim=nparticles, typegen=tg)
+ weights = (w,)
+
+ with s._function_():
+ P.declare(s)
+ if (remesh_criteria_eps is not None):
+ eps.declare(s)
+ s.jumpline()
+
+ s.decl_aligned_vars(find, ind, y)
+ s.decl_vars(*weights)
+ s.jumpline()
+
+ with if_thread_active():
+ code='{} = fract({}*{}, &{});'.format(y, pos, inv_dx, find)
+ s.append(code)
+
+ code = '{} = convert_{}_rtn({});'.format(ind, ivtype, find)
+ s.append(code)
+
+ #ind.affect(s, init='convert_{}_rtn({}*{})'.format(ivtype, pos, inv_dx))
+ #y.affect(s, init='({} - convert_{}({})*{})*{}'.format(pos, fvtype, ind, dx, inv_dx))
+ s.jumpline()
+
+ if debug_mode:
+ code = 'printf("%lu computed ind={vni}, y={vnf}, s0={vnf}.\\n", {}, {}, {}, s0);'.format(
+ 'get_local_id(0)', ind, y,
+ vnf=vnf, vni=vni)
+ s.append(code)
+
+ # periodicity is handled via scalar cache ghosts
+ #if is_periodic:
+ #ind.affect(s, init='{} - {} + {}'.format(ind, P, grid_size))
+ #else:
+ ind.affect(s, init='{} - {} - {}'.format(ind, P, line_offset))
+
+ for i, Pi in enumerate(self.polynomials):
+ s.jumpline()
+ with if_thread_active():
+ #if is_periodic:
+ #ind.affect(s, init='({}+1) % {}'.format(ind, grid_size))
+ #else:
+ s.append('{} += 1;'.format(ind))
+ with s._align_() as al:
+ for wj,Pij,yj in zip(weights, Pi, (y,'1-{}'.format(y))):
+ wj.affect(al, align=True, init=Pij(y=yj))
+ if poly_splitted:
+ if nparticles>1:
+ w.affect(al, align=True, init='select({}, {}, ({}<{}))'.format(
+ wl, wr, y, tg.dump(0.5)))
+ else:
+ w.affect(al, align=True, init='convert_{fvtype}({}<{})*{} + convert_{fvtype}({}>={})*{}'.format(
+ y,tg.dump(0.5), wl, y, tg.dump(0.5), wr, fvtype=fvtype))
+
+ for iscal, (cached_scalar, scalar) in enumerate(zip(cached_scalars, scalars)):
+ if nparticles>1:
+ comment='Remeshing scalar {}, {} particles at a time.'.format(iscal, nparticles)
+ s.jumpline()
+ s.comment(comment)
+ with s._block_():
+ for ipart in xrange(nparticles):
+ cache_idx='{}+{}'.format(cache_ghosts, ind[ipart])
+ if use_atomics:
+ atomic_add = s.reqs['atomic_add']
+ base = '({}) && {};'.format(
+ '{criteria}',
+ atomic_add(p='{}+{}'.format(cached_scalar,cache_idx), val='{val}'))
+ else:
+ base = '({}) && ({} += {});'.format('{criteria}', cached_scalar[cache_idx],
+ '{val}')
+ val = '{}*{}'.format(w[ipart],scalar[ipart])
+ if (remesh_criteria_eps is None):
+ criteria = '{}!={}'.format(scalar[ipart], tg.dump(0.0))
+ else:
+ criteria = 'fabs({}) > {}*eps'.format(scalar[ipart], remesh_criteria_eps)
+ code = base.format(val=val, criteria=criteria)
+ s.append(code)
+ if debug_mode:
+ val='{}*{}'.format(w,scalars[0])
+ cache_idx='{}+{}'.format(cache_ghosts, ind[0])
+
+ if poly_splitted:
+ printf = 'printf("BATCH {}: %lu wrote {vnf} at idx={vni} with Wl={vnf}, Wr={vnf}, W={vnf}, cond={vni}.\\n",{},{},{},{},{},{},{});'.format(
+ i, 'get_local_id(0)', val, ind, wl, wr, w, 'y<0.5f', vnf=vnf, vni=vni)
+ else:
+ printf = 'printf("BATCH {}: %lu wrote {vnf} at idx {vni} with W={vnf}.\\n",{},{},{},{});'.format(
+ i, 'get_local_id(0)', val, ind, w, vni=vni, vnf=vnf)
+ s.append(printf)
+ if not use_atomics:
+ s.barrier(_local=True)
+ if use_atomics:
+ s.barrier(_local=True)
+
+ # def per_work_statistics(self):
+ # dim = self.dim
+ # ftype = self.ftype
+ # storage = self.storage
+
+ # stats = self.reqs['apply_stencil'].per_work_statistics()
+
+ # if 'alpha' in self.known_args:
+ # alpha = self.known_args['alpha']
+ # else:
+ # alpha = 0.5
+ # stats.ops_per_type[ftype] += int(alpha!=0)*dim*3
+ # stats.ops_per_type[ftype] += int(alpha!=1)*dim*2 + 2
+
+ # retur
+if __name__ == '__main__':
+ from hysop.backend.device.codegen.base.test import _test_typegen
+ from hysop.numerics.remesh.remesh import RemeshKernel
+
+ tg = _test_typegen('float')
+
+ kernel = RemeshKernel(2, 2, split_polys=True)
+
+ work_dim = 3
+ nparticles = 2
+ nscalars = 2
+
+ use_atomics = True
+ remesh_criteria_eps = None
+
+ drf = DirectionalRemeshFunction(tg, work_dim, 'int', tg.fbtype,
+ nparticles, nscalars,
+ (BoundaryCondition.PERIODIC,BoundaryCondition.PERIODIC),
+ kernel, use_atomics, remesh_criteria_eps)
+ drf.edit()
diff --git a/hysop/codegen/functions/empty.py b/hysop/backend/device/codegen/functions/empty.py
similarity index 63%
rename from hysop/codegen/functions/empty.py
rename to hysop/backend/device/codegen/functions/empty.py
index 7b55956928d319353be881a05c9fa9f0654778a1..ba21818bcd562b35b3dec1796b7dfb219d9ad541 100644
--- a/hysop/codegen/functions/empty.py
+++ b/hysop/backend/device/codegen/functions/empty.py
@@ -1,9 +1,9 @@
-from hysop.codegen.base.codegen import CodeGenerator
-from hysop.codegen.base.function_codegen import FunctionCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable
-from hysop.codegen.base.types import TypeGen
-from hysop.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.codegen import CodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import FunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable
+from hysop.backend.device.opencl.opencl_types import TypeGen
+from hysop.backend.device.codegen.base.utils import ArgDict
class EmptyFunction(FunctionCodeGenerator):
@@ -13,7 +13,7 @@ class EmptyFunction(FunctionCodeGenerator):
args['data'] = CodegenVariable(typegen.fbtype,'data',ptr=True,const=True,typegen=typegen)
fname = 'empty_function'
name = '{}_{}'.format(fname,typegen.fbtype[0])
- super(EmptyFunction,self).__init__(name=name,fname=fname,ext='.c', output='void',args=args,typegen=typegen)
+ super(EmptyFunction,self).__init__(basename=fname,ext='.c', output='void',args=args,typegen=typegen)
self.gencode()
def gencode(self):
diff --git a/hysop/codegen/functions/gradient.py b/hysop/backend/device/codegen/functions/gradient.py
similarity index 87%
rename from hysop/codegen/functions/gradient.py
rename to hysop/backend/device/codegen/functions/gradient.py
index bd7d3b073ea210cf0f63da83a7453c851e7211fe..876e5814de01ba90868faad128bb47bab14f6357 100644
--- a/hysop/codegen/functions/gradient.py
+++ b/hysop/backend/device/codegen/functions/gradient.py
@@ -1,17 +1,17 @@
import numpy as np
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.function_codegen import OpenClFunctionCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import ArgDict
-from hysop.codegen.maths.stencil.stencil import Stencil1D, Stencil
+from hysop.numerics.stencil.stencil import Stencil
-from hysop.codegen.functions.compute_index import ComputeIndexFunction
-from hysop.codegen.functions.cache_load import CacheLoadFunction
-from hysop.codegen.functions.apply_stencil import ApplyStencilFunction
+from hysop.backend.device.codegen.functions.compute_index import ComputeIndexFunction
+from hysop.backend.device.codegen.functions.cache_load import CacheLoadFunction
+from hysop.backend.device.codegen.functions.apply_stencil import ApplyStencilFunction
class GradientFunction(OpenClFunctionCodeGenerator):
@@ -156,7 +156,8 @@ class GradientFunction(OpenClFunctionCodeGenerator):
if __name__ == '__main__':
- tg = OpenClTypeGen('float', float_dump_mode='dec')
+ from hysop.backend.device.codegen.base.test import test_typegen
+ tg = test_typegen('float', float_dump_mode='dec')
gf = GradientFunction(tg,dim=3,order=6, known_args=dict(local_size=(8,8,8)))
gf.edit()
diff --git a/hysop/backend/device/codegen/functions/polynomial.py b/hysop/backend/device/codegen/functions/polynomial.py
new file mode 100644
index 0000000000000000000000000000000000000000..1cb592148fae61c55e39231cf09c09c0d7f020c8
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/polynomial.py
@@ -0,0 +1,103 @@
+
+from hysop.deps import sm, np
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+class PolynomialFunction(OpenClFunctionCodeGenerator):
+
+ def __init__(self, typegen, ftype, dim, coeffs, name, var='x',
+ use_fma=True, known_args=None):
+
+ vtype = typegen.vtype(ftype,dim)
+
+ args = self.build_prototype(typegen, ftype, dim, var)
+
+ reqs = self.build_requirements(typegen, ftype, dim)
+
+ super(PolynomialFunction,self).__init__(basename=name,
+ output=vtype, typegen=typegen, inline=True,
+ args=args, known_args=known_args)
+
+ self.update_requirements(reqs)
+
+ self.dim = dim
+ self.ftype = ftype
+ self.vtype = vtype
+ self.coeffs = np.asarray(coeffs)
+ self.use_fma = use_fma
+ self.var = var
+
+ self.gencode()
+
+ def build_prototype(self, typegen, ftype, dim, var):
+ args = ArgDict()
+ args[var] = CodegenVectorClBuiltin(var, ftype, dim, typegen, add_impl_const=True)
+ return args
+
+ def build_requirements(self, typegen, ftype, dim):
+ reqs = WriteOnceDict()
+ return reqs
+
+ def gencode(self):
+ s = self
+ dim = s.dim
+ tg = self.typegen
+
+ ftype = s.ftype
+ vtype = s.vtype
+
+ coeffs = s.coeffs
+ use_fma = s.use_fma
+
+ assert coeffs.size >= 1
+
+ x = s.args[s.var]
+
+ C = [ tg.dump(float(Ci)) if Ci != 0 else None
+ for Ci in coeffs ]
+
+ with s._function_():
+ mul = '{}*{}'
+ fma = 'fma({},{},{})' if use_fma else '({}*{}+{})'
+
+ i=0
+ while (C[i] is None):
+ i+=1
+ P = C[i]
+ for Ci in C[i+1:]:
+ if Ci is None:
+ P = mul.format(x,P)
+ else:
+ P = fma.format(x,P,Ci)
+ P = 'return {};'.format(P)
+ s.append(P)
+
+ def per_work_statistics(self):
+ from hysop.backend.device.codegen.base.statistics import WorkStatistics
+ dim = self.dim
+ ftype = self.ftype
+ ncoeffs = np.sum(self.coeffs!=0)
+ print self.coeffs
+
+ stats = WorkStatistics()
+ stats.ops_per_type[ftype] = 2*(ncoeffs-1)*dim
+
+ return stats
+
+if __name__ == '__main__':
+
+ from hysop.backend.device.codegen.base.test import _test_typegen
+
+ tg = _test_typegen('float')
+ pf = PolynomialFunction(tg,'float',4,
+ [0,1,2,3,4,0,0,0,5,6,7,8,9,0], 'test_poly', True)
+ pf.edit()
+
+ print pf.per_work_statistics()
+
+ pf.test_compile()
diff --git a/hysop/backend/device/codegen/functions/runge_kutta.py b/hysop/backend/device/codegen/functions/runge_kutta.py
new file mode 100644
index 0000000000000000000000000000000000000000..7e237dda31342a1cc6200788052dcb25ffd4d376
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/runge_kutta.py
@@ -0,0 +1,202 @@
+import hashlib, copy
+import numpy as np
+
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenArray
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta
+
+class RungeKuttaFunction(OpenClFunctionCodeGenerator):
+
+ _default_used_vars = {
+ 't':'t',
+ 'dt':'dt',
+ 'y':'y',
+ 'step': 'step'
+ }
+
+ def __init__(self,typegen,ftype,method,rhs,
+ used_vars=_default_used_vars,
+ known_args=None):
+
+ check_instance(method,ExplicitRungeKutta)
+ check_instance(rhs,OpenClFunctionCodeGenerator)
+ method.dump = typegen.dump
+
+ #find out rhs function arguments
+ rhs_args_name = set(rhs.args.keys())
+ rhs_args_name = rhs_args_name.difference(rhs.known_args.keys())
+
+ t = used_vars['t']
+ dt = used_vars['dt']
+ y = used_vars['y']
+ step = used_vars['step']
+
+ has_time = (t in rhs_args_name)
+ has_step = (step in rhs_args_name)
+ has_dt = (dt in rhs_args_name)
+ has_var = (y in rhs_args_name)
+
+ # runge kutta function args
+ # it is ok for the rhs not to depend on 't' or 'dt' but not on the scheme variable 'y'
+ args = ArgDict()
+ rhs_args = {}
+ if has_time:
+ args[t] = rhs.args[t]
+ rhs_args[t] = args[t]
+ if has_dt:
+ args[dt] = rhs.args[dt]
+ rhs_args[dt] = args[dt]
+ else:
+ args[dt] = CodegenVariable(dt, ftype, typegen, add_impl_const=True)
+ if has_var:
+ args[y] = rhs.args[y]
+ rhs_args[y] = args[y]
+ else:
+ msg = '{} function does not depend on variable {}.'.format(rhs.fname, y)
+ raise RuntimeError(msg)
+ for arg in sorted(rhs_args_name):
+ if (arg not in args) and (arg not in [t,dt,y,step]):
+ args[arg] = rhs.args[arg]
+ rhs_args[arg] = args[arg]
+
+ rhs_name = hashlib.md5(rhs.fname).hexdigest()[0:8]
+ ctype = args[y].ctype
+ basename = 'apply_{}_{}_{}'.format(method.name(),ctype,rhs_name)
+
+ ctype = args[y].ctype
+
+ super(RungeKuttaFunction,self).__init__(basename=basename,
+ output=ctype,typegen=typegen,inline=True,
+ args=args, known_args=known_args)
+
+ self.update_requirements({'rhs':rhs})
+
+ self.ftype = ftype
+ self.method = method
+
+ self.has_time = has_time
+ self.has_step = has_step
+ self.rhs_args = rhs_args
+ self.used_vars = used_vars
+ self.rhs = rhs
+
+ self.gencode()
+
+ def gencode(self):
+ s = self
+ tg = s.typegen
+ ftype = s.ftype
+ method = s.method
+ used_vars = s.used_vars
+
+ has_time = s.has_time
+ has_step = s.has_step
+ rhs_args = s.rhs_args
+ rhs = s.reqs['rhs']
+
+ dt = s.vars[used_vars['dt']]
+ y = s.vars[used_vars['y']]
+ if has_time:
+ t = s.vars[used_vars['t']]
+ if has_step:
+ step = rhs.args[used_vars['step']]
+ rhs_args[used_vars['step']] = step
+
+ Ti = CodegenVariable('ti',ftype,tg)
+ Ki = copy.copy(y)
+ Yi = copy.copy(y)
+
+ K = CodegenArray('K',Yi.ctype,tg,shape=(method.order,))
+
+ dy = copy.copy(y)
+ dy.name = 'k'
+
+
+ with s._function_():
+
+ s.jumpline()
+ s.comment('Estimated slopes')
+ s.append(K.declare())
+ if has_step:
+ step.declare(s,init=0)
+ __sum = ''
+ for i in xrange(method.stages):
+ s.jumpline()
+ alpha = method.alpha[i]
+ beta = method.beta[i]
+ gamma = method.gamma[i-1,:]
+ s.comment('Computing Runge-Kutta step {}'.format(i))
+ if has_time:
+ _t = t()
+ if alpha!=0:
+ _t += ' + {}*{}'.format(tg.dump(alpha), dt())
+ _sum = ''
+ if i>0:
+ for j,g in enumerate(gamma):
+ if g==0:
+ continue
+ else:
+ _sum += '+{}*{}'.format(tg.dump(g),K[j])
+
+ with s._block_():
+ Yi.name='{}{}'.format(y(),i)
+ rhs_args[used_vars['y']] = Yi
+ if has_time:
+ Ti.name='{}{}'.format(t(),i)
+ s.append(Ti.declare(init=_t))
+ rhs_args[used_vars['t']] = Ti
+ if i>0:
+ Ki.name='{}{}'.format('k',i)
+ s.append(Ki.declare(init=_sum))
+ s.append(Yi.declare(init='{} + {}*{}'.format(y(),Ki(),dt())))
+ else:
+ s.append(Yi.declare(init=y()))
+
+ code='{} = {};'.format(K[i], rhs(**rhs_args))
+ s.append(code)
+ if beta!=0:
+ __sum += '+{}*{}'.format(tg.dump(beta),K[i])
+
+ if has_step:
+ s.append('{} += 1;'.format(step()))
+
+ s.jumpline()
+ s.append(dy.declare(const=True, init=__sum))
+ s.append('return {} + {}*{};'.format(y(),dy(),dt()))
+
+ def per_work_statistics(self):
+ ftype = self.ftype
+ method = self.method
+ stages = method.stages
+ rhs = self.rhs
+ has_time = int(self.has_time)
+
+ ops = {}
+ ops[ftype] = 2*stages
+ ops[ftype] += 2*has_time*np.sum(method.alpha!=0)
+ ops[ftype] += np.sum(2*np.sum(method.gamma!=0,axis=1)-1)
+ ops[ftype] += 2*np.sum(method.beta !=0)-1
+
+ stats = WorkStatistics()
+ stats.ops_per_type = ops
+
+ return stats + stages*rhs.per_work_statistics()
+
+
+if __name__ == '__main__':
+
+ from hysop.backend.device.codegen.base.test import test_typegen
+
+ method = ExplicitRungeKutta('RK4_38')
+
+ tg = test_typegen('float')
+ rkf = RungeKuttaFunction(tg,ftype=tg.fbtype,method=method,rhs='function')
+ rkf.edit()
+ print
+
diff --git a/hysop/backend/device/codegen/functions/stretching_rhs.py b/hysop/backend/device/codegen/functions/stretching_rhs.py
new file mode 100644
index 0000000000000000000000000000000000000000..5cda6360b57475de224a40f03b96e93645925e42
--- /dev/null
+++ b/hysop/backend/device/codegen/functions/stretching_rhs.py
@@ -0,0 +1,328 @@
+
+from hysop.deps import sm
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.function_codegen import OpenClFunctionCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+from hysop.methods import StretchingFormulation
+from hysop.constants import BoundaryCondition
+
+from hysop.backend.device.codegen.functions.apply_stencil import ApplyStencilFunction
+
+from hysop.numerics.stencil.stencil_generator import StencilGenerator
+
+# compute alpha*grad(u).w + (1-alpha)*grad(u)^T.w
+# where u may be cached and w is private
+# with finite difference centred stencil of given order
+class DirectionalStretchingRhsFunction(OpenClFunctionCodeGenerator):
+
+ _default_used_variables = {
+ 'U': 'U',
+ 'W': 'W',
+ 'components': 'xyz',
+ 'directions': 'XYZ'
+ }
+
+ def __init__(self, typegen, dim, ftype, order, direction, formulation, cached, boundary,
+ ptr_restrict=True, vectorize_u=False,
+ itype='int',
+ used_variables = _default_used_variables,
+ known_args=None):
+
+ assert dim==3
+ assert direction<dim
+ assert order>1 and order%2==0
+ check_instance(formulation,StretchingFormulation)
+ check_instance(boundary,tuple, values=BoundaryCondition)
+
+ is_conservative = (formulation==StretchingFormulation.CONSERVATIVE)
+ is_periodic = (boundary[0]==BoundaryCondition.PERIODIC) and \
+ (boundary[1]==BoundaryCondition.PERIODIC)
+
+ if cached:
+ storage='__local'
+ else:
+ storage='__global'
+
+ vtype = typegen.vtype(ftype,dim)
+
+ (args,basename) = self.build_prototype(typegen,dim,itype,ftype,vtype,order,
+ direction,cached,ptr_restrict,storage,vectorize_u,used_variables,
+ formulation,is_conservative,is_periodic)
+
+ reqs = self.build_requirements(typegen,dim,itype,ftype,vtype,order,direction,
+ boundary,cached,ptr_restrict,storage,vectorize_u,used_variables,
+ is_conservative,is_periodic,args)
+
+ super(DirectionalStretchingRhsFunction,self).__init__(basename=basename,
+ output=vtype,typegen=typegen,inline=True,
+ args=args, known_args=known_args)
+
+ self.update_requirements(reqs)
+
+ self.dim = dim
+ self.itype = itype
+ self.ftype = ftype
+ self.vtype = vtype
+
+ self.order = order
+ self.direction = direction
+ self.used_variables = used_variables
+ self.vectorize_u = vectorize_u
+ self.storage = storage
+ self.is_conservative = is_conservative
+ self.is_periodic = is_periodic
+ self.formulation = formulation
+ self.cached = cached
+ self.boundary = boundary
+
+ self.gencode()
+
+ def build_prototype(self,typegen,dim,itype,ftype,vtype,order,direction,cached,
+ ptr_restrict,storage, vectorize_u,used_variables,formulation,is_conservative,is_periodic):
+
+ U = used_variables['U']
+ W = used_variables['W']
+ xyz = used_variables['components']
+ XYZ = used_variables['directions']
+
+ args = ArgDict()
+ if vectorize_u:
+ args[U] = CodegenVariable(U, vtype, typegen, const=True, add_impl_const=True, storage=storage, ptr=True, ptr_restrict=ptr_restrict,nl=True)
+ else:
+ for i in xrange(dim):
+ Uxyz= '{}{}'.format(U,xyz[i])
+ args[Uxyz] = CodegenVariable(Uxyz, ftype, typegen, const=True, add_impl_const=True, storage=storage, ptr=True, ptr_restrict=ptr_restrict, nl=True)
+ if is_conservative:
+ Wd= '{}{}'.format(W,xyz[direction])
+ args[Wd] = CodegenVariable(Wd, ftype, typegen, const=False, add_impl_const=True, storage=storage, ptr=True, ptr_restrict=ptr_restrict, nl=True)
+
+ args[W] = CodegenVectorClBuiltin(W, ftype, dim, typegen, add_impl_const=True)
+ args['inv_dx'] = CodegenVariable('inv_dx', ftype, typegen, add_impl_const=True, nl=True)
+
+ if is_conservative:
+ args['rk_step'] = CodegenVariable('rk_step', itype, typegen, add_impl_const=True)
+ if is_periodic and (not cached):
+ args['base'] = CodegenVariable('base', itype, typegen, add_impl_const=True, nl=True)
+ args['offset'] = CodegenVariable('offset', itype, typegen, add_impl_const=True, nl=True)
+ args['width'] = CodegenVariable('width', itype, typegen, add_impl_const=True, nl=True)
+ else:
+ args['offset'] = CodegenVariable('offset', itype, typegen, add_impl_const=True, nl=True)
+ args['lidx'] = CodegenVariable('lidx', itype, typegen, add_impl_const=True)
+ args['Lx'] = CodegenVariable('Lx', itype, typegen, add_impl_const=True, nl=True)
+ args['active'] = CodegenVariable('active','bool',typegen)
+
+ basename = 'stretching_rhs_{}_{}{}{}_fdc{}'.format(str(formulation).lower(),
+ ftype[0],dim,('v' if vectorize_u else ''),order)
+ basename+='_'+XYZ[direction]
+
+ return (args,basename)
+
+ def build_stencil(self,order):
+ assert order%2==0
+ h = order/2
+ sg = StencilGenerator()
+ sg.configure(dim=1,derivative=1,order=order)
+ stencil = sg.generate_exact_stencil(origin=h)
+ return stencil
+
+ def build_requirements(self, typegen,dim,itype,ftype,vtype,order,direction,boundary,cached,
+ ptr_restrict,storage,vectorize_u,used_variables,is_conservative,is_periodic,args):
+
+ reqs = WriteOnceDict()
+
+ U = used_variables['U']
+ W = used_variables['W']
+ xyz = used_variables['components']
+
+ vector_inputs = [U]
+ if is_conservative:
+ scalar_inputs = ['{}{}'.format(W,xyz[direction])]
+ op = '{vinput0}[{id}] * {sinput0}[{id}]'
+ else:
+ scalar_inputs = []
+ op = '{vinput0}[{id}]'
+
+ if is_periodic and not cached:
+ base = args['base']
+ offset = args['offset']
+ width = args['width']
+ extra_inputs = [base,offset,width]
+ custom_id = '{}+({}+{}+{})%{}'.format(base(),width(),offset(),'{offset}',width())
+ known_args={}
+ else:
+ extra_inputs=[]
+ custom_id=None
+ known_args={'stride':1}
+
+ inv_dx_s = sm.Symbol('inv_dx')
+ inv_dx_var = CodegenVariable('inv_dx', ftype, typegen, add_impl_const=True, nl=True)
+
+ stencil = self.build_stencil(order)
+ stencil.replace_symbols({stencil.dx:1/inv_dx_s})
+ symbol2vars = {inv_dx_s:inv_dx_var}
+
+ apply_stencil = ApplyStencilFunction(typegen=typegen,
+ stencil=stencil,
+ symbol2vars=symbol2vars,
+ ftype=ftype, itype=itype,
+ data_storage=storage,
+ vectorize=vectorize_u,
+ components=dim,
+ extra_inputs = extra_inputs,
+ scalar_inputs = scalar_inputs,
+ vector_inputs = vector_inputs,
+ vector_suffixes = xyz,
+ op=op,
+ custom_id=custom_id,
+ known_args=known_args)
+ reqs['apply_stencil'] = apply_stencil
+
+ return reqs
+
+ def gencode(self):
+ s = self
+ dim = s.dim
+ tg = self.typegen
+
+ cached = s.cached
+ direction = s.direction
+ formulation = s.formulation
+ vectorize_u = s.vectorize_u
+ itype = s.itype
+ ftype = s.ftype
+ order = s.order
+
+ is_conservative = s.is_conservative
+ is_periodic = s.is_periodic
+
+ apply_stencil = s.reqs['apply_stencil']
+
+ used_variables=s.used_variables
+ U = used_variables['U']
+ W = used_variables['W']
+ xyz = used_variables['components']
+
+ fargs = {}
+ if is_periodic and not cached:
+ fargs['base'] = s.args['base']
+ fargs['offset'] = s.args['offset']
+ fargs['width'] = s.args['width']
+ else:
+ fargs['offset'] = s.args['offset']
+ fargs['inv_dx'] = s.args['inv_dx']
+ if vectorize_u:
+ fargs[U] = s.args[U]
+ else:
+ for i in xrange(dim):
+ Ui = U+xyz[i]
+ fargs[Ui] = s.args[Ui]
+ if is_conservative:
+ Wd = W+xyz[direction]
+ fargs[Wd] = s.args[Wd]
+ Wd = s.args[Wd]
+ call = apply_stencil(**fargs)
+
+ W = s.args[W]
+ lidx = s.args['lidx']
+ Lx = s.args['Lx']
+ if is_conservative:
+ rk_step = s.args['rk_step']
+
+ offset = s.args['offset']
+ active = s.args['active']
+
+ dw_dt = CodegenVectorClBuiltin('dW_dt', ftype, dim, tg)
+ ghosts = CodegenVariable('ghosts', itype, tg, const=True, value=order/2, symbolic_mode=True)
+
+ with s._function_():
+ s.jumpline()
+
+ ghosts.declare(s)
+
+ if is_conservative:
+ s.jumpline()
+ s.comment('Synchronize required vorticiy component across workitems')
+ s.barrier(_local=cached,_global=not cached)
+ with s._if_(active()):
+ code = '{} = {};'.format(Wd[offset()], W[direction])
+ s.append(code)
+ s.barrier(_local=cached,_global=not cached)
+ s.jumpline(2)
+
+ dw_dt.declare(s,init=0)
+
+ if is_conservative:
+ cond = '({active}) && ({lid}>={step}*{ghosts}) && ({lid}<{L}-{step}*{ghosts})'.format(
+ active=active(), lid=lidx(), L=Lx(), ghosts=ghosts(), step='({}+1)'.format(rk_step()))
+ else:
+ cond = '({active}) && ({lid}>={ghosts}) && ({lid}<{L}-{ghosts})'.format(
+ active=active(), lid=lidx(), L=Lx(), ghosts=ghosts())
+
+ with s._if_(cond):
+
+ if is_conservative:
+ s.comment('compute d(U*W{0})/d{0} using finite difference stencil'.format(xyz[direction]))
+ du_dx = CodegenVectorClBuiltin('dUW{0}_d{0}'.format(xyz[direction]), ftype, dim, tg, const=True)
+ du_dx.declare(s,init=call)
+
+ s.jumpline()
+
+ s.comment('directional contribution due to div(U:W)')
+ code = '{} += {};'.format(dw_dt(),du_dx())
+ s.append(code)
+ else:
+ s.comment('compute dU/dx using finite difference stencil')
+ du_dx = CodegenVectorClBuiltin('dU_d'+xyz[direction], ftype, dim, tg, const=True)
+ du_dx.declare(s,init=call)
+
+ s.jumpline()
+ if formulation==StretchingFormulation.GRAD_UW:
+ s.comment('directional contribution due to grad(U).W')
+ code = '{} += {}*{};'.format(dw_dt(), du_dx(), W[direction])
+ s.append(code)
+
+ elif formulation==StretchingFormulation.GRAD_UW_T:
+ s.comment('directional contribution due to grad(U)^T.W')
+ code = '{} += dot({},{});'.format(dw_dt[direction], du_dx(), W())
+ s.append(code)
+
+ elif formulation==StretchingFormulation.MIXED_GRAD_UW:
+ s.comment('directional contribution due to grad(U).W')
+ code = '{} += 0.5*{}*{};'.format(dw_dt(), du_dx(), W[direction])
+ s.append(code)
+ s.comment('directional contribution due to grad(U)^T.W')
+ code = '{} += 0.5*dot({},{});'.format(dw_dt[direction], du_dx(), W())
+ s.append(code)
+ else:
+ raise ValueError()
+
+ s.append('return {};'.format(dw_dt()))
+
+ def per_work_statistics(self):
+ dim = self.dim
+ ftype = self.ftype
+ storage = self.storage
+
+ stats = self.reqs['apply_stencil'].per_work_statistics()
+
+ if 'alpha' in self.known_args:
+ alpha = self.known_args['alpha']
+ else:
+ alpha = 0.5
+ stats.ops_per_type[ftype] += int(alpha!=0)*dim*3
+ stats.ops_per_type[ftype] += int(alpha!=1)*dim*2 + 2
+
+ return stats
+
+if __name__ == '__main__':
+
+ from hysop.backend.device.codegen.base.test import test_typegen
+ formulation = StretchingFormulation.GRAD_UW
+
+ tg = test_typegen('float')
+ asf = DirectionalStretchingRhsFunction(tg,3,tg.fbtype,4,1,vectorize_u=False,formulation=formulation,cached=False)
+ asf.edit()
diff --git a/hysop/codegen/maths/__init__.py b/hysop/backend/device/codegen/kernels/__init__.py
similarity index 100%
rename from hysop/codegen/maths/__init__.py
rename to hysop/backend/device/codegen/kernels/__init__.py
diff --git a/hysop/backend/device/codegen/kernels/bandwidth.py b/hysop/backend/device/codegen/kernels/bandwidth.py
new file mode 100644
index 0000000000000000000000000000000000000000..84df0d7f7cf682dd4418e54cec4836f7d5b67d7d
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/bandwidth.py
@@ -0,0 +1,102 @@
+
+import contextlib
+from contextlib import contextmanager
+
+import operator, hashlib
+
+from hysop import __VERBOSE__, __KERNEL_DEBUG__
+
+from hysop.tools.misc import Utils
+from hysop.constants import np
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+
+from hysop.backend.device.opencl import cl, clCharacterize
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.kernel_autotuner import KernelAutotuner, AutotunerConfig
+
+class BandwidthKernel(KernelCodeGenerator):
+
+ @staticmethod
+ def codegen_name(vtype,nreads,nwrites):
+ vtype = vtype.replace(' ','_')
+ name = 'bandwidth_{}_{}_{}'.format(vtype,nreads,nwrites)
+ return name
+
+ def __init__(self, typegen, vtype, nreads, nwrites, known_vars=None):
+
+ assert nreads>0 and nwrites>0
+
+ kernel_args = self.gen_kernel_arguments(typegen, vtype)
+
+ name = BandwidthKernel.codegen_name(vtype, nreads, nwrites)
+
+ super(BandwidthKernel,self).__init__(
+ name=name,
+ typegen=typegen,
+ work_dim=1,
+ kernel_args=kernel_args,
+ known_vars=known_vars)
+
+ self.vtype = vtype
+ self.nreads = nreads
+ self.nwrites = nwrites
+ self.gencode()
+
+
+ def gen_kernel_arguments(self, typegen, vtype):
+ kargs = ArgDict()
+ kargs['dst'] = CodegenVariable(ctype=vtype,name='dst',ptr=True,typegen=typegen,
+ nl=True,restrict=True,storage='__global')
+ kargs['src'] = CodegenVariable(ctype=vtype,name='src',ptr=True,typegen=typegen,
+ nl=True,restrict=True,storage='__global',const=True)
+ return kargs
+
+ def gencode(self):
+ s = self
+ vtype = s.vtype
+
+ global_id = s.vars['global_id']
+ global_size = s.vars['global_size']
+
+ dst = s.vars['dst']
+ src = s.vars['src']
+
+ buf = CodegenVariable(ctype=vtype,name='buffer',typegen=self.typegen,init=0)
+
+ with s._kernel_():
+ global_size.declare(s,const=True)
+ global_id.declare(s,const=True)
+ s.jumpline()
+ buf.declare(s)
+ s.jumpline()
+
+ if global_size.known():
+ s.pragma('unroll')
+ with s._for_('int {i}=0; {i}<{N}; {i}++'.format(i='i',N=self.nreads)):
+ offset = '{}+i*{}'.format(global_id(),global_size())
+ code = '{} += {};'.format(buf(), src[offset])
+ s.append(code)
+
+ s.jumpline()
+
+ if global_size.known():
+ s.pragma('unroll')
+ with s._for_('int {i}=0; {i}<{N}; {i}++'.format(i='i',N=self.nwrites)):
+ offset = '{}+i*{}'.format(global_id(),global_size())
+ code = '{} = {};'.format(dst[offset], buf())
+ s.append(code)
+
+if __name__ == '__main__':
+ from hysop.backend.device.codegen.base.test import test_typegen
+
+ tg = test_typegen('float')
+ vtype = 'float'
+
+ ck = BandwidthKernel(tg, vtype, nreads=99, nwrites=1, known_vars={'global_size':1024})
+ ck.edit()
diff --git a/hysop/backend/device/codegen/kernels/copy_kernel.py b/hysop/backend/device/codegen/kernels/copy_kernel.py
new file mode 100644
index 0000000000000000000000000000000000000000..66752bd7808b2101dfae4b395498637d38254018
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/copy_kernel.py
@@ -0,0 +1,241 @@
+
+import contextlib
+from contextlib import contextmanager
+
+import operator, hashlib
+
+from hysop import __VERBOSE__, __KERNEL_DEBUG__
+
+from hysop.tools.misc import Utils
+from hysop.constants import np
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+
+from hysop.backend.device.opencl import cl, clCharacterize
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.kernel_autotuner import KernelAutotuner, AutotunerConfig
+
+class CopyKernel(KernelCodeGenerator):
+
+ @staticmethod
+ def codegen_name(src_mem,dst_mem,vtype,restrict,vectorized):
+ name = 'copy_{}_{}_{}'.format(src_mem,dst_mem,vtype)
+ if restrict:
+ name += '_noalias'
+ if vectorized>1:
+ name += '_v{}'.format(vectorized)
+ return name
+
+ def __init__(self, typegen, vtype, vectorized=1,
+ src_mem='global', dst_mem='global', restrict=True,
+ known_vars = None,
+ force_symbolic = False):
+
+ if vectorized==1:
+ pass
+ elif vectorized not in typegen.vsizes:
+ raise ValueError('Invalid vector size.')
+ elif typegen.basetype(vtype)!=vtype:
+ raise ValueError('Cannot vectorize vector types.')
+
+ kernel_args = self.gen_kernel_arguments(typegen, vtype, src_mem, dst_mem, restrict)
+
+ name = CopyKernel.codegen_name(src_mem, dst_mem, vtype, restrict, vectorized)
+
+ super(CopyKernel,self).__init__(
+ name=name,
+ typegen=typegen,
+ work_dim=1,
+ kernel_args=kernel_args,
+ known_vars=known_vars,
+ vec_type_hint=vtype,
+ symbolic_mode=force_symbolic)
+
+ self.vtype = vtype
+ self.src_mem = src_mem
+ self.dst_mem = dst_mem
+ self.restrict = restrict;
+ self.vectorized = vectorized
+
+ self.gencode()
+
+
+ def gen_kernel_arguments(self, typegen, vtype, src_mem, dst_mem, restrict):
+
+ ftype = typegen.basetype(vtype)
+ components = typegen.components(vtype)
+ is_base_type = (components==1)
+
+ _src_mem = OpenClCodeGenerator.default_keywords[src_mem]
+ _dst_mem = OpenClCodeGenerator.default_keywords[dst_mem]
+
+ kargs = ArgDict()
+
+ kargs['dst'] = CodegenVariable(ctype=vtype,name='dst',ptr=True,typegen=typegen,
+ nl=True,restrict=restrict,storage=_src_mem)
+ kargs['src'] = CodegenVariable(ctype=vtype,name='src',ptr=True,typegen=typegen,
+ nl=True,restrict=restrict,storage=_dst_mem,const=True)
+ kargs['count'] = CodegenVariable(ctype='unsigned int',name='count',
+ typegen=typegen,add_impl_const=True,nl=True)
+
+ return kargs
+
+ def gencode(self):
+ s = self
+
+ global_id = s.vars['global_id']
+ global_size = s.vars['global_size']
+
+ dst = s.vars['dst']
+ src = s.vars['src']
+ count = s.vars['count']
+
+
+ with s._kernel_():
+ global_size.declare(s,const=True)
+
+ if global_size.known():
+ s.pragma('unroll')
+ with s._for_('int {gid}={fval}; {gid}<{N}; {gid}+={gsize}'.format(gid=global_id(),
+ fval=global_id.fval(0),gsize=global_size(),N=count())):
+ N=s.vectorized
+ if(N>1):
+ vload = 'vload{N}({offset}, {src})'.format(N=N,offset=global_id(), src=src())
+ vstore = 'vstore{N}({vload}, {offset}, {dst});'.format(vload=vload,N=N,offset=global_id(), dst=dst())
+ s.append(vstore)
+ else:
+ s.append("{} = {};".format(dst[global_id()],src[global_id()]))
+
+ @staticmethod
+ def autotune(cl_env, src, dst, vtype, count, restrict,
+ build_opts, autotuner_config):
+
+ if not isinstance(cl_env,OpenClEnvironment):
+ raise ValueError('cl_env is not an OpenClEnvironment.')
+ if not isinstance(cl_env.typegen,OpenClTypeGen):
+ raise ValueError('typegen is not an OpenClTypeGen.')
+
+ device = cl_env.device
+ context = cl_env.ctx
+ platform = cl_env.platform
+ queue = cl_env.queue
+ typegen = cl_env.typegen
+
+ if vtype not in typegen.builtin_types:
+ raise ValueError('{} is not an opencl bultin type.'.format(vtype))
+ if count < 0:
+ raise ValueError('count < 0')
+
+ if context is None:
+ raise ValueError('context cannot be None.')
+ if device is None:
+ raise ValueError('device cannot be None.')
+ if platform is None:
+ raise ValueError('platform cannot be None.')
+ if queue is None:
+ raise ValueError('queue cannot be None.')
+ if typegen.platform!=platform or typegen.device!=device:
+ raise ValueError('platform or device mismatch.')
+
+ # autotuner parameters
+ work_size=count
+ min_local_size = max(1,clCharacterize.get_simd_group_size(device,1))
+ max_workitem_workload = 256
+
+ symbolic_mode = __KERNEL_DEBUG__
+ dump_src = __KERNEL_DEBUG__
+
+
+ ## kernel generator
+ def kernel_generator(work_size, global_size, local_size, kernel_args, vectorized,
+ force_verbose=False, force_debug=False,
+ **kargs):
+
+ ## Compile time known variables
+ known_vars = dict(
+ global_size=global_size[0],
+ local_size=local_size[0],
+ count = work_size[0]
+ )
+
+ ## CodeGenerator
+ codegen = CopyKernel(typegen=typegen, vtype=vtype, vectorized=vectorized,
+ src_mem='global', dst_mem='global', restrict=restrict,
+ force_symbolic=symbolic_mode,
+ known_vars=known_vars)
+
+ ## generate source code and build kernel
+ src = codegen.__str__()
+ src_hash = hashlib.sha512(src).hexdigest()
+ prg = cl_env.build_raw_src(src, build_opts,
+ kernel_name=codegen.name,
+ force_verbose=force_verbose, force_debug=force_debug)
+ kernel = prg.all_kernels()[0]
+
+ return (kernel, kernel_args, 0, src_hash)
+
+ ## Kernel Autotuner
+ def _autotune(vectorized):
+
+ if work_size%vectorized!=0:
+ raise ValueError('Invalid vector size.')
+
+ codegen_name =CopyKernel.codegen_name('global','global',vtype,restrict,vectorized)
+ autotuner = KernelAutotuner(name=codegen_name,
+ work_dim=1,
+ build_opts=build_opts,
+ autotuner_config=autotuner_config)
+ autotuner.add_filter('1d_shape_min', autotuner.min_workitems_per_direction)
+ autotuner.enable_variable_workitem_workload(max_workitem_workload=max_workitem_workload)
+
+ kernel_args = [dst,src]
+ kernel_args_mapping={
+ 'dst':slice(1,2,1),
+ 'src':slice(2,3,1)
+ }
+
+ (gwi, lwi, stats, wl) = autotuner.bench(typegen=typegen,
+ work_size=work_size/vectorized, kernel_args=kernel_args,
+ kernel_generator=kernel_generator,
+ dump_src=dump_src,
+ min_local_size=min_local_size,
+ vectorized=vectorized)
+
+ (kernel, kernel_args, cached_bytes, src_hash) = kernel_generator(
+ work_size=[work_size/vectorized], global_size=gwi,local_size=lwi,
+ kernel_args=kernel_args, vectorized=vectorized,
+ force_verbose=None,force_debug=None)
+
+ kernel_launcher = OpenClKernelLauncher(kernel, queue, list(gwi), list(lwi))
+ return (stats, kernel_launcher, kernel_args, kernel_args_mapping, cached_bytes)
+
+ candidates = [i for i in typegen.vsizes if work_size%i==0]
+
+ best = None
+ for vectorized in candidates:
+ res = _autotune(vectorized);
+ if (best is None) or res[0]<best[0]:
+ best = res
+ return best[1:]
+
+
+if __name__ == '__main__':
+ from hysop.backend.device.codegen.base.test import test_typegen
+
+ tg = test_typegen('float','dec')
+ vtype = 'float'
+
+ ck = CopyKernel(tg, vtype, vectorized=16,
+ force_symbolic=True,
+ known_vars=dict(
+ count=1024*1024,
+ local_size=1024,
+ global_size=1024*512
+ )
+ )
+ ck.edit()
diff --git a/hysop/backend/device/codegen/kernels/directional_advection.py b/hysop/backend/device/codegen/kernels/directional_advection.py
new file mode 100644
index 0000000000000000000000000000000000000000..283ad06fc37d1191626bef91e7845fff664a6260
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/directional_advection.py
@@ -0,0 +1,782 @@
+
+import contextlib
+from contextlib import contextmanager
+
+from hysop.deps import math, operator, hashlib
+
+from hysop import __VERBOSE__, __KERNEL_DEBUG__
+from hysop.backend.device.opencl import cl
+
+from hysop.tools.misc import Utils
+from hysop.tools.types import check_instance
+
+from hysop.deps import np
+from hysop.constants import DirectionLabels, BoundaryCondition, Backend
+from hysop.core.arrays.all import OpenClArray
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, \
+ CodegenVectorClBuiltin, CodegenArray
+from hysop.backend.device.opencl import cl, clTools
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+from hysop.backend.device.codegen.base.variables import CodegenStruct
+from hysop.backend.device.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
+
+from hysop.backend.device.codegen.functions.compute_index import ComputeIndexFunction
+from hysop.backend.device.codegen.functions.cache_load import CacheLoadFunction
+from hysop.backend.device.codegen.functions.runge_kutta import RungeKuttaFunction
+from hysop.backend.device.codegen.functions.advection_rhs import DirectionalAdvectionRhsFunction
+
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta
+
+from hysop.backend.device.opencl import cl, clCharacterize
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.kernel_autotuner import KernelAutotuner, AutotunerFlags, \
+ KernelGenerationError
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
+
+from hysop.fields.discrete import DiscreteField
+
+class DirectionalAdvectionKernel(KernelCodeGenerator):
+
+ @staticmethod
+ def codegen_name(ftype, is_cached, rk_scheme, nparticles, min_ghosts, **kargs):
+ cache = 'cached_' if is_cached else ''
+ return 'directional_{}advection_{}_{}{}p_{}g'.format(cache,rk_scheme.name(),
+ ftype[0],nparticles,min_ghosts)
+
+ def __init__(self, typegen, work_dim, ftype,
+ is_cached, rk_scheme,
+ vboundary, nparticles,
+ min_ghosts=0,
+ symbolic_mode = False,
+ debug_mode = False,
+ known_vars = None):
+
+ assert work_dim>0 and work_dim<=3
+ assert nparticles in [1,2,4,8,16]
+ check_instance(vboundary[0],BoundaryCondition)
+ check_instance(vboundary[1],BoundaryCondition)
+ check_instance(rk_scheme, ExplicitRungeKutta)
+
+ known_vars = known_vars or dict()
+
+ assert vboundary[0] in [BoundaryCondition.PERIODIC, BoundaryCondition.NONE]
+ assert vboundary[1] in [BoundaryCondition.PERIODIC, BoundaryCondition.NONE]
+ is_periodic = (vboundary[0]==BoundaryCondition.PERIODIC \
+ and vboundary[1]==BoundaryCondition.PERIODIC)
+ assert (is_periodic and not is_cached) or min_ghosts>0
+
+ local_size_known = ('local_size' in known_vars)
+
+ _global = OpenClCodeGenerator.default_keywords['global']
+ _local = OpenClCodeGenerator.default_keywords['local']
+
+ if is_cached:
+ storage = _local
+ else:
+ storage = _global
+
+ self._global, self._local = _global, _local
+
+ itype = 'int'
+
+ name = DirectionalAdvectionKernel.codegen_name(ftype,is_cached,rk_scheme,nparticles,
+ min_ghosts)
+
+ kernel_reqs = self.build_requirements(typegen, work_dim, itype, ftype, is_cached,
+ rk_scheme, vboundary, nparticles, symbolic_mode, storage, is_periodic,
+ known_vars)
+
+ kernel_args = self.gen_kernel_arguments(typegen, work_dim, itype, ftype, kernel_reqs,
+ is_cached, local_size_known, debug_mode)
+
+ super(DirectionalAdvectionKernel,self).__init__(
+ name=name,
+ typegen=typegen,
+ work_dim=work_dim,
+ kernel_args=kernel_args,
+ known_vars=known_vars,
+ vec_type_hint=ftype,
+ symbolic_mode=symbolic_mode)
+
+ self.update_requirements(kernel_reqs)
+
+ self.itype = itype
+ self.ftype = ftype
+ self.work_dim = work_dim
+ self.vboundary = vboundary
+ self.nparticles = nparticles
+ self.rk_scheme = rk_scheme
+ self.storage = storage
+ self.local_size_known = local_size_known
+ self.is_periodic = is_periodic
+ self.is_cached = is_cached
+ self.min_ghosts = min_ghosts
+
+ self.gencode()
+
+
+ @staticmethod
+ def cache_ghosts(cfl):
+ return int(math.ceil(cfl))
+
+ #return minimal number of ghosts required on the grid
+ #@staticmethod
+ #def min_ghosts(work_dim,boundaries,cfl):
+ #ghosts = [0]*work_dim
+ #(lboundary, rboundary) = boundaries
+ #if lboundary != BoundaryCondition.PERIODIC:
+ #assert rboundary != BoundaryCondition.PERIODIC
+ #ghosts[0] = self.cache_ghosts(cfl)
+ #return np.asarray(ghosts)
+
+ @staticmethod
+ def min_wg_size(work_dim,rk_scheme):
+ size = [1]*work_dim
+ size[0] = 32
+ return np.asarray(size)
+
+ #return global_work_size from effective work_size without
+ # taking into account local_work_size alignment
+ @staticmethod
+ def get_max_global_size(work_size, work_load, nparticles,**kargs):
+ work_size = np.asarray(work_size).copy()
+ work_load = np.asarray(work_load).copy()
+
+ assert work_load[0] == 1
+ work_load[0] = nparticles
+
+ global_size = work_size.copy()
+ global_size = ((global_size+work_load-1)/work_load)
+ return global_size
+
+ #return global_work_size from effective work_size and given local_work_size
+ # global_work_size will be a multiple of local_work_size
+ def get_global_size(self, work_size, local_work_size, work_load=None):
+ work_dim = self.work_dim
+ work_load = [1]*work_dim if (work_load is None) else work_load
+
+ work_size = np.asarray(work_size)
+ work_load = np.asarray(work_load)
+ local_work_size = np.asarray(local_work_size)
+
+ nparticles = self.nparticles
+
+ # for var in [work_size, work_load, local_work_size]:
+ # msg = 'Dimension mismatch for variable {}, expected work_dim is {}.'
+ # msg = msg.format(var, work_dim)
+ # if var.size != work_dim:
+ # raise ValueError(msg)
+ for i in xrange(1,work_dim):
+ assert (local_work_size[i] == 1), 'local_work_size error!'
+
+ if 'local_size' in self.known_vars:
+ assert (self.known_vars['local_size'] == local_work_size[:work_dim]).all(),\
+ 'local_work_size mismatch!'
+
+ max_global_size = self.get_max_global_size(work_size, work_load, nparticles)
+ global_size = ((max_global_size+local_work_size-1)/local_work_size) * local_work_size
+ global_size[0] = local_work_size[0]
+
+ return global_size
+
+ #return a tuple of required (static,dynamic,total) cache bytes per workgroup
+ def required_workgroup_cache_size(self, local_work_size):
+ work_dim = self.work_dim
+ ftype = self.ftype
+ is_cached = self.is_cached
+ flt_bytes = self.typegen.FLT_BYTES[ftype]
+
+ local_work_size = np.asarray(local_work_size)
+
+ sc,dc = 0,0
+ if is_cached:
+ count = self.nparticles*local_work_size[0]+2*self.min_ghosts
+ if 'local_size' in self.known_vars:
+ assert (self.known_vars['local_size'] == local_work_size[:work_dim]).all()
+ sc += count
+ else:
+ dc += count
+
+ sc *= flt_bytes
+ dc *= flt_bytes
+ tc = sc+dc
+
+ return (sc,dc,tc)
+
+ def build_requirements(self,typegen,work_dim,itype,ftype,is_cached,rk_scheme,
+ vboundary,nparticles,force_symbolic,storage,is_periodic,known_vars):
+ tg=typegen
+ reqs = WriteOnceDict()
+
+ mesh_base_struct = MeshBaseStruct(typegen=typegen, typedef='MeshBase_s')
+ reqs['MeshBaseStruct'] = mesh_base_struct
+
+ mesh_info_struct = MeshInfoStruct(typegen=typegen, typedef='MeshInfo_s')
+ reqs['MeshInfoStruct'] = mesh_info_struct
+
+ if is_cached:
+ cache_load = CacheLoadFunction(typegen=tg,ftype=ftype,work_dim=1,
+ components=1, src_vectorize=False, dst_vectorize=False,
+ boundary=vboundary[0], with_gid_ghost_offset=False)
+ reqs['cache_load'] = cache_load
+
+ advection_rhs = DirectionalAdvectionRhsFunction(typegen=typegen, work_dim=work_dim,
+ ftype=ftype, is_cached=is_cached,
+ boundary=vboundary[0], nparticles=nparticles,
+ ptr_restrict=True,
+ itype=itype)
+
+ used_vars = RungeKuttaFunction._default_used_vars.copy()
+ used_vars['y']='X'
+ used_vars['step']='rk_step'
+ runge_kutta = RungeKuttaFunction(typegen=tg, ftype=ftype,
+ method=rk_scheme,
+ rhs=advection_rhs,
+ used_vars=used_vars,
+ known_args=None)
+ reqs['runge_kutta'] = runge_kutta
+
+ return reqs
+
+ def gen_kernel_arguments(self, typegen, work_dim, itype, ftype, requirements,is_cached,
+ local_size_known, debug_mode):
+
+ kargs = ArgDict()
+ kargs['dt'] = CodegenVariable(ctype=ftype,name='dt',typegen=typegen,
+ add_impl_const=True,nl=True)
+
+ kargs['velocity_base'] = CodegenVariable(storage=self._global,name='velocity_base',
+ ctype=ftype, typegen=typegen, ptr_restrict=True,ptr=True,const=True,
+ add_impl_const=True, nl=False)
+ kargs['velocity_offset'] = CodegenVariable(ctype='unsigned long',name='velocity_offset',
+ typegen=typegen, add_impl_const=True,nl=True)
+
+ kargs['position_base'] = CodegenVariable(storage=self._global,name='position_base',
+ ctype=ftype, typegen=typegen, ptr_restrict=True, ptr=True,const=False,
+ add_impl_const=True, nl=False)
+ kargs['position_offset'] = CodegenVariable(ctype='unsigned long',name='position_offset',
+ typegen=typegen,add_impl_const=True,nl=True)
+
+ if debug_mode:
+ kargs['dbg0'] = CodegenVariable(storage=self._global,name='dbg0',ctype=itype,
+ typegen=typegen, ptr_restrict=True,ptr=True,const=False,add_impl_const=True)
+ kargs['dbg1'] = CodegenVariable(storage=self._global,name='dbg1',ctype=itype,
+ typegen=typegen, ptr_restrict=True,ptr=True,const=False,add_impl_const=True)
+
+ kargs['velocity_mesh_info'] = requirements['MeshInfoStruct'].build_codegen_variable(
+ const=True, name='velocity_mesh_info')
+ kargs['position_mesh_info'] = requirements['MeshInfoStruct'].build_codegen_variable(
+ const=True, name='position_mesh_info')
+
+ if is_cached and not local_size_known:
+ kargs['Vc'] = CodegenVariable(storage=_local,ctype=ftype, add_impl_const=True,
+ name='Vc', ptr=True, ptr_restrict=True, typegen=typegen, nl=False)
+
+ return kargs
+
+ def gencode(self):
+ s = self
+ tg = s.typegen
+
+ work_dim = s.work_dim
+ itype = s.itype
+ ftype = s.ftype
+ vboundary = s.vboundary
+ storage = s.storage
+ nparticles = s.nparticles
+ min_ghosts = s.min_ghosts
+
+ symbolic_mode = s.symbolic_mode
+
+ is_periodic = s.is_periodic
+ is_cached = s.is_cached
+ local_size_known = s.local_size_known
+
+ vtype = tg.vtype(ftype,work_dim)
+
+ global_id = s.vars['global_id']
+ local_id = s.vars['local_id']
+ group_id = s.vars['group_id']
+
+ global_index = s.vars['global_index']
+ local_index = s.vars['local_index']
+
+ global_size = s.vars['global_size']
+ local_size = s.vars['local_size']
+
+ dt = s.vars['dt']
+ position_mesh_info = s.vars['position_mesh_info']
+ velocity_mesh_info = s.vars['velocity_mesh_info']
+
+ velocity_base = s.vars['velocity_base']
+ position_base = s.vars['position_base']
+ velocity_offset = s.vars['velocity_offset']
+ position_offset = s.vars['position_offset']
+
+ velocity = CodegenVariable(storage=s._global,name='velocity',
+ ctype=ftype, typegen=tg, ptr_restrict=True, ptr=True, const=True,
+ add_impl_const=True)
+ position = CodegenVariable(storage=s._global,name='position',
+ ctype=ftype, typegen=tg, ptr_restrict=True, ptr=True, const=False)
+
+ grid_size = position_mesh_info['local_mesh']['resolution'].view(
+ 'grid_size', slice(None,work_dim))
+ compute_grid_size = position_mesh_info['local_mesh']['compute_resolution'].view(
+ 'compute_grid_size',slice(None,work_dim))
+ compute_grid_ghosts = position_mesh_info['ghosts'].view(
+ 'compute_grid_ghosts', slice(0,work_dim), const=True)
+ dx = position_mesh_info['dx'].view('dx', slice(0,1), const=True)
+ inv_dx = position_mesh_info['inv_dx'].view('inv_dx', slice(0,1), const=True)
+ xmin = position_mesh_info['local_mesh']['xmin'].view('xmin',
+ slice(0,1), const=True)
+ s.update_vars(grid_size=grid_size, inv_dx=inv_dx,
+ compute_grid_ghosts=compute_grid_ghosts, compute_grid_size=compute_grid_size,
+ velocity=velocity, position=position)
+
+ if is_cached:
+ cache_load = self.reqs['cache_load']
+ runge_kutta = self.reqs['runge_kutta']
+
+ line_index = CodegenVariable(name='line_index', ctype=itype, typegen=tg)
+ line_offset = CodegenVariable(name='line_offset', ctype=itype, typegen=tg,const=True)
+ line_velocity = CodegenVariable(name='line_velocity', ctype=ftype, ptr=True,
+ storage='__global', ptr_restrict=True, const=True, add_impl_const=True, typegen=tg)
+
+ X = CodegenVectorClBuiltin('X', ftype, nparticles, typegen=tg)
+ pid = CodegenVectorClBuiltin('pid', itype, nparticles, typegen=tg,
+ const=True)
+ poffset = CodegenVectorClBuiltin('poffset', itype, nparticles, typegen=tg)
+
+ npart = CodegenVariable(name='npart', ctype=itype, typegen=tg, init=nparticles)
+ if is_cached:
+ cache_ghosts = CodegenVariable('cache_ghosts', itype, typegen=tg, value=min_ghosts,
+ symbolic_mode=symbolic_mode)
+ cache_width = CodegenVariable('cache_width', itype, typegen=tg,
+ init='{}*{} + 2*{}'.format(npart(),local_size[0],cache_ghosts()))
+ if local_size_known:
+ L = s.known_vars['local_size']
+ Vc = CodegenArray(name='Vc',dim=1,ctype=ftype,typegen=tg,
+ shape=(nparticles*L[0]+2*min_ghosts,), storage='__local')
+ else:
+ Vc = s.vars['Vc']
+
+ part_ftype = X.ctype
+ part_itype = pid.ctype
+
+ active = CodegenVariable('active','bool',tg, const=True)
+
+ @contextmanager
+ def _work_iterate_(i):
+ try:
+ if i==0:
+ fval = 0
+ gsize = 1
+ N = '({Sx}+{npart}*{Lx}-1)/({npart}*{Lx})'.format(
+ Sx=compute_grid_size[i], npart=npart(),Lx=local_size[0])
+ else:
+ fval = global_id.fval(i)
+ gsize = global_size[i]
+ N = '{Sx}'.format(Sx=compute_grid_size[i])
+ ghosts = compute_grid_ghosts[i]
+
+ s.append('#pragma unroll 4')
+ with s._for_('int {i}={fval}; {i}<{N}; {i}+={gsize}'.format(
+ i='kji'[i], fval=fval, gsize=gsize,N=N)) as ctx:
+ if i==0:
+ s.append('{} = k*{}+{};'.format(global_id[0], local_size[0],
+ local_id[0]))
+ else:
+ s.append('{} = {}+{};'.format(global_id[i], 'kji'[i], ghosts))
+ if i==1 or work_dim==1:
+ init = '0'
+ if work_dim>2:
+ init = '{}*{}'.format(global_id[2],grid_size[1])
+ if work_dim>1:
+ init = '({}+{})*{}'.format(init, global_id[1],grid_size[0])
+ line_index.declare(s, const=True, init=init)
+ line_velocity.declare(s, init='{}+{}'.format(velocity(),line_index()))
+
+ yield ctx
+ except:
+ raise
+ nested_loops = [_work_iterate_(i) for i in xrange(work_dim-1,-1,-1)]
+
+ with s._kernel_():
+ with s._align_() as al:
+ velocity.declare(al,align=True,init='(__global {} const *)((__global char const *)({})+{})'.format(
+ ftype, velocity_base, velocity_offset))
+ position.declare(al,align=True,init='(__global {} *)((__global char *)({})+{})'.format(
+ ftype, position_base, position_offset))
+ s.jumpline()
+ with s._align_() as al:
+ local_id.declare(al,align=True,const=True)
+ global_size.declare(al,align=True,const=True)
+ local_size.declare(al,align=True,const=True)
+ s.jumpline()
+
+ with s._align_() as al:
+ compute_grid_size.declare(al,const=True,align=True)
+ compute_grid_ghosts.declare(al,align=True)
+ grid_size.declare(al,align=True,const=True)
+ al.jumpline()
+ xmin.declare(al,align=True)
+ inv_dx.declare(al,align=True)
+ dx.declare(al,align=True)
+ s.jumpline()
+
+ with s._align_() as al:
+ npart.declare(al, const=True, align=True)
+ if is_cached:
+ cache_ghosts.declare(al,const=True, align=True)
+ cache_width.declare(al,const=True, align=True)
+ s.jumpline()
+
+ if is_cached and local_size_known:
+ Vc.declare(s);
+ s.jumpline()
+
+ poffset.declare(s,init=range(nparticles),const=True)
+ global_id.declare(s,init=False)
+ s.jumpline()
+
+ with contextlib.nested(*nested_loops):
+ active.declare(s, init='({}*{}+{}-1 < {})'.format(npart(),global_id[0], npart(),
+ compute_grid_size[0]))
+ s.jumpline()
+
+ if is_cached:
+ line_offset.declare(s,init='{}*{}*{}-{}'.format('k',local_size[0],npart(),
+ cache_ghosts()))
+ else:
+ line_offset.declare(s,init=0)
+
+ s.jumpline()
+
+ if is_cached:
+ cid = CodegenVariable(name='cid',ctype=itype,typegen=tg,const=True)
+ cid.declare(s,init='{} + {}'.format(line_offset(), local_id[0]))
+ kargs = {
+ 'src0': line_velocity,
+ 'dst0': Vc,
+ 'src_size': grid_size[0],
+ 'local_size': local_size[0],
+ 'local_id': local_id[0],
+ 'global_id': cid,
+ 'lghosts': cache_ghosts,
+ 'rghosts': cache_ghosts,
+ 'multiplier': npart,
+ }
+ call = cache_load(**kargs)
+ s.append(call+';')
+ s.jumpline()
+
+ with s._if_(active()):
+ pid.declare(s, init='{}*{}+{}+{}'.format(npart(),global_id[0],poffset(),
+ compute_grid_ghosts[0]))
+ X.declare(s, init='convert_{}({}+{})*{}'.format(part_ftype,pid(),
+ compute_grid_ghosts[0], dx()));
+
+ s.jumpline()
+
+ rk_args = {
+ 'X': X,
+ 'dt': dt,
+ 'inv_dx': inv_dx,
+ 'line_offset': line_offset
+ }
+ if is_cached:
+ rk_args['line_velocity'] = Vc
+ else:
+ rk_args['line_velocity'] = line_velocity
+ if is_periodic:
+ rk_args['line_width'] = grid_size[0]
+ call = runge_kutta(**rk_args)
+ code = '{} = {};'.format(X(), call)
+ s.append(code)
+
+ s.append('{} += {};'.format(X(), xmin()))
+ s.jumpline()
+
+ if nparticles>1:
+ code = 'vstore{}({}, {}, {}+{});'.format(nparticles,X(),
+ global_id[0], position(), line_index())
+ s.append(code)
+ else:
+ code = '{} = {};'.format(
+ position['{}+{}'.format(line_index(),pid())],X())
+ s.append(code)
+
+
+ @staticmethod
+ def autotune(direction, time_integrator, cfl,
+ cl_env, precision, build_opts, autotuner_config,
+ velocity, position,
+ velocity_mesh_info, position_mesh_info):
+
+ dim = velocity.nb_components
+ dir = direction
+
+ ftype = clTools.dtype_to_ctype(precision)
+
+ if not isinstance(cl_env,OpenClEnvironment):
+ raise ValueError('cl_env is not an OpenClEnvironment.')
+ if not isinstance(cl_env.typegen,OpenClTypeGen):
+ raise ValueError('typegen is not an OpenClTypeGen.')
+
+ device = cl_env.device
+ context = cl_env.context
+ platform = cl_env.platform
+ queue = cl_env.queue
+ typegen = cl_env.typegen
+
+ if context is None:
+ raise ValueError('context cannot be None.')
+ if device is None:
+ raise ValueError('device cannot be None.')
+ if platform is None:
+ raise ValueError('platform cannot be None.')
+ if queue is None:
+ raise ValueError('queue cannot be None.')
+ if typegen.platform!=platform or typegen.device!=device:
+ raise ValueError('platform or device mismatch.')
+
+ if dim<1 or dim>3:
+ raise ValueError('Dimension mismatch...')
+ if direction<0 or direction>=dim:
+ raise ValueError('Direction mismatch...')
+ if not isinstance(time_integrator, ExplicitRungeKutta):
+ msg = 'Given time integrator is not an instance of ExplicitRungeKutta, '
+ msg+= 'got a \'{}\'.'.format(rk_scheme.__class__.__name__)
+ raise ValueError(msg)
+ rk_scheme = time_integrator
+ del time_integrator
+
+ if not isinstance(velocity,DiscreteField) or velocity.backend.kind!=Backend.OPENCL:
+ raise ValueError('velocity is not a OpenClDiscreteField')
+ if (velocity.nb_components != dim):
+ raise ValueError('Velocity vector components mismatch with dim {}.'.format(dim))
+
+ if not isinstance(position,OpenClArray):
+ raise ValueError('position is not a OpenClArray but a {}.'\
+ .format(position.__class__.__name__))
+
+ if (not isinstance(velocity_mesh_info,CodegenStruct)) \
+ or (not velocity_mesh_info.known()):
+ msg='velocity_mesh_info is not a known MeshInfoStruct codegen variable.'
+ raise ValueError(msg)
+ if (not isinstance(position_mesh_info,CodegenStruct)) \
+ or (not position_mesh_info.known()):
+ msg='position_mesh_info is not a known MeshInfoStruct codegen variable.'
+ raise ValueError(msg)
+
+ v_resolution = velocity_mesh_info['local_mesh']['compute_resolution'].value[:dim]
+ v_lboundary = velocity_mesh_info['local_mesh']['lboundary'].value[:dim]
+ v_rboundary = velocity_mesh_info['local_mesh']['rboundary'].value[:dim]
+ v_ghosts = velocity_mesh_info['ghosts'].value[:dim]
+ v_dx = velocity_mesh_info['dx'].value[:dim]
+
+ p_resolution = position_mesh_info['local_mesh']['compute_resolution'].value[:dim]
+ p_lboundary = position_mesh_info['local_mesh']['lboundary'].value[:dim]
+ p_rboundary = position_mesh_info['local_mesh']['rboundary'].value[:dim]
+ p_ghosts = position_mesh_info['ghosts'].value[:dim]
+ p_dx = position_mesh_info['dx'].value[:dim]
+
+ vboundary = (v_lboundary[0], v_rboundary[0])
+
+ min_v_ghosts = int(math.ceil(cfl))
+ min_p_ghosts = 0
+ assert (min_v_ghosts>=1)
+
+ if not cl_env.is_multi_device:
+ if v_lboundary[0] == BoundaryCondition.PERIODIC:
+ assert v_rboundary[0] == BoundaryCondition.PERIODIC
+ min_v_ghosts = 0
+
+ if (v_ghosts[0] < min_v_ghosts):
+ msg= 'Given boundary condition implies minimum ghosts numbers to be at least {} '
+ msg+='in current direction for velocity but only {} ghosts '
+ msg+='are present in the grid.'
+ msg=msg.format(min_v_ghosts, v_ghosts[0])
+ raise ValueError(msg)
+
+ is_multi_scale = (v_resolution[0] != p_resolution[0])
+ if is_multi_scale:
+ msg='Compute_resolution mismatch between velocity and particles, '
+ msg+='got {} and {} and multiscale has not been implemented yet.'
+ msg=msg.format(v_resolution,p_resolution)
+ raise ValueError(msg)
+
+ cache_ghosts = DirectionalAdvectionKernel.cache_ghosts(cfl)
+ min_wg_size = DirectionalAdvectionKernel.min_wg_size(dim, rk_scheme)
+
+ # work size is the resolution without ghosts
+ work_size = np.ones(3,dtype=np.int32)
+ work_size[:dim] = p_resolution
+
+ # autotuner parameters
+
+ dump_src = __KERNEL_DEBUG__
+ symbolic_mode = __KERNEL_DEBUG__
+
+ min_simd_group_size = [1]*dim
+ min_simd_group_size[0] = clCharacterize.get_simd_group_size(device,1)
+ min_local_size = np.minimum(np.maximum( min_wg_size, min_simd_group_size), work_size)
+
+ autotuner_flag = autotuner_config.autotuner_flag
+ if (autotuner_flag == AutotunerFlags.ESTIMATE):
+ max_workitem_workload = [1,1,1]
+ caching_options = [True,False]
+ nparticles_options = [1]
+ elif (autotuner_flag == AutotunerFlags.MEASURE):
+ max_workitem_workload = [1,8,1]
+ caching_options = [True,False]
+ nparticles_options = [1,2,4]
+ elif (autotuner_flag == AutotunerFlags.PATIENT):
+ max_workitem_workload = [1,8,8]
+ caching_options = [True,False]
+ nparticles_options = [1,2,4,8,16]
+ elif (autotuner_flag == AutotunerFlags.EXHAUSTIVE):
+ max_workitem_workload = [1,16,16]
+ caching_options = [True,False]
+ nparticles_options = [1,2,4,8,16]
+
+ max_workitem_workload = np.asarray(max_workitem_workload)
+ max_workitem_workload[dim:] = 1
+
+ ## kernel generator
+ def kernel_generator(work_size, work_load, local_work_size,
+ kernel_args,
+ extra_parameters,
+ force_verbose=False, force_debug=False,
+ return_codegen = False,
+ **kargs):
+
+ ## Compile time known variables
+ # dt is not known because it depends on splitting direction
+ # and simulation current time_step
+ known_vars = dict(
+ velocity_mesh_info=velocity_mesh_info,
+ position_mesh_info=position_mesh_info,
+ local_size=local_work_size[:dim]
+ )
+
+ ## CodeGenerator
+ name = DirectionalAdvectionKernel.codegen_name(ftype=ftype,
+ rk_scheme=rk_scheme, min_ghosts=cache_ghosts,**extra_parameters)
+ codegen = DirectionalAdvectionKernel(typegen=typegen,
+ work_dim=dim,
+ vboundary=vboundary,
+ rk_scheme=rk_scheme,
+ symbolic_mode=symbolic_mode, ftype=ftype,
+ min_ghosts=cache_ghosts,
+ known_vars=known_vars, **extra_parameters)
+
+ global_size = codegen.get_global_size(work_size=work_size,
+ work_load=work_load, local_work_size=local_work_size)
+
+ usable_cache_bytes_per_wg = clCharacterize.usable_local_mem_size(device)
+ if codegen.required_workgroup_cache_size(local_work_size[:dim])[2] > \
+ usable_cache_bytes_per_wg:
+ raise KernelGenerationError('Insufficient device cache.')
+
+ ## generate source code and build kernel
+ src = codegen.__str__()
+ src_hash = hashlib.sha512(src).hexdigest()
+ prg = cl_env.build_raw_src(src, build_opts,
+ kernel_name=name,
+ force_verbose=force_verbose, force_debug=force_debug)
+ kernel = prg.all_kernels()[0]
+
+ if return_codegen:
+ return (codegen, kernel, kernel_args, src_hash, global_size)
+ else:
+ return (kernel, kernel_args, src_hash, global_size)
+
+ ## Kernel Autotuner
+ name = DirectionalAdvectionKernel.codegen_name(ftype, False, rk_scheme, 0,
+ cache_ghosts)
+ autotuner = KernelAutotuner(name=name, work_dim=dim, local_work_dim=1,
+ build_opts=build_opts, autotuner_config=autotuner_config)
+ autotuner.add_filter('1d_shape_min', autotuner.min_workitems_per_direction)
+ autotuner.register_extra_parameter('is_cached', caching_options)
+ autotuner.register_extra_parameter('nparticles', nparticles_options)
+ autotuner.enable_variable_workitem_workload(
+ max_workitem_workload=max_workitem_workload)
+
+ kernel_args = [precision(1),
+ velocity[direction].base_data, np.uint64(velocity[direction].offset),
+ position.base_data, np.uint64(position.offset)]
+ kernel_args_mapping= {
+ 'dt': (0, precision),
+ 'velocity_base': (1, cl.MemoryObjectHolder),
+ 'velocity_offset': (2, np.uint64),
+ 'position_base': (3, cl.MemoryObjectHolder),
+ 'position_offset': (4, np.uint64)
+ }
+
+ (gwi, lwi, stats, work_load, extra_params) = autotuner.bench(typegen=typegen,
+ work_size=work_size, kernel_args=kernel_args,
+ kernel_generator=kernel_generator,
+ dump_src=dump_src,
+ min_local_size=min_local_size,
+ get_max_global_size=DirectionalAdvectionKernel.get_max_global_size)
+
+ (codegen, kernel, kernel_args, src_hash, global_size) = kernel_generator(
+ work_size=work_size, work_load=work_load,
+ local_work_size=lwi, kernel_args=kernel_args,
+ extra_parameters=extra_params,
+ return_codegen=True)
+
+ kernel_launcher = OpenClKernelLauncher(kernel, queue, list(gwi), list(lwi))
+
+ total_work = work_size[0]*work_size[1]*work_size[2]
+ # per_work_statistics = codegen.per_work_statistics()
+ per_work_statistics = None
+
+ cache_info = codegen.required_workgroup_cache_size(lwi)
+
+ return (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistics, cache_info)
+
+
+if __name__ == '__main__':
+ from hysop.backend.device.opencl import cl
+ from hysop.backend.device.codegen.base.test import _test_mesh_info, _test_typegen
+
+ work_dim=3
+ ghosts=(0,0,0)
+ vresolution=(128,64,32)
+ presolution=(1024,512,256)
+ local_size = (1024,1,1)
+ global_size = (16050,55,440)
+
+ tg = _test_typegen('float')
+ (_,vmesh_info) = _test_mesh_info('velocity_mesh_info',tg,work_dim,ghosts,vresolution)
+ (_,pmesh_info) = _test_mesh_info('position_mesh_info',tg,work_dim,ghosts,presolution)
+
+ dak = DirectionalAdvectionKernel(typegen=tg, ftype=tg.fbtype,
+ work_dim=work_dim,
+ rk_scheme=ExplicitRungeKutta('RK2'),
+ boundary=BoundaryCondition.PERIODIC,
+ is_cached=True,
+ min_ghosts=10,
+ nparticles=4,
+ symbolic_mode=True,
+ known_vars=dict(
+ velocity_mesh_info=vmesh_info,
+ position_mesh_info=pmesh_info,
+ local_size=local_size[:work_dim],
+ global_size=global_size[:work_dim]
+ )
+ )
+ dak.edit()
+ dak.test_compile()
+
+
diff --git a/hysop/backend/device/codegen/kernels/directional_remesh.py b/hysop/backend/device/codegen/kernels/directional_remesh.py
new file mode 100644
index 0000000000000000000000000000000000000000..562e1ada679c8d4d0b17ee7339bda70762e9eb27
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/directional_remesh.py
@@ -0,0 +1,1245 @@
+
+import contextlib
+from contextlib import contextmanager
+
+from hysop.deps import math, operator, hashlib
+
+from hysop import __VERBOSE__, __KERNEL_DEBUG__
+from hysop.backend.device.opencl import cl
+
+from hysop.tools.misc import Utils
+from hysop.tools.types import check_instance
+
+from hysop.deps import np
+from hysop.constants import DirectionLabels, BoundaryCondition, Backend
+from hysop.core.arrays.all import OpenClArray
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, \
+ CodegenVectorClBuiltin, CodegenArray
+from hysop.backend.device.opencl import cl, clTools
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+from hysop.backend.device.codegen.base.variables import CodegenStruct
+from hysop.backend.device.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
+
+from hysop.backend.device.opencl import cl, clCharacterize
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.kernel_autotuner import KernelAutotuner, AutotunerFlags, \
+ KernelGenerationError
+
+from hysop.fields.continuous import Field
+from hysop.fields.discrete import DiscreteField
+from hysop.core.arrays.all import OpenClArrayBackend
+from hysop.numerics.remesh.remesh import RemeshKernel
+from hysop.constants import DirectionLabels
+
+from hysop.backend.device.codegen.functions.directional_remesh import DirectionalRemeshFunction
+
+class DirectionalRemeshKernel(KernelCodeGenerator):
+
+ @staticmethod
+ def codegen_name(work_dim,
+ remesh_kernel, ftype,
+ nparticles, nscalars,
+ remesh_criteria_eps,
+ use_atomics, is_inplace):
+ inplace = 'inplace_' if is_inplace else ''
+ atomic = 'atomic_' if use_atomics else ''
+ criteria = '{}eps__'.format(remesh_criteria_eps) if (remesh_criteria_eps is not None) else 'full'
+ return 'directional_{}{}remesh_{}d__lambda_{}_{}__{}__{}p__{}s__{}'.format(
+ inplace, atomic, work_dim,
+ remesh_kernel.n, remesh_kernel.r, ftype,
+ nparticles, nscalars,
+ criteria)
+
+ @classmethod
+ def scalars_out_cache_ghosts(cls, scalar_cfl, remesh_kernel):
+ assert scalar_cfl > 0
+ assert remesh_kernel.n % 2 == 0
+ min_ghosts = int(1+np.floor(scalar_cfl)+remesh_kernel.n/2)
+ return min_ghosts
+
+ @classmethod
+ def min_wg_size(cls, work_dim, scalar_cfl, remesh_kernel):
+ size = [1]*work_dim
+ min_ghosts = cls.scalars_out_cache_ghosts(scalar_cfl, remesh_kernel)
+ size[0] = 2*min_ghosts+1
+ return np.asarray(size)
+
+ @classmethod
+ def get_max_global_size(cls, work_size, work_load, nparticles, **kargs):
+ """
+ Return global_work_size from effective work_size without
+ taking into account local_work_size alignment
+ """
+ work_size = np.asarray(work_size).copy()
+ work_load = np.asarray(work_load).copy()
+
+ assert work_load[0] == 1
+ work_load[0] = nparticles
+
+ global_size = work_size.copy()
+ global_size = ((global_size+work_load-1)/work_load)
+ return global_size
+
+ def get_global_size(self, work_size, local_work_size, work_load=None):
+ """
+ Return global_work_size from effective work_size and given local_work_size
+ global_work_size will be a multiple of local_work_size
+ """
+ work_dim = self.work_dim
+ work_load = [1]*work_dim if (work_load is None) else work_load
+
+ work_size = np.asarray(work_size)
+ work_load = np.asarray(work_load)
+ local_work_size = np.asarray(local_work_size)
+
+ nparticles = self.nparticles
+
+ for i in xrange(1,work_dim):
+ assert (local_work_size[i] == 1), 'local_work_size error!'
+
+ if 'local_size' in self.known_vars:
+ assert (self.known_vars['local_size'] == local_work_size[:work_dim]).all(),\
+ 'local_work_size mismatch!'
+
+ max_global_size = self.get_max_global_size(work_size, work_load, nparticles)
+ global_size = ((max_global_size+local_work_size-1)/local_work_size) * local_work_size
+ global_size[0] = local_work_size[0]
+
+ return global_size
+
+ def required_workgroup_cache_size(self, local_work_size):
+ """
+ Return a tuple of required (static,dynamic,total) cache bytes per workgroup
+ """
+ work_dim = self.work_dim
+ ftype = self.ftype
+ flt_bytes = self.typegen.FLT_BYTES[ftype]
+
+ local_work_size = np.asarray(local_work_size)
+
+ sc,dc = 0,0
+ count = self.nscalars*(self.nparticles*local_work_size[0]+2*self.min_ghosts)
+ if self.is_periodic:
+ count += 2*self.nscalars*self.min_ghosts
+ if self.local_size_known:
+ assert (self.known_vars['local_size'] == local_work_size[:work_dim]).all()
+ sc += count
+ else:
+ dc += count
+
+ sc *= flt_bytes
+ dc *= flt_bytes
+ tc = sc+dc
+
+ return (sc,dc,tc)
+
+
+ def __init__(self, typegen, work_dim, ftype,
+ nparticles, nscalars, sboundary, is_inplace,
+ scalar_cfl, remesh_kernel,
+ group_scalars=None,
+ remesh_criteria_eps=None,
+ use_atomics = False,
+ symbolic_mode = False,
+ debug_mode = False,
+ known_vars = None):
+
+ assert work_dim>0 and work_dim<=3
+ assert nscalars>0
+ assert nparticles in [1,2,4,8,16]
+ check_instance(sboundary,tuple,values=BoundaryCondition)
+ check_instance(remesh_kernel, RemeshKernel)
+
+ group_scalars = group_scalars or tuple(1 for _ in xrange(nscalars))
+ check_instance(group_scalars, tuple, values=int)
+ assert sum(group_scalars) == nscalars
+ nfields = len(group_scalars)
+
+ assert sboundary[0] in [BoundaryCondition.PERIODIC, BoundaryCondition.NONE]
+ assert sboundary[1] in [BoundaryCondition.PERIODIC, BoundaryCondition.NONE]
+ is_periodic = (sboundary[0]==BoundaryCondition.PERIODIC \
+ and sboundary[1]==BoundaryCondition.PERIODIC)
+
+ known_vars = known_vars or dict()
+ local_size_known = ('local_size' in known_vars)
+
+ itype = 'int'
+ vftype = typegen.vtype(ftype, nparticles)
+ vitype = typegen.vtype(itype, nparticles)
+
+ name = DirectionalRemeshKernel.codegen_name(work_dim,
+ remesh_kernel, ftype,
+ nparticles, nscalars, remesh_criteria_eps,
+ use_atomics, is_inplace)
+
+ kernel_reqs = self.build_requirements(typegen, work_dim, itype, ftype,
+ sboundary, nparticles, nscalars, nfields, group_scalars,
+ symbolic_mode, is_periodic,
+ remesh_criteria_eps, use_atomics, remesh_kernel,
+ known_vars, debug_mode)
+
+ kernel_args = self.gen_kernel_arguments(typegen, work_dim, itype, ftype,
+ nparticles, nscalars, nfields, group_scalars, local_size_known, is_inplace,
+ debug_mode, kernel_reqs)
+
+ super(DirectionalRemeshKernel,self).__init__(
+ name=name,
+ typegen=typegen,
+ work_dim=work_dim,
+ kernel_args=kernel_args,
+ known_vars=known_vars,
+ vec_type_hint=ftype,
+ symbolic_mode=symbolic_mode)
+
+ self.update_requirements(kernel_reqs)
+
+ self.min_ghosts = self.scalars_out_cache_ghosts(scalar_cfl, remesh_kernel)
+ self.itype = itype
+ self.ftype = ftype
+ self.vitype = vitype
+ self.vftype = vftype
+ self.work_dim = work_dim
+ self.sboundary = sboundary
+ self.nparticles = nparticles
+ self.nscalars = nscalars
+ self.nfields = nfields
+ self.group_scalars = group_scalars
+ self.local_size_known = local_size_known
+ self.is_periodic = is_periodic
+ self.is_inplace = is_inplace
+ self.use_atomics = use_atomics
+ self.remesh_kernel = remesh_kernel
+ self.debug_mode = debug_mode
+
+ self.gencode()
+
+ def build_requirements(self, typegen, work_dim, itype, ftype,
+ sboundary, nparticles, nscalars, nfields, group_scalars, symbolic_mode, is_periodic,
+ remesh_criteria_eps, use_atomics, remesh_kernel,
+ known_vars, debug_mode):
+ reqs = WriteOnceDict()
+
+ mesh_base_struct = MeshBaseStruct(typegen=typegen, typedef='MeshBase_s')
+ reqs['MeshBaseStruct'] = mesh_base_struct
+
+ mesh_info_struct = MeshInfoStruct(typegen=typegen, typedef='MeshInfo_s')
+ reqs['MeshInfoStruct'] = mesh_info_struct
+
+ # without atomics we can only remesh on particle at a time
+ nparticles_remeshed = nparticles if use_atomics else 1
+ reqs['remesh'] = DirectionalRemeshFunction(typegen=typegen, work_dim=work_dim,
+ itype=itype, ftype=ftype, nparticles=nparticles_remeshed, nscalars=nscalars,
+ sboundary=sboundary, remesh_kernel=remesh_kernel, use_atomics=use_atomics,
+ remesh_criteria_eps=remesh_criteria_eps, debug_mode=debug_mode)
+
+ return reqs
+
+ def gen_kernel_arguments(self, typegen, work_dim, itype, ftype,
+ nparticles, nscalars, nfields, group_scalars, local_size_known, is_inplace,
+ debug_mode, kernel_reqs):
+
+ kargs = ArgDict()
+ self.position = OpenClArrayBackend.build_codegen_argument(kargs, name='position',
+ storage=self._global, ctype=ftype, typegen=typegen,
+ ptr_restrict=True, const=True)
+
+ scalars_in = []
+ for i in xrange(nfields):
+ args_in = []
+ for j in xrange(group_scalars[i]):
+ if is_inplace:
+ arg = OpenClArrayBackend.build_codegen_argument(kargs, name='S{}_{}_inout'.format(i,j),
+ storage=self._global, ctype=ftype, typegen=typegen,
+ const=False, ptr_restrict=True)
+ else:
+ arg = OpenClArrayBackend.build_codegen_argument(kargs, name='S{}_{}_in'.format(i,j),
+ storage=self._global, ctype=ftype, typegen=typegen,
+ const=True, ptr_restrict=True)
+ args_in.append(arg)
+ scalars_in.append(tuple(args_in))
+ scalars_in = tuple(scalars_in)
+
+ if is_inplace:
+ scalars_out = scalars_in
+ else:
+ scalars_out = []
+ for i in xrange(nfields):
+ args_out = []
+ for j in xrange(group_scalars[i]):
+ arg_out = OpenClArrayBackend.build_codegen_argument(kargs, name='S{}_{}_out'.format(i,j),
+ storage=self._global, ctype=ftype, typegen=typegen,
+ const=False, ptr_restrict=True)
+ args_out.append(arg_out)
+ scalars_out.append(tuple(args_out))
+ scalars_out = tuple(scalars_out)
+
+ self.scalars_in = scalars_in
+ self.scalars_out = scalars_out
+
+ if debug_mode:
+ kargs['dbg0'] = CodegenVariable(storage=self._global,name='dbg0',ctype=itype,
+ typegen=typegen, ptr_restrict=True,ptr=True,const=False,add_impl_const=True)
+ kargs['dbg1'] = CodegenVariable(storage=self._global,name='dbg1',ctype=itype,
+ typegen=typegen, ptr_restrict=True,ptr=True,const=False,add_impl_const=True)
+
+ kargs['position_mesh_info'] = kernel_reqs['MeshInfoStruct'].build_codegen_variable(
+ const=True, name='position_mesh_info')
+
+ if is_inplace:
+ for i in xrange(nfields):
+ kargs['S{}_inout_mesh_info'.format(i)] = \
+ kernel_reqs['MeshInfoStruct'].build_codegen_variable(
+ const=True, name='S{}_inout_mesh_info'.format(i), nl=True)
+ else:
+ for i in xrange(nfields):
+ kargs['S{}_in_mesh_info'.format(i)] = \
+ kernel_reqs['MeshInfoStruct'].build_codegen_variable(
+ const=True, name='S{}_in_mesh_info'.format(i), nl=True)
+ for i in xrange(nfields):
+ kargs['S{}_out_mesh_info'.format(i)] = \
+ kernel_reqs['MeshInfoStruct'].build_codegen_variable(
+ const=True, name='S{}_out_mesh_info'.format(i), nl=True)
+
+ if not local_size_known:
+ kargs['buffer'] = CodegenVariable(storage=self._local, ctype=ftype,
+ add_impl_const=True, name='buffer', ptr=True, ptr_restrict=True,
+ typegen=typegen, nl=False)
+
+ return kargs
+
+ def gencode(self):
+ s = self
+ tg = s.typegen
+
+ dim = s.work_dim
+ itype = s.itype
+ ftype = s.ftype
+ vitype = s.vitype
+ vftype = s.vftype
+ sboundary = s.sboundary
+ nparticles = s.nparticles
+ nscalars = s.nscalars
+ nfields = s.nfields
+ min_ghosts = s.min_ghosts
+ is_inplace = s.is_inplace
+ use_atomics = s.use_atomics
+ work_dim = s.work_dim
+ debug_mode = s.debug_mode
+
+ symbolic_mode = s.symbolic_mode
+ group_scalars = s.group_scalars
+
+ is_periodic = s.is_periodic
+ local_size_known = s.local_size_known
+
+ global_id = s.vars['global_id']
+ local_id = s.vars['local_id']
+ group_id = s.vars['group_id']
+
+ global_index = s.vars['global_index']
+ local_index = s.vars['local_index']
+
+ global_size = s.vars['global_size']
+ local_size = s.vars['local_size']
+
+ if debug_mode:
+ dbg0 = s.vars['dbg0']
+ dbg1 = s.vars['dbg1']
+
+ position_mesh_info = s.vars['position_mesh_info']
+
+ if is_inplace:
+ scalars_mesh_info_in = [s.vars['S{}_inout_mesh_info'.format(i)] for i in xrange(nfields)]
+ scalars_mesh_info_out = scalars_mesh_info_in
+ else:
+ scalars_mesh_info_in = [s.vars['S{}_in_mesh_info'.format(i)] for i in xrange(nfields)]
+ scalars_mesh_info_out = [s.vars['S{}_out_mesh_info'.format(i)] for i in xrange(nfields)]
+
+ position_base = s.vars['position_base']
+ position_offset = s.vars['position_offset']
+
+ position = s.position
+ scalars_in = s.scalars_in
+ scalars_out = s.scalars_out
+
+ compute_grid_size = position_mesh_info['local_mesh']['compute_resolution'].view(
+ 'compute_grid_size',slice(None,work_dim),const=True)
+
+ position_grid_size = position_mesh_info['local_mesh']['resolution'].view(
+ 'pos_grid_size', slice(0,work_dim), const=True)
+ position_grid_ghosts = position_mesh_info['ghosts'].view(
+ 'pos_grid_ghosts', slice(0,work_dim), const=True)
+ position_global_id = CodegenVectorClBuiltin('pos_gid', itype, work_dim, typegen=tg)
+
+ dx = position_mesh_info['dx'].view('dx', slice(0,1), const=True)
+ inv_dx = position_mesh_info['inv_dx'].view('inv_dx', slice(0,1), const=True)
+ xmin = position_mesh_info['local_mesh']['xmin'].view('xmin', slice(0,1), const=True)
+
+ if is_inplace:
+ scalars_in_grid_size = tuple(smi['local_mesh']['resolution'].view(
+ 'S{}_inout_grid_size'.format(i), slice(0,work_dim), const=True)
+ for (i,smi) in enumerate(scalars_mesh_info_out))
+ scalars_in_grid_ghosts = tuple(smi['ghosts'].view(
+ 'S{}_inout_grid_ghosts'.format(i),slice(0,work_dim), const=True)
+ for (i,smi) in enumerate(scalars_mesh_info_out))
+
+ scalars_in_global_id = tuple(CodegenVectorClBuiltin('S{}_inout_gid'.format(i),
+ itype, work_dim, typegen=tg) for i in xrange(nfields))
+
+ scalars_out_grid_size = scalars_in_grid_size
+ scalars_out_grid_ghosts = scalars_in_grid_ghosts
+ scalars_out_global_id = scalars_in_global_id
+
+ grid_ghosts = (position_grid_ghosts,) + scalars_in_grid_ghosts
+ grid_sizes = (position_grid_size,) + scalars_in_grid_size
+ global_ids = (position_global_id,) + scalars_in_global_id
+ else:
+ scalars_in_grid_size = tuple(smi['local_mesh']['resolution'].view(
+ 'S{}_in_grid_size'.format(i), slice(0,work_dim), const=True)
+ for (i,smi) in enumerate(scalars_mesh_info_in))
+ scalars_out_grid_size = tuple(smi['local_mesh']['resolution'].view(
+ 'S{}_out_grid_size'.format(i), slice(0,work_dim), const=True)
+ for (i,smi) in enumerate(scalars_mesh_info_out))
+
+ scalars_in_grid_ghosts = tuple(smi['ghosts'].view('S{}_in_grid_ghosts'.format(i),
+ slice(0,work_dim), const=True) for (i,smi) in enumerate(scalars_mesh_info_in))
+ scalars_out_grid_ghosts = tuple(smi['ghosts'].view('S{}_out_grid_ghosts'.format(i),
+ slice(0,work_dim), const=True) for (i,smi) in enumerate(scalars_mesh_info_out))
+
+ scalars_in_global_id = tuple(CodegenVectorClBuiltin('S{}_in_gid'.format(i),
+ itype, work_dim, typegen=tg) for i in xrange(nfields))
+ scalars_out_global_id = tuple(CodegenVectorClBuiltin('S{}_out_gid'.format(i),
+ itype, work_dim, typegen=tg) for i in xrange(nfields))
+
+ grid_ghosts = (position_grid_ghosts,) + scalars_in_grid_ghosts + \
+ scalars_out_grid_ghosts
+ grid_sizes = (position_grid_size,) + scalars_in_grid_size + scalars_out_grid_size
+ global_ids = (position_global_id,) + scalars_in_global_id + scalars_out_global_id
+
+ s.update_vars(position=position,
+ inv_dx=inv_dx,
+ position_grid_ghosts=position_grid_ghosts, compute_grid_size=compute_grid_size)
+ s.update_vars(**dict((sij.name,sij) for si in scalars_in for sij in si))
+ if not is_inplace:
+ s.update_vars(**dict((sij.name,sij) for si in scalars_out for sij in si))
+
+
+ npart = CodegenVariable(name='nparticles', ctype=itype, typegen=tg, value=nparticles)
+
+ cache_ghosts = CodegenVariable('cache_ghosts', itype, typegen=tg,
+ value=min_ghosts,
+ symbolic_mode=symbolic_mode)
+ cache_width = CodegenVariable('cache_width', itype, typegen=tg,
+ init='{}*{} + 2*{}'.format(npart, local_size[0], cache_ghosts))
+
+ local_work = CodegenVariable('lwork', 'int', tg, const=True,
+ init='{}*{}'.format(nparticles,local_size[0]))
+
+ local_offset = CodegenVariable('local_offset',itype,tg)
+ line_offset = CodegenVariable('line_offset',itype,tg)
+ particle_offset = CodegenVariable('particle_offset',itype,tg)
+
+ def _line_init(base_ptr, global_id, grid_size):
+ if work_dim > 1:
+ _id = '{}'.format(global_id[-1])
+ for i in xrange(work_dim-2, 0, -1):
+ _id = '({})$*{} $+ {}'.format(_id,grid_size[work_dim-i-1], global_id[i])
+ _id = ' $+ ({})$*{}'.format(_id, grid_size[0])
+ else:
+ _id=''
+ _id += ' $+ ({} $- {})'.format(global_id[0], particle_offset)
+ return '{}{}'.format(base_ptr, _id)
+
+ line_position = position.newvar('line_position',
+ init=_line_init(position, position_global_id, position_grid_size))
+
+ line_scalars_in = []
+ line_scalars_out = []
+ for (Si, Si_global_id, Si_grid_size) in \
+ zip(scalars_in, scalars_in_global_id, scalars_in_grid_size):
+ Li = []
+ for Sij in Si:
+ lij = Sij.newvar('line_{}'.format(Sij.name),
+ init=_line_init(Sij, Si_global_id, Si_grid_size))
+ Li.append(lij)
+ line_scalars_in.append(tuple(Li))
+ for (Si, Si_global_id, Si_grid_size) in \
+ zip(scalars_out, scalars_out_global_id, scalars_out_grid_size):
+ Li = []
+ for Sij in Si:
+ lij = Sij.newvar('line_{}'.format(Sij.name),
+ init=_line_init(Sij, Si_global_id, Si_grid_size))
+ Li.append(lij)
+ line_scalars_out.append(tuple(Li))
+ line_scalars_in = tuple(line_scalars_in)
+ line_scalars_out = tuple(line_scalars_out)
+
+ line_vars = ((line_position,),) + line_scalars_in
+ if not is_inplace:
+ line_vars += line_scalars_out
+
+ cached_scalars = []
+ boundary_scalars = []
+ if local_size_known:
+ L = s.known_vars['local_size']
+ for i in xrange(nfields):
+ Si = []
+ BSi = []
+ for j in xrange(group_scalars[i]):
+ Sij = CodegenArray(name='S{}_{}'.format(i,j),
+ dim=1, ctype=ftype, typegen=tg,
+ shape=(nparticles*L[0]+2*min_ghosts,), storage=self._local)
+ Si.append(Sij)
+
+ if is_periodic:
+ BSij = CodegenArray(name='boundary_S{}_{}'.format(i,j),
+ dim=1, ctype=ftype, typegen=tg,
+ shape=(2*min_ghosts,), storage=self._local)
+ BSi.append(BSij)
+ cached_scalars.append(tuple(Si))
+ if is_periodic:
+ boundary_scalars.append(tuple(BSi))
+ else:
+ buf = self.vars['buffer']
+ k=0
+ for i in xrange(nfields):
+ Si = []
+ BSi = []
+ for j in xrange(group_scalars[i]):
+ Sij = CodegenVariable(name='S{}_{}'.format(i,j),ctype=ftype,typegen=tg,
+ ptr_restrict=True, ptr=True, storage=self._local,
+ ptr_const=True,
+ init='{} + {}*{}'.format(buf,k,cache_width))
+ Si.append(Sij)
+
+ if is_periodic:
+ BSij = CodegenVariable(name='boundary_S{}_{}'.format(i,j), ctype=ftype, typegen=tg,
+ ptr_restrict=True, ptr=True, storage=self._local,
+ ptr_const=True,
+ init='{} + {}*{} + 2*{}*{}'.format(buf, nscalars, cache_width, k, min_ghosts))
+ BSi.append(BSij)
+ k+=1
+ cached_scalars.append(tuple(Si))
+ if is_periodic:
+ boundary_scalars.append(tuple(BSi))
+ cache_scalars = tuple(cached_scalars)
+ boundary_scalars = tuple(boundary_scalars)
+
+ pos = CodegenVectorClBuiltin('p', ftype, nparticles, tg)
+ scalars = []
+ for i in xrange(nfields):
+ si = []
+ for j in xrange(group_scalars[i]):
+ sij = CodegenVectorClBuiltin('s{}_{}'.format(i,j), ftype, nparticles, tg)
+ si.append(sij)
+ scalars.append(tuple(si))
+ scalars = tuple(scalars)
+
+
+ vzero = CodegenVectorClBuiltin('vzero', ftype, nparticles, tg,
+ value=np.zeros(shape=(nparticles,), dtype=np.float64))
+
+ kmax = CodegenVariable('kmax', itype, tg, const=True,
+ init='(({}+{lwork}-1)/{lwork})'.format(
+ compute_grid_size[0], lwork=local_work))
+
+ loopvars = 'kji'
+ first = CodegenVariable('first', 'bool', tg, const=True, init='({}==0)'.format(loopvars[0]))
+ last = CodegenVariable('last', 'bool', tg, const=True, init='({}=={}-1)'.format(loopvars[0],kmax))
+ active = CodegenVariable('active','bool', tg, const=True)
+ last_active = CodegenVariable('last_active','bool', tg, const=True)
+
+ last_particle = CodegenVariable('last_particle', itype, tg, const=True,
+ init='{} - {}*({}-1)*{}'.format(compute_grid_size[0], nparticles, kmax, local_size[0]))
+
+ @contextlib.contextmanager
+ def _work_iterate_(i):
+ try:
+ if i==0:
+ fval = '0'
+ gsize = '1'
+ N = kmax
+ ghosts = '({}-{})'.format(position_grid_ghosts[i],cache_ghosts)
+ else:
+ fval = global_id.fval(i)
+ gsize = global_size[i]
+ N = '{Sx}'.format(Sx=compute_grid_size[i])
+ ghosts = position_grid_ghosts[i]
+
+ if i==0:
+ s.append('#pragma unroll 8')
+ with s._for_('int {i}={fval}; {i}<{N}; {i}+={gsize}'.format(
+ i=loopvars[i], fval=fval, gsize=gsize,N=N)) as ctx:
+
+ if i==0:
+ with s._align_() as al:
+ line_offset.declare(al, align=True, const=True, init='{}*{}'.format(
+ loopvars[0], local_work))
+ local_offset.declare(al, align=True, const=True, init='{}*{}'.format(
+ nparticles,local_id[0]))
+ particle_offset.declare(al, align=True, const=True, init='{} + {}'.format(
+ line_offset, local_offset))
+ s.jumpline()
+ with s._align_() as al:
+ first.declare(al, align=True)
+ last.declare(al, align=True)
+ active.declare(al, init='({} < {})'.format(particle_offset,
+ compute_grid_size[0]), align=True)
+ last_active.declare(al, init='{} && ({}+{}-1 >= {})'.format(active, particle_offset,
+ nparticles, compute_grid_size[0]), align=True)
+ elif i==1:
+ kmax.declare(s)
+ last_particle.declare(s)
+ s.jumpline()
+
+ if i>0:
+ with s._align_() as al:
+ for field_gid, field_ghosts in zip(global_ids, grid_ghosts) :
+ al.append('{} $= {} $+ {};'.format(field_gid[i],
+ loopvars[i], field_ghosts[i]))
+ al.jumpline()
+ yield ctx
+ except:
+ raise
+
+ # when compute_grid_size is not a multiple of nparticles,
+ # we need to go back to scalars load/store for the last particles.
+ def if_last_thread_active(cond=None):
+ cond = last_active if (cond is None) else cond
+ with s._if_(cond):
+ with s._align_() as al:
+ for j in xrange(nparticles):
+ cond = '({}+{}$ < {})'.format(particle_offset, j, compute_grid_size[0])
+ yield al, cond, j
+
+ @contextlib.contextmanager
+ def if_thread_active(not_first=False):
+ if not_first:
+ cond = '(!{}) && {}'.format(first, active)
+ else:
+ cond = active
+ with s._elif_(cond):
+ yield
+
+ def if_first_or_last_thread_active():
+ if is_periodic and is_inplace and nparticles==1:
+ cond= '{} || ({} && ({}>=2*{}))'.format(last_active, first, local_id[0], cache_ghosts)
+ else:
+ cond= '{} || {}'.format(last_active, first)
+ return if_last_thread_active(cond)
+
+ with s._kernel_():
+ s.jumpline()
+
+ vars_ = ((position,),)+scalars_in
+ if not is_inplace:
+ vars_ += scalars_out
+ s.decl_aligned_vars(*tuple(vij for vi in vars_ for vij in vi))
+
+ s.decl_aligned_vars(local_id, global_size, local_size, const=True)
+
+ s.decl_aligned_vars(xmin, inv_dx, dx, const=True)
+
+ s.decl_aligned_vars(npart, cache_ghosts, cache_width, local_work, const=True)
+
+ s.decl_aligned_vars(vzero, const=True)
+
+ s.decl_vars(compute_grid_size)
+ s.jumpline()
+
+ s.decl_aligned_vars(*grid_sizes)
+ s.decl_aligned_vars(*grid_ghosts)
+
+ for vargroup in cached_scalars:
+ s.decl_vars(*vargroup)
+ if is_periodic:
+ for vargroup in boundary_scalars:
+ s.decl_vars(*vargroup)
+ s.jumpline()
+
+ s.decl_vars(*global_ids)
+
+ with s._align_() as al:
+ s.decl_vars(pos, *tuple(sij for si in scalars for sij in si), align=True, codegen=al)
+ s.jumpline()
+
+
+ nested_loops = [_work_iterate_(i) for i in xrange(dim-1,-1,-1)]
+ if work_dim==1:
+ kmax.declare(s)
+ last_particle.declare(s)
+ with contextlib.nested(*nested_loops):
+
+ s.comment('Compute global offsets and line pointers')
+ with s._align_() as al:
+ position_global_id.affect(al, i=0, align=True,
+ init='{} + {}'.format(particle_offset, position_grid_ghosts[0]))
+ if not is_inplace:
+ for _gid, _ghosts in zip(scalars_in_global_id, scalars_in_grid_ghosts):
+ _gid.affect(al, i=0, align=True,
+ init='{} + {}'.format(particle_offset, _ghosts[0]))
+ for _gid, _ghosts in zip(scalars_out_global_id, scalars_out_grid_ghosts):
+ _gid.affect(al, i=0, align=True,
+ init='{} + {} - {}'.format(particle_offset, _ghosts[0],
+ cache_ghosts if not is_periodic else 0))
+ s.jumpline()
+ s.decl_aligned_vars(*(lvij for lvi in line_vars for lvij in lvi))
+
+ s.comment('Get back left cache from right cache')
+ with s._if_('({} < 2*{})'.format(local_id[0], cache_ghosts)):
+ with s._if_('{}'.format(first)):
+ with s._align_() as al:
+ for csi in cached_scalars:
+ for csij in csi:
+ csij.affect(al, align=True,
+ i=local_id[0],
+ init=tg.dump(+0.0))
+ with s._else_():
+ end_id='{}+{}'.format(local_work, local_id[0])
+ if debug_mode:
+ s.append('printf("%i loaded back %f from position %i.\\n", {}, {}, {});'.format(local_id[0], cached_scalars[0][0][end_id], end_id))
+ with s._align_() as al:
+ for csi in cached_scalars:
+ for csij in csi:
+ csij.affect(al, align=True,
+ i='{}'.format(local_id[0]),
+ init=csij[end_id])
+ s.jumpline()
+
+
+ s.comment('Fill right cache with zeros, excluding left ghosts')
+ for al, active_cond, k in if_last_thread_active():
+ for csi in cached_scalars:
+ for csij in csi:
+ offset = '{}+2*{}+${}'.format(local_offset, cache_ghosts, k)
+ store = s.vstore(1, csij, offset, vzero[k], align=True,
+ suppress_semicolon=True)
+ code = '{} $&& ({});'.format(active_cond, store)
+ al.append(code)
+ with if_thread_active():
+ for csi in cached_scalars:
+ for csij in csi:
+ offset = '{}+2*{}'.format(local_offset, cache_ghosts)
+ s.append(s.vstore(nparticles, csij, offset, vzero))
+ s.jumpline()
+
+ s.comment('Load position and scalars at current index, {} particles at a time.'.format(nparticles))
+ for al, active_cond, k in if_last_thread_active():
+ load = self.vload(1, line_position, '{}+{}'.format(particle_offset,k), align=True)
+ code = '{} $= ({} $? {} $: {});'.format(pos[k], active_cond, load, tg.dump(0.0))
+ al.append(code)
+ if is_inplace and not is_periodic:
+ _id = '{}+{}+{}'.format(particle_offset, cache_ghosts, k)
+ else:
+ _id = '{}+{}'.format(particle_offset, k)
+ for si, line_si in zip(scalars, line_scalars_in):
+ for sij, line_sij in zip(si, line_si):
+ load = self.vload(1, line_sij, _id, align=True)
+ code = '{} $= ({} $? {} $: {});'.format(sij[k], active_cond, load, tg.dump(0.0))
+ al.append(code)
+
+ with if_thread_active():
+ with s._align_() as al:
+ pos.affect(al, align=True,
+ init=self.vload(nparticles, line_position, particle_offset, align=True))
+
+ if is_inplace and not is_periodic:
+ _id = '{}+{}'.format(particle_offset, cache_ghosts)
+ else:
+ _id = particle_offset
+ for si, line_si in zip(scalars, line_scalars_in):
+ for sij, line_sij in zip(si, line_si):
+ sij.affect(al, align=True,
+ init=self.vload(nparticles, line_sij, _id, align=True))
+ s.barrier(_local=True)
+ s.jumpline()
+
+
+ s.comment('Remesh scalars in cache.')
+ remesh = s.reqs['remesh']
+ remesh_kargs = {
+ 'dx':dx,
+ 'inv_dx':inv_dx,
+ 'cache_ghosts': cache_ghosts,
+ 'active': active,
+ 'line_offset': line_offset
+ }
+
+ k=0
+ for ci in cached_scalars:
+ for cij in ci:
+ remesh_kargs['S{}'.format(k)] = cij
+ k+=1
+ if is_periodic:
+ remesh_kargs['grid_size'] = compute_grid_size[0]
+
+ if use_atomics:
+ # with atomic summation in cache, we can remesh everything at a time
+ remesh_kargs['p'] = pos
+ k=0
+ for si in scalars:
+ for sij in si:
+ remesh_kargs['s{}'.format(k)] = sij
+ k+=1
+ call = remesh(**remesh_kargs)
+ s.append('{};'.format(call))
+ else:
+ # without atomics we can only remesh on particle at a time
+ for p in xrange(nparticles):
+ remesh_kargs['p'] = pos[p]
+ k=0
+ for si in scalars:
+ for sij in si:
+ remesh_kargs['s{}'.format(k)] = sij[p]
+ k+=1
+ call = remesh(**remesh_kargs)
+ s.append('{};'.format(call))
+
+ s.jumpline()
+
+
+ s.comment('Store back remeshed scalars to global memory')
+ for al, active_cond, k in if_first_or_last_thread_active():
+ for si, li in zip(cached_scalars, line_scalars_out):
+ for sij, lij in zip(si, li):
+ load = self.vload(1, sij, '{}+{}'.format(local_offset, k))
+ if is_periodic:
+ _id = '({}+{}+{}-{})%{}'.format(particle_offset, compute_grid_size[0], k, cache_ghosts, compute_grid_size[0])
+ else:
+ _id = '{}+{}'.format(particle_offset, k)
+ store = self.vstore(1, lij, _id, load, align=True, jmp=True, suppress_semicolon=True)
+ code = '{} $&& ({})'.format(active_cond, store)
+ if debug_mode:
+ code += ' && (printf("last_active %i wrote %2.2f from cache position %i to global id %i.\\n", {},{},{},{}));'.format(
+ local_id[0], load, '{}+{}'.format(local_offset,k), _id)
+ else:
+ code += ';'
+ al.append(code)
+ with if_thread_active(not_first=True):
+ with s._align_() as al:
+ if debug_mode:
+ s.append('printf("%i wrote {vnf} from cache position %i to global id %i.\\n", {},{},{},{});'.format(
+ local_id[0],
+ self.vload(nparticles, cached_scalars[0], local_offset),
+ local_offset, particle_offset if not is_periodic else '({}+{}-{})%{}'.format(particle_offset, compute_grid_size[0], cache_ghosts, compute_grid_size[0]),
+ vnf='[%2.2v{}f]'.format(nparticles) if nparticles>1 else '%2.2f'))
+ for ci, li in zip(cached_scalars, line_scalars_out):
+ for cij, lij in zip(ci, li):
+ load = self.vload(nparticles, cij, '{}'.format(local_offset))
+ if is_periodic:
+ _id = '({}+{}-{})%{}'.format(particle_offset, compute_grid_size[0], cache_ghosts, compute_grid_size[0])
+ else:
+ _id = particle_offset
+ store = self.vstore(nparticles, lij, _id, load, align=True, jmp=True)
+ al.append(store)
+
+ if is_periodic:
+ s.jumpline()
+ _id = '({}+{}-{}+{})%{}'.format(particle_offset, compute_grid_size[0], cache_ghosts, '{}', compute_grid_size[0])
+ with s._if_('{} && ({} < 2*{})'.format(first, local_id[0], cache_ghosts)):
+ with s._align_() as al:
+ for ci, bci in zip(cached_scalars, boundary_scalars):
+ for cij, bcij in zip(ci, bci):
+ load = cij[local_id[0]]
+ store = bcij.affect(al, align=True, i=local_id[0], init=load)
+ s.jumpline()
+
+ with s._if_('{} && ({} < 2*{})'.format(last, local_id[0], cache_ghosts)):
+ if is_periodic:
+ offset = '{}+{}-{}+{}'.format(line_offset, last_particle, cache_ghosts, local_id[0])
+ _gid = '({}+{})%{}'.format(offset, compute_grid_size[0], compute_grid_size[0])
+ with s._align_() as al:
+ for ci, bci, li in zip(cached_scalars, boundary_scalars, line_scalars_out):
+ for cij, bcij, lij in zip(ci,bci,li):
+ val0 = bcij[local_id[0]]
+ val1 = cij['{}+{}'.format(last_particle, local_id[0])]
+ code = '{} $= {}+{};'.format(lij[_gid], val0, val1)
+ al.append(code)
+ if debug_mode:
+ s.append('printf("%i initiated last write of value %2.2f + %2.2f = %2.2f from cache position %i+%i=%i to global id %i+%i-%i+%i=%i.\\n", {}, {},{},{}, {},{},{}, {},{},{},{},{});'.format(
+ local_id[0],
+ val0, val1, '{}+{}'.format(val0,val1),
+ last_particle, local_id[0], '{}+{}'.format(last_particle, local_id[0]),
+ line_offset, last_particle, cache_ghosts, local_id[0],
+ _gid))
+ else:
+ with s._align_() as al:
+ _gid = '{}+{}+{}'.format(line_offset, last_particle, local_id[0])
+ for ci, li in zip(cached_scalars, line_scalars_out):
+ for cij, lij in zip(ci,li):
+ init=cij['{}+{}'.format(last_particle, local_id[0])]
+ lij.affect(i=_gid, init=init, align=True, codegen=al)
+ if debug_mode:
+ s.append('printf("%i initiated last write from cache position %i+%i=%i to global id %i+%i+%i=%i.\\n", {}, {},{},{},{}, {},{},{});'.format(
+ local_id[0],
+ last_particle, local_id[0],
+ '{}+{}'.format(last_particle, local_id[0]),
+ line_offset, last_particle, local_id[0],
+ '{}+{}+{}'.format(line_offset, last_particle, local_id[0])))
+ s.barrier(_local=True)
+
+
+ @staticmethod
+ def autotune(cl_env, precision, direction, scalar_cfl,
+ remesh_kernel, remesh_criteria_eps,
+ position, scalars_in, scalars_out,
+ scalars_in_mesh_info, scalars_out_mesh_info, is_inplace,
+ autotuner_config, build_opts,
+ force_atomics=False, relax_min_particles=False,
+ dump_src=False, symbolic_mode=False):
+
+ check_instance(position, dict, keys=OpenClArray, values=CodegenStruct)
+ position_mesh_info = position.values()[0]
+ position = position.keys()[0]
+
+ ftype = clTools.dtype_to_ctype(precision)
+ domain = scalars_in.keys()[0].domain
+ dim = domain.dimension
+
+ if dim<0 or dim>3:
+ raise ValueError('Dimension mismatch...')
+ if direction<0 or direction>=dim:
+ raise ValueError('Direction mismatch...')
+ if (force_atomics and relax_min_particles):
+ msg= 'Cannot relax min particles when force_atomics is set because '
+ msg+='there is no minimum particles to be used when using atomic accumulators.'
+ raise ValueError(msg)
+
+ check_instance(cl_env, OpenClEnvironment)
+ device = cl_env.device
+ context = cl_env.context
+ platform = cl_env.platform
+ queue = cl_env.queue
+ typegen = cl_env.typegen
+
+ if context is None:
+ raise ValueError('context cannot be None.')
+ if device is None:
+ raise ValueError('device cannot be None.')
+ if platform is None:
+ raise ValueError('platform cannot be None.')
+ if queue is None:
+ raise ValueError('queue cannot be None.')
+ if not isinstance(typegen, OpenClTypeGen):
+ raise ValueError('typegen should be a OpenClTypeGen')
+ if typegen.platform!=platform or typegen.device!=device:
+ raise ValueError('platform or device mismatch between typegen and cl_env.')
+
+ if (scalars_in.keys()!=scalars_out.keys()):
+ extra_fields = set(scalars_in.keys()) ^ set(scalars_out.keys())
+ print 'Missing input or output for fields:'
+ for field in extra_fields:
+ print ' *field {}'.format(field.name)
+ raise RuntimeError('Unmatched scalar input or output.')
+
+ for scalars, mesh_infos in zip((scalars_in, scalars_out),
+ (scalars_in_mesh_info, scalars_out_mesh_info)):
+ for field in scalars.keys():
+ dfield = scalars[field]
+ mesh_info = mesh_infos[field]
+ if not isinstance(field, Field):
+ msg='{} is not a Field.'.format(field.name)
+ if not isinstance(dfield,DiscreteField):
+ msg='{} is not a DiscreteField'.format(dfield.name)
+ raise ValueError(msg)
+ if dfield.backend.kind != Backend.OPENCL:
+ msg='{} is not a DiscreteField defined on an OPENCL backend.'
+ msg=msg.format(dfield.name)
+ raise ValueError(msg)
+ if (dfield.domain != domain):
+ msg='{} domain mismatch with reference one.'.format(dfield.name)
+ raise ValueError(msg)
+ if not isinstance(mesh_info, CodegenStruct):
+ msg='{} mesh info is not a CodegenStruct.'
+ msg=msg.format(dfield.name)
+ raise ValueError(msg)
+ if not mesh_info.known():
+ msg='{} mesh info is not a known CodegenStruct dfieldiable.'
+ msg=msg.format(dfield.name)
+ raise ValueError(msg)
+ if is_inplace:
+ for field in scalars_in:
+ dfield_in = scalars_in[field]
+ dfield_out = scalars_out[field]
+ if dfield_in != dfield_out:
+ msg='Remeshing inplace but input and output discrete Field differs '
+ msg+='for {} and {}.'.format(dfield_in.name, dfield_out.name)
+ raise RuntimeError(msg)
+
+ group_scalars = tuple(dfield.nb_components for dfield in scalars_in.values())
+ nfields = len(group_scalars)
+ nscalars = sum(group_scalars)
+
+ p_resolution = position_mesh_info['local_mesh']['compute_resolution'].value[:dim]
+ p_lboundary = position_mesh_info['local_mesh']['lboundary'].value[:dim]
+ p_rboundary = position_mesh_info['local_mesh']['rboundary'].value[:dim]
+ p_ghosts = position_mesh_info['ghosts'].value[:dim]
+ p_dx = position_mesh_info['dx'].value[:dim]
+
+ scalars_mesh_info = scalars_in_mesh_info.values()[0]
+ s_resolution = scalars_mesh_info['local_mesh']['compute_resolution'].value[:dim]
+ s_lboundary = scalars_mesh_info['local_mesh']['lboundary'].value[:dim]
+ s_rboundary = scalars_mesh_info['local_mesh']['rboundary'].value[:dim]
+ s_dx = scalars_mesh_info['dx'].value[:dim]
+
+ sboundary = (s_lboundary[0], s_rboundary[0])
+
+ min_s_ghosts = DirectionalRemeshKernel.scalars_out_cache_ghosts(scalar_cfl,
+ remesh_kernel)
+ min_wg_size = DirectionalRemeshKernel.min_wg_size(dim, scalar_cfl,
+ remesh_kernel)
+
+ min_nparticles = 2 if relax_min_particles else int(2*np.ceil(scalar_cfl))
+ assert (min_s_ghosts>=1)
+ assert (min_nparticles>=2)
+
+ if not cl_env.is_multi_device:
+ if s_lboundary[0] == BoundaryCondition.PERIODIC:
+ assert p_lboundary[0] == BoundaryCondition.PERIODIC
+ assert p_rboundary[0] == BoundaryCondition.PERIODIC
+ assert s_rboundary[0] == BoundaryCondition.PERIODIC
+ min_s_ghosts = 0
+
+ for scalars_mesh_info in scalars_in_mesh_info.values()\
+ +scalars_out_mesh_info.values():
+ _s_resolution = scalars_mesh_info['local_mesh']['compute_resolution']\
+ .value[:dim]
+ _s_lboundary = scalars_mesh_info['local_mesh']['lboundary'].value[:dim]
+ _s_rboundary = scalars_mesh_info['local_mesh']['rboundary'].value[:dim]
+ _s_dx = scalars_mesh_info['dx'].value[:dim]
+ assert (_s_resolution == s_resolution).all()
+ assert (_s_lboundary == s_lboundary).all()
+ assert (_s_rboundary == s_rboundary).all()
+ assert (_s_dx == s_dx).all()
+
+ for scalars_mesh_info in scalars_out_mesh_info.values():
+ _s_ghosts = scalars_mesh_info['ghosts'].value[:dim]
+ if (_s_ghosts[0] < min_s_ghosts):
+ msg= 'Given boundary condition implies minimum ghosts numbers to be at '
+ msg+='least {} in current direction for output scalar but only {} ghosts '
+ msg+='are present in the grid for scalar {}.'
+ msg=msg.format(min_s_ghosts, s_ghosts[0], scalar.name)
+ raise ValueError(msg)
+
+ is_multi_scale = (s_resolution[0] != p_resolution[0])
+ if is_multi_scale:
+ msg='Resolution mismatch between particles and scalars, '
+ msg+='got {} and {}, cannot remesh.'
+ msg=msg.format(p_resolution, s_resolution)
+ raise ValueError(msg)
+
+ # work size is the resolution without ghosts
+ work_size = np.ones(3,dtype=np.int32)
+ work_size[:dim] = p_resolution
+
+ # autotuner parameters
+
+ dump_src = dump_src or __KERNEL_DEBUG__
+ symbolic_mode = symbolic_mode or __KERNEL_DEBUG__
+
+ min_simd_group_size = [1]*dim
+ min_simd_group_size[0] = clCharacterize.get_simd_group_size(device,1)
+ min_local_size = np.maximum(min_wg_size, min_simd_group_size)
+
+ nparticles_options = [1,2,4,8,16]
+ use_atomics_options = [True] if force_atomics else [False, True]
+
+ autotuner_flag = autotuner_config.autotuner_flag
+ if (autotuner_flag == AutotunerFlags.ESTIMATE):
+ max_workitem_workload = [1,1,1]
+ elif (autotuner_flag == AutotunerFlags.MEASURE):
+ max_workitem_workload = [1,8,1]
+ elif (autotuner_flag == AutotunerFlags.PATIENT):
+ max_workitem_workload = [1,8,8]
+ elif (autotuner_flag == AutotunerFlags.EXHAUSTIVE):
+ max_workitem_workload = [1,16,16]
+
+ max_workitem_workload = np.asarray(max_workitem_workload)
+ max_workitem_workload[dim:] = 1
+
+ ## Compile time known variables
+ known_vars = {}
+ kernel_args = []
+ kernel_args_mapping = {}
+
+ varname='position'
+ kernel_args_mapping[varname+'_base'] = (0, cl.MemoryObjectHolder)
+ kernel_args_mapping[varname+'_offset'] = (1, np.uint64)
+ kernel_args.append(position.base_data)
+ kernel_args.append(np.uint64(position.offset))
+ known_vars[varname+'_mesh_info'] = position_mesh_info
+
+ k=0
+ if is_inplace:
+ it = zip(('_inout',), (scalars_in,),(scalars_in_mesh_info,))
+ else:
+ it = zip(('_in','_out'),
+ (scalars_in, scalars_out),
+ (scalars_in_mesh_info, scalars_out_mesh_info))
+ for (postfix, scalars, mesh_infos) in it:
+ for i,scalar in enumerate(scalars.keys()):
+ dscalar = scalars[scalar]
+ mesh_info = mesh_infos[scalar]
+ assert dscalar.nb_components == group_scalars[i]
+ base_varname='S{}'.format(i)
+ for j in xrange(dscalar.nb_components):
+ varname='{}_{}{}'.format(base_varname,j,postfix)
+ kernel_args_mapping[varname+'_base'] = (2+2*k+0, cl.MemoryObjectHolder)
+ kernel_args_mapping[varname+'_offset'] = (2+2*k+1, np.uint64)
+ kernel_args.append(dscalar[j].base_data)
+ kernel_args.append(np.uint64(dscalar[j].offset))
+ k+=1
+ known_vars[base_varname+postfix+'_mesh_info'] = mesh_info
+ assert k==(2-is_inplace)*nscalars
+
+ ## kernel generator
+ def kernel_generator(work_size, work_load, local_work_size,
+ kernel_args,
+ extra_parameters,
+ force_verbose=False, force_debug=False,
+ return_codegen = False,
+ **kargs):
+
+ _nparticles = extra_parameters['nparticles']
+ _use_atomics = extra_parameters['use_atomics']
+
+ if (not _use_atomics) and (_nparticles < min_nparticles):
+ msg='Insufficient number of particles, min={}, got {}.'
+ msg=msg.format(min_nparticles, _nparticles)
+ raise KernelGenerationError(msg)
+
+ ## Compile time known variables
+ known_vars['local_size'] = local_work_size[:dim]
+
+ ## CodeGenerator
+ name = DirectionalRemeshKernel.codegen_name(dim,
+ remesh_kernel, ftype,
+ _nparticles, nscalars, remesh_criteria_eps,
+ _use_atomics, is_inplace)
+
+ codegen = DirectionalRemeshKernel(typegen=typegen,
+ work_dim=dim, ftype=ftype,
+ nparticles=_nparticles, nscalars=nscalars,
+ sboundary=sboundary, is_inplace=is_inplace,
+ scalar_cfl=scalar_cfl, remesh_kernel=remesh_kernel,
+ group_scalars=group_scalars,
+ remesh_criteria_eps=remesh_criteria_eps,
+ use_atomics = _use_atomics,
+ symbolic_mode = symbolic_mode,
+ debug_mode = False,
+ known_vars = known_vars)
+ global_size = codegen.get_global_size(work_size=work_size,
+ local_work_size=local_work_size, work_load=work_load)
+
+ usable_cache_bytes_per_wg = clCharacterize.usable_local_mem_size(device)
+ if codegen.required_workgroup_cache_size(local_work_size[:dim])[2] > \
+ usable_cache_bytes_per_wg:
+ raise KernelGenerationError('Insufficient device cache.')
+
+ ## generate source code and build kernel
+ src = codegen.__str__()
+ src_hash = hashlib.sha512(src).hexdigest()
+ prg = cl_env.build_raw_src(src, build_opts,
+ kernel_name=name,
+ force_verbose=force_verbose, force_debug=force_debug)
+ kernel = prg.all_kernels()[0]
+
+ if return_codegen:
+ return (codegen, kernel, kernel_args, src_hash, global_size)
+ else:
+ return (kernel, kernel_args, src_hash, global_size)
+
+ ## Kernel Autotuner
+ name = DirectionalRemeshKernel.codegen_name(dim,
+ remesh_kernel, ftype,
+ 1, nscalars, remesh_criteria_eps,
+ force_atomics, is_inplace)
+ autotuner = KernelAutotuner(name=name, work_dim=dim, local_work_dim=1,
+ build_opts=build_opts, autotuner_config=autotuner_config)
+ autotuner.add_filter('1d_shape_min', autotuner.min_workitems_per_direction)
+ autotuner.register_extra_parameter('use_atomics', use_atomics_options)
+ autotuner.register_extra_parameter('nparticles', nparticles_options)
+ autotuner.enable_variable_workitem_workload(
+ max_workitem_workload=max_workitem_workload)
+
+ (gwi, lwi, stats, work_load, extra_params) = autotuner.bench(typegen=typegen,
+ work_size=work_size,
+ kernel_generator=kernel_generator,
+ kernel_args=kernel_args,
+ dump_src=dump_src,
+ min_local_size=min_local_size,
+ get_max_global_size=DirectionalRemeshKernel.get_max_global_size)
+
+ (codegen, kernel, kernel_args, src_hash, global_size) = kernel_generator(
+ work_size=work_size, work_load=work_load,
+ local_work_size=lwi, kernel_args=kernel_args,
+ extra_parameters=extra_params,
+ return_codegen=True)
+
+ kernel_launcher = OpenClKernelLauncher(kernel, queue, list(gwi), list(lwi))
+
+ total_work = work_size[0]*work_size[1]*work_size[2]
+ # per_work_statistics = codegen.per_work_statistics()
+ per_work_statistics = None
+
+ cache_info = codegen.required_workgroup_cache_size(lwi)
+
+ return (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistics, cache_info)
+
+
+
+if __name__ == '__main__':
+ from hysop.backend.device.opencl import cl
+ from hysop.backend.device.codegen.base.test import _test_mesh_info, _test_typegen
+ from hysop.numerics.remesh.remesh import RemeshKernel
+
+ kernel = RemeshKernel(2,2)
+
+ work_dim=3
+ ghosts=(0,0,0)
+ sresolution =(1024,512,256)
+ local_size = (1024,1,1)
+ global_size = (16050,55,440)
+
+ tg = _test_typegen('float')
+ (_,smesh_info) = _test_mesh_info('scalars_mesh_info',tg,work_dim,ghosts,sresolution)
+ (_,pmesh_info) = _test_mesh_info('position_mesh_info',tg,work_dim,ghosts,sresolution)
+
+ scalar_cfl = 1.5
+
+ dak = DirectionalRemeshKernel(typegen=tg, ftype=tg.fbtype,
+ work_dim=work_dim,
+ nparticles=4,
+ nscalars=1,
+ remesh_kernel=kernel,
+ scalar_cfl=scalar_cfl,
+ use_atomics=True,
+ is_inplace=False,
+ symbolic_mode=False,
+ debug_mode=False,
+ sboundary=(BoundaryCondition.PERIODIC, BoundaryCondition.PERIODIC),
+ known_vars=dict(
+ S0_in_mesh_info=smesh_info,
+ S1_in_mesh_info=smesh_info,
+ S0_out_mesh_info=smesh_info,
+ S1_out_mesh_info=smesh_info,
+ position_mesh_info=pmesh_info,
+ local_size=local_size[:work_dim],
+ global_size=global_size[:work_dim]
+ )
+ )
+
+ print 'scalars_out_min_gosts = {}'.format(dak.scalars_out_cache_ghosts(scalar_cfl, kernel))
+ print 'required cache: {}'.format(dak.required_workgroup_cache_size(local_size))
+
+ dak.edit()
+ dak.test_compile()
+
diff --git a/hysop/backend/device/codegen/kernels/directional_stretching.py b/hysop/backend/device/codegen/kernels/directional_stretching.py
new file mode 100644
index 0000000000000000000000000000000000000000..96363a696b4dc43f73b5f8b45fa172c30ba392ac
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/directional_stretching.py
@@ -0,0 +1,953 @@
+
+from hysop.deps import np, operator, hashlib, contextlib
+
+from hysop import __VERBOSE__, __KERNEL_DEBUG__
+
+from hysop.tools.misc import Utils
+from hysop.tools.types import check_instance
+
+from hysop.constants import DirectionLabels, BoundaryCondition, Backend, SpaceDiscretization
+from hysop.methods import StretchingFormulation
+from hysop.fields.discrete import DiscreteField
+
+from hysop.backend.device.opencl import clTools
+
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, \
+ CodegenVectorClBuiltin, CodegenArray
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+from hysop.backend.device.codegen.base.variables import CodegenStruct
+from hysop.backend.device.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
+
+from hysop.backend.device.codegen.functions.compute_index import ComputeIndexFunction
+from hysop.backend.device.codegen.functions.cache_load import CacheLoadFunction
+from hysop.backend.device.codegen.functions.runge_kutta import RungeKuttaFunction
+from hysop.backend.device.codegen.functions.stretching_rhs \
+ import DirectionalStretchingRhsFunction
+
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta
+
+from hysop.backend.device.opencl import cl, clCharacterize
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.kernel_autotuner import KernelAutotuner, AutotunerFlags, \
+ KernelGenerationError
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
+
+class DirectionalStretchingKernel(KernelCodeGenerator):
+
+ @staticmethod
+ def codegen_name(ftype,is_cached,is_inplace,direction,formulation):
+ inplace ='inplace_' if is_inplace else ''
+ cache = 'cached_' if is_cached else ''
+ sformulation = str(formulation).lower()
+ return 'directional_{}{}stretching_{}_{}{}'.format(cache,inplace,sformulation,
+ ftype[0],DirectionLabels[direction])
+
+ def __init__(self, typegen, dim, ftype, order, direction,
+ is_cached, is_inplace,
+ boundary, formulation, time_integrator,
+ symbolic_mode = False,
+ known_vars = None):
+
+ check_instance(formulation, StretchingFormulation)
+ check_instance(boundary[0], BoundaryCondition)
+ check_instance(boundary[1], BoundaryCondition)
+ check_instance(time_integrator,ExplicitRungeKutta)
+ check_instance(is_inplace, bool)
+
+ assert dim==3
+ assert direction<dim
+ assert order>1 and order%2==0
+ assert boundary[0] in [BoundaryCondition.NONE,BoundaryCondition.PERIODIC]
+ assert boundary[1] in [BoundaryCondition.NONE,BoundaryCondition.PERIODIC]
+
+ if known_vars is None:
+ known_vars = {}
+
+ local_size_known = ('local_size' in known_vars)
+ is_conservative = (formulation==StretchingFormulation.CONSERVATIVE)
+ is_periodic = (boundary[0]==BoundaryCondition.PERIODIC) \
+ and (boundary[1]==BoundaryCondition.PERIODIC)
+
+ if is_cached:
+ storage = OpenClCodeGenerator.default_keywords['local']
+ else:
+ storage = OpenClCodeGenerator.default_keywords['global']
+
+ if is_inplace and is_conservative and not is_cached:
+ raise ValueError('Inplace conservetive stretching requires caching.')
+
+ name = DirectionalStretchingKernel.codegen_name(ftype,is_cached,is_inplace,
+ direction,formulation)
+
+ kernel_reqs = self.build_requirements(typegen, dim, ftype, order, is_cached,
+ time_integrator, direction, boundary, symbolic_mode, formulation, storage,
+ is_periodic, is_inplace)
+
+ kernel_args = self.gen_kernel_arguments(typegen, dim, ftype, kernel_reqs, is_cached,
+ is_inplace, local_size_known)
+
+ super(DirectionalStretchingKernel,self).__init__(
+ name=name,
+ typegen=typegen,
+ work_dim=dim,
+ kernel_args=kernel_args,
+ known_vars=known_vars,
+ vec_type_hint=ftype,
+ symbolic_mode=symbolic_mode)
+
+ self.update_requirements(kernel_reqs)
+
+ self.order = order
+ self.ftype = ftype
+ self.direction = direction
+ self.dim = dim
+ self.boundary = boundary
+ self.time_integrator = time_integrator
+ self.formulation = formulation
+ self.storage = storage
+ self.local_size_known = local_size_known
+
+ self.is_conservative = is_conservative
+ self.is_periodic = is_periodic
+ self.is_cached = is_cached
+ self.is_inplace = is_inplace
+
+ self.gencode()
+
+ #return minimal number of ghosts required on the grid
+ # for input velocity and vorticity.
+ @staticmethod
+ def min_ghosts(boundary, formulation, order, time_integrator, direction):
+ (lboundary, rboundary) = boundary
+ u_ghosts = [0]*3
+ if (lboundary == BoundaryCondition.PERIODIC) and \
+ (rboundary == BoundaryCondition.PERIODIC):
+ pass
+ elif lboundary in [BoundaryCondition.NONE, BoundaryCondition.PERIODIC]:
+ stencil_ghost = order/2
+ if formulation == StretchingFormulation.CONSERVATIVE:
+ u_ghosts[direction] = time_integrator.stages * stencil_ghost
+ else:
+ u_ghosts[direction] = stencil_ghost
+ else:
+ raise ValueError('Unknown lboundary {}.'.format(lboundary))
+ if (formulation == StretchingFormulation.CONSERVATIVE):
+ # div(u x w)
+ w_ghosts = u_ghosts
+ else:
+ # (a*grad(u) + (1-a)*grad(u)^T) w
+ w_ghosts = [0]*3
+ return np.asarray(u_ghosts), np.asarray(w_ghosts)
+
+ @staticmethod
+ def min_wg_size(formulation, order, time_integrator):
+ ghosts = [1]*3
+ stencil_ghost = order/2
+ if formulation == StretchingFormulation.CONSERVATIVE:
+ ghosts[0] = time_integrator.stages * stencil_ghost
+ else:
+ ghosts[0] = stencil_ghost
+ ghosts[0]*=4
+ return np.asarray(ghosts)
+
+ #return global_work_size from effective work_size without
+ # taking into account local_work_size alignment
+ @staticmethod
+ def get_max_global_size(work_size, work_load, **kargs):
+ work_size = np.asarray(work_size)
+ work_load = np.asarray(work_load)
+ assert work_load[0] == 1
+
+ global_size = work_size.copy()
+ global_size = ((global_size+work_load-1)/work_load)
+ return global_size
+
+ #return global_work_size from effective work_size and given local_work_size
+ # global_work_size will be a multiple of local_work_size
+ def get_global_size(self, work_size, local_work_size, work_load=[1,1,1]):
+ work_size = np.asarray(work_size)
+ work_load = np.asarray(work_load)
+ local_work_size = np.asarray(local_work_size)
+ v_min_ghosts, w_min_ghosts = self._min_ghosts()
+
+ assert (local_work_size[1] == 1) and (local_work_size[2]==1)
+ assert (local_work_size > 2*w_min_ghosts).all()
+
+ if 'local_size' in self.known_vars:
+ assert (self.known_vars['local_size'] == local_work_size).all()
+ if 'velocity_mesh_info' in self.known_vars and (not self.is_periodic):
+ velocity_mesh_info = self.known_vars['velocity_mesh_info'].value
+ vghosts = velocity_mesh_info['ghosts'][:3]
+ assert (vghosts>=v_min_ghosts).all()
+ if 'vorticity_mesh_info' in self.known_vars and (not self.is_periodic):
+ vorticity_mesh_info = self.known_vars['vorticity_mesh_info'].value
+ wghosts = vorticity_mesh_info['ghosts'][:3]
+ assert (wghosts>=w_min_ghosts).all()
+
+ max_global_size = self.get_max_global_size(work_size, work_load)
+ max_global_size[0] = local_work_size[0]
+ global_size = ((max_global_size+local_work_size-1)/local_work_size) * local_work_size
+
+ return global_size
+
+ #return a tuple of required (static,dynamic,total) cache bytes per workgroup
+ def required_workgroup_cache_size(self, local_work_size):
+ dim = self.work_dim
+ ftype = self.ftype
+ is_cached = self.is_cached
+ direction = self.direction
+ cache_ghosts = self._cache_ghosts()
+ is_periodic = self.is_periodic
+ is_conservative = self.is_conservative
+ flt_bytes = self.typegen.FLT_BYTES[ftype]
+
+ local_work_size = np.asarray(local_work_size)
+
+ sc,dc = 0,0
+ if is_cached:
+ count = dim*local_work_size[0]
+ if is_conservative:
+ count += local_work_size[0]
+
+ if 'local_size' in self.known_vars:
+ assert (self.known_vars['local_size'] == local_work_size).all()
+ sc += count
+ else:
+ dc += count
+
+ sc += 2*dim*(2*cache_ghosts)
+ if self.is_periodic:
+ sc += 2*dim*(2*cache_ghosts)
+
+ sc *= flt_bytes
+ dc *= flt_bytes
+ tc = sc+dc
+
+ return (sc,dc,tc)
+
+ def _cache_ghosts(self):
+ stencil_ghost = self.order/2
+ if self.is_conservative:
+ return self.time_integrator.stages * stencil_ghost
+ else:
+ return stencil_ghost
+ def _min_ghosts(self):
+ return self.min_ghosts(self.boundary, self.formulation,
+ self.order, self.time_integrator, self.direction)
+
+
+ def build_requirements(self,typegen,work_dim,ftype,order,is_cached,time_integrator,direction,
+ boundary,force_symbolic,formulation,storage,is_periodic,is_inplace):
+ tg=typegen
+ reqs = WriteOnceDict()
+
+ compute_id = ComputeIndexFunction(typegen=typegen, dim=work_dim, itype='int',
+ wrap=is_periodic)
+ reqs['compute_id'] = compute_id
+
+ mesh_base_struct = MeshBaseStruct(typegen=typegen, typedef='MeshBase_s')
+ reqs['MeshBaseStruct'] = mesh_base_struct
+
+ mesh_info_struct = MeshInfoStruct(typegen=typegen, typedef='MeshInfo_s')
+ reqs['MeshInfoStruct'] = mesh_info_struct
+
+ stretching_rhs = DirectionalStretchingRhsFunction(typegen=typegen, dim=work_dim,
+ ftype=ftype, cached=is_cached,
+ order=order, direction=direction, boundary=boundary,
+ formulation=formulation,
+ ptr_restrict=True, vectorize_u=False,
+ itype='int')
+
+ used_vars = RungeKuttaFunction._default_used_vars.copy()
+ used_vars['y']='W'
+ used_vars['step']='rk_step'
+ runge_kutta = RungeKuttaFunction(typegen=tg, ftype=ftype,
+ method=time_integrator,
+ rhs=stretching_rhs,
+ used_vars=used_vars,
+ known_args=None)
+ reqs['runge_kutta'] = runge_kutta
+
+ return reqs
+
+ def gen_kernel_arguments(self, typegen, work_dim, ftype, requirements,is_cached,is_inplace,
+ local_size_known):
+
+ xyz = 'xyz'
+ svelocity = 'U'
+ svorticity = 'W'
+
+ kargs = ArgDict()
+ kargs['dt'] = CodegenVariable(ctype=ftype,name='dt',typegen=typegen,
+ add_impl_const=True,nl=True)
+
+ _global = OpenClCodeGenerator.default_keywords['global']
+ _local = OpenClCodeGenerator.default_keywords['local']
+ for i in xrange(work_dim):
+ name = svelocity+xyz[i]
+ kargs[name] = CodegenVariable(storage=_global,name=name,typegen=typegen,
+ ctype=ftype,ptr=True,ptr_restrict=True,const=True,add_impl_const=True)
+
+ for i in xrange(work_dim):
+ name = svorticity+xyz[i]+'_in'
+ kargs[name] = CodegenVariable(storage=_global,name=name,typegen=typegen,
+ ctype=ftype,ptr=True,ptr_restrict=(not is_inplace),const=True,add_impl_const=True)
+
+ for i in xrange(work_dim):
+ name = svorticity+xyz[i]+'_out'
+ kargs[name] = CodegenVariable(storage=_global,name=name,typegen=typegen,
+ ctype=ftype,ptr=True,ptr_restrict=(not is_inplace),const=False,add_impl_const=True)
+
+ kargs['velocity_mesh_info'] = \
+ requirements['MeshInfoStruct'].build_codegen_variable(const=True,
+ name='velocity_mesh_info')
+ kargs['vorticity_mesh_info'] = \
+ requirements['MeshInfoStruct'].build_codegen_variable(const=True,
+ name='vorticity_mesh_info')
+
+ if is_cached and not local_size_known:
+ kargs['buffer'] = CodegenVariable(storage=_local,ctype=ftype,
+ add_impl_const=True, name='buffer', ptr=True, ptr_restrict=True,
+ typegen=typegen, nl=False)
+
+ self.svorticity = svorticity
+ self.svelocity = svelocity
+ self.xyz = xyz
+
+ return kargs
+
+ def gencode(self):
+ s = self
+ tg = s.typegen
+
+ direction = s.direction
+ work_dim = s.work_dim
+ dim = s.dim
+ ftype = s.ftype
+ boundary = s.boundary
+ is_cached = s.is_cached
+ storage = s.storage
+
+ symbolic_mode = s.symbolic_mode
+
+ formulation = s.formulation
+ is_conservative = s.is_conservative
+ is_periodic = s.is_periodic
+ local_size_known = s.local_size_known
+
+ xyz = s.xyz
+ vtype = tg.vtype(ftype,work_dim)
+
+ global_id = s.vars['global_id']
+ local_id = s.vars['local_id']
+ group_id = s.vars['group_id']
+
+ global_index = s.vars['global_index']
+ local_index = s.vars['local_index']
+
+ global_size = s.vars['global_size']
+ local_size = s.vars['local_size']
+
+ dt = s.vars['dt']
+ velocity_mesh_info = s.vars['velocity_mesh_info']
+ vorticity_mesh_info = s.vars['vorticity_mesh_info']
+
+ grid_size = vorticity_mesh_info['local_mesh']['resolution'].view(
+ 'grid_size', slice(None,dim))
+ compute_grid_size = vorticity_mesh_info['local_mesh']['compute_resolution'].view(
+ 'compute_grid_size',slice(None,dim))
+ compute_grid_ghosts = vorticity_mesh_info['ghosts'].view(
+ 'compute_grid_ghosts', slice(0,dim), const=True)
+ inv_dx = vorticity_mesh_info['inv_dx'].view(
+ 'inv_dx', slice(0,1), const=True)
+ s.update_vars(grid_size=grid_size, inv_dx=inv_dx,
+ compute_grid_ghosts=compute_grid_ghosts, compute_grid_size=compute_grid_size)
+
+ compute_index = self.reqs['compute_id']
+ runge_kutta = self.reqs['runge_kutta']
+
+ W = CodegenVectorClBuiltin('W',ftype,dim,tg)
+ U = CodegenVectorClBuiltin('U',ftype,dim,tg)
+
+ first = CodegenVariable('first','bool',tg,init='true')
+ active = CodegenVariable('active','bool',tg, const=True)
+
+ cache_ghosts = CodegenVariable('cache_ghosts','int',tg,
+ const=True,value=self._cache_ghosts())
+ local_work = CodegenVariable('lwork','int',tg,const=True)
+
+ cached_vars = ArgDict()
+ if is_cached:
+ for i in xrange(work_dim):
+ Vi = self.svelocity+self.xyz[i]
+ if local_size_known:
+ Vic = CodegenArray(name=Vi+'c',dim=1,ctype=ftype,typegen=tg,
+ shape=(local_size.value[0],), storage=storage)
+ else:
+ buf = s.vars['buffer']
+ init = '{} + {}*{}'.format(buf(), i, local_size[0])
+ Vic = CodegenVariable(storage=storage,name=Vi+'c',ctype=ftype,typegen=tg,
+ const=True, ptr_restrict=True,ptr=True,init=init)
+ cached_vars[Vi] = Vic
+
+ if is_conservative:
+ Wi = self.svorticity+self.xyz[direction]
+ if local_size_known:
+ Wic = CodegenArray(storage=storage,name=Wi+'c',dim=1,ctype=ftype,
+ typegen=tg,shape=(local_size.value[0],))
+ else:
+ buf = s.vars['buffer']
+ init = '{} + {}*{}'.format(buf(), work_dim, local_size[0])
+ Wic = CodegenVariable(storage=storage,name=Wi+'c',ctype=ftype,typegen=tg,
+ const=True, ptr_restrict=True,ptr=True,init=init)
+ cached_vars[Wi] = Wic
+
+ _U = self.svelocity
+ size = cache_ghosts.value
+ Ur = CodegenArray(storage='__local',name=_U+'r',dim=1,ctype=vtype,typegen=tg,
+ shape=(2*size,))
+ _W = self.svorticity
+ size = cache_ghosts.value
+ Wr = CodegenArray(storage='__local',name=_W+'r',dim=1,ctype=vtype,typegen=tg,
+ shape=(2*size,))
+ if is_periodic:
+ Ul = CodegenArray(storage='__local',name=_U+'l',dim=1,ctype=vtype,typegen=tg,
+ shape=(2*size,))
+ Wl = CodegenArray(storage='__local',name=_W+'l',dim=1,ctype=vtype,typegen=tg,
+ shape=(2*size,))
+
+
+ @contextlib.contextmanager
+ def _work_iterate_(i):
+ try:
+ if i==0:
+ fval = '0'
+ gsize = local_work()
+ N = '(({}+2*{}+{lwork}-1)/{lwork})*{lwork}'.format(compute_grid_size[i],
+ cache_ghosts(),lwork=local_work())
+ ghosts = '({}-{})'.format(compute_grid_ghosts[i],cache_ghosts())
+ else:
+ fval = global_id.fval(i)
+ gsize = global_size[i]
+ N = '{Sx}'.format(Sx=compute_grid_size[i])
+ ghosts = compute_grid_ghosts[i]
+
+ s.append('#pragma unroll 8')
+ with s._for_('int {i}={fval}; {i}<{N}; {i}+={gsize}'.format(
+ i='kji'[i], fval=fval, gsize=gsize,N=N)) as ctx:
+
+ if i==0:
+ s.append('{} = {}+{};'.format(global_id[i], 'kji'[i], local_id[0]))
+ else:
+ s.append('{} = {}+{};'.format(global_id[i], 'kji'[i], ghosts))
+
+ if i==0:
+ active.declare(s, init='({} < {}+2*{})'.format(
+ global_id[0], compute_grid_size[0], cache_ghosts()))
+ s.append('{} += {};'.format(global_id[i], ghosts))
+ elif i==1:
+ first.declare(s)
+
+ yield ctx
+ except:
+ raise
+ nested_loops = [_work_iterate_(i) for i in xrange(dim-1,-1,-1)]
+
+ @contextlib.contextmanager
+ def if_thread_active():
+ with s._if_('{}'.format(active())):
+ yield
+
+ with s._kernel_():
+ s.jumpline()
+ with s._align_() as al:
+ local_id.declare(al,align=True,const=True)
+ global_size.declare(al,align=True,const=True)
+ local_size.declare(al,align=True,const=True)
+ s.jumpline()
+
+ with s._align_() as al:
+ compute_grid_size.declare(al,const=True,align=True)
+ compute_grid_ghosts.declare(al,align=True)
+ grid_size.declare(al,align=True,const=True)
+ inv_dx.declare(al,align=True)
+ s.jumpline()
+
+ with s._align_() as al:
+ cache_ghosts.declare(al,align=True)
+ local_work.declare(al,align=True,
+ init='{} - 2*{}'.format(local_size[0],cache_ghosts()))
+ s.jumpline()
+
+ if is_cached:
+ with s._align_() as al:
+ for varname,var in cached_vars.iteritems():
+ var.declare(al,align=True)
+ s.jumpline()
+
+ Ur.declare(s)
+ Wr.declare(s)
+ s.jumpline()
+
+ if is_periodic:
+ Ul.declare(s)
+ Wl.declare(s)
+ s.jumpline()
+
+ s.jumpline()
+
+ global_id.declare(s,init=False)
+ s.jumpline()
+
+ with contextlib.nested(*nested_loops):
+ s.jumpline()
+ init = compute_index(idx=global_id, size=grid_size)
+ global_index.declare(s, init=init, const=True)
+
+ winit, uinit = '',''
+ for i in xrange(work_dim):
+ Wi_in = self.svorticity+self.xyz[i]+'_in'
+ Wi_out = self.svorticity+self.xyz[i]+'_out'
+ Ui = self.svelocity+self.xyz[i]
+ uinit += self.args[Ui][global_index()] + ','
+ winit += self.args[Wi_in][global_index()] + ','
+ uinit='({}{})({})'.format(ftype, work_dim, uinit[:-1])
+ winit='({}{})({})'.format(ftype, work_dim, winit[:-1])
+
+
+ s.jumpline()
+ s.append('{} {},{};'.format(U.ctype,U(),W()))
+ with if_thread_active():
+ with s._if_('{}'.format(first())):
+ s.append('{} = {};'.format(U(), uinit))
+ s.append('{} = {};'.format(W(), winit))
+ s.append('{} = false;'.format(first()))
+ if is_periodic:
+ with s._if_('{lid} < 2*{ghosts}'.format(lid=local_id[0],
+ ghosts=cache_ghosts())):
+ s.append('{} = {};'.format(Ul[local_id[0]], U()))
+ s.append('{} = {};'.format(Wl[local_id[0]], W()))
+ with s._else_():
+ if is_periodic:
+ with s._if_('{} >= {}-{}'.format(global_id[0],
+ compute_grid_size[0],cache_ghosts())):
+ _id = '{}-{}+{}'.format(global_id[0],
+ compute_grid_size[0],cache_ghosts())
+ s.append('{} = {};'.format(U(), Ul[_id]))
+ s.append('{} = {};'.format(W(), Wl[_id]))
+ with s._elif_('{} < 2*{}'.format(local_id[0],cache_ghosts())):
+ s.append('{} = {};'.format(U(), Ur[local_id[0]]))
+ s.append('{} = {};'.format(W(), Wr[local_id[0]]))
+ else:
+ with s._if_('{} < 2*{}'.format(local_id[0],cache_ghosts())):
+ s.append('{} = {};'.format(U(), Ur[local_id[0]]))
+ s.append('{} = {};'.format(W(), Wr[local_id[0]]))
+ with s._else_():
+ s.append('{} = {};'.format(U(), uinit))
+ s.append('{} = {};'.format(W(), winit))
+
+
+ s.barrier(_local=True)
+ s.jumpline()
+
+
+ with if_thread_active():
+ if self.is_cached:
+ for i in xrange(work_dim):
+ Ui = self.svelocity+self.xyz[i]
+ Uic = cached_vars[Ui]
+ code = '{} = {};'.format(Uic[local_id[0]],U[i])
+ s.append(code)
+ s.jumpline()
+
+
+ with s._if_('{} >= {}-2*{}'.format(local_id[0],local_size[0],
+ cache_ghosts())):
+ _id = '{}-{}+2*{}'.format(local_id[0],local_size[0],cache_ghosts())
+ s.append('{} = {};'.format(Ur[_id], U()))
+ s.append('{} = {};'.format(Wr[_id], W()))
+
+
+ s.barrier(_local=True)
+ s.jumpline()
+
+
+ rk_args={'dt': dt,
+ 'inv_dx': inv_dx,
+ 'W': W,
+ 'active': active,
+ 'Lx' : local_size[0],
+ 'lidx' : local_id[0]}
+
+ if is_periodic and (not is_cached):
+ base = CodegenVariable('base','int',typegen=tg,const=True)
+ base.declare(s,init='({}/{}) * {}'.format(global_index(),grid_size[0],
+ grid_size[0]))
+ offset = CodegenVariable('offset','int',typegen=tg,const=True)
+ offset.declare(s,init='{}-{}'.format(global_index(),base()))
+ rk_args['base'] = base
+ rk_args['offset'] = offset
+ rk_args['width'] = grid_size[0]
+ else:
+ rk_args['offset'] = local_id[0] if is_cached else global_index
+
+ for i in xrange(work_dim):
+ Ui_name = self.svelocity+xyz[i]
+ if is_cached:
+ Ui = cached_vars[Ui_name]
+ else:
+ Ui = s.vars[Ui_name]
+ rk_args[Ui_name] = Ui
+
+ if is_conservative:
+ Wd_name = self.svorticity+xyz[direction]
+ if is_cached:
+ Wd = cached_vars[Wd_name]
+ else:
+ Wd = s.vars[Wd_name]
+ rk_args[Wd_name] = Wd
+
+ call = runge_kutta(**rk_args)
+ code = '{} = {};'.format(W(), call)
+ s.append(code)
+ s.jumpline()
+
+ with if_thread_active():
+ if is_periodic:
+ cond = '({lid}>={ghosts}) && ({lid}<{L}-{ghosts}) && ({gidx}<{size})'
+ cond = cond.format(
+ lid=local_id[0], ghosts=cache_ghosts(), L=local_size[0],
+ gidx=global_id[0], size=compute_grid_size[0])
+ else:
+ cond = '({lid}>={ghosts}) && ({lid}<{L}-{ghosts})'.format(
+ lid=local_id[0], ghosts=cache_ghosts(), L=local_size[0])
+ with s._if_(cond):
+ for i in xrange(work_dim):
+ Wi_out = self.svorticity+self.xyz[i]+'_out'
+ Wi_out = s.vars[Wi_out]
+ code='{} = {};'.format(Wi_out[global_index()], W[i])
+ s.append(code)
+
+
+ def per_work_statistics(self):
+ tg = self.typegen
+ dim = self.dim
+ ftype = self.ftype
+ cached = self.is_cached
+
+ compute_id = self.reqs['compute_id']
+ runge_kutta = self.reqs['runge_kutta']
+
+ stats = compute_id.per_work_statistics()
+ stats += runge_kutta.per_work_statistics()
+
+ size = tg.FLT_BYTES[ftype]
+ stats.global_mem_byte_reads += dim*size
+ stats.global_mem_byte_writes += dim*size
+
+ return stats
+
+ @staticmethod
+ def autotune(cl_env, precision, build_options,autotuner_config,
+ direction, time_integrator, formulation, discretization,
+ velocity, vorticity_in, vorticity_out,
+ velocity_mesh_info, vorticity_mesh_info):
+
+ dir = direction
+
+ assert precision in [np.float32, np.float64]
+ ftype = clTools.dtype_to_ctype(precision)
+
+ if not isinstance(cl_env,OpenClEnvironment):
+ raise ValueError('cl_env is not an OpenClEnvironment.')
+ if not isinstance(cl_env.typegen,OpenClTypeGen):
+ raise ValueError('typegen is not an OpenClTypeGen.')
+
+ device = cl_env.device
+ context = cl_env.context
+ platform = cl_env.platform
+ queue = cl_env.default_queue
+ typegen = cl_env.typegen
+
+ if context is None:
+ raise ValueError('context cannot be None.')
+ if device is None:
+ raise ValueError('device cannot be None.')
+ if platform is None:
+ raise ValueError('platform cannot be None.')
+ if queue is None:
+ raise ValueError('queue cannot be None.')
+ if typegen.platform!=platform or typegen.device!=device:
+ raise ValueError('platform or device mismatch.')
+
+ if not isinstance(velocity,DiscreteField) or \
+ velocity.backend.kind != Backend.OPENCL:
+ raise ValueError('velocity is not a DiscreteField of kind OpenCL.')
+ if not isinstance(vorticity_in,DiscreteField) or \
+ velocity.backend.kind != Backend.OPENCL:
+ raise ValueError('vorticity_in is not a DiscreteField of kind OpenCL.')
+ if not isinstance(vorticity_out,DiscreteField) or \
+ velocity.backend.kind != Backend.OPENCL:
+ raise ValueError('vorticity_out is not a DiscreteField of kind OpenCL')
+
+ dim = velocity.nb_components
+ if dim != 3:
+ raise ValueError('Stretching only appears in 3D...')
+ if (direction>=dim):
+ raise ValueError('direction >= dim.')
+ if (velocity.nb_components != dim) or \
+ (vorticity_in.nb_components != dim) or \
+ (vorticity_out.nb_components != dim):
+ raise ValueError('Vector components mismatch with dim {}.'.format(dim))
+
+ if not isinstance(time_integrator, ExplicitRungeKutta):
+ msg = 'Given time integrator is not an instance of ExplicitRungeKutta, '
+ msg+='got a {}.'.format(time_integrator.__class__)
+ raise TypeError(msg)
+
+ if not isinstance(formulation, StretchingFormulation):
+ msg = 'Unknown stretching formulation of type \'{}\', valid ones are {}.'
+ msg=msg.format(formulation.__class__, formulation.svalues())
+ raise TypeError(msg)
+
+ if not isinstance(discretization, SpaceDiscretization):
+ msg='Discretization parameter is not an instance of SpaceDiscretization, '
+ msg+='but a {}.'.format(discretization.__class__)
+ raise TypeError(msg)
+ elif discretization == SpaceDiscretization.FDC2:
+ order=2
+ elif discretization == SpaceDiscretization.FDC4:
+ order=4
+ elif discretization == SpaceDiscretization.FDC6:
+ order=6
+ elif discretization == SpaceDiscretization.FDC8:
+ order=8
+ else:
+ msg='Unknown discretization {}.'.format(discretization)
+ raise ValueError(msg)
+ if order%2 != 0:
+ raise ValueError('order must be even.')
+
+ if (not isinstance(velocity_mesh_info, CodegenStruct)) or \
+ (not velocity_mesh_info.known()):
+ msg='velocity_mesh_info is not a known MeshInfoStruct codegen variable.'
+ raise ValueError(msg)
+ if (not isinstance(vorticity_mesh_info, CodegenStruct)) or \
+ (not vorticity_mesh_info.known()):
+ msg='vorticity_mesh_info is not a known MeshInfoStruct codegen variable.'
+ raise ValueError(msg)
+
+ v_resolution = velocity_mesh_info['local_mesh']['compute_resolution'].value[:dim]
+ v_lboundary = velocity_mesh_info['local_mesh']['lboundary'].value[:dim]
+ v_rboundary = velocity_mesh_info['local_mesh']['rboundary'].value[:dim]
+ v_ghosts = velocity_mesh_info['ghosts'].value[:dim]
+ v_dx = velocity_mesh_info['dx'].value[:dim]
+
+ w_resolution = vorticity_mesh_info['local_mesh']['compute_resolution'].value[:dim]
+ w_lboundary = vorticity_mesh_info['local_mesh']['lboundary'].value[:dim]
+ w_rboundary = vorticity_mesh_info['local_mesh']['rboundary'].value[:dim]
+ w_ghosts = vorticity_mesh_info['ghosts'].value[:dim]
+ w_dx = vorticity_mesh_info['dx'].value[:dim]
+
+ is_multi_scale = (v_resolution != w_resolution).any()
+ is_inplace = (vorticity_in.data[0].data == vorticity_out.data[0].data) \
+ or (vorticity_in.data[1].data == vorticity_out.data[1].data) \
+ or (vorticity_in.data[2].data == vorticity_out.data[2].data)
+
+
+ w_boundary = (w_lboundary[dir], w_rboundary[dir])
+ v_boundary = (v_lboundary[dir], v_rboundary[dir])
+ if (v_boundary != w_boundary):
+ msg = 'Boundaries mismatch:\n *velocity: {}\n *vorticity: {}\n'
+ msg=msg.formulation(v_boundary, w_boundary)
+ raise ValueError(boundary)
+ boundary = v_boundary
+
+ (min_v_ghosts, min_w_ghosts) = DirectionalStretchingKernel.min_ghosts(
+ boundary, formulation, order, time_integrator, direction)
+
+ assert (min_v_ghosts>=0).all()
+ assert (min_w_ghosts>=0).all()
+
+ if (v_ghosts < min_v_ghosts).any():
+ msg= 'Given boundary condition implies minimum ghosts numbers to be at least {}'
+ msg+='in current direction for velocity but only {} ghosts '
+ msg+='are present in the grid.'
+ msg=msg.format(min_v_ghosts, v_ghosts)
+ raise ValueError(msg)
+
+ if (w_ghosts < min_w_ghosts).any():
+ msg= 'Given boundary condition implies minimum ghosts numbers to be at least {}'
+ msg+='in current direction for position but only {} ghosts '
+ msg+='are present in the grid.'
+ msg=msg.format(min_w_ghosts, w_ghosts)
+ raise ValueError(msg)
+
+ if is_multi_scale:
+ msg='Compute_resolution mismatch between velocity and vorticity, '
+ msg+='got {} and {} and multiscale has not been implemented yet.'
+ msg=msg.format(v_resolution,w_resolution)
+ raise ValueError(msg)
+
+ min_wg_size = DirectionalStretchingKernel.min_wg_size(formulation, order,
+ time_integrator)
+
+ # work size is the resolution without ghosts
+ compute_resolution = w_resolution
+ work_size = np.ones(3,dtype=np.int32)
+ work_size[:dim] = compute_resolution
+
+ # autotuner parameters
+
+ dump_src = __KERNEL_DEBUG__
+ symbolic_mode = __KERNEL_DEBUG__
+
+ min_local_size = np.maximum( min_wg_size,
+ [clCharacterize.get_simd_group_size(device,1),1,1])
+
+ caching_options = [True]
+ if formulation != StretchingFormulation.CONSERVATIVE:
+ caching_options.append(False)
+
+ autotuner_flag = autotuner_config.autotuner_flag
+ if (autotuner_flag == AutotunerFlags.ESTIMATE):
+ max_workitem_workload = (1,1,1)
+ elif (autotuner_flag == AutotunerFlags.MEASURE):
+ max_workitem_workload = (1,1,8)
+ elif (autotuner_flag == AutotunerFlags.PATIENT):
+ max_workitem_workload = (1,8,8)
+ elif (autotuner_flag == AutotunerFlags.EXHAUSTIVE):
+ max_workitem_workload = (1,16,16)
+
+ ## kernel generator
+ def kernel_generator(work_size, work_load, local_work_size,
+ kernel_args,
+ extra_parameters,
+ force_verbose = False,
+ force_debug = False,
+ return_codegen = False,
+ **kargs):
+
+ ## Compile time known variables
+ # dt is not known because it depends on splitting direction
+ # and simulation current time_step
+ known_vars = dict(
+ velocity_mesh_info=velocity_mesh_info,
+ vorticity_mesh_info=vorticity_mesh_info,
+ local_size=local_work_size[:dim]
+ )
+
+ ## CodeGenerator
+ cached=True
+ codegen = DirectionalStretchingKernel(typegen=typegen,
+ order=order, dim=dim, direction=direction, boundary=boundary,
+ formulation=formulation, time_integrator=time_integrator,
+ is_inplace=is_inplace,
+ symbolic_mode=symbolic_mode, ftype=ftype,
+ known_vars=known_vars, **extra_parameters)
+
+ global_size = codegen.get_global_size(work_size=work_size,
+ work_load=work_load, local_work_size=local_work_size)
+
+ usable_cache_bytes_per_wg = clCharacterize.usable_local_mem_size(device)
+ if codegen.required_workgroup_cache_size(local_work_size[:dim])[2] > \
+ usable_cache_bytes_per_wg:
+ raise KernelGenerationError('Insufficient device cache.')
+
+ ## generate source code and build kernel
+ src = codegen.__str__()
+ src_hash = hashlib.sha512(src).hexdigest()
+ prg = cl_env.build_raw_src(src, build_options,
+ kernel_name=codegen.name,
+ force_verbose=force_verbose, force_debug=force_debug)
+ kernel = prg.all_kernels()[0]
+
+ if return_codegen:
+ return (codegen, kernel, kernel_args, src_hash, global_size)
+ else:
+ return (kernel, kernel_args, src_hash, global_size)
+
+ ## Kernel Autotuner
+ name = DirectionalStretchingKernel.codegen_name(ftype, False, is_inplace,
+ direction, formulation)
+
+ autotuner = KernelAutotuner(name=name, work_dim=dim, local_work_dim=1,
+ build_opts=build_options, autotuner_config=autotuner_config)
+ autotuner.add_filter('1d_shape_min', autotuner.min_workitems_per_direction)
+ autotuner.register_extra_parameter('is_cached', caching_options)
+ autotuner.enable_variable_workitem_workload(
+ max_workitem_workload=max_workitem_workload)
+
+ dt=1.0
+ kernel_args = [precision(dt)]
+ kernel_args += velocity.buffers + vorticity_in.buffers+ vorticity_out.buffers
+
+ kernel_args_mapping = {
+ 'dt': (0,precision),
+ 'velocity': (slice(1+0*dim, 1+1*dim, 1), cl.MemoryObjectHolder),
+ 'vorticity_in': (slice(1+1*dim, 1+2*dim, 1), cl.MemoryObjectHolder),
+ 'vorticity_out': (slice(1+2*dim, 1+3*dim, 1), cl.MemoryObjectHolder),
+ }
+
+ (gwi, lwi, stats, work_load, extra_params) = autotuner.bench(typegen=typegen,
+ work_size=work_size, kernel_args=kernel_args,
+ kernel_generator=kernel_generator,
+ dump_src=dump_src,
+ min_local_size=min_local_size,
+ get_max_global_size=DirectionalStretchingKernel.get_max_global_size)
+
+ (codegen, kernel, kernel_args, src_hash, global_size) = kernel_generator(
+ work_size=work_size, work_load=work_load,
+ local_work_size=lwi, kernel_args=kernel_args,
+ extra_parameters=extra_params,
+ force_verbose=None,force_debug=None,
+ return_codegen=True)
+
+ kernel_launcher = OpenClKernelLauncher(kernel, queue, list(gwi), list(lwi))
+
+ total_work = work_size[0]*work_size[1]*work_size[2]
+ per_work_statistics = codegen.per_work_statistics()
+
+ cache_info = codegen.required_workgroup_cache_size(lwi)
+
+ return (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistics, cache_info)
+
+
+if __name__ == '__main__':
+ from hysop.backend.device.opencl import cl
+ from hysop.backend.device.codegen.base.test import _test_mesh_info, _test_typegen
+
+ dim=3
+ ghosts=(0,0,0)
+ v_resolution=(256,128,64)
+ w_resolution=(1024,512,256)
+ local_size = (1024,1,1)
+
+ tg = _test_typegen('float')
+ (_,w_mesh_info) = _test_mesh_info('vorticity_mesh_info',tg,dim,ghosts,w_resolution)
+ (_,v_mesh_info) = _test_mesh_info('velocity_mesh_info',tg,dim,ghosts,v_resolution)
+
+ dsk = DirectionalStretchingKernel(typegen=tg, ftype=tg.fbtype,
+ order=4, dim=dim, direction=0,
+ formulation=StretchingFormulation.GRAD_UW,
+ time_integrator=ExplicitRungeKutta('RK2'),
+ is_cached=True,
+ is_inplace=True,
+ symbolic_mode=True,
+ boundary=(BoundaryCondition.NONE,BoundaryCondition.NONE),
+ known_vars=dict(
+ velocity_mesh_info=v_mesh_info,
+ vorticity_mesh_info=w_mesh_info,
+ local_size=local_size[:dim]
+ )
+ )
+ dsk.edit()
+ dsk.test_compile()
+
diff --git a/hysop/codegen/kernels/empty.py b/hysop/backend/device/codegen/kernels/empty.py
similarity index 75%
rename from hysop/codegen/kernels/empty.py
rename to hysop/backend/device/codegen/kernels/empty.py
index 66263aaf653520f9c587d741a3aa261251bd72ea..23412a6e3b44d8c0f1cf6d77c774fac96adac779 100644
--- a/hysop/codegen/kernels/empty.py
+++ b/hysop/backend/device/codegen/kernels/empty.py
@@ -1,8 +1,8 @@
-from hysop.codegen.base.variables import CodegenVectorClBuiltin
-from hysop.codegen.base.kernel_codegen import KernelCodeGenerator
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import ArgDict
+from hysop.backend.device.codegen.base.variables import CodegenVectorClBuiltin
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import ArgDict
class EmptyKernel(KernelCodeGenerator):
@@ -26,7 +26,8 @@ class EmptyKernel(KernelCodeGenerator):
if __name__ == '__main__':
- typegen = OpenClTypeGen('float')
+ from hysop.backend.device.codegen.base.test import test_typegen
+ typegen = test_typegen('float')
ek = EmptyKernel(typegen)
print ek
diff --git a/hysop/codegen/kernels/stretching.py b/hysop/backend/device/codegen/kernels/stretching.py
similarity index 74%
rename from hysop/codegen/kernels/stretching.py
rename to hysop/backend/device/codegen/kernels/stretching.py
index 128777239d66329f3b3815310452d6785a08872b..c3f88911838b38a5a236997b8a7d52683b2b8213 100644
--- a/hysop/codegen/kernels/stretching.py
+++ b/hysop/backend/device/codegen/kernels/stretching.py
@@ -2,16 +2,16 @@
import operator
import numpy as np
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.kernel_codegen import KernelCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
-from hysop.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
+from hysop.backend.device.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
-from hysop.codegen.functions.compute_index import ComputeIndexFunction
-from hysop.codegen.functions.gradient import GradientFunction
+from hysop.backend.device.codegen.functions.compute_index import ComputeIndexFunction
+from hysop.backend.device.codegen.functions.gradient import GradientFunction
class CachedStretchingKernel(KernelCodeGenerator):
@@ -19,9 +19,10 @@ class CachedStretchingKernel(KernelCodeGenerator):
def codegen_name(ftype,work_dim):
return 'cached_stretching_{}_{}d'.format(ftype,work_dim)
- def __init__(self, typegen, dim, order=2,
+ def __init__(self, typegen, dim,
+ device,context,
+ order=2,
ftype=None,
- device=None,context=None,
known_vars = None,
symbolic_mode=True):
@@ -29,7 +30,8 @@ class CachedStretchingKernel(KernelCodeGenerator):
ftype = ftype if ftype is not None else typegen.fbtype
work_dim=3
- kernel_reqs = self.build_requirements(typegen,work_dim, order, cached)
+ kernel_reqs = self.build_requirements(typegen=typegen,device=device,context=context,
+ work_dim=work_dim, order=order, cached=cached)
kernel_args = self.gen_kernel_arguments(typegen, work_dim, ftype, kernel_reqs)
name = CachedStretchingKernel.codegen_name(ftype, dim)
@@ -55,16 +57,16 @@ class CachedStretchingKernel(KernelCodeGenerator):
return reduce(operator.mul, local_size+order, 1)*self.typegen.FLT_BYTES[self.ftype]
- def build_requirements(self,typegen,work_dim,order,cached):
+ def build_requirements(self,typegen,device,context,work_dim,order,cached):
reqs = WriteOnceDict()
compute_id = ComputeIndexFunction(typegen=typegen, dim=work_dim, itype='int', wrap=False)
reqs['compute_id'] = compute_id
- mesh_base_struct = MeshBaseStruct(typegen=typegen, typedef='MeshBaseStruct_s')
+ mesh_base_struct = MeshBaseStruct(device=device,context=context,typegen=typegen, typedef='MeshBaseStruct_s')
reqs['MeshBaseStruct'] = mesh_base_struct
- mesh_info_struct = MeshInfoStruct(typegen=typegen, typedef='MeshInfoStruct_s')
+ mesh_info_struct = MeshInfoStruct(device=device, context=context, typegen=typegen, typedef='MeshInfoStruct_s')
reqs['MeshInfoStruct'] = mesh_info_struct
gradient = GradientFunction(typegen=typegen, dim=work_dim, order=order,
@@ -163,11 +165,23 @@ class CachedStretchingKernel(KernelCodeGenerator):
if __name__ == '__main__':
-
- tg = OpenClTypeGen('float', 'dec')
- ek = CachedStretchingKernel(typegen=tg, order=16, dim=1 ,ftype=tg.fbtype,
- known_vars=dict(local_size=(1024,1,1)))
- ek.edit()
- ek.test_compile()
- #print ek
- print
+
+ import pyopencl as cl
+ from hysop.backend.device.codegen.base.test import test_typegen
+
+ devices = []
+ contexts = {}
+ for plat in cl.get_platforms():
+ devices += plat.get_devices()
+ for dev in devices:
+ ctx = cl.Context([dev])
+ contexts[dev] = ctx
+
+ tg = test_typegen('float', 'dec')
+ for dev,ctx in contexts.iteritems():
+ ek = CachedStretchingKernel(typegen=tg, context=ctx, device=dev,
+ order=16, dim=1 ,ftype=tg.fbtype,
+ known_vars=dict(local_size=(1024,1,1)))
+ ek.edit()
+ ek.test_compile()
+ break
diff --git a/hysop/backend/device/codegen/kernels/tests/test_directional_advection.py b/hysop/backend/device/codegen/kernels/tests/test_directional_advection.py
new file mode 100644
index 0000000000000000000000000000000000000000..5c9d905dff9f80269f3479d8cb13aa39cc464e20
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/tests/test_directional_advection.py
@@ -0,0 +1,446 @@
+
+import copy, math
+
+from hysop import __ENABLE_LONG_TESTS__
+from hysop.backend.device.opencl import cl
+from hysop.tools.types import check_instance
+from hysop.constants import np, BoundaryCondition
+from hysop.backend.device.codegen.base.test import _test_mesh_info , _test_typegen
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta
+from hysop.backend.device.codegen.kernels.directional_advection import DirectionalAdvectionKernel
+
+class TestDirectionalAdvection(object):
+
+ @classmethod
+ def setup_class(cls,
+ enable_extra_tests=__ENABLE_LONG_TESTS__,
+ enable_error_plots=False):
+ typegen = _test_typegen('double','dec')
+ dtype = np.float64
+
+ queue = cl.CommandQueue(typegen.context)
+ ctx = typegen.context
+
+ grid_size = np.asarray([64,64,1])
+ (A,grid_mesh_info) = _test_mesh_info('velocity_mesh_info',typegen,3,0,grid_size)
+ (_,position_mesh_info) = _test_mesh_info('position_mesh_info',typegen,3,0,grid_size)
+
+ dx = A['dx'][0][0]
+ inv_dx = A['inv_dx'][0][0]
+ dt = 0.1
+
+ umax = 1.0
+ min_ghosts = int(math.ceil(dt*umax/float(dx)))
+ ghosts = min_ghosts
+
+ print 'min ghosts are: {}'.format(min_ghosts)
+ print 'actual ghosts are: {}'.format(ghosts)
+
+ compute_grid_ghosts = np.asarray([ghosts,0,0])
+ compute_grid_size = grid_size + 2*compute_grid_ghosts
+ (B,compute_grid_mesh_info) = _test_mesh_info('velocity_mesh_info',typegen,3,compute_grid_ghosts,compute_grid_size)
+
+ grid_shape = grid_size[::-1]
+ compute_grid_shape = compute_grid_size[::-1]
+
+ assert A['dx'][0] == B['dx'][0]
+
+ grid_bytes = grid_size.size * typegen.FLT_BYTES[typegen.fbtype]
+ compute_grid_bytes = compute_grid_size.size * typegen.FLT_BYTES[typegen.fbtype]
+
+ mf = cl.mem_flags
+
+ host_buffers_init = {
+ 'no_ghosts': {
+ 'u': umax * np.random.rand(*grid_shape).astype(dtype),
+ 'pos': -1 * np.ones(shape=grid_shape, dtype=dtype),
+ 'dbg0': -1 * np.ones(shape=grid_shape, dtype=np.int32),
+ 'dbg1': -1 * np.ones(shape=grid_shape, dtype=np.int32),
+ },
+ 'with_ghosts': {
+ 'u': umax * np.random.rand(*compute_grid_shape).astype(dtype),
+ 'pos': -1 * np.ones(shape=grid_shape, dtype=dtype),
+ 'dbg0': -1 * np.ones(shape=compute_grid_shape, dtype=np.int32),
+ 'dbg1': -1 * np.ones(shape=compute_grid_shape, dtype=np.int32),
+ }
+ }
+
+ device_buffers = {
+ 'no_ghosts': {
+ 'u': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['u']),
+ 'pos': cl.Buffer(ctx, flags=mf.WRITE_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['pos']),
+ 'dbg0': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['dbg0']),
+ 'dbg1': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['dbg1']),
+ },
+ 'with_ghosts': {
+ 'u': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['u']),
+ 'pos': cl.Buffer(ctx, flags=mf.WRITE_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['pos']),
+ 'dbg0': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['dbg0']),
+ 'dbg1': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['dbg1']),
+ }
+ }
+
+ host_buffers_reference = copy.deepcopy(host_buffers_init)
+ host_buffers_gpu = copy.deepcopy(host_buffers_init)
+
+ cls.typegen = typegen
+ cls.queue = queue
+
+ cls.min_ghosts = min_ghosts
+
+ cls.grid_size = grid_size
+ cls.grid_shape = grid_shape
+ cls.grid_bytes = grid_bytes
+
+ cls.grid_mesh_info = grid_mesh_info
+ cls.compute_grid_mesh_info = compute_grid_mesh_info
+ cls.position_mesh_info = position_mesh_info
+
+ cls.compute_grid_ghosts = compute_grid_ghosts
+ cls.compute_grid_size = compute_grid_size
+ cls.compute_grid_shape = compute_grid_shape
+ cls.compute_grid_bytes = compute_grid_bytes
+
+ cls.host_buffers_init = host_buffers_init
+ cls.host_buffers_reference = host_buffers_reference
+ cls.host_buffers_gpu = host_buffers_gpu
+ cls.device_buffers = device_buffers
+
+ Lx = min(typegen.device.max_work_item_sizes[0], typegen.device.max_work_group_size)
+ Lx = min(Lx, grid_size[0])
+
+ cls.local_work_size = np.asarray([Lx,1,1])
+ cls.work_load = np.asarray([1,1,1])
+
+ cls.dx = dx
+ cls.inv_dx = inv_dx
+ cls.dt = dtype(dt)
+
+ cls.enable_extra_tests = enable_extra_tests
+ cls.enable_error_plots = enable_error_plots
+
+
+ @classmethod
+ def teardown_class(cls):
+ pass
+
+ def setup_method(self, method):
+ pass
+
+ def teardown_method(self, method):
+ pass
+
+ def _do_compute_cpu(self, rk_scheme, boundary):
+
+ dt = self.dt
+ dx = self.dx
+ inv_dx = self.inv_dx
+ ghosts = self.compute_grid_ghosts
+ grid_size = self.grid_size
+ grid_ghosts = self.compute_grid_ghosts
+ compute_grid_size = self.compute_grid_size
+
+ is_periodic = False
+ if boundary == BoundaryCondition.PERIODIC:
+ is_periodic = True
+ target = 'no_ghosts'
+ grid_ghosts*=0
+ view = [slice(0,grid_size[2]),
+ slice(0,grid_size[1]),
+ slice(0,grid_size[0])]
+ elif boundary == BoundaryCondition.NONE:
+ target = 'with_ghosts'
+ view = [slice(ghosts[2],grid_size[2]+ghosts[2]),
+ slice(ghosts[1],grid_size[1]+ghosts[1]),
+ slice(ghosts[0],grid_size[0]+ghosts[0])]
+ else:
+ raise ValueError()
+
+ host_init_buffers = self.host_buffers_init[target]
+ host_buffers_reference = self.host_buffers_reference[target]
+
+ velocity = host_init_buffers['u']
+ position = host_init_buffers['pos']
+ pos = np.zeros_like(position)
+ pos[:,:,:] = np.arange(grid_size[0])[None,None,:]+grid_ghosts[0]
+ pos*=dx
+
+ def interp_velocity(X):
+ Gx = grid_size[0]
+ X = X.copy() * inv_dx
+ lidx = np.floor(X).astype(np.int32)
+ alpha = X-lidx
+ if is_periodic:
+ lidx = (lidx+Gx)%Gx
+ ridx = (lidx+1)%Gx
+ else:
+ ridx = lidx+1
+ Vl = np.empty_like(X)
+ Vr = np.empty_like(X)
+ for i in xrange(*view[0].indices(grid_size[2])):
+ for j in xrange(*view[1].indices(grid_size[1])):
+ Vl[i,j,:] = velocity[i,j,lidx[i,j,:]]
+ Vr[i,j,:] = velocity[i,j,ridx[i,j,:]]
+ return Vl + alpha*(Vr-Vl)
+
+ if rk_scheme.name() == 'Euler':
+ pos += velocity[view]*dt
+ elif rk_scheme.name() == 'RK2':
+ X0 = pos.copy()
+ K0 = velocity[view]
+ X1 = X0 + 0.5*K0*dt;
+ K1 = interp_velocity(X1)
+ K = K1;
+ pos = X0+K*dt
+ elif rk_scheme.name() == 'RK4':
+ X0 = pos.copy()
+ K0 = velocity[view]
+ X1 = X0 + 0.5*K0*dt;
+ K1 = interp_velocity(X1)
+ X2 = X0 + 0.5*K1*dt;
+ K2 = interp_velocity(X2)
+ X3 = X0 + 1.0*K2*dt;
+ K3 = interp_velocity(X3)
+ K = 1./6*K0 + 2./6*K1 + 2./6*K2 + 1./6*K3
+ pos = X0+K*dt
+ else:
+ msg = 'Unknown Runge-Kutta scheme {}.'.format(rk_scheme)
+ raise ValueError(msg)
+
+ host_buffers_reference['pos'] = pos
+
+ def _do_compute_gpu_and_check(self, rk_scheme, boundary, cached, nparticles, work_dim):
+
+ msg = '\nTesting {}directional {}d advection with {} scheme and {} boundaries, {} particles at a time.'\
+ .format('cached ' if cached else '',
+ work_dim,
+ rk_scheme.name(),
+ str(boundary).lower(),
+ nparticles)
+ print msg
+
+ dt = self.dt
+ work_size = self.grid_size
+ work_load = self.work_load
+ local_work_size = self.local_work_size
+ queue = self.queue
+
+ grid_size = self.grid_size
+ grid_shape = self.grid_shape
+ ghosts = self.compute_grid_ghosts
+
+ if boundary != BoundaryCondition.PERIODIC or cached:
+ min_ghosts = self.min_ghosts
+ else:
+ min_ghosts = self.min_ghosts*0
+
+ assert grid_size[0] % nparticles == 0
+
+ kernel_args = [dt]
+ position_mesh_info = self.position_mesh_info
+ if boundary == BoundaryCondition.PERIODIC:
+ target = 'no_ghosts'
+ velocity_mesh_info = self.grid_mesh_info
+ view = [slice(0,grid_size[2]),
+ slice(0,grid_size[1]),
+ slice(0,grid_size[0])]
+ elif boundary == BoundaryCondition.NONE:
+ target = 'with_ghosts'
+ velocity_mesh_info = self.compute_grid_mesh_info
+ view = [slice(ghosts[2],grid_size[2]+ghosts[2]),
+ slice(ghosts[1],grid_size[1]+ghosts[1]),
+ slice(ghosts[0],grid_size[0]+ghosts[0])]
+ else:
+ raise ValueError()
+
+ for i in xrange(work_dim,3):
+ view[2-i] = 0
+
+ grid_size = grid_size[:work_dim]
+ grid_shape = grid_shape[:work_dim]
+ ghosts = ghosts[:work_dim]
+
+ work_size = work_size[:work_dim]
+ work_load = work_load[:work_dim]
+ local_work_size = local_work_size[:work_dim]
+
+ known_vars = {
+ 'local_size': local_work_size,
+ 'velocity_mesh_info': velocity_mesh_info,
+ 'position_mesh_info': position_mesh_info
+ }
+
+ host_init_buffers = self.host_buffers_init[target]
+ host_buffers_reference = self.host_buffers_reference[target]
+ host_buffers_gpu = self.host_buffers_gpu[target]
+ device_buffers = self.device_buffers[target]
+
+ dak = DirectionalAdvectionKernel(
+ typegen=self.typegen,
+ ftype=self.typegen.fbtype,
+ work_dim=work_dim,
+ rk_scheme=rk_scheme,
+ is_cached=cached,
+ vboundary=(boundary, boundary),
+ nparticles = nparticles,
+ min_ghosts=min_ghosts,
+ symbolic_mode=False,
+ debug_mode=True,
+ known_vars=known_vars)
+ # dak.edit()
+
+ global_work_size = dak.get_global_size(work_size,local_work_size,work_load)
+ (static_shared_bytes, dynamic_shared_bytes, total_bytes) = \
+ dak.required_workgroup_cache_size(local_work_size)
+
+ variables = ['u','pos']
+ debug = ['dbg0', 'dbg1']
+ for varname in variables:
+ kernel_args.append(device_buffers[varname])
+ kernel_args.append(np.uint64(0))
+ for varname in debug:
+ kernel_args.append(device_buffers[varname])
+ if (dynamic_shared_bytes != 0):
+ shared_buffer = cl.LocalMemory(dynamic_shared_bytes)
+ kernel_args.append(shared_buffer)
+
+ print '\tGenerating and compiling Kernel...'
+ source = dak.__str__()
+ prg = cl.Program(self.typegen.context, source)
+ prg.build(devices=[self.typegen.device])
+ kernel = prg.all_kernels()[0]
+ kernel.set_args(*kernel_args)
+
+ print '\tCPU => GPU'
+ for buf in variables+debug:
+ src = host_init_buffers[buf]
+ dst = device_buffers[buf]
+ cl.enqueue_copy(queue,dst,src)
+
+ print '\tKernel execution <<<{},{}>>>'.format(global_work_size,local_work_size)
+ evt = cl.enqueue_nd_range_kernel(queue, kernel,
+ global_work_size.tolist(), local_work_size.tolist())
+ evt.wait()
+
+ print '\tGPU => CPU'
+ for buf in variables+debug:
+ src = device_buffers[buf]
+ dst = host_buffers_gpu[buf]
+ cl.enqueue_copy(queue,dst,src)
+
+ print '\tSynchronize queue'
+ queue.flush()
+ queue.finish()
+
+ buffers = [(varname,host_buffers_reference[varname],host_buffers_gpu[varname])
+ for varname in variables]
+ self._cmp_buffers(buffers,view,dak,work_dim)
+
+ def _cmp_buffers(self,buffers,view,dak,work_dim):
+ good = True
+ err_buffers = []
+
+ for (name,host,dev) in buffers:
+ (l1,l2,linf) = self._distances(host,dev,view)
+ print '\t{} -> l1={} l2={} linf={}'.format(name,l1,l2,linf)
+ if linf>1e-12:
+ err_buffers.append(name)
+ good = False
+ if not good:
+ msg = '\n[FAIL] Buffer comparisson failed for buffers {}.\n'.format(err_buffers)
+ print msg
+ dak.edit()
+ if self.enable_error_plots:
+ from matplotlib import pyplot as plt
+ for (name,host,dev) in buffers:
+ if name in err_buffers:
+
+ host = host[view]
+ dev = dev[view]
+
+ d = (dev-host)*(dev-host)
+ d -= np.mean(d)
+
+ if work_dim==3:
+ fig,axes = plt.subplots(2,2)
+ axes[0][0].imshow(np.sum(d,axis=0),interpolation='nearest')
+ axes[0][1].imshow(np.sum(d,axis=1),interpolation='nearest')
+ axes[1][0].imshow(np.sum(d,axis=2),interpolation='nearest')
+ axes[1][1].imshow(np.sum(d,axis=(0,1))[np.newaxis,:],interpolation='nearest')
+ plt.title(name)
+ fig.show()
+ raw_input('Press enter to close all windows.')
+ break
+ elif work_dim==2:
+ fig,axe = plt.subplots()
+ axe.imshow(d,interpolation='nearest')
+ plt.title(name)
+ fig.show()
+ raw_input('Press enter to close all windows.')
+ break
+ else:
+ pass
+ raise RuntimeError(msg)
+
+ def _distances(self,lhs,rhs,view):
+ d = rhs[view]-lhs[view]
+ da = np.abs(d)
+
+ l1 = np.sum(da)/d.size
+ l2 = np.sqrt(np.sum(d*d))/d.size
+ linf = np.max(da)
+ return (l1,l2,linf)
+
+
+ def _check_kernels(self, rk_scheme):
+ check_instance(rk_scheme,ExplicitRungeKutta)
+
+ cached=[False,True]
+ boundaries=[BoundaryCondition.PERIODIC]
+
+ if self.enable_extra_tests:
+ nparticles=[1,2,4,8,16]
+ work_dims=[1,2,3]
+ else:
+ nparticles=[1,4]
+ work_dims=[2,3]
+
+ for boundary in boundaries:
+ self._do_compute_cpu(boundary=boundary, rk_scheme=rk_scheme)
+ for work_dim in work_dims:
+ for cache in cached:
+ for nparticle in nparticles:
+ self._do_compute_gpu_and_check(boundary=boundary,rk_scheme=rk_scheme,
+ work_dim=work_dim, nparticles=nparticle, cached=cache)
+
+
+ def test_advection_Euler(self):
+ rk_scheme=ExplicitRungeKutta('Euler')
+ self._check_kernels(rk_scheme=rk_scheme)
+
+ def test_advection_RK2(self):
+ rk_scheme=ExplicitRungeKutta('RK2')
+ self._check_kernels(rk_scheme=rk_scheme)
+
+ def test_advection_RK4(self):
+ rk_scheme=ExplicitRungeKutta('RK4')
+ self._check_kernels(rk_scheme=rk_scheme)
+
+if __name__ == '__main__':
+ TestDirectionalAdvection.setup_class(enable_extra_tests=False, enable_error_plots=True)
+ test = TestDirectionalAdvection()
+
+ test.test_advection_Euler()
+ test.test_advection_RK2()
+ test.test_advection_RK4()
+
+ TestDirectionalAdvection.teardown_class()
+
diff --git a/hysop/backend/device/codegen/kernels/tests/test_directional_remesh.py b/hysop/backend/device/codegen/kernels/tests/test_directional_remesh.py
new file mode 100644
index 0000000000000000000000000000000000000000..a2481753b3fd9f1674130d3c62bad5b6be77352d
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/tests/test_directional_remesh.py
@@ -0,0 +1,1105 @@
+
+from hysop import __ENABLE_LONG_TESTS__
+from hysop.testsenv import __HAS_OPENCL_BACKEND__, iter_clenv, opencl_failed
+from hysop.deps import np, copy, math
+from hysop.backend.device.opencl import cl
+from hysop.tools.types import check_instance
+from hysop.constants import BoundaryCondition, Precision
+from hysop.backend.device.codegen.base.test import _test_mesh_info , _test_typegen, make_slice_views
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta
+from hysop.backend.device.codegen.kernels.directional_remesh import DirectionalRemeshKernel
+from hysop.numerics.remesh.remesh import RemeshKernel
+from hysop.tools.contexts import printoptions
+
+class TestDirectionalRemesh(object):
+
+ DEBUG = False
+
+ @classmethod
+ def setup_class(cls,
+ enable_extra_tests=__ENABLE_LONG_TESTS__,
+ enable_error_plots=False):
+
+ cls.enable_extra_tests = enable_extra_tests
+ cls.enable_error_plots = enable_error_plots
+ cls.MAX_MOMENTS = 8
+ cls.random = np.random.RandomState()
+
+ print '::Setup TestDirectionalRemesh ::'
+ print ' enable_error_plots: {}'.format(enable_error_plots)
+ print ' enable_extra_tests: {}'.format(enable_extra_tests)
+ print ' MAX_MOMENTS: {}'.format(cls.MAX_MOMENTS)
+ print ' DEBUG: {}'.format(cls.DEBUG)
+
+ def _initialize(self, cl_env, cfl):
+
+ typegen = cl_env.typegen
+ dtype = cl_env.precision
+ eps = np.finfo(dtype).eps
+
+ # compute grid
+ compute_grid_size = np.asarray([97,17,23])
+ compute_grid_shape = compute_grid_size[::-1]
+ (A,compute_grid_mesh_info) = _test_mesh_info('base_mesh_info',typegen,3,0,compute_grid_size)
+
+ view = [slice(0,compute_grid_size[2]),
+ slice(0,compute_grid_size[1]),
+ slice(0,compute_grid_size[0])]
+
+ dx = A['dx'][0][0]
+ inv_dx = A['inv_dx'][0][0]
+
+ # velocity bounds
+ umax = +10.0
+ umin = -10.0
+ uinf = max(abs(umax),abs(umin))
+
+ # compute timestep
+ dt = cfl * dx/uinf
+ assert(umin<umax)
+ assert cfl>0
+ assert dt>0
+
+ # scalar bounds
+ S0_min=-1.0
+ S0_max=+1.0
+
+ S1_min=-10.0
+ S1_max=+10.0
+
+ # compute max offsets due to advection and remeshing
+ assert self.MAX_MOMENTS % 2 == 0
+ MAX_P=(1+self.MAX_MOMENTS/2)
+ assert MAX_P > 0
+
+ MAX_ADVEC = int(np.floor(dt*uinf*inv_dx))
+ assert MAX_ADVEC >= 0
+
+ theorical_min_ind_advec = int(np.floor(0 + umin*dt*inv_dx))
+ theorical_max_ind_advec = int(np.floor(compute_grid_size[0]-1 + umax*dt*inv_dx))
+
+ # required ghosts for non periodic boundaries
+ min_ghosts_in = 0
+ min_ghosts_out = MAX_ADVEC + MAX_P
+
+ # inject extra ghosts on scalars for testing purpose
+ S0_in_ghosts = min_ghosts_in + 4
+ S1_in_ghosts = min_ghosts_in + 2
+ S0_out_ghosts = min_ghosts_out + 1
+ S1_out_ghosts = min_ghosts_out + 3
+
+ # build 3D view, grid_size, grid_shape, ghosts, mesh_info, ...
+ # size is XYZ, shape is ZYX
+ S0_in_view, S0_in_grid_size, S0_in_grid_shape, S0_in_grid_ghosts, _, _ = \
+ make_slice_views(compute_grid_size, S0_in_ghosts, S0_in_ghosts)
+ S0_out_view, S0_out_grid_size, S0_out_grid_shape, S0_out_grid_ghosts, _, _ = \
+ make_slice_views(compute_grid_size, S0_out_ghosts, S0_out_ghosts)
+ (B, S0_in_mesh_info) = _test_mesh_info('S0_mesh_info_in',
+ typegen,3,S0_in_grid_ghosts,S0_in_grid_size)
+ (C, S0_out_mesh_info) = _test_mesh_info('S0_mesh_info_out',
+ typegen,3,S0_out_grid_ghosts,S0_out_grid_size)
+
+ S1_in_view, S1_in_grid_size, S1_in_grid_shape, S1_in_grid_ghosts, _, _ = \
+ make_slice_views(compute_grid_size, S1_in_ghosts, S1_in_ghosts)
+ S1_out_view, S1_out_grid_size, S1_out_grid_shape, S1_out_grid_ghosts, _, _ = \
+ make_slice_views(compute_grid_size, S1_out_ghosts, S1_out_ghosts)
+ (D, S1_in_mesh_info) = _test_mesh_info('S1_mesh_info_in',
+ typegen,3,S1_in_grid_ghosts,S1_in_grid_size)
+ (E, S1_out_mesh_info) = _test_mesh_info('S1_mesh_info_out',
+ typegen,3,S1_out_grid_ghosts,S1_out_grid_size)
+
+ assert A['dx'][0] == B['dx'][0]
+ assert A['dx'][0] == C['dx'][0]
+ assert A['dx'][0] == D['dx'][0]
+ assert A['dx'][0] == E['dx'][0]
+
+ itemsize = np.dtype(dtype).itemsize
+ compute_grid_bytes = compute_grid_size.size * itemsize
+
+ ctx = cl_env.context
+ device = cl_env.device
+ platform = cl_env.platform
+
+ mf = cl.mem_flags
+
+ ## allocate and initialize buffers
+ random = self.random
+ #random.seed(42)
+
+ uinit = (umax-umin) * random.rand(*compute_grid_shape).astype(dtype) + umin
+ # force worst case on boundaries
+ uinit[:,:,0] = umin
+ uinit[:,:,-1] = umax
+
+ S0_in_init = (S0_max-S0_min)*random.rand(*compute_grid_shape).astype(dtype) + S0_min
+ S1_in_init = (S1_max-S1_min)*random.rand(*compute_grid_shape).astype(dtype) + S1_min
+ S0_out_init = np.full(fill_value=np.inf, shape=compute_grid_shape, dtype=dtype)
+ S1_out_init = np.full(fill_value=np.inf, shape=compute_grid_shape, dtype=dtype)
+
+ S0_in_init_ghosts = np.full(fill_value=np.nan, shape=S0_in_grid_shape, dtype=dtype)
+ S1_in_init_ghosts = np.full(fill_value=np.nan, shape=S1_in_grid_shape, dtype=dtype)
+ S0_out_init_ghosts = np.full(fill_value=np.inf, shape=S0_out_grid_shape, dtype=dtype)
+ S1_out_init_ghosts = np.full(fill_value=np.inf, shape=S1_out_grid_shape, dtype=dtype)
+
+ S0_in_init_ghosts[S0_in_view] = S0_in_init
+ S1_in_init_ghosts[S1_in_view] = S1_in_init
+
+ pos_init = np.full(fill_value=np.nan, shape=compute_grid_shape, dtype=dtype)
+
+ dbg0_init = -1* np.ones(shape=compute_grid_shape, dtype=np.int32)
+ dbg1_init = -1* np.ones(shape=compute_grid_shape, dtype=np.int32)
+
+ host_buffers_init = {
+ 'no_ghosts': {
+ 'u': uinit,
+ 'S0_in': S0_in_init,
+ 'S1_in': S1_in_init,
+ 'S0_out': S0_out_init,
+ 'S1_out': S1_out_init,
+ 'pos': pos_init,
+ 'dbg0': dbg0_init,
+ 'dbg1': dbg1_init
+ },
+ 'with_ghosts': {
+ 'u': uinit,
+ 'S0_in': S0_in_init_ghosts,
+ 'S1_in': S1_in_init_ghosts,
+ 'S0_out': S0_out_init_ghosts,
+ 'S1_out': S1_out_init_ghosts,
+ 'pos': pos_init,
+ 'dbg0': dbg0_init,
+ 'dbg1': dbg1_init
+ }
+ }
+
+ device_buffers = {
+ 'no_ghosts': {
+ 'pos': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['pos']),
+ 'S0_in': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['S0_in']),
+ 'S1_in': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['S1_in']),
+ 'S0_out': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['S0_out']),
+ 'S1_out': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['S1_out']),
+ 'dbg0': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['dbg0']),
+ 'dbg1': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['dbg1']),
+ },
+ 'with_ghosts': {
+ 'pos': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['pos']),
+ 'S0_in': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['S0_in']),
+ 'S1_in': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['S1_in']),
+ 'S0_out': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['S0_out']),
+ 'S1_out': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['S1_out']),
+ 'dbg0': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['dbg0']),
+ 'dbg1': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['dbg1']),
+ }
+ }
+
+ host_buffers_reference = copy.deepcopy(host_buffers_init)
+ host_buffers_gpu = copy.deepcopy(host_buffers_init)
+
+ Lx = min(typegen.device.max_work_item_sizes[0], typegen.device.max_work_group_size)
+ Lx = min(Lx, 1 << int(np.floor(np.log2(compute_grid_size[0]))))
+ local_work_size = np.asarray([Lx,1,1])
+ work_load = np.asarray([1,3,2])
+
+ self.dx = dx
+ self.inv_dx = inv_dx
+ self.dt = dtype(dt)
+ self.cfl = cfl
+ self.umax = umax
+ self.umin = umin
+ self.uinf = uinf
+
+ self.eps = eps
+ self.itemsize = itemsize
+
+ self.cl_env = cl_env
+ self.typegen = cl_env.typegen
+ self.queue = cl_env.default_queue
+ self.context = ctx
+ self.device = device
+ self.local_work_size = local_work_size
+ self.work_load = work_load
+
+ self.MAX_P = MAX_P
+ self.MAX_ADVEC = MAX_ADVEC
+ self.min_ghosts_in = min_ghosts_in
+ self.min_ghosts_out = min_ghosts_out
+ self.theorical_min_ind_advec = theorical_min_ind_advec
+ self.theorical_max_ind_advec = theorical_max_ind_advec
+
+ self.compute_grid_size = compute_grid_size
+ self.compute_grid_shape = compute_grid_shape
+ self.compute_grid_bytes = compute_grid_bytes
+ self.compute_grid_mesh_info = compute_grid_mesh_info
+ self.view = view
+
+ self.S0_min = S0_min
+ self.S0_max = S0_max
+ self.S1_min = S1_min
+ self.S1_max = S1_max
+
+ self.S0_in_ghosts = S0_in_ghosts
+ self.S0_in_grid_ghosts = S0_in_grid_ghosts
+ self.S0_in_grid_size = S0_in_grid_size
+ self.S0_in_grid_shape = S0_in_grid_shape
+ self.S0_in_mesh_info = S0_in_mesh_info
+ self.S0_in_view_ghosts = S0_in_view
+
+ self.S0_out_ghosts = S0_out_ghosts
+ self.S0_out_grid_ghosts = S0_out_grid_ghosts
+ self.S0_out_grid_size = S0_out_grid_size
+ self.S0_out_grid_shape = S0_out_grid_shape
+ self.S0_out_mesh_info = S0_out_mesh_info
+ self.S0_out_view_ghosts = S0_out_view
+
+ self.S1_in_ghosts = S1_in_ghosts
+ self.S1_in_grid_ghosts = S1_in_grid_ghosts
+ self.S1_in_grid_size = S1_in_grid_size
+ self.S1_in_grid_shape = S1_in_grid_shape
+ self.S1_in_mesh_info = S1_in_mesh_info
+ self.S1_in_view_ghosts = S1_in_view
+
+ self.S1_out_ghosts = S1_out_ghosts
+ self.S1_out_grid_ghosts = S1_out_grid_ghosts
+ self.S1_out_grid_size = S1_out_grid_size
+ self.S1_out_grid_shape = S1_out_grid_shape
+ self.S1_out_mesh_info = S1_out_mesh_info
+ self.S1_out_view_ghosts = S1_out_view
+
+ self.host_buffers_init = host_buffers_init
+ self.host_buffers_reference = host_buffers_reference
+ self.host_buffers_gpu = host_buffers_gpu
+ self.device_buffers = device_buffers
+
+ print \
+'''
+== Directional Remesh Test ==
+ platform: {}
+ device: {}
+ dtype: {}
+
+ compute_grid_size: {}
+ dx: {}
+ inv_dx: {}
+
+ S0_in_grid_ghosts: {}
+ S1_in_grid_ghosts: {}
+ S0_out_grid_ghosts: {}
+ S1_out_grid_ghosts: {}
+
+ MAX_ADVEC: {}
+ MAX_P: {}
+ min_ghosts_in: {}
+ min_ghosts_out: {}
+
+ umin: {}
+ umax: {}
+ cfl: {}
+ dt: {}
+
+ local_work_size: {}
+ work_load: {}
+======= end of setup ========
+'''.format(platform.name, device.name, dtype.__name__,
+ compute_grid_size, dx, inv_dx,
+ S0_in_grid_ghosts, S1_in_grid_ghosts,
+ S0_out_grid_ghosts, S1_out_grid_ghosts,
+ MAX_ADVEC, MAX_P, min_ghosts_in, min_ghosts_out,
+ umin, umax, cfl, dt,
+ local_work_size, work_load)
+
+
+ @classmethod
+ def teardown_class(cls):
+ pass
+
+ def setup_method(self, method):
+ pass
+
+ def teardown_method(self, method):
+ pass
+
+ def _do_advec_on_cpu(self, rk_scheme, boundary):
+ print '_do_advec_on_cpu({}, {})'.format(rk_scheme.name(), boundary)
+ dt = self.dt
+ dx = self.dx
+ inv_dx = self.inv_dx
+ compute_grid_size = self.compute_grid_size
+
+ is_periodic = False
+ view = copy.copy(self.view)
+ if boundary == BoundaryCondition.PERIODIC:
+ target = 'no_ghosts'
+ is_periodic = True
+ elif boundary == BoundaryCondition.NONE:
+ target = 'with_ghosts'
+ else:
+ msg='Unknown boundary.'
+ raise ValueError(msg)
+
+ host_init_buffers = self.host_buffers_init[target]
+ host_buffers_reference = self.host_buffers_reference[target]
+ device_buffers = self.device_buffers[target]
+
+ velocity = host_init_buffers['u']
+ pos = host_init_buffers['pos']
+
+ pos[...] = np.arange(compute_grid_size[0])[None,None,:]
+
+ pos*=dx
+
+ def interp_velocity(X):
+ Gx = compute_grid_size[0]
+ X = X.copy() * inv_dx
+ lidx = np.floor(X).astype(np.int32)
+ alpha = X-lidx
+ if is_periodic:
+ lidx = (lidx+Gx)%Gx
+ ridx = (lidx+1)%Gx
+ else:
+ ridx = lidx+1
+ Vl = np.empty_like(X)
+ Vr = np.empty_like(X)
+ for i in xrange(*view[0].indices(compute_grid_size[2])):
+ for j in xrange(*view[1].indices(compute_grid_size[1])):
+ Vl[i,j,:] = velocity[i,j, lidx[i,j,:]]
+ Vr[i,j,:] = velocity[i,j, ridx[i,j,:]]
+ return Vl + alpha*(Vr-Vl)
+
+ if rk_scheme.name() == 'Euler':
+ pos += velocity[view]*dt
+ elif rk_scheme.name() == 'RK2':
+ X0 = pos.copy()
+ K0 = velocity[view]
+ X1 = X0 + 0.5*K0*dt;
+ K1 = interp_velocity(X1)
+ K = K1;
+ pos = X0+K*dt
+ elif rk_scheme.name() == 'RK4':
+ X0 = pos.copy()
+ K0 = velocity[view]
+ X1 = X0 + 0.5*K0*dt;
+ K1 = interp_velocity(X1)
+ X2 = X0 + 0.5*K1*dt;
+ K2 = interp_velocity(X2)
+ X3 = X0 + 1.0*K2*dt;
+ K3 = interp_velocity(X3)
+ K = 1./6*K0 + 2./6*K1 + 2./6*K2 + 1./6*K3
+ pos = X0+K*dt
+ else:
+ msg = 'Unknown Runge-Kutta scheme {}.'.format(rk_scheme)
+ raise ValueError(msg)
+
+ host_buffers_reference['pos'] = pos
+ cl.enqueue_copy(self.queue,device_buffers['pos'], pos)
+
+ def _do_remesh_on_cpu(self, rk_scheme, boundary, kernel, remesh_criteria_eps):
+ print
+ print '_do_remesh_on_cpu({}, {}, {}, {})'.format(rk_scheme, boundary,
+ kernel, remesh_criteria_eps)
+
+ assert (kernel.n <= self.MAX_MOMENTS)
+ assert (kernel.n % 2 == 0)
+ assert (remesh_criteria_eps is None) or (remesh_criteria_eps>0)
+
+ P = 1 + kernel.n/2
+
+ eps = self.eps
+ dt = self.dt
+ dx = self.dx
+ inv_dx = self.inv_dx
+
+ compute_grid_size = self.compute_grid_size
+ compute_grid_shape = self.compute_grid_shape
+
+ theorical_min_ind_advec = self.theorical_min_ind_advec
+ theorical_max_ind_advec = self.theorical_max_ind_advec
+
+ theorical_min_ind = theorical_min_ind_advec - P
+ theorical_max_ind = theorical_max_ind_advec + P
+ G = self.MAX_ADVEC + P
+
+ view = copy.copy(self.view)
+ no_ghosts = [0,0,0]
+
+ if boundary == BoundaryCondition.PERIODIC:
+ S0_ghosts_in = no_ghosts
+ S1_ghosts_in = no_ghosts
+ S0_ghosts_out = no_ghosts
+ S1_ghosts_out = no_ghosts
+
+ S0_in_view = view
+ S1_in_view = view
+ S0_out_view = view
+ S1_out_view = view
+
+ is_periodic = True
+ target = 'no_ghosts'
+ elif boundary == BoundaryCondition.NONE:
+ S0_ghosts_in = self.S0_in_grid_ghosts
+ S1_ghosts_in = self.S1_in_grid_ghosts
+ S0_ghosts_out = self.S0_out_grid_ghosts
+ S1_ghosts_out = self.S1_out_grid_ghosts
+ assert S0_ghosts_out[0] >= G
+ assert S1_ghosts_out[0] >= G
+
+ S0_in_view = self.S0_in_view_ghosts
+ S1_in_view = self.S1_in_view_ghosts
+ S0_out_view = self.S0_out_view_ghosts
+ S1_out_view = self.S1_out_view_ghosts
+
+ is_periodic = False
+ target = 'with_ghosts'
+ else:
+ msg='Unknown boundary.'
+ raise ValueError(msg)
+
+ host_init_buffers = self.host_buffers_init[target]
+ host_buffers_reference = self.host_buffers_reference[target]
+ device_buffers = self.device_buffers[target]
+
+ S0_in = host_init_buffers['S0_in']
+ S1_in = host_init_buffers['S1_in']
+ S0_out = host_buffers_reference['S0_out']
+ S1_out = host_buffers_reference['S1_out']
+ pos = host_buffers_reference['pos']
+
+ dx, inv_dx = self.dx, self.inv_dx
+
+ min_pos = 0
+ pos -= min_pos
+
+ # floor is round toward negative infinity in numpy
+ ind = np.floor(pos*inv_dx).astype(np.int32)
+ y = (pos - ind*dx)*inv_dx
+
+ min_ind, max_ind = np.min(ind), np.max(ind)
+ ymin, ymax = np.min(y), np.max(y)
+
+ if self.DEBUG:
+ print 'imin={}, imax={}'.format(min_ind, max_ind)
+ print 'ymin={}, ymax={}'.format(ymin, ymax)
+ y = np.clip(y, 0.0, 1.0)
+ #assert (y>=0.0).all() and (y<1.0).all()
+
+
+ if min_ind < theorical_min_ind:
+ msg0='min_ind={} <= floor(umin*dt*inv_dx)={}'.format(min_ind, theorical_min_ind_advec)
+ raise RuntimeError(msg0)
+
+ if max_ind > theorical_max_ind:
+ msg1='max_ind={} <= floor(umax*dt*inv_dx)={}'.format(max_ind, theorical_max_ind_advec)
+ raise RuntimeError(msg1)
+
+ Gx = compute_grid_size[0]
+ ind -= P
+ if is_periodic:
+ ind = (ind+Gx)%Gx
+ assert (G+ind+1>=0).all()
+
+ S0_out[...] = 0.0
+ S1_out[...] = 0.0
+ S0_not_remeshed = 0.0
+ S1_not_remeshed = 0.0
+ for q in xrange(-P, +P):
+ yi = y+q
+ wi = kernel.gamma(yi)
+ ind += 1
+ if is_periodic:
+ ind %= Gx
+ if self.DEBUG:
+ print 'ind', ind[0,0,:]
+ print 'yi', yi[0,0,:]
+ print
+
+ _min_ind, _max_ind = np.min(ind), np.max(ind)
+ assert (_min_ind >= theorical_min_ind).all()
+ assert (_max_ind <= theorical_max_ind).all()
+
+ for i in xrange(*view[0].indices(compute_grid_size[2])):
+ for j in xrange(*view[1].indices(compute_grid_size[1])):
+ for k in xrange(*view[2].indices(compute_grid_size[0])):
+ in_index = (S0_ghosts_in[2] + i,
+ S0_ghosts_in[1] + j,
+ S0_ghosts_in[0] + k)
+ out_index = (S0_ghosts_out[2] + i,
+ S0_ghosts_out[1] + j,
+ S0_ghosts_out[0] + ind[i,j,k])
+ sin = S0_in[in_index]
+ W = wi[i,j,k]
+ val = W * sin
+ if (remesh_criteria_eps is None) or (abs(sin)>remesh_criteria_eps*eps):
+ S0_out[out_index] += val
+ else:
+ S0_not_remeshed += val
+
+ if self.DEBUG and (i==0) and (j==0):
+ print 'wrote {:0.6f} to index {} with y={}, s0={} and W={}'.format(val,
+ out_index[2], y[i,j,k], sin, W )
+
+ in_index = (S1_ghosts_in[2] + i,
+ S1_ghosts_in[1] + j,
+ S1_ghosts_in[0] + k)
+ out_index = (S1_ghosts_out[2] + i,
+ S1_ghosts_out[1] + j,
+ S1_ghosts_out[0] + ind[i,j,k])
+ sin = S1_in[in_index]
+ val = W * sin
+ if (remesh_criteria_eps is None) or (abs(sin)>remesh_criteria_eps*eps):
+ S1_out[out_index] += val
+ else:
+ S1_not_remeshed += val
+
+
+ # check if scalar was conserved
+ I0 = np.sum(S0_in[S0_in_view])
+ I1 = np.sum(S0_out)
+ J0 = np.sum(S1_in[S1_in_view])
+ J1 = np.sum(S1_out)
+
+ err0 = I1-I0+S0_not_remeshed
+ err1 = J1-J0+S1_not_remeshed
+
+ if not np.allclose(I0, I1+S0_not_remeshed):
+ msg = '#S0 failed: I0:{} != I1:{}, not remeshed {:3.02}%'.format(I0,I1,
+ abs(100*S1_not_remeshed/J0))
+ raise ValueError(msg)
+ else:
+ print '#S0 remesh error: {} ({} eps, not remeshed {:3.02}%)'.format(err0, int(err0/eps),
+ abs(100*S0_not_remeshed/I0))
+
+ if not np.isclose(J0, J1+S1_not_remeshed):
+ msg = '#S1 failed: J0:{} != J1:{}, not remesh {:3.02}%'.format(J0,J1,
+ abs(100*S1_not_remeshed/J0))
+
+ raise ValueError(msg)
+ else:
+ print '#S0 remesh error: {} ({} eps, not remeshed {:3.02}%)'.format(err1, int(err1/eps),
+ abs(100*S1_not_remeshed/J0))
+
+ host_buffers_reference['S0_out'][...] = S0_out
+ host_buffers_reference['S1_out'][...] = S1_out
+
+ def _do_compute_on_gpu_and_check(self, cl_env,
+ boundary, kernel, work_dim,
+ is_inplace, use_atomics,
+ remesh_criteria_eps,
+ nparticles, nscalars):
+
+ msg = '\n*testing directional {}d remesh with {}\n'
+ msg+= ' boundaries={}, npart={}, nscalars={} inplace={}, atomic={}, criteria={}'
+ msg=msg.format(work_dim, kernel, str(boundary).lower(),
+ nparticles, nscalars, is_inplace, use_atomics, remesh_criteria_eps)
+ print msg
+
+ work_size = self.compute_grid_size
+ work_load = self.work_load
+ local_work_size = self.local_work_size
+ queue = self.queue
+
+ eps = self.eps
+ itemsize = self.itemsize
+
+ sboundary = (boundary, boundary,)
+ typegen = cl_env.typegen
+ ftype = typegen.fbtype
+ scalar_cfl = self.cfl
+
+ compute_grid_size = self.compute_grid_size
+ compute_grid_shape = self.compute_grid_shape
+ compute_grid_mesh_info = self.compute_grid_mesh_info
+ pos_mesh_info = compute_grid_mesh_info
+
+ assert compute_grid_size[0] >= nparticles
+ assert kernel.n % 2 == 0
+ P = 1 + kernel.n/2
+ G = self.MAX_ADVEC + P
+
+ view = copy.copy(self.view)
+
+ if boundary == BoundaryCondition.PERIODIC:
+ S0_in_mesh_info = compute_grid_mesh_info
+ S1_in_mesh_info = compute_grid_mesh_info
+ S0_out_mesh_info = compute_grid_mesh_info
+ S1_out_mesh_info = compute_grid_mesh_info
+
+ S0_in_grid_size = compute_grid_size
+ S0_out_grid_size = compute_grid_size
+ S1_in_grid_size = compute_grid_size
+ S1_out_grid_size = compute_grid_size
+
+ S0_in_grid_ghosts = [0,0,0]
+ S0_out_grid_ghosts = [0,0,0]
+ S1_out_grid_ghosts = [0,0,0]
+ S1_in_grid_ghosts = [0,0,0]
+
+ S0_in_view = copy.copy(view)
+ S1_in_view = copy.copy(view)
+ S0_out_view = copy.copy(view)
+ S1_out_view = copy.copy(view)
+
+ S0_out_compute_grid_view = copy.copy(view)
+ S1_out_compute_grid_view = copy.copy(view)
+
+ S0_in_offset = 0
+ S1_in_offset = 0
+ S0_out_offset = 0
+ S1_out_offset = 0
+
+ is_periodic = True
+ target = 'no_ghosts'
+
+ elif boundary == BoundaryCondition.NONE:
+ S0_in_mesh_info = self.S0_in_mesh_info
+ S1_in_mesh_info = self.S1_in_mesh_info
+ S0_out_mesh_info = self.S0_out_mesh_info
+ S1_out_mesh_info = self.S1_out_mesh_info
+
+ S0_in_grid_size = self.S0_in_grid_size
+ S0_out_grid_size = self.S0_out_grid_size
+ S1_in_grid_size = self.S1_in_grid_size
+ S1_out_grid_size = self.S1_out_grid_size
+
+ S0_in_grid_ghosts = self.S0_in_grid_ghosts
+ S0_out_grid_ghosts = self.S0_out_grid_ghosts
+ S1_out_grid_ghosts = self.S1_out_grid_ghosts
+ S1_in_grid_ghosts = self.S1_in_grid_ghosts
+
+ S0_in_view = copy.copy(self.S0_in_view_ghosts)
+ S1_in_view = copy.copy(self.S1_in_view_ghosts)
+ S0_out_view = copy.copy(self.S0_out_view_ghosts)
+ S1_out_view = copy.copy(self.S1_out_view_ghosts)
+
+ S0_out_compute_grid_view = copy.copy(self.S0_out_view_ghosts)
+ S1_out_compute_grid_view = copy.copy(self.S1_out_view_ghosts)
+
+ S0_in_offset = 0
+ S1_in_offset = 0
+ S0_out_offset = 0
+ S1_out_offset = 0
+
+ if work_dim == 3:
+ pass
+ elif work_dim == 2:
+ S0_in_offset = S0_in_grid_ghosts[2]*S0_in_grid_size[1]*S0_in_grid_size[0]
+ S1_in_offset = S1_in_grid_ghosts[2]*S1_in_grid_size[1]*S1_in_grid_size[0]
+ S0_out_offset = S0_out_grid_ghosts[2]*S0_out_grid_size[1]*S0_out_grid_size[0]
+ S1_out_offset = S1_out_grid_ghosts[2]*S1_out_grid_size[1]*S1_out_grid_size[0]
+ elif work_dim == 1:
+ S0_in_offset = (S0_in_grid_ghosts[2]*S0_in_grid_size[1]+S0_in_grid_ghosts[1])*S0_in_grid_size[0]
+ S1_in_offset = (S1_in_grid_ghosts[2]*S1_in_grid_size[1]+S1_in_grid_ghosts[1])*S1_in_grid_size[0]
+ S0_out_offset = (S0_out_grid_ghosts[2]*S0_out_grid_size[1]+S0_out_grid_ghosts[1])*S0_out_grid_size[0]
+ S1_out_offset = (S1_out_grid_ghosts[2]*S1_out_grid_size[1]+S1_out_grid_ghosts[1])*S1_out_grid_size[0]
+ else:
+ msg='Invalid work dimesion {}.'.format(work_dim)
+ raise ValueError(msg)
+
+ S0_in_offset *= itemsize
+ S1_in_offset *= itemsize
+ S0_out_offset *= itemsize
+ S1_out_offset *= itemsize
+
+ assert S0_out_grid_ghosts[0] >= G
+ assert S1_out_grid_ghosts[0] >= G
+ S0_out_view[-1] = slice(S0_out_grid_ghosts[0] - G, compute_grid_size[0] + (S0_out_grid_ghosts[0] - G) + 2*G)
+ S1_out_view[-1] = slice(S1_out_grid_ghosts[0] - G, compute_grid_size[0] + (S1_out_grid_ghosts[0] - G) + 2*G)
+
+ is_periodic = False
+ target = 'with_ghosts'
+ else:
+ msg='Unknown boundary.'
+ raise ValueError(msg)
+
+ # adapt to current work_dim
+ for i in xrange(work_dim,3):
+ view[2-i] = 0
+ S0_in_view[2-i] = S0_in_grid_ghosts[2-i]
+ S1_in_view[2-i] = S1_in_grid_ghosts[2-i]
+ S0_out_view[2-i] = S0_out_grid_ghosts[2-i]
+ S1_out_view[2-i] = S1_out_grid_ghosts[2-i]
+ S0_out_compute_grid_view[2-i] = S0_out_grid_ghosts[2-i]
+ S1_out_compute_grid_view[2-i] = S1_out_grid_ghosts[2-i]
+
+ compute_grid_size = compute_grid_size[:work_dim]
+ compute_grid_shape = compute_grid_shape[:work_dim]
+
+ work_size = work_size[:work_dim]
+ work_load = work_load[:work_dim]
+ local_work_size = local_work_size[:work_dim]
+
+ views = {
+ 'u': view,
+ 'pos': view,
+ 'S0_in': S0_in_view,
+ 'S1_in': S1_in_view,
+ 'S0_out': S0_out_view,
+ 'S1_out': S1_out_view,
+ }
+
+ known_vars = {
+ 'local_size': local_work_size,
+ 'position_mesh_info': pos_mesh_info,
+ 'S0_in_mesh_info': S0_in_mesh_info,
+ 'S1_in_mesh_info': S1_in_mesh_info,
+ 'S0_out_mesh_info': S0_out_mesh_info,
+ 'S1_out_mesh_info': S1_out_mesh_info,
+ }
+
+ host_init_buffers = self.host_buffers_init[target]
+ host_buffers_reference = self.host_buffers_reference[target]
+ host_buffers_gpu = self.host_buffers_gpu[target]
+ device_buffers = self.device_buffers[target]
+
+ drk = DirectionalRemeshKernel(typegen=typegen,
+ work_dim=work_dim, ftype=ftype,
+ nparticles=nparticles, nscalars=nscalars,
+ sboundary=sboundary, is_inplace=is_inplace,
+ remesh_kernel=kernel,
+ scalar_cfl=scalar_cfl,
+ use_atomics=use_atomics,
+ remesh_criteria_eps=remesh_criteria_eps,
+ symbolic_mode=False,
+ debug_mode=self.DEBUG,
+ known_vars=known_vars)
+
+ #drk.edit()
+
+ global_work_size = drk.get_global_size(work_size, local_work_size, work_load)
+ (static_shared_bytes, dynamic_shared_bytes, total_sharedbytes) = \
+ drk.required_workgroup_cache_size(local_work_size)
+ assert dynamic_shared_bytes==0
+
+ in_variables = ['pos']
+ in_variables_offsets = [0]
+
+ out_variables = []
+ out_variables_offsets = []
+
+ if is_inplace:
+ in_variables += ['S{}_out'.format(i) for i in xrange(nscalars)]
+ in_variables_offsets += [S0_out_offset, S1_out_offset][:nscalars]
+ else:
+ in_variables += ['S{}_in'.format(i) for i in xrange(nscalars)]
+ in_variables_offsets += [S0_in_offset, S1_in_offset][:nscalars]
+ out_variables += ['S{}_out'.format(i) for i in xrange(nscalars)]
+ out_variables_offsets += [S0_out_offset, S1_out_offset][:nscalars]
+
+ if self.DEBUG:
+ print 'in_variables: {}'.format(in_variables)
+ print 'in_variables_offsets: {}'.format(in_variables_offsets)
+ print
+ print 'out_variables: {}'.format(out_variables)
+ print 'out_variables_offsets: {}'.format(out_variables_offsets)
+ print
+
+ debug = ['dbg0', 'dbg1']
+
+ kernel_args = []
+ for varname, varoffset in zip(in_variables, in_variables_offsets):
+ kernel_args.append(device_buffers[varname])
+ kernel_args.append(np.uint64(varoffset))
+
+ if not is_inplace:
+ for varname, varoffset in zip(out_variables, out_variables_offsets):
+ kernel_args.append(device_buffers[varname])
+ kernel_args.append(np.uint64(varoffset))
+ if self.DEBUG:
+ for varname in debug:
+ kernel_args.append(device_buffers[varname])
+ if (dynamic_shared_bytes > 0):
+ shared_buffer = cl.LocalMemory(dynamic_shared_bytes)
+ kernel_args.append(shared_buffer)
+
+ if self.DEBUG:
+ print ' Generating and compiling Kernel...'
+ source = drk.__str__()
+ prg = cl.Program(self.context, source)
+ prg.build(devices=[self.device])
+ cl_kernel = prg.all_kernels()[0]
+
+ try:
+ cl_kernel.set_args(*kernel_args)
+ except:
+ msg='call to set_args failed, args were: {}'.format(kernel_args)
+ raise RuntimeError(msg)
+
+ if self.DEBUG:
+ print ' CPU => GPU: ',
+ for buf in in_variables + out_variables + debug:
+ if self.DEBUG:
+ print '{}, '.format(buf),
+ if buf == 'pos':
+ src = host_buffers_reference[buf]
+ elif is_inplace and buf in ['S0_out', 'S1_out']:
+ src = np.full_like(fill_value=np.nan, a=host_init_buffers[buf])
+ if buf == 'S0_out':
+ src[S0_out_compute_grid_view] = host_init_buffers['S0_in'][S0_in_view]
+ if self.DEBUG:
+ print ' set to: ', src[S0_out_view]
+ print
+ else:
+ src[S1_out_compute_grid_view] = host_init_buffers['S1_in'][S1_in_view]
+ if self.DEBUG:
+ print ' set to: ', src[S1_out_view]
+ print
+ else:
+ src = host_init_buffers[buf]
+ dst = device_buffers[buf]
+ cl.enqueue_copy(queue,dst,src)
+ if self.DEBUG:
+ print
+
+ if self.DEBUG:
+ print ' Kernel execution <<<{},{}>>>'.format(global_work_size,local_work_size)
+ evt = cl.enqueue_nd_range_kernel(queue, cl_kernel,
+ global_work_size.tolist(), local_work_size.tolist())
+ evt.wait()
+
+ if self.DEBUG:
+ print ' GPU => CPU: ',
+ for buf in in_variables+out_variables+debug:
+ if self.DEBUG:
+ print '{}, '.format(buf),
+ src = device_buffers[buf]
+ dst = host_buffers_gpu[buf]
+ cl.enqueue_copy(queue,dst,src)
+
+ if self.DEBUG:
+ print
+ print ' Synchronizing queue'
+ print
+
+ queue.flush()
+ queue.finish()
+
+ if (self.DEBUG):
+ print 'WORKDIM = {}'.format(work_dim)
+ print 'ADVEC = {}'.format(self.MAX_ADVEC)
+ print 'P = {}'.format(P)
+ print 'G = {}'.format(G)
+ print
+ if not is_inplace:
+ print '::S0_in::\n *grid_size={}\n *ghosts={}\n *offset={}\n *view={}'.format(
+ S0_in_grid_size, S0_in_grid_ghosts, S0_in_offset, S0_in_view)
+ print
+ if nscalars > 1:
+ print '::S1_in::\n *grid_size={}\n *ghosts={}\n *offset={}\n *view={}'.format(
+ S1_in_grid_size, S1_in_grid_ghosts, S1_in_offset, S1_in_view)
+ print
+ print '::S0_out::\n *grid_size={}\n *ghosts={}\n *offset={}\n *compute_grid_view={}\n *view={}'.format(
+ S0_out_grid_size, S0_out_grid_ghosts, S0_out_offset, S0_out_compute_grid_view, S0_out_view)
+ print
+ if nscalars > 1:
+ print '::S1_out::\n *grid_size={}\n *ghosts={}\n *offset={}\n *compute_grid_view={}\n *view={}'.format(
+ S1_out_grid_size, S1_out_grid_ghosts, S1_out_offset, S1_out_compute_grid_view, S1_out_view)
+ print
+
+ if work_dim < 3:
+ print '::velocity CPU::\n{}'.format(host_buffers_reference['u'][view])
+ print '::velocity GPU::\n{}'.format(host_buffers_gpu['u'][view])
+ print
+
+ print '::pos CPU::\n{}'.format(host_buffers_reference['pos'][view])
+ print '::pos GPU::\n{}'.format(host_buffers_gpu['pos'][view])
+ print
+
+ print '::S0_in CPU::\n{}'.format(host_init_buffers['S0_in'][S0_in_view])
+ if not is_inplace:
+ print '::S0_in GPU::\n{}'.format(host_buffers_gpu['S0_in'][S0_in_view])
+ print
+ else:
+ print
+
+ if nscalars > 1:
+ print '::S1_in CPU::\n{}'.format(host_init_buffers['S1_in'][S1_in_view])
+ if not is_inplace:
+ print '::S1_in GPU::\n{}'.format(host_buffers_gpu['S1_in'][S1_in_view])
+ print
+ else:
+ print
+
+ print '::S0_out CPU::\n{}'.format(host_buffers_reference['S0_out'][S0_out_view])
+ print '::S0_out GPU::\n{}'.format(host_buffers_gpu['S0_out'][S0_out_view])
+ print
+
+ if nscalars > 1:
+ print '::S1_out CPU::\n{}'.format(host_buffers_reference['S1_out'][S1_out_view])
+ print '::S1_out GPU::\n{}'.format(host_buffers_gpu['S1_out'][S1_out_view])
+ print
+
+ print '::DBG0 GPU::\n{}'.format(host_buffers_gpu['dbg0'][view])
+ print '::DBG1 GPU::\n{}'.format(host_buffers_gpu['dbg1'][view])
+ print
+
+ variables = out_variables
+ if self.DEBUG:
+ variables += in_variables
+ if not is_inplace:
+ variables.remove('S0_in')
+ if nscalars > 1:
+ variables.remove('S1_in')
+
+ buffers = [(varname,
+ host_buffers_reference[varname][views[varname]],
+ host_buffers_gpu[varname][views[varname]])
+ for varname in variables]
+ self._cmp_buffers(buffers,drk,work_dim,kernel)
+
+ def _cmp_buffers(self, buffers,drk,work_dim,kernel):
+ good = True
+ err_buffers = []
+ eps = self.eps
+
+ for (name,host,dev) in buffers:
+ (l1,l2,linf) = self._distances(host,dev)
+ neps = (1<<(kernel.r+10))*int(max((self.S0_max - self.S0_min), (self.S1_max - self.S1_min)))
+ prec = neps*eps
+ print ' {} -> l1={} ({} eps) l2={} ({} eps) linf={} ({} eps)'.format(name,
+ l1, int(l1/eps) if np.isfinite(l1) else l1,
+ l2, int(l2/eps) if np.isfinite(l2) else l2,
+ linf, int(linf/eps) if np.isfinite(linf) else linf)
+ if l2>prec:
+ err_buffers.append(name)
+ good = False
+ if not good:
+ print ' max error was set to {} eps ({}).'.format(neps, prec)
+ msg = '\n[FAIL] Buffer comparisson failed for buffers {}.\n'.format(err_buffers)
+ print msg
+ drk.edit()
+ if self.enable_error_plots:
+ from matplotlib import pyplot as plt
+ for (name,host,dev) in buffers:
+ if name in err_buffers:
+
+ host = host
+ dev = dev
+
+ d = (dev-host)*(dev-host)
+ d -= np.mean(d)
+
+ def on_key_press(evt):
+ if evt.key in ['enter', 'escape']:
+ plt.close(evt.canvas.figure)
+
+ if work_dim==3:
+ fig,axes = plt.subplots(2,2)
+ fig.canvas.mpl_connect('key_press_event', on_key_press)
+ axes[0][0].imshow(np.sum(d,axis=0),interpolation='nearest')
+ axes[0][1].imshow(np.sum(d,axis=1),interpolation='nearest')
+ axes[1][0].imshow(np.sum(d,axis=2),interpolation='nearest')
+ axes[1][1].imshow(np.sum(d,axis=(0,1))[np.newaxis,:],
+ interpolation='nearest')
+ plt.title(name)
+ print('Press any key to close all windows.')
+ plt.show(block=True)
+ break
+ elif work_dim==2:
+ fig,axe = plt.subplots()
+ fig.canvas.mpl_connect('key_press_event', on_key_press)
+ axe.imshow(d,interpolation='nearest')
+ print('Press any key to close all windows.')
+ plt.show(block=True)
+ break
+ else:
+ pass
+ raise RuntimeError(msg)
+
+ def _distances(self,lhs,rhs):
+ d = rhs-lhs
+ da = np.abs(d)
+
+ l1 = np.sum(da)/d.size
+ l2 = np.sqrt(np.sum(d*d)/d.size)
+ linf = np.max(da)
+ return (l1,l2,linf)
+
+
+ def _check_kernels(self, rk_scheme, cfl):
+ assert cfl>0
+ check_instance(rk_scheme,ExplicitRungeKutta)
+
+ nscalars=[2]
+ boundaries=[BoundaryCondition.PERIODIC, BoundaryCondition.NONE]
+
+ split_polys=[False, True]
+ use_atomics=[False, True]
+ is_inplaces=[False, True]
+ remesh_criterias=[None, 1000000]
+ nparticles=[1,2,4,8,16]
+
+ if self.enable_extra_tests:
+ kernels=[(2,1), (2,2), (4,2), (4,4), (6,4), (6,6), (8,4)]
+ work_dims=[1,2,3]
+ else:
+ kernels=[(2,1),(8,4)]
+ work_dims=[2]
+
+ ntests = 0
+ for cl_env in iter_clenv(precision=Precision.FLOAT):
+ self._initialize(cl_env=cl_env, cfl=cfl)
+ for boundary in boundaries:
+ print
+ self._do_advec_on_cpu(boundary=boundary, rk_scheme=rk_scheme)
+ for kernel_config in kernels:
+ for split_poly in split_polys:
+ kernel = RemeshKernel(*kernel_config, split_polys=split_poly, verbose=False)
+ for remesh_criteria_eps in remesh_criterias:
+ self._do_remesh_on_cpu(boundary=boundary, rk_scheme=rk_scheme,
+ kernel=kernel, remesh_criteria_eps=remesh_criteria_eps)
+ for work_dim in work_dims:
+ for is_inplace in is_inplaces:
+ for use_atomic in use_atomics:
+ for nparticle in nparticles:
+ if (not use_atomic) and (nparticle<=int(2*np.floor(cfl)+1)):
+ continue
+ for nscalar in nscalars:
+ self._do_compute_on_gpu_and_check(cl_env=cl_env,
+ boundary=boundary, kernel=kernel, work_dim=work_dim,
+ is_inplace=is_inplace, use_atomics=use_atomic,
+ remesh_criteria_eps=remesh_criteria_eps,
+ nparticles=nparticle, nscalars=nscalar)
+ ntests += 1
+ print
+ print 'DirectionalRemesh: All {} tests passed.'.format(ntests)
+
+
+ @opencl_failed
+ def test_remesh_from_Euler_advection_low_cfl(self, cfl=0.5788):
+ rk_scheme=ExplicitRungeKutta('Euler')
+ self._check_kernels(rk_scheme=rk_scheme, cfl=cfl)
+
+ @opencl_failed
+ def test_remesh_from_Euler_advection_high_cfl(self, cfl=1.78):
+ rk_scheme=ExplicitRungeKutta('Euler')
+ self._check_kernels(rk_scheme=rk_scheme, cfl=cfl)
+
+if __name__ == '__main__':
+ if not __HAS_OPENCL_BACKEND__:
+ msg='OpenCL is not present.'
+ raise RuntimeError(msg)
+
+ TestDirectionalRemesh.setup_class(enable_extra_tests=False,
+ enable_error_plots=True)
+ test = TestDirectionalRemesh()
+
+ with printoptions(linewidth=200,
+ formatter={'float':lambda x: '{:0.2f}'.format(x)}):
+ test.test_remesh_from_Euler_advection_low_cfl()
+ test.test_remesh_from_Euler_advection_high_cfl()
+
+ TestDirectionalRemesh.teardown_class()
+
diff --git a/hysop/backend/device/codegen/kernels/tests/test_directional_stretching.py b/hysop/backend/device/codegen/kernels/tests/test_directional_stretching.py
new file mode 100644
index 0000000000000000000000000000000000000000..ef41f9b03e95b007d079ba523586fddea00cebc2
--- /dev/null
+++ b/hysop/backend/device/codegen/kernels/tests/test_directional_stretching.py
@@ -0,0 +1,581 @@
+
+import copy
+
+from hysop import __ENABLE_LONG_TESTS__
+from hysop.backend.device.opencl import cl
+from hysop.tools.types import check_instance
+from hysop.constants import np, BoundaryCondition
+from hysop.backend.device.codegen.base.test import _test_mesh_info , _test_typegen
+from hysop.backend.device.codegen.kernels.directional_stretching import DirectionalStretchingKernel
+from hysop.methods import StretchingFormulation
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta
+
+class TestDirectionalStretching(object):
+
+ @classmethod
+ def setup_class(cls,
+ do_extra_tests=__ENABLE_LONG_TESTS__,
+ enable_error_plots=False):
+ typegen = _test_typegen('double','dec')
+ dtype = np.float64
+
+ queue = cl.CommandQueue(typegen.context)
+ ctx = typegen.context
+
+ grid_size = np.asarray([50,10,10])
+ compute_grid_ghosts = np.asarray([3*4,0,0])
+ compute_grid_size = grid_size + 2*compute_grid_ghosts
+
+ (A,grid_mesh_info) = _test_mesh_info('grid_mesh_info', typegen,3,0,grid_size)
+ (B,compute_grid_mesh_info) = _test_mesh_info('compute_grid_mesh_info', typegen,3,compute_grid_ghosts,compute_grid_size)
+
+ grid_shape = grid_size[::-1]
+ compute_grid_shape = compute_grid_size[::-1]
+
+ assert A['inv_dx'][0] == B['inv_dx'][0]
+ inv_dx = A['inv_dx'][0]
+
+ grid_bytes = grid_size.size * typegen.FLT_BYTES[typegen.fbtype]
+ compute_grid_bytes = compute_grid_size.size * typegen.FLT_BYTES[typegen.fbtype]
+
+ mf = cl.mem_flags
+
+ host_buffers_init = {
+ 'no_ghosts': {
+ 'ux': np.random.rand(*grid_shape).astype(dtype),
+ 'uy': np.random.rand(*grid_shape).astype(dtype),
+ 'uz': np.random.rand(*grid_shape).astype(dtype),
+ 'wx': np.random.rand(*grid_shape).astype(dtype),
+ 'wy': np.random.rand(*grid_shape).astype(dtype),
+ 'wz': np.random.rand(*grid_shape).astype(dtype),
+ 'dbg0': -np.ones(shape=grid_shape, dtype=np.int32),
+ 'dbg1': -np.ones(shape=grid_shape, dtype=np.int32),
+ },
+ 'with_ghosts': {
+ 'ux': np.random.rand(*compute_grid_shape).astype(dtype),
+ 'uy': np.random.rand(*compute_grid_shape).astype(dtype),
+ 'uz': np.random.rand(*compute_grid_shape).astype(dtype),
+ 'wx': np.random.rand(*compute_grid_shape).astype(dtype),
+ 'wy': np.random.rand(*compute_grid_shape).astype(dtype),
+ 'wz': np.random.rand(*compute_grid_shape).astype(dtype),
+ 'dbg0': -np.ones(shape=compute_grid_shape, dtype=np.int32),
+ 'dbg1': -np.ones(shape=compute_grid_shape, dtype=np.int32),
+ }
+ }
+
+ device_buffers = {
+ 'no_ghosts': {
+ 'ux': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['ux']),
+ 'uy': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['uy']),
+ 'uz': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['uz']),
+ 'wx': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['wx']),
+ 'wy': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['wy']),
+ 'wz': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['wz']),
+ 'dbg0': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['dbg0']),
+ 'dbg1': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['no_ghosts']['dbg1']),
+ },
+ 'with_ghosts': {
+ 'ux': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['ux']),
+ 'uy': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['uy']),
+ 'uz': cl.Buffer(ctx, flags=mf.READ_ONLY | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['uz']),
+ 'wx': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['wx']),
+ 'wy': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['wy']),
+ 'wz': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['wz']),
+ 'dbg0': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['dbg0']),
+ 'dbg1': cl.Buffer(ctx, flags=mf.READ_WRITE | mf.COPY_HOST_PTR,
+ hostbuf=host_buffers_init['with_ghosts']['dbg1']),
+ }
+ }
+
+ host_buffers_reference = copy.deepcopy(host_buffers_init)
+ host_buffers_gpu = copy.deepcopy(host_buffers_init)
+
+ cls.typegen = typegen
+ cls.queue = queue
+
+ cls.grid_size = grid_size
+ cls.grid_shape = grid_shape
+ cls.grid_bytes = grid_bytes
+
+ cls.grid_mesh_info = grid_mesh_info
+ cls.compute_grid_mesh_info = compute_grid_mesh_info
+
+ cls.compute_grid_ghosts = compute_grid_ghosts
+ cls.compute_grid_size = compute_grid_size
+ cls.compute_grid_shape = compute_grid_shape
+ cls.compute_grid_bytes = compute_grid_bytes
+
+ cls.host_buffers_init = host_buffers_init
+ cls.host_buffers_reference = host_buffers_reference
+ cls.host_buffers_gpu = host_buffers_gpu
+ cls.device_buffers = device_buffers
+
+ Lx = min(typegen.device.max_work_item_sizes[0], typegen.device.max_work_group_size)
+ Lx = min(Lx, grid_size[0])
+
+ cls.local_work_size = np.asarray([Lx,1,1])
+ cls.work_load = np.asarray([1,2,3])
+ cls.inv_dx = inv_dx
+ cls.dt = dtype(0.5)
+
+ cls.do_extra_tests = do_extra_tests
+ cls.enable_error_plots = enable_error_plots
+
+
+ @classmethod
+ def teardown_class(cls):
+ pass
+
+ def setup_method(self, method):
+ pass
+
+ def teardown_method(self, method):
+ pass
+
+ def _do_compute_cpu(self, formulation, rk_scheme, order, direction,
+ boundary):
+
+ dt = self.dt
+ ghosts = self.compute_grid_ghosts
+ grid_size = self.grid_size
+
+ if boundary == BoundaryCondition.PERIODIC:
+ target = 'no_ghosts'
+ elif boundary == BoundaryCondition.NONE:
+ target = 'with_ghosts'
+ else:
+ raise ValueError()
+
+ if order==2:
+ stencil = [-1./2, 0, +1./2]
+ elif order==4:
+ stencil = [+1./12, -2./3, 0 , +2./3, -1./12]
+ elif order==6:
+ stencil = [-1./60, +3./20, -3./4, 0 , +3./4, -3./20, +1./60]
+ else:
+ raise ValueError()
+
+ def deriv(field):
+ res = np.zeros_like(field)
+ for i in xrange(-order/2,order/2+1,1):
+ res += stencil[i+order/2]*np.roll(field,-i,axis=2)
+ return res*self.inv_dx[0]
+
+ host_init_buffers = self.host_buffers_init[target]
+ host_buffers_reference = self.host_buffers_reference[target]
+
+ vorticity = ['wx','wy','wz']
+ velocity = ['ux','uy','uz']
+ U = [host_init_buffers[name].copy() for name in velocity]
+ W = [host_init_buffers[name].copy() for name in vorticity]
+ dUdx = [deriv(ui) for ui in U]
+
+ if rk_scheme.name() == 'Euler':
+ Wc = [ w.copy() for w in W ]
+ if formulation==StretchingFormulation.GRAD_UW:
+ for i in xrange(3):
+ W[i] += dt*dUdx[i]*Wc[direction]
+ elif formulation==StretchingFormulation.GRAD_UW_T:
+ for i in xrange(3):
+ W[direction] += dt*dUdx[i]*Wc[i]
+ elif formulation==StretchingFormulation.MIXED_GRAD_UW:
+ for i in xrange(3):
+ W[i] += 0.5*dt*dUdx[i]*Wc[direction]
+ W[direction] += 0.5*dt*dUdx[i]*Wc[i]
+ elif formulation==StretchingFormulation.CONSERVATIVE:
+ W0 = Wc
+ K0 = [deriv(ui*W0[direction]) for ui in U]
+ W1 = [W0[i] + dt*K0[i] for i in xrange(3)]
+ W = W1
+ else:
+ msg = 'Unknown stretching formulation scheme {}.'.format(formulation)
+ raise ValueError(msg)
+ elif rk_scheme.name() == 'RK2':
+ Wc = [ w.copy() for w in W ]
+ if formulation==StretchingFormulation.GRAD_UW:
+ W0 = Wc
+ K0 = [dUdx[i]*W0[direction] for i in xrange(3)]
+ W1 = [W0[i] + 0.5*dt*K0[i] for i in xrange(3)]
+ K1 = [dUdx[i]*W1[direction] for i in xrange(3)]
+ W2 = [W0[i] + 1.0*dt*K1[i] for i in xrange(3)]
+ W = W2
+ elif formulation==StretchingFormulation.GRAD_UW_T:
+ W0 = Wc
+ K0 = sum([dUdx[i]*W0[i] for i in xrange(3)])
+ W1 = W0[direction] + 0.5*dt*K0
+ K1 = sum([dUdx[i]*W0[i] for i in xrange(3) if i!=direction]) + W1*dUdx[direction]
+ W2 = W0
+ W2[direction] += dt*K1
+ W = W2
+ elif formulation==StretchingFormulation.MIXED_GRAD_UW:
+ W0 = Wc
+ K0 = [0.5*dUdx[i]*W0[direction] for i in xrange(3)]
+ K0[direction] += sum([0.5*dUdx[i]*W0[i] for i in xrange(3)])
+ W1 = [W0[i] + 0.5*dt*K0[i] for i in xrange(3)]
+ K1 = [0.5*dUdx[i]*W1[direction] for i in xrange(3)]
+ K1[direction] += sum([0.5*dUdx[i]*W1[i] for i in xrange(3)])
+ W2 = [W0[i] + 1.0*dt*K1[i] for i in xrange(3)]
+ W = W2
+ elif formulation==StretchingFormulation.CONSERVATIVE:
+ W0 = Wc
+ K0 = [deriv(ui*W0[direction]) for ui in U]
+ W1 = [W0[i] + 0.5*dt*K0[i] for i in xrange(3)]
+ K1 = [deriv(ui*W1[direction]) for ui in U]
+ W2 = [W0[i] + 1.0*dt*K1[i] for i in xrange(3)]
+ W = W2
+ else:
+ msg = 'Unknown stretching formulation scheme {}.'.format(formulation)
+ raise ValueError(msg)
+ elif rk_scheme.name() == 'RK4':
+ Wc = [ w.copy() for w in W ]
+ if formulation==StretchingFormulation.GRAD_UW:
+ W0 = Wc
+ K0 = [dUdx[i]*W0[direction] for i in xrange(3)]
+ W1 = [W0[i] + 0.5*dt*K0[i] for i in xrange(3)]
+ K1 = [dUdx[i]*W1[direction] for i in xrange(3)]
+ W2 = [W0[i] + 0.5*dt*K1[i] for i in xrange(3)]
+ K2 = [dUdx[i]*W2[direction] for i in xrange(3)]
+ W3 = [W0[i] + 1.0*dt*K2[i] for i in xrange(3)]
+ K3 = [dUdx[i]*W3[direction] for i in xrange(3)]
+ K = [1./6*K0[i] + 1./3*K1[i] + 1./3*K2[i] + 1./6*K3[i] for i in xrange(3)]
+ W4 = [W0[i] + dt*K[i] for i in xrange(3)]
+ W = W4
+ elif formulation==StretchingFormulation.GRAD_UW_T:
+ W0 = Wc
+ K0 = sum([dUdx[i]*W0[i] for i in xrange(3)])
+ W1 = W0[direction] + 0.5*dt*K0
+ K1 = sum([dUdx[i]*W0[i] for i in xrange(3) if i!=direction]) + W1*dUdx[direction]
+ W2 = W0[direction] + 0.5*dt*K1
+ K2 = sum([dUdx[i]*W0[i] for i in xrange(3) if i!=direction]) + W2*dUdx[direction]
+ W3 = W0[direction] + 1.0*dt*K2
+ K3 = sum([dUdx[i]*W0[i] for i in xrange(3) if i!=direction]) + W3*dUdx[direction]
+ K = 1./6*K0 + 1./3*K1 + 1./3*K2 + 1./6*K3
+ W4 = W0
+ W4[direction] += dt*K
+ W = W4
+ elif formulation==StretchingFormulation.MIXED_GRAD_UW:
+ W0 = Wc
+ K0 = [0.5*dUdx[i]*W0[direction] for i in xrange(3)]
+ K0[direction] += sum([0.5*dUdx[i]*W0[i] for i in xrange(3)])
+ W1 = [W0[i] + 0.5*dt*K0[i] for i in xrange(3)]
+ K1 = [0.5*dUdx[i]*W1[direction] for i in xrange(3)]
+ K1[direction] += sum([0.5*dUdx[i]*W1[i] for i in xrange(3)])
+ W2 = [W0[i] + 0.5*dt*K1[i] for i in xrange(3)]
+ K2 = [0.5*dUdx[i]*W2[direction] for i in xrange(3)]
+ K2[direction] += sum([0.5*dUdx[i]*W2[i] for i in xrange(3)])
+ W3 = [W0[i] + 1.0*dt*K2[i] for i in xrange(3)]
+ K3 = [0.5*dUdx[i]*W3[direction] for i in xrange(3)]
+ K3[direction] += sum([0.5*dUdx[i]*W3[i] for i in xrange(3)])
+ K = [1./6*K0[i] + 1./3*K1[i] + 1./3*K2[i] + 1./6*K3[i] for i in xrange(3)]
+ W4 = [W0[i] + dt*K[i] for i in xrange(3)]
+ W = W4
+ elif formulation==StretchingFormulation.CONSERVATIVE:
+ W0 = Wc
+ K0 = [deriv(ui*W0[direction]) for ui in U]
+ W1 = [W0[i] + 0.5*dt*K0[i] for i in xrange(3)]
+ K1 = [deriv(ui*W1[direction]) for ui in U]
+ W2 = [W0[i] + 0.5*dt*K1[i] for i in xrange(3)]
+ K2 = [deriv(ui*W2[direction]) for ui in U]
+ W3 = [W0[i] + 1.0*dt*K2[i] for i in xrange(3)]
+ K3 = [deriv(ui*W3[direction]) for ui in U]
+ K = [1./6*K0[i] + 1./3*K1[i] + 1./3*K2[i] + 1./6*K3[i] for i in xrange(3)]
+ W4 = [W0[i] + dt*K[i] for i in xrange(3)]
+ W = W4
+ else:
+ msg = 'Unknown stretching formulation scheme {}.'.format(formulation)
+ raise ValueError(msg)
+ else:
+ msg = 'Unknown Runge-Kutta scheme {}.'.format(rk_scheme)
+ raise ValueError(msg)
+
+ for i,name in enumerate(vorticity):
+ host_buffers_reference[name] = W[i]
+
+ def _do_compute_gpu_and_check(self, formulation, rk_scheme, order, direction,
+ boundary, cached):
+
+ msg = '\nTesting {}{} with order {} and scheme {} in direction {} with {} boundaries.'\
+ .format('cached ' if cached else '',
+ str(formulation).lower(),
+ order,
+ rk_scheme.name(),
+ direction,
+ str(boundary).lower())
+ print msg
+
+ dt = self.dt
+ work_size = self.grid_size
+ work_load = self.work_load
+ local_work_size = self.local_work_size
+ queue = self.queue
+
+ grid_size = self.grid_size
+ grid_shape = self.grid_shape
+ ghosts = self.compute_grid_ghosts
+
+ kernel_args = [dt]
+ if boundary == BoundaryCondition.PERIODIC:
+ target = 'no_ghosts'
+ mesh_info = self.grid_mesh_info
+ view = [slice(0,grid_size[2]),
+ slice(0,grid_size[1]),
+ slice(0,grid_size[0])]
+ elif boundary == BoundaryCondition.NONE:
+ target = 'with_ghosts'
+ mesh_info = self.compute_grid_mesh_info
+ view = [slice(ghosts[2],grid_size[2]+ghosts[2]),
+ slice(ghosts[1],grid_size[1]+ghosts[1]),
+ slice(ghosts[0],grid_size[0]+ghosts[0])]
+ else:
+ raise ValueError()
+
+ known_vars = {
+ 'local_size': local_work_size,
+ 'mesh_info': mesh_info
+ }
+
+ host_init_buffers = self.host_buffers_init[target]
+ host_buffers_reference = self.host_buffers_reference[target]
+ host_buffers_gpu = self.host_buffers_gpu[target]
+ device_buffers = self.device_buffers[target]
+
+ dsk = DirectionalStretchingKernel(
+ typegen=self.typegen,
+ dim=3,
+ ftype=self.typegen.fbtype,
+ order=order,
+ direction=direction,
+ is_cached=cached,
+ is_inplace=True,
+ boundary=(boundary, boundary),
+ formulation=formulation,
+ time_integrator=rk_scheme,
+ symbolic_mode=False,
+ known_vars=known_vars)
+
+ global_work_size = dsk.get_global_size(work_size,local_work_size,work_load)
+ (static_shared_bytes, dynamic_shared_bytes, total_bytes) = \
+ dsk.required_workgroup_cache_size(local_work_size)
+
+ vorticity = ['wx','wy','wz']
+ velocity = ['ux','uy','uz']
+ debug = ['dbg0', 'dbg1']
+ for varname in vorticity + velocity:
+ kernel_args.append(device_buffers[varname])
+ if (dynamic_shared_bytes != 0):
+ shared_buffer = cl.LocalMemory(dynamic_shared_bytes)
+ kernel_args.append(shared_buffer)
+
+ print '\tGenerating and compiling Kernel...'
+ dsk.edit()
+ source = dsk.__str__()
+ prg = cl.Program(self.typegen.context, source)
+ prg.build(devices=[self.typegen.device])
+ kernel = prg.all_kernels()[0]
+ kernel.set_args(*kernel_args)
+
+ print '\tCPU => GPU'
+ for buf in velocity+vorticity:
+ src = host_init_buffers[buf]
+ dst = device_buffers[buf]
+ cl.enqueue_copy(queue,dst,src)
+
+ print '\tKernel execution <<<{},{}>>>'.format(global_work_size,local_work_size)
+ evt = cl.enqueue_nd_range_kernel(queue, kernel,
+ global_work_size.tolist(), local_work_size.tolist())
+ evt.wait()
+
+ print '\tGPU => CPU'
+ for buf in vorticity:
+ src = device_buffers[buf]
+ dst = host_buffers_gpu[buf]
+ cl.enqueue_copy(queue,dst,src)
+
+ print '\tSynchronize queue'
+ queue.flush()
+ queue.finish()
+
+ buffers = [(varname,host_buffers_reference[varname],host_buffers_gpu[varname])
+ for varname in vorticity]
+ self._cmp_buffers(buffers,view,dsk)
+
+ def _cmp_buffers(self,buffers,view,dsk):
+ good = True
+ err_buffers = []
+
+ for (name,host,dev) in buffers:
+ (l1,l2,linf) = self._distances(host,dev,view)
+ print '\t{} -> l1={} l2={} linf={}'.format(name,l1,l2,linf)
+ if l2>1e-8:
+ err_buffers.append(name)
+ good = False
+ if not good:
+ msg = '\n[FAIL] Buffer comparisson failed for buffers {}.\n'.format(err_buffers)
+ print msg
+ dsk.edit()
+ if self.enable_error_plots:
+ from matplotlib import pyplot as plt
+ for (name,host,dev) in buffers:
+ if name in err_buffers:
+ fig,axes = plt.subplots(2,2)
+
+ host = host[view]
+ dev = dev[view]
+
+ d = (dev-host)*(dev-host)
+ d -= np.mean(d)
+
+ plt.title(name)
+
+ axes[0][0].imshow(np.sum(d,axis=0),interpolation='nearest')
+ axes[0][1].imshow(np.sum(d,axis=1),interpolation='nearest')
+ axes[1][0].imshow(np.sum(d,axis=2),interpolation='nearest')
+ axes[1][1].imshow(np.sum(d,axis=(0,1))[np.newaxis,:],
+ interpolation='nearest')
+
+ fig.show()
+ break
+ raw_input('Press enter to close all windows.')
+ raise RuntimeError(msg)
+
+ def _distances(self,lhs,rhs,view):
+ d = rhs[view]-lhs[view]
+ da = np.abs(d)
+
+ l1 = np.sum(da)/d.size
+ l2 = np.sqrt(np.sum(d*d))/d.size
+ linf = np.max(da)
+ return (l1,l2,linf)
+
+
+ def _check_kernels(self, formulation, rk_scheme):
+ check_instance(formulation,StretchingFormulation)
+ check_instance(rk_scheme,ExplicitRungeKutta)
+
+ cached=[False,True]
+ boundaries=[BoundaryCondition.NONE, BoundaryCondition.PERIODIC]
+
+ if self.do_extra_tests:
+ directions=[0,1,2]
+ orders=[2,4,6]
+ else:
+ directions=[1]
+ orders=[4]
+
+ for cache in cached:
+ if (formulation==StretchingFormulation.CONSERVATIVE) and not cache:
+ continue
+ for boundary in boundaries:
+ for direction in directions:
+ for order in orders:
+ self._do_compute_cpu(order=order, direction=direction, boundary=boundary,
+ formulation=formulation, rk_scheme=rk_scheme)
+
+ self._do_compute_gpu_and_check(order=order, direction=direction,
+ boundary=boundary, formulation=formulation,
+ rk_scheme=rk_scheme, cached=cache)
+
+
+
+
+ def test_stretching_gradUW_Euler(self):
+ formulation=StretchingFormulation.GRAD_UW
+ rk_scheme=ExplicitRungeKutta('Euler')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_gradUW_T_Euler(self):
+ formulation=StretchingFormulation.GRAD_UW_T
+ rk_scheme=ExplicitRungeKutta('Euler')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_mixed_gradUW_Euler(self):
+ formulation=StretchingFormulation.MIXED_GRAD_UW
+ rk_scheme=ExplicitRungeKutta('Euler')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_conservative_Euler(self):
+ formulation=StretchingFormulation.CONSERVATIVE
+ rk_scheme=ExplicitRungeKutta('Euler')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+
+
+ def test_stretching_gradUW_RK2(self):
+ formulation=StretchingFormulation.GRAD_UW
+ rk_scheme=ExplicitRungeKutta('RK2')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_gradUW_T_RK2(self):
+ formulation=StretchingFormulation.GRAD_UW_T
+ rk_scheme=ExplicitRungeKutta('RK2')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_mixed_gradUW_RK2(self):
+ formulation=StretchingFormulation.MIXED_GRAD_UW
+ rk_scheme=ExplicitRungeKutta('RK2')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_conservative_RK2(self):
+ formulation=StretchingFormulation.CONSERVATIVE
+ rk_scheme=ExplicitRungeKutta('RK2')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+
+
+ def test_stretching_gradUW_RK4(self):
+ formulation=StretchingFormulation.GRAD_UW
+ rk_scheme=ExplicitRungeKutta('RK4')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_gradUW_T_RK4(self):
+ formulation=StretchingFormulation.GRAD_UW_T
+ rk_scheme=ExplicitRungeKutta('RK4')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_mixed_gradUW_RK4(self):
+ formulation=StretchingFormulation.MIXED_GRAD_UW
+ rk_scheme=ExplicitRungeKutta('RK4')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+ def test_stretching_conservative_RK4(self):
+ formulation=StretchingFormulation.CONSERVATIVE
+ rk_scheme=ExplicitRungeKutta('RK4')
+ self._check_kernels(formulation=formulation, rk_scheme=rk_scheme)
+
+
+if __name__ == '__main__':
+ TestDirectionalStretching.setup_class(do_extra_tests=False, enable_error_plots=False)
+ test = TestDirectionalStretching()
+
+ test.test_stretching_gradUW_Euler()
+ test.test_stretching_gradUW_T_Euler()
+ test.test_stretching_mixed_gradUW_Euler()
+ test.test_stretching_conservative_Euler()
+
+ test.test_stretching_gradUW_RK2()
+ test.test_stretching_gradUW_T_RK2()
+ test.test_stretching_mixed_gradUW_RK2()
+ test.test_stretching_conservative_RK2()
+
+ test.test_stretching_gradUW_RK4()
+ test.test_stretching_gradUW_T_RK4()
+ test.test_stretching_mixed_gradUW_RK4()
+ test.test_stretching_conservative_RK4()
+
+ TestDirectionalStretching.teardown_class()
+
diff --git a/hysop/codegen/kernels/transpose.py b/hysop/backend/device/codegen/kernels/transpose.py
similarity index 85%
rename from hysop/codegen/kernels/transpose.py
rename to hysop/backend/device/codegen/kernels/transpose.py
index 783fbcd4d01deacfed1b37a0c30d78cdb3fdef4d..4d974f35cc616bfac4347e599656c53a3c865ae3 100644
--- a/hysop/codegen/kernels/transpose.py
+++ b/hysop/backend/device/codegen/kernels/transpose.py
@@ -1,13 +1,13 @@
import operator
import numpy as np
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.kernel_codegen import KernelCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenArray
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import WriteOnceDict, ArgDict
+from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+from hysop.backend.device.codegen.base.kernel_codegen import KernelCodeGenerator
+from hysop.backend.device.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenArray
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.codegen.base.utils import WriteOnceDict, ArgDict
-from hysop.codegen.functions.compute_index import ComputeIndexFunction
+from hysop.backend.device.codegen.functions.compute_index import ComputeIndexFunction
class TransposeKernel(KernelCodeGenerator):
@@ -110,7 +110,8 @@ class TransposeKernel(KernelCodeGenerator):
if __name__ == '__main__':
- tg = OpenClTypeGen('float')
+ from hysop.backend.device.codegen.base.test import test_typegen
+ typegen = test_typegen('float')
ek = TransposeKernel(typegen=tg, work_dim=3, dtype='float4',
tile_size=(8,8,), tile_padding=1,
known_vars=dict())
diff --git a/hysop/codegen/maths/stencil/__init__.py b/hysop/backend/device/codegen/structs/__init__.py
similarity index 100%
rename from hysop/codegen/maths/stencil/__init__.py
rename to hysop/backend/device/codegen/structs/__init__.py
diff --git a/hysop/codegen/structs/mesh_info.py b/hysop/backend/device/codegen/structs/mesh_info.py
similarity index 63%
rename from hysop/codegen/structs/mesh_info.py
rename to hysop/backend/device/codegen/structs/mesh_info.py
index 9b9552a9e8a5e71551eb42479a99c07f5f1ae156..833a2b406204acded7e6c963dde0db3a8954c4d3 100644
--- a/hysop/codegen/structs/mesh_info.py
+++ b/hysop/backend/device/codegen/structs/mesh_info.py
@@ -1,31 +1,25 @@
-from hysop.constants import np
-from hysop.constants import MeshDir, MeshState
-from hysop.codegen.base.enum_codegen import EnumCodeGenerator
-from hysop.codegen.base.struct_codegen import StructCodeGenerator
-from hysop.codegen.base.types import OpenClTypeGen
+from hysop.deps import np
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.enum_codegen import EnumCodeGenerator
+from hysop.backend.device.codegen.base.struct_codegen import StructCodeGenerator
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.constants import BoundaryCondition
-
-class MeshDirEnum(EnumCodeGenerator):
- def __init__(self):
- super(MeshDirEnum,self).__init__(MeshDir)
-
-class MeshStateEnum(EnumCodeGenerator):
- def __init__(self):
- super(MeshStateEnum,self).__init__(MeshState)
+BoundaryConditionEnum = EnumCodeGenerator(BoundaryCondition)
+ # comments='Mesh boundary conditions enumeration')
class MeshBaseStruct(StructCodeGenerator):
- def __init__(self, typegen, device, context, typedef=None):
+ def __init__(self, typegen, typedef=None):
name = 'MeshBase'
dtype,comments = MeshBaseStruct.build_dtype(typegen)
super(MeshBaseStruct,self).__init__(name=name,
dtype=dtype,
typegen=typegen,
typedef=typedef,
- comments=comments,
- device=device,
- context=context,
- ext='.cl')
+ comments=comments)
+
+ self.reqs['boundary_enum'] = BoundaryConditionEnum
@staticmethod
def build_dtype(typegen):
@@ -40,69 +34,89 @@ class MeshBaseStruct(StructCodeGenerator):
for fn in ['xmin', 'xmax', 'size']:
field = (fn, float4)
dtype.append(field)
+
+ dtype.append(('lboundary', int4))
+ dtype.append(('rboundary', int4))
comments = [
"Resolution of the mesh -including- ghosts",
"Resolution of the mesh -excluding- ghosts",
"Coordinates of the 'lowest' point including ghosts",
"Coordinates of the 'highest' point including ghosts",
- "size = xmax - xmin"
+ "size = xmax - xmin",
+ "Left boundary conditions",
+ "Right boundary conditions"
]
return np.dtype(dtype), comments
- def create(self,name,
- resolution, compute_resolution,
+ def create(self, name,
+ resolution, compute_resolution, boundaries,
xmin, xmax, size,
**kargs):
+
+ def extend(var,d=0):
+ return np.asarray(tuple(var)+(d,)*(4-len(var)))
tg = self.typegen
dtype,_ = MeshBaseStruct.build_dtype(tg)
+ lboundary, rboundary = boundaries
+ lboundary = extend(lboundary, BoundaryCondition.NONE)
+ rboundary = extend(rboundary, BoundaryCondition.NONE)
+ _lboundary = [ bd() for bd in lboundary ]
+ _rboundary = [ bd() for bd in rboundary ]
+
mesh_base_vals = {
- 'resolution' : tg.make_intn(resolution,4),
- 'compute_resolution' : tg.make_intn(compute_resolution,4),
- 'xmin' : tg.make_floatn(xmin,4),
- 'xmax' : tg.make_floatn(xmax,4),
- 'size' : tg.make_floatn(size,4)
+ 'resolution': tg.make_intn(resolution,4),
+ 'compute_resolution': tg.make_intn(compute_resolution,4),
+ 'lboundary': tg.make_intn(_lboundary, 4),
+ 'rboundary': tg.make_intn(_rboundary, 4),
+ 'xmin': tg.make_floatn(xmin,4),
+ 'xmax': tg.make_floatn(xmax,4),
+ 'size': tg.make_floatn(size,4)
}
var = np.empty(shape=(1,), dtype=dtype)
for k in mesh_base_vals:
var[k] = mesh_base_vals[k]
-
- def extend(var,d=0):
- return np.asarray(tuple(var)+(d,)*(4-len(var)))
+
+ lboundary = BoundaryCondition.array_variable('lboundary',
+ typegen=tg, vals=lboundary)
+ rboundary = BoundaryCondition.array_variable('rboundary',
+ typegen=tg, vals=rboundary)
+
value = dict(resolution=extend(resolution),
compute_resolution=extend(compute_resolution),
xmin=extend(xmin),
xmax=extend(xmax),
size=extend(size))
- cg_var = self.build_codegen_variable(name=name,value=value,**kargs)
+ var_overrides = { 'lboundary': rboundary,
+ 'rboundary': lboundary }
+ cg_var = self.build_codegen_variable(name=name,value=value,
+ var_overrides=var_overrides, **kargs)
return (var, cg_var)
class MeshInfoStruct(StructCodeGenerator):
- def __init__(self, typegen, device, context,
+ def __init__(self, typegen,
typedef=None,
mbs_typedef='MeshBase_s'):
name = 'MeshInfo'
- dtype,comments,ctype_overrides, reqs = MeshInfoStruct.build_dtype(typegen,mbs_typedef=mbs_typedef,device=device,context=context)
+ dtype,comments,ctype_overrides, reqs = MeshInfoStruct.build_dtype(typegen,mbs_typedef=mbs_typedef)
super(MeshInfoStruct,self).__init__(name=name, dtype=dtype, typegen=typegen,
typedef=typedef,
comments=comments,
- ctype_overrides=ctype_overrides,
- device=device, context=context,
- ext='.cl')
+ ctype_overrides=ctype_overrides)
for req in reqs:
self.require(req.name, req)
self.mesh_base = reqs[0]
@staticmethod
- def build_dtype(typegen,device,context,mbs_typedef='MeshBase_s'):
+ def build_dtype(typegen,mbs_typedef='MeshBase_s'):
tg = typegen
int4 = tg.dtype_from_str('int4')
float4 = tg.dtype_from_str('fbtype4')
@@ -121,40 +135,23 @@ class MeshInfoStruct(StructCodeGenerator):
_append( (fn, float4) )
i+=1
- mesh_base = MeshBaseStruct(tg, typedef=mbs_typedef,device=device,context=context)
+ mesh_base = MeshBaseStruct(tg, typedef=mbs_typedef)
_append( ('local_mesh', mesh_base.dtype) )
_append( ('global_mesh', mesh_base.dtype) )
i+=2
- mesh_dir = MeshDirEnum()
- mesh_dir_field = i
- _append( ('direction', mesh_dir.dtype) )
- i+=1
-
- mesh_state = MeshStateEnum()
- mesh_state_field = i
- _append( ('state', mesh_state.dtype) )
- i+=1
-
- ctype_overrides = {
- mesh_dir_field:mesh_dir.ctype,
- mesh_state_field:mesh_state.ctype
- }
-
comments = [
"Dimension of the mesh",
- "Position of the first local compute point in the global grid",
- "Position of the last local compute point in the global grid",
+ "Index of the first local compute point in the global grid",
+ "Index of the last local compute point in the global grid",
"Number of ghosts in each direction",
"Space discretization",
"1/dx",
"Local mesh",
"Global mesh",
- "Current memory aligned component",
- "Current components reordering state"
]
- return dtypes, comments, ctype_overrides, [mesh_base, mesh_dir, mesh_state]
+ return dtypes, comments, None, [mesh_base]
def create(self,
name,
@@ -162,7 +159,6 @@ class MeshInfoStruct(StructCodeGenerator):
start, stop, ghosts,
dx,
local_mesh, global_mesh,
- mesh_dir, mesh_state,
**kargs):
if dim>4:
@@ -170,14 +166,9 @@ class MeshInfoStruct(StructCodeGenerator):
raise ValueError(msg)
tg = self.typegen
- device=self.device
- context=self.context
- dtype,_,_,_ = MeshInfoStruct.build_dtype(tg,device=device,context=context)
+ dtype,_,_,_ = MeshInfoStruct.build_dtype(tg)
- direction = MeshDir.value(mesh_dir)
- state = MeshState.value(mesh_state)
-
dx = np.asarray(dx)
mesh_info_vals = {
'dim' : tg.make_intn(dim,1),
@@ -187,9 +178,7 @@ class MeshInfoStruct(StructCodeGenerator):
'dx' : tg.make_floatn(dx,4),
'inv_dx' : tg.make_floatn(1.0/dx,4),
'local_mesh' : local_mesh[0],
- 'global_mesh': global_mesh[0],
- 'direction' : direction,
- 'state' : state
+ 'global_mesh': global_mesh[0]
}
def extend(var,d=0):
@@ -213,8 +202,6 @@ class MeshInfoStruct(StructCodeGenerator):
var_overrides = dict(
local_mesh=local_mesh[1],
global_mesh=global_mesh[1],
- direction = MeshDir.variable('direction',tg,mesh_dir),
- state = MeshState.variable('state',tg,mesh_state)
)
cg_var = self.build_codegen_variable(name=name,
value=value,var_overrides=var_overrides,
@@ -226,20 +213,15 @@ class MeshInfoStruct(StructCodeGenerator):
return (var, cg_var)
@staticmethod
- def create_from_mesh(name,cl_env, mesh,
- mesh_dir=MeshDir.X, mesh_state=MeshState.XYZ,
- **kargs):
+ def create_from_mesh(name, cl_env, mesh, **kargs):
from hysop.domain.mesh import Mesh
- assert isinstance(mesh,Mesh)
- assert mesh_dir in MeshDir.entries()
- assert mesh_state in MeshState.entries()
-
+ check_instance(name,str)
+ check_instance(mesh,Mesh)
+
tg = cl_env.typegen
- device = cl_env.device
- context = cl_env.ctx
- mesh_base = MeshBaseStruct(tg,typedef='MeshBase_s',device=device,context=context)
- mesh_info = MeshInfoStruct(tg,typedef='MeshInfo_s',device=device,context=context)
+ mesh_base = MeshBaseStruct(tg,typedef='MeshBase_s')
+ mesh_info = MeshInfoStruct(tg,typedef='MeshInfo_s')
dim = mesh._dim
start = mesh.start()
@@ -252,27 +234,28 @@ class MeshInfoStruct(StructCodeGenerator):
gxmin = mesh.global_origin
gxmax = mesh.global_origin + mesh.global_length
gsize = mesh.global_length
+ gboundaries = mesh.global_boundaries
lresolution = mesh.resolution
lcompute_resolution = mesh.compute_resolution
lxmin = mesh.origin
lxmax = mesh.end
lsize = lxmax - lxmin
+ lboundaries = mesh.boundaries
const = kargs['const'] if ('const' in kargs) else False
- gmesh = mesh_base.create(tg,
- gresolution, gcompute_resolution,
+ gmesh = mesh_base.create(name+'_global_mesh',
+ gresolution, gcompute_resolution, gboundaries,
gxmin, gxmax, gsize, const=const)
- lmesh = mesh_base.create(tg,
- lresolution, lcompute_resolution,
+ lmesh = mesh_base.create(name+'_local_mesh',
+ lresolution, lcompute_resolution, lboundaries,
lxmin, lxmax, lsize, const=const)
(var, cg_var) = mesh_info.create(name,
dim,
- start,stop,ghosts,
+ start, stop, ghosts,
dx,
- lmesh,gmesh,
- mesh_dir,mesh_state,
+ lmesh, gmesh,
**kargs)
return (var, cg_var)
@@ -282,22 +265,25 @@ class MeshInfoStruct(StructCodeGenerator):
if var_overrides is None:
const = kargs['const'] if ('const' in kargs) else False
var_overrides = dict(
- local_mesh = self.mesh_base.build_codegen_variable('local_mesh',const=const),
- global_mesh = self.mesh_base.build_codegen_variable('global_mesh',const=const),
- direction = MeshDir.variable('direction',tg),
- state = MeshState.variable('state',tg)
+ local_mesh = self.mesh_base.build_codegen_variable('local_mesh',
+ const=const),
+ global_mesh = self.mesh_base.build_codegen_variable('global_mesh',
+ const=const),
)
return super(MeshInfoStruct,self).build_codegen_variable(name=name,var_overrides=var_overrides,**kargs)
if __name__ == '__main__':
- typegen = OpenClTypeGen('double')
- mbs = MeshBaseStruct(typegen, typedef='MeshBase_s')
- mis = MeshInfoStruct(typegen, typedef='MeshInfo_s', mbs_typedef=mbs.typedef)
+ from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+ from hysop.backend.device.codegen.base.test import test_typegen
- from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
- cg = OpenClCodeGenerator('test_generator',typegen)
+ tg = test_typegen('double', float_dump_mode='dec')
+
+ mbs = MeshBaseStruct(tg, typedef='MeshBase_s')
+ mis = MeshInfoStruct(tg, typedef='MeshInfo_s', mbs_typedef=mbs.typedef)
+
+ cg = OpenClCodeGenerator('test_generator',tg)
- # declare mesh MeshInfoStruct and its dependancies (MeshBaseStruct,MeshDirEnum,MeshStateEnum)
+ # declare mesh MeshInfoStruct and its dependancies (MeshBaseStruct,MeshDirectionEnum,TranspositionStateEnum)
cg.require('mis',mis)
# create a local numpy and a codegen MeshInfoStruct variable
@@ -315,8 +301,8 @@ if __name__ == '__main__':
3,
(0,0,0,), (1024,1024,1024,), (1,1,1,),
(0.1,0.2,0.3),
- local_mesh, global_mesh,
- MeshDir.X, MeshState.XYZ)
+ local_mesh, global_mesh)
+ # MeshDirection.X, TranspositionState.XYZ)
# declare and intialize the nested struct in the __constant address space
cg.jumpline()
diff --git a/hysop/codegen/structs/__init__.py b/hysop/backend/device/codegen/unions/__init__.py
similarity index 100%
rename from hysop/codegen/structs/__init__.py
rename to hysop/backend/device/codegen/unions/__init__.py
diff --git a/hysop/backend/device/codegen/unions/float_int.py b/hysop/backend/device/codegen/unions/float_int.py
new file mode 100644
index 0000000000000000000000000000000000000000..643d85f6e84465e469480c668bd608ecc9a7c67d
--- /dev/null
+++ b/hysop/backend/device/codegen/unions/float_int.py
@@ -0,0 +1,71 @@
+
+
+from hysop.deps import np
+from hysop.tools.types import check_instance
+from hysop.backend.device.codegen.base.union_codegen import UnionCodeGenerator
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+
+class FloatIntegerUnion(UnionCodeGenerator):
+ def __init__(self, ftype, typegen, typedef=None):
+
+ name,dtype,comments = self.build_dtype(typegen, ftype)
+
+ super(FloatIntegerUnion,self).__init__(name=name,
+ dtype=dtype,
+ typegen=typegen,
+ typedef=typedef,
+ comments=comments)
+
+ @staticmethod
+ def build_dtype(typegen, ftype):
+ tg = typegen
+
+ name = 'float_int'
+
+ dtype = []
+ if ftype == 'half':
+ name+='16'
+ dtype.append(('intval', np.int16))
+ dtype.append(('uintval', np.uint16))
+ dtype.append(('floatval', np.float16))
+ elif ftype == 'float':
+ name+='32'
+ dtype.append(('intval', np.int32))
+ dtype.append(('uintval', np.uint32))
+ dtype.append(('floatval', np.float32))
+ elif ftype == 'double':
+ name+='64'
+ dtype.append(('intval', np.int64))
+ dtype.append(('uintval', np.uint64))
+ dtype.append(('floatval', np.float64))
+ else:
+ msg='Unknown ftype \'{}\', only half, float and double are supported.'
+ msg=msg.format(ftype)
+ raise ValueError(msg)
+
+ comments = [
+ 'Access value as a signed integer',
+ 'Access value as a unsigned integer',
+ 'Access value as a floating point',
+ ]
+
+ return name, dtype, comments
+
+
+if __name__ == '__main__':
+ from hysop.backend.device.codegen.base.opencl_codegen import OpenClCodeGenerator
+ from hysop.backend.device.codegen.base.test import _test_typegen
+
+ tg = _test_typegen()
+
+ u1 = FloatIntegerUnion('double', tg)
+ u2 = FloatIntegerUnion('float', tg, 'custom32')
+
+ cg = OpenClCodeGenerator('test_generator',tg)
+ cg.declare_cl_extension('cl_khr_fp64')
+ cg.require('u1',u1)
+ cg.require('u2',u2)
+
+ cg.edit()
+
+ cg.test_compile()
diff --git a/hysop/backend/device/device_allocator.py b/hysop/backend/device/device_allocator.py
new file mode 100644
index 0000000000000000000000000000000000000000..794d519d3c214072a8da22b48b26ebdaaf457a0b
--- /dev/null
+++ b/hysop/backend/device/device_allocator.py
@@ -0,0 +1,13 @@
+
+from hysop.core.memory.allocator import AllocatorBase
+
+class DeviceAllocator(AllocatorBase):
+ """
+ Allocator that allocates DeviceBuffers.
+ """
+
+ def is_on_host(self):
+ """
+ Return true if buffers are allocated in host memory.
+ """
+ return False
diff --git a/hysop/backend/device/device_buffer.py b/hysop/backend/device/device_buffer.py
new file mode 100644
index 0000000000000000000000000000000000000000..861361b5b96b3c868d024149874328c1149fdf29
--- /dev/null
+++ b/hysop/backend/device/device_buffer.py
@@ -0,0 +1,9 @@
+
+from abc import ABCMeta
+from hysop.core.memory.buffer import Buffer
+
+class DeviceBuffer(Buffer):
+ """
+ Abstract device buffer class.
+ """
+ __metaclass__=ABCMeta
diff --git a/hysop/backend/device/device_platform.py b/hysop/backend/device/device_platform.py
new file mode 100644
index 0000000000000000000000000000000000000000..bac6cf037ab2ba0e0578b408307b2a9b9d109e6b
--- /dev/null
+++ b/hysop/backend/device/device_platform.py
@@ -0,0 +1,27 @@
+
+from hysop.backend.handle import Handle
+
+from abc import ABCMeta, abstractmethod
+
+class Platform(Handle):
+
+ __metaclass__ = ABCMeta
+
+ def __init__(self, backend, platform_handle, hardware_topo, **kargs):
+ super(Platform,self).__init__(handle=platform_handle, **kargs)
+ self._backend = backend
+ self._logical_devices = []
+ self._discover_devices(hardware_topo)
+
+ def backend(self):
+ return self._backend
+
+ def logical_devices(self):
+ return self._logical_devices
+
+ def physical_devices(self):
+ return [dev.physical_device() for dev in self.logical_devices()]
+
+ @abstractmethod
+ def _discover_devices(self, hardware_topo):
+ pass
diff --git a/hysop/backend/device/kernel_autotuner.py b/hysop/backend/device/kernel_autotuner.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb625d9c6976fdca8b9bcee2f1e5b4498fb948cc
--- /dev/null
+++ b/hysop/backend/device/kernel_autotuner.py
@@ -0,0 +1,677 @@
+
+from hysop.deps import pickle, os, it, hashlib, gzip
+from hysop.tools.io_utils import IO
+from hysop.tools.misc import Utils
+
+from hysop.constants import np, AutotunerFlags, \
+ __DEBUG__, __VERBOSE__, __KERNEL_DEBUG__, \
+ DEFAULT_AUTOTUNER_FLAG, DEFAULT_AUTOTUNER_PRUNE_THRESHOLD
+from hysop.backend.device.opencl import cl, KERNEL_DUMP_FOLDER
+
+class KernelGenerationError(RuntimeError):
+ pass
+
+class OpenClKernelStatistics(object):
+ """Execution statistics from kernel events.
+ """
+ def __init__(self,nruns=0,events=None):
+ if events is not None:
+ p0 = events[0].profile
+ t0 = p0.end - p0.start
+ total = 0
+ maxi = t0
+ mini = t0
+ for evt in events:
+ dt = evt.profile.end - evt.profile.start
+ total += dt
+ if dt<mini:
+ mini = dt
+ if dt>maxi:
+ maxi = dt
+
+ self.tot = total
+ self.min = mini
+ self.max = maxi
+ self.mean = total/len(events)
+ else:
+ self.tot = None
+ self.min = None
+ self.max = None
+ self.mean = None
+ self.nruns = nruns
+
+ def __str__(self):
+ mini = self.min * 1e-6
+ maxi = self.max * 1e-6
+ total = self.tot * 1e-6
+ mean = self.mean * 1e-6
+ return 'min={:.2f}ms, max={:.2f}ms, mean={:.2f}ms (nruns={})'.format(mini,maxi,mean,self.nruns)
+
+ @staticmethod
+ def cmp(lhs,rhs):
+ if lhs.mean==rhs.mean:
+ if lhs.max==rhs.max:
+ if lhs.min==rhs.min:
+ return 0
+ elif lhs.min>rhs.min:
+ return 1
+ else:
+ return -1
+ elif lhs.max > rhs.max:
+ return 1
+ else:
+ return -1
+ elif lhs.mean>rhs.mean:
+ return 1
+ else:
+ return -1
+ def __lt__(self, other):
+ return self.cmp(self, other) < 0
+ def __gt__(self, other):
+ return self.cmp(self, other) > 0
+ def __eq__(self, other):
+ return self.cmp(self, other) == 0
+ def __le__(self, other):
+ return self.cmp(self, other) <= 0
+ def __ge__(self, other):
+ return self.cmp(self, other) >= 0
+ def __ne__(self, other):
+ return self.cmp(self, other) != 0
+
+class AutotunerConfig(object):
+
+ _default_initial_runs = {
+ AutotunerFlags.ESTIMATE: 2,
+ AutotunerFlags.MEASURE: 4,
+ AutotunerFlags.PATIENT: 8,
+ AutotunerFlags.EXHAUSTIVE: 16
+ }
+
+ def __init__(self,
+ autotuner_flag = DEFAULT_AUTOTUNER_FLAG,
+ prune_threshold = DEFAULT_AUTOTUNER_PRUNE_THRESHOLD,
+ verbose = 1 if __VERBOSE__ else 0,
+ debug = __KERNEL_DEBUG__,
+ dump_folder = KERNEL_DUMP_FOLDER,
+ override_cache = False,
+ nruns = None):
+
+ self.autotuner_flag = autotuner_flag
+ self.prune_threshold = prune_threshold
+ self.verbose = verbose
+ self.debug = debug
+ self.override_cache = override_cache
+ if (nruns is None):
+ self.nruns = AutotunerConfig._default_initial_runs[autotuner_flag]
+ elif (nruns<1):
+ raise ValueError('nruns<1.')
+ else:
+ self.nruns = nruns
+
+class KernelAutotuner(object):
+ cache_dir = IO.cache_path() + '/autotune'
+ config_file = cache_dir+'/configs.pklz'
+ if not os.path.exists(cache_dir):
+ os.makedirs(cache_dir)
+
+ FULL_RESULTS_KEY = '__FULL_RESULTS__'
+
+ """OpenCl kernel work group size autotuner.
+ """
+ def __init__(self,name,work_dim,build_opts,autotuner_config,local_work_dim=None):
+ """Initialize a KernelAutotuner.
+
+ Parameters
+ ----------
+ work_dim: int
+ Work dimension used in targetted OpenCL kernels.
+ local_work_dim: int
+ Work dimension used in workgroup sizes.
+ """
+
+ if not isinstance(autotuner_config, AutotunerConfig):
+ raise ValueError('autotuner_config is not an AutotunerConfig.')
+
+ self.name = name
+ self.work_dim = work_dim
+ self.local_work_dim = work_dim if (local_work_dim is None) else local_work_dim
+ self.build_opts = build_opts
+ self.autotuner_config = autotuner_config
+
+ self.enable_variable_workload = False
+ self.max_workitem_workload = None
+ self.workloads = [(1,1,1)]
+
+ self.extra_parameters = None
+
+ self._init_and_load_cache()
+ self._load_default_filters()
+
+ @staticmethod
+ def _hash_func():
+ return hashlib.new('sha256')
+
+ @staticmethod
+ def _load_configs():
+ configs = {}
+ if os.path.isfile(KernelAutotuner.config_file):
+ try:
+ with gzip.open(KernelAutotuner.config_file, 'rb') as f:
+ configs.update(pickle.loads(f.read()))
+ except EOFError:
+ msg='Failed to read cached file \'{}\'.'
+ msg=msg.format(KernelAutotuner.config_file)
+ print msg
+ return configs
+
+ @staticmethod
+ def _make_config_key(work_dim, local_work_dim, typegen, build_opts,
+ enable_variable_workload, max_workitem_workload, extra_parameters):
+ concat_unique_list = lambda L: '['+'_'.join([str(val) for val in frozenset(L)])+']'
+ hasher = KernelAutotuner._hash_func()
+ hasher.update('{}_{}_{}_{}{}{}'.format(work_dim, local_work_dim,
+ concat_unique_list(build_opts), typegen.__repr__(),
+ '_{}'.format(max_workitem_workload) if enable_variable_workload else '',
+ '_{}'.format('__'.join(['{}={}'.format(k,extra_parameters[k])
+ for k in extra_parameters.keys()]))))
+ return hasher.hexdigest()
+
+ @staticmethod
+ def _make_bench_key(work_size, kernel_generator, get_max_global_size, **kargs):
+ bench_key = 'bench__{}'.format(work_size)
+ if (kernel_generator is not None):
+ bench_key+='__{}:{}'.format(kernel_generator.__module__,
+ kernel_generator.__name__)
+ if (get_max_global_size is not None):
+ bench_key+='__{}:{}'.format(get_max_global_size.__module__,
+ get_max_global_size.__name__)
+ bench_key += '__'+'__'.join('{}={}'.format(k,kargs[k]) for k in sorted(kargs.keys()))
+ hasher = KernelAutotuner._hash_func()
+ hasher.update(bench_key)
+ return hasher.hexdigest()
+
+ def _update_configs(self):
+ configs = KernelAutotuner._load_configs()
+ if configs.keys() != self.configs.keys():
+ configs.update(self.configs)
+ with gzip.open(KernelAutotuner.config_file, 'wb') as f:
+ pickle.dump(configs,f)
+ self.configs = configs
+
+ def _init_and_load_cache(self):
+ cache_file = '{}/{}.pklz'.format(KernelAutotuner.cache_dir,self.name.replace(' ','_'))
+ if os.path.isfile(cache_file):
+ with gzip.open(cache_file, 'rb') as f:
+ self.results = pickle.loads(f.read())
+ else:
+ self.results = {}
+ self.configs = KernelAutotuner._load_configs()
+ self.cache_file = cache_file
+
+ def _dump_cache(self):
+ with gzip.open(self.cache_file, 'wb') as f:
+ pickle.dump(self.results,f)
+
+
+ def enable_variable_workitem_workload(self, max_workitem_workload):
+ max_workitem_workload = np.asarray(max_workitem_workload)
+ self.max_workitem_workload = max_workitem_workload
+ assert (max_workitem_workload>0).all()
+
+ def _compute_pows(max_workload):
+ pows = [1]
+ workload = 1
+ while(workload<max_workload):
+ workload <<= 1
+ pows.append(workload)
+ return pows
+
+ self.enable_variable_workload = True
+ if np.isscalar(max_workitem_workload):
+ workloads = _compute_pows(max_workitem_workload)
+ workloads = it.product(workloads, repeat=3)
+ else:
+ workloads = [_compute_pows(mww) for mww in max_workitem_workload]
+ workloads = it.product(*workloads)
+ self.workloads = [w for w in workloads]
+
+ def register_extra_parameter(self,name, values):
+ if self.extra_parameters is None:
+ self.extra_parameters = {}
+ self.extra_parameters[name] = values
+
+ def add_filter(self,fname, f):
+ self.filters[fname] = f
+ return self
+
+ def get_candidates(self,**kargs):
+ return np.asarray([c for c in self._get_wi_candidates(**kargs)])
+
+ def get_workloads(self,global_size):
+ def F(wl):
+ return (wl[0]<=global_size[0]) \
+ and (wl[1]<=global_size[1]) \
+ and (wl[2]<=global_size[2])
+ candidates = it.ifilter(F, self.workloads)
+ return np.asarray([c for c in candidates])
+
+ def get_extra_parameters(self):
+ if self.extra_parameters is None:
+ return [None]
+ else:
+ return it.product(*self.extra_parameters.values())
+
+ def bench(self,typegen,work_size,kernel_args,
+ kernel_generator = None,
+ get_max_global_size = None,
+ **kargs):
+
+ assert 'global_size' not in kargs, \
+ 'global_size has been replaced by work_size, ' \
+ +'due to the variable workload per workitem option.'
+
+ if np.isscalar(work_size):
+ work_size = [work_size]
+ else:
+ work_size = list(work_size)
+ work_size += [1]*(3-len(work_size))
+ work_size = np.asarray(work_size)
+ ws = tuple(work_size,)
+
+
+ if not isinstance(kernel_args, list):
+ msg='kernel_args should be a list.'
+ raise ValueError(msg)
+
+ if (get_max_global_size is None):
+ get_max_global_size = lambda work_size, work_load, **kargs: \
+ (work_size+workload-1)/workload
+
+ platform = typegen.platform
+ device = typegen.device
+ ctx = typegen.context
+
+ verbose = self.autotuner_config.verbose
+ if verbose:
+ print
+ print '== Kernel {} Autotuning =='.format(self.name)
+ print ' *config: {} (nruns={}, prune={})'.format(
+ self.autotuner_config.autotuner_flag,
+ self.autotuner_config.nruns,
+ self.autotuner_config.prune_threshold)
+ print ' *platform: {}'.format(platform.name)
+ print ' *device: {}'.format(device.name)
+ print ' *work_size: {}'.format(work_size)
+ print ' *fbtype: {}'.format(typegen.fbtype)
+ print ' *build_opts: {}'.format(self.build_opts)
+
+ config = KernelAutotuner._make_config_key(self.work_dim, self.local_work_dim,
+ typegen, self.build_opts,
+ self.enable_variable_workload, self.max_workitem_workload,
+ self.extra_parameters)
+ if config not in self.configs.keys():
+ self.configs[config] = {'work_dim':self.work_dim,
+ 'local_work_dim': self.local_work_dim,
+ 'build_opts':self.build_opts,
+ 'typegen':typegen.__repr__()}
+ self._update_configs()
+
+ results = self.results.setdefault(config, {})
+ full_results = results.setdefault(KernelAutotuner.FULL_RESULTS_KEY, {})
+
+ bench_key = KernelAutotuner._make_bench_key(work_size,
+ kernel_generator, get_max_global_size, **kargs)
+
+ do_bench = True
+
+ autotuner_config = self.autotuner_config
+ if (not autotuner_config.override_cache) and (bench_key in full_results):
+ result, result_autotuner_config = full_results[bench_key]
+ if (result_autotuner_config.autotuner_flag() >= autotuner_config.autotuner_flag()) and \
+ (result_autotuner_config.prune_threshold >= autotuner_config.prune_threshold) and \
+ (result_autotuner_config.nruns >= autotuner_config.nruns):
+ do_bench = False
+
+ separator = '_'*100
+
+ if not do_bench:
+ (best_global_size, best_local_size, best_stats, best_workload, best_extra_params) = result
+ if verbose:
+ print
+ print ' Loading cached autotuner result...'
+ print ' Autotuner config was:'
+ print ' *config: {} (nruns={}, prune={})'.format(result_autotuner_config.autotuner_flag,
+ result_autotuner_config.nruns,
+ result_autotuner_config.prune_threshold)
+ print
+ else:
+ if verbose==1:
+ verbose=False
+ print
+ print ' This may take a while...'
+ print
+
+ best_workload = None
+ best_global_size = None
+ best_local_size = None
+ best_stats = None
+ best_extra_params = None
+
+ dump_cache = False
+
+ indent = lambda i: ' '*i
+
+ for extra_parameters in self.get_extra_parameters():
+ if self.extra_parameters is None:
+ extra_parameters = {}
+ else:
+ extra_parameters = dict(zip(self.extra_parameters.keys(), extra_parameters))
+
+ params_hash = hashlib.sha256(str(hash(frozenset(sorted(extra_parameters.items())))))
+ params_hash = params_hash.hexdigest()[:8]
+
+ best_params_workload = None
+ best_params_global_size = None
+ best_params_local_size = None
+ best_params_stats = None
+
+ if verbose:
+ print separator
+ print '::Current tuning parameters:: {}'.format(extra_parameters)
+
+ workloads = self.get_workloads(work_size)
+ for workload in workloads:
+ workload=np.asarray(workload)
+ max_global_size = get_max_global_size(work_size, workload, **extra_parameters)
+
+ best_workload_global_size = None
+ best_workload_local_size = None
+ best_workload_stats = None
+ best_workload_candidate = None
+ best_workload_ids = None
+
+ if verbose:
+ print separator
+ print indent(1)+'::Current workload {}::'.format(workload)
+ print indent(2)+'-> global_size is set to {}'.format(max_global_size)
+
+ candidates = self.get_candidates(ctx=ctx,device=device,
+ max_global_size=max_global_size,**kargs)
+ unpruned_candidates = np.zeros_like(candidates)
+ nruns=self.autotuner_config.nruns
+
+ step=0
+ all_pruned=False
+ while step==0 or candidates.shape[0]>1:
+ stats = []
+ pruned_count = 0
+ unpruned_count = 0
+
+ if verbose and candidates.shape[0]>0:
+ msg='\n'+indent(2)+'Step {} :: running {} candidates over {} runs:'
+ print msg.format(step,candidates.shape[0],nruns)
+
+ for local_work_size in candidates:
+ local_work_size = np.asarray(local_work_size)
+ lwi = tuple(local_work_size)
+
+ try:
+ (_kernel,_kernel_args, src_hash, global_size) = kernel_generator(
+ ctx=ctx,device=device,
+ work_size=work_size,work_load=workload,local_work_size=lwi,
+ build_opts=self.build_opts,
+ kernel_args=kernel_args,
+ extra_parameters=extra_parameters,
+ **kargs)
+ except KernelGenerationError as e:
+ pruned_count += 1
+ print e
+ continue
+
+ global_size = np.asarray(global_size)
+ gwi = tuple(global_size)
+
+ update=False
+ pms = params_hash
+
+ if (not self.autotuner_config.override_cache) \
+ and src_hash in results.keys() \
+ and pms in results[src_hash].keys() \
+ and ws in results[src_hash][pms].keys() \
+ and gwi in results[src_hash][pms][ws].keys() \
+ and lwi in results[src_hash][pms][ws][gwi].keys():
+
+ stat = self.results[config][src_hash][pms][ws][gwi][lwi]
+ if stat.nruns >= nruns:
+ if verbose:
+ print indent(3)+'{} {} => {} (cached)'.format(gwi, lwi,
+ stat)
+ unpruned_candidates[unpruned_count,:] = local_work_size
+ unpruned_count+=1
+ stats.append(stat)
+ continue
+ else:
+ update=True
+
+ if (best_stats is not None):
+ current_best_stats = best_stats
+ elif (best_params_stats is not None):
+ current_best_stats = best_params_stats
+ elif (best_workload_stats is not None):
+ current_best_stats = best_workload_stats
+ else:
+ current_best_stats = None
+
+ (stat,pruned) = self._bench_one(ctx, device, gwi, lwi, _kernel,
+ _kernel_args, nruns, current_best_stats)
+
+ if not pruned:
+ unpruned_candidates[unpruned_count,:] = local_work_size
+ unpruned_count+=1
+ status='update' if update else 'new'
+ stats.append(stat)
+ else:
+ pruned_count+=1
+ status='pruned'
+
+ if verbose:
+ print indent(3)+'{} {} => {} ({})'.format(gwi, lwi, stat, status)
+
+ if not pruned:
+ if src_hash not in results.keys():
+ results[src_hash] = {}
+ if pms not in results[src_hash].keys():
+ results[src_hash][pms] = {}
+ if ws not in results[src_hash][pms].keys():
+ results[src_hash][pms][ws] = {}
+ if gwi not in results[src_hash][pms][ws].keys():
+ results[src_hash][pms][ws][gwi] = {}
+ results[src_hash][pms][ws][gwi][lwi] = stat
+ dump_cache = True
+
+ all_pruned = (pruned_count==candidates.shape[0])
+ if unpruned_count+pruned_count!=candidates.shape[0]:
+ raise RuntimeError()
+ if all_pruned:
+ break
+
+ keep = max(1,unpruned_count//2)
+ best_workload_ids=Utils.argsort(stats)[:keep]
+ candidates=unpruned_candidates[best_workload_ids,:]
+
+ nruns *= 2
+ step += 1
+
+ if all_pruned:
+ if verbose:
+ print separator
+ print indent(1)+' Workload {} winner for kernel {}:'.format(workload,
+ self.name)
+ print indent(2)+'no winner (all candidates were pruned)'
+ continue
+
+ if (candidates.shape[0]!=1 or len(best_workload_ids)!=1):
+ raise RuntimeError()
+
+ if dump_cache:
+ self.results[config] = results
+ self._dump_cache()
+ dump_cache=False
+
+ best_workload_id = best_workload_ids[0]
+ best_workload_stats = stats[best_workload_id]
+ best_workload_candidate = candidates[0]
+
+ best_workload_local_size = best_workload_candidate
+ (_,_,_,best_workload_global_size) = kernel_generator(
+ ctx=ctx,device=device,
+ work_size=work_size,work_load=workload,
+ local_work_size=best_workload_local_size,
+ build_opts=self.build_opts,
+ kernel_args=kernel_args,
+ extra_parameters=extra_parameters,
+ **kargs)
+
+ if verbose:
+ print separator
+ print indent(1)+' Workload {} winner for kernel {}:'.format(workload, self.name)
+ print indent(2)+'{} {} => {}'.format(best_workload_global_size,
+ best_workload_local_size, best_workload_stats)
+
+ if (best_params_stats is None) or (best_workload_stats<best_workload_stats):
+ best_params_workload = workload
+ best_params_stats = best_workload_stats
+ best_params_global_size = best_workload_global_size
+ best_params_local_size = best_workload_local_size
+
+ if verbose:
+ print separator
+ print ' Current parameters winner for kernel {}:'.format(self.name)
+ if (best_params_stats is None):
+ print indent(1)+'no winner (all candidates were pruned)'
+ else:
+ print indent(1)+'{} {} => {}'.format(best_params_global_size,
+ best_params_local_size, best_params_stats)
+
+ if (best_params_stats is not None) and \
+ ((best_stats is None) or (best_params_stats<best_stats)):
+ best_workload = best_params_workload
+ best_stats = best_params_stats
+ best_global_size = best_params_global_size
+ best_local_size = best_params_local_size
+ best_extra_params = extra_parameters
+
+ if (self.autotuner_config.verbose>0):
+ if verbose>1:
+ print separator
+ print ' BEST OVERALL RESULT for kernel {}:'.format(self.name)
+ print ' => Extra params: {}'.format(best_extra_params)
+ print ' => WL={} G={} L={} => {}'.format(best_workload, best_global_size, best_local_size,
+ best_stats)
+ if verbose>1:
+ print separator
+ print '='*len('== Kernel {} Autotuning =='.format(self.name))
+ print
+
+ ret = (best_global_size, best_local_size, best_stats, best_workload, best_extra_params)
+ full_results[bench_key] = (ret, self.autotuner_config)
+ self._dump_cache()
+
+ return ret
+
+
+ def _bench_one(self,ctx,device,global_size,local_work_size,kernel,kernel_args,nruns,
+ best_stat):
+
+ assert(nruns>=1)
+ profiling_enable=cl.command_queue_properties.PROFILING_ENABLE
+ kernel.set_args(*kernel_args)
+
+
+ evts = []
+ with cl.CommandQueue(ctx,device,profiling_enable) as queue:
+ evt = cl.enqueue_nd_range_kernel(queue, kernel, global_size, local_work_size)
+ evts.append(evt)
+ stats = OpenClKernelStatistics(events=evts, nruns=1)
+ if (best_stat is None):
+ pruned = False
+ else:
+ pruned = (stats.min > self.autotuner_config.prune_threshold*best_stat.max)
+
+ if not pruned and nruns>1:
+ with cl.CommandQueue(ctx,device,profiling_enable) as queue:
+ for i in xrange(nruns-1):
+ evt = cl.enqueue_nd_range_kernel(queue, kernel, global_size, local_work_size)
+ evts.append(evt)
+ stats = OpenClKernelStatistics(events=evts,nruns=nruns)
+ return (stats, pruned)
+
+ def _get_wi_candidates(self,ctx,device,max_global_size,**kargs):
+ pows = []
+ size = 1
+
+ max_size = device.max_work_group_size
+ while(size<=max_size):
+ pows.append(size)
+ size <<= 1
+ pows = np.asarray(pows)
+
+ product = []
+ for i in xrange(self.work_dim):
+ good = (pows<=max_global_size[i])
+ product.append(pows[good])
+ for i in xrange(3-self.work_dim):
+ product.append([1])
+ candidates = it.product(*product)
+
+ for fname,f in self.filters.iteritems():
+ F = f(ctx=ctx,device=device,max_global_size=max_global_size,**kargs)
+ candidates = it.ifilter(F, candidates)
+ return candidates
+
+ def _load_default_filters(self):
+ self.filters = {}
+ self.add_filter('dim_reqs',self._dim_filter)
+ self.add_filter('minmax_wi',self._minmax_workitems_filter)
+
+ #default filters
+ def _dim_filter(self,device,**kargs):
+ work_dim = self.local_work_dim
+ max_wi_dim = device.max_work_item_dimensions
+ return lambda local_work_size: (work_dim<=max_wi_dim) and \
+ (work_dim==3
+ or (work_dim==2 and local_work_size[2]==1)
+ or (work_dim==1 and local_work_size[1]==1 and local_work_size[2]==1))
+ def _minmax_workitems_filter(self, device, min_load_factor=None, **kargs):
+ def filter(local_work_size, **kargs):
+ max_wg_size = device.max_work_group_size
+ wi=1
+ for i in xrange(3):
+ wi*=local_work_size[i]
+ if min_load_factor is None:
+ return (wi<=max_wg_size)
+ else:
+ return (wi>=max_wg_size/min_load_factor) and (wi<=max_wg_size)
+ return filter
+
+ #user available filters
+ def ordering_filter(self, **kargs):
+ return lambda local_work_size: (local_work_size[2]<=local_work_size[1]) \
+ and (local_work_size[1]<=local_work_size[0])
+ def min_workitems_per_direction(self, min_local_size, **kargs):
+ if np.isscalar(min_local_size):
+ min_local_size = [min_local_size]
+ else:
+ min_local_size = list(min_local_size)
+ min_local_size = np.asarray(min_local_size)
+ wd = self.work_dim
+ return lambda local_work_size,**kargs: (local_work_size[:wd]>=min_local_size).all()
+ def max_workitems_per_direction(self, max_local_size, **kargs):
+ if np.isscalar(max_local_size):
+ max_local_size = [max_local_size]
+ else:
+ max_local_size = list(max_local_size)
+ max_local_size = np.asarray(max_local_size)
+ wd = self.work_dim
+ return lambda local_work_size,**kargs: (local_work_size[:wd]<=max_local_size).all()
+
diff --git a/hysop/backend/device/kernel_config.py b/hysop/backend/device/kernel_config.py
new file mode 100644
index 0000000000000000000000000000000000000000..fa642b94402aa41335eb70c563333312749fb8c5
--- /dev/null
+++ b/hysop/backend/device/kernel_config.py
@@ -0,0 +1,23 @@
+
+from hysop.constants import DeviceType, Precision
+from hysop.backend.device.kernel_autotuner import AutotunerConfig
+from hysop.tools.types import check_instance
+
+class KernelConfig(object):
+
+ def __init__(self,
+ user_build_options=[],
+ user_size_constants=[],
+ autotuner_config=AutotunerConfig(),
+ precision=Precision.SAME):
+
+ check_instance(user_build_options, list, values=str)
+ check_instance(user_size_constants, list)
+ check_instance(precision, Precision)
+ check_instance(autotuner_config, AutotunerConfig)
+
+ self.user_build_options = user_build_options
+ self.user_size_constants = user_size_constants
+ self.precision = precision
+ self.autotuner_config = autotuner_config
+
diff --git a/hysop/backend/device/logical_device.py b/hysop/backend/device/logical_device.py
new file mode 100644
index 0000000000000000000000000000000000000000..77a27049f16b4ab13bba2a9534b177c28d964e6e
--- /dev/null
+++ b/hysop/backend/device/logical_device.py
@@ -0,0 +1,307 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.tools.enum import EnumFactory
+from hysop.backend.handle import Handle
+
+class UnknownDeviceAttribute(object):
+ def __str__(self):
+ return 'unknown'
+
+
+class LogicalDevice(Handle):
+
+ __metaclass__ = ABCMeta
+
+ def __init__(self, platform, device_handle, hardware_topo, **kargs):
+ super(LogicalDevice,self).__init__(handle=device_handle, **kargs)
+ self._platform = platform
+ if hardware_topo:
+ self._physical_device = self._match_physical_device(hardware_topo)
+ else:
+ self._physical_device = None
+
+ def backend(self):
+ return self._platform.backend()
+
+ def platform(self):
+ return self._platform
+
+ def physical_device(self):
+ return self._physical_device
+
+ @abstractmethod
+ def _match_physical_device(self, hardware_topo):
+ pass
+
+#DEVICE
+ @abstractmethod
+ def name(self):
+ pass
+ @abstractmethod
+ def platform_name(self):
+ pass
+ @abstractmethod
+ def type(self):
+ pass
+ @abstractmethod
+ def vendor(self):
+ pass
+ @abstractmethod
+ def vendor_id(self):
+ pass
+ @abstractmethod
+ def max_clock_frequency(self):
+ pass
+ @abstractmethod
+ def address_bits(self):
+ pass
+ @abstractmethod
+ def little_endian(self):
+ pass
+ @abstractmethod
+ def available(self):
+ pass
+ @abstractmethod
+ def compiler_available(self):
+ pass
+ @abstractmethod
+ def error_correction_support(self):
+ pass
+
+#KERNEL
+ @abstractmethod
+ def max_grid_dim(self):
+ pass
+ @abstractmethod
+ def max_grid_size(self):
+ pass
+ @abstractmethod
+ def max_block_dim(self):
+ pass
+ @abstractmethod
+ def max_block_size(self):
+ pass
+ @abstractmethod
+ def max_threads_per_block(self):
+ pass
+ @abstractmethod
+ def simd_lane_size(self):
+ pass
+
+ @abstractmethod
+ def max_constant_args(self):
+ pass
+
+#MEMORY
+ @abstractmethod
+ def global_mem_size(self):
+ pass
+ @abstractmethod
+ def global_mem_cache_size(self):
+ pass
+ @abstractmethod
+ def global_mem_cacheline_size(self):
+ pass
+ @abstractmethod
+ def global_mem_cache_type(self):
+ pass
+ @abstractmethod
+ def max_global_alloc_size(self):
+ pass
+
+ @abstractmethod
+ def local_mem_size(self):
+ pass
+ @abstractmethod
+ def local_mem_type(self):
+ pass
+
+
+#DEVICE SPLITTING
+ @abstractmethod
+ def has_device_partition_support(self):
+ pass
+ @abstractmethod
+ def max_subdevices(self):
+ pass
+ @abstractmethod
+ def partition_device(self, n):
+ pass
+
+# QUEUES
+ @abstractmethod
+ def has_queue_priority_support(self):
+ pass
+
+#FP SUPPORT
+ @abstractmethod
+ def has_fp16(self):
+ pass
+ @abstractmethod
+ def has_fp32(self):
+ pass
+ @abstractmethod
+ def has_fp64(self):
+ pass
+ @abstractmethod
+ def fp16_config(self):
+ pass
+ @abstractmethod
+ def fp32_config(self):
+ pass
+ @abstractmethod
+ def fp64_config(self):
+ pass
+
+#IMAGES
+ def has_image_support(self):
+ pass
+ def max_image_args(self):
+ pass
+ def max_read_image_args(self):
+ pass
+ def max_write_image_args(self):
+ pass
+ def max_samplers(self):
+ pass
+
+ def has_1d_image_support(self):
+ pass
+ def has_2d_image_support(self):
+ pass
+ def has_3d_image_support(self):
+ pass
+
+ def has_1d_image_write_support(self):
+ pass
+ def has_2d_image_write_support(self):
+ pass
+ def has_3d_image_write_support(self):
+ pass
+
+ def has_1d_image_array_support(self):
+ pass
+ def has_2d_array_image_support(self):
+ pass
+
+ def max_1d_image_size(self):
+ pass
+ def max_1d_image_array_size(self):
+ pass
+
+ def max_2d_image_size(self):
+ pass
+ def max_2d_image_array_size(self):
+ pass
+
+ def max_3d_image_size(self):
+ pass
+
+
+ def has_2d_image_from_buffer_support(self):
+ pass
+ def has_2d_image_from_image_support(self):
+ pass
+
+ def image_base_address_alignment(self):
+ pass
+ def image_pitch_aligment(self):
+ pass
+ def image_max_buffer_size(self):
+ pass
+ def image_max_array_size(self):
+ pass
+
+
+#ATOMICS
+ @abstractmethod
+ def has_global_int32_atomics(self):
+ pass
+ @abstractmethod
+ def has_global_int64_atomics(self):
+ pass
+ @abstractmethod
+ def has_global_float32_atomics(self):
+ pass
+ @abstractmethod
+ def has_global_float64_atomics(self):
+ pass
+
+ @abstractmethod
+ def has_local_int32_atomics(self):
+ pass
+ @abstractmethod
+ def has_local_int64_atomics(self):
+ pass
+ @abstractmethod
+ def has_local_float32_atomics(self):
+ pass
+ @abstractmethod
+ def has_local_float64_atomics(self):
+ pass
+
+ @abstractmethod
+ def has_mixed_int32_atomics(self):
+ pass
+ @abstractmethod
+ def has_mixed_int64_atomics(self):
+ pass
+ @abstractmethod
+ def has_mixed_float32_atomics(self):
+ pass
+ @abstractmethod
+ def has_mixed_float64_atomics(self):
+ pass
+
+ @abstractmethod
+ def has_int32_hardware_atomic_counters(self):
+ pass
+ @abstractmethod
+ def has_int64_hardware_atomic_counters(self):
+ pass
+
+ @abstractmethod
+ def preferred_platform_atomic_alignment(self):
+ pass
+ @abstractmethod
+ def preferred_local_atomic_alignment(self):
+ pass
+ @abstractmethod
+ def preferred_global_atomic_alignment(self):
+ pass
+
+# PROFILING
+ @abstractmethod
+ def has_profiling_support(self):
+ pass
+ @abstractmethod
+ def profiling_time_resolution(self):
+ pass
+
+# PRINTF
+ @abstractmethod
+ def has_printf_support(self):
+ pass
+ @abstractmethod
+ def printf_buffer_size(self):
+ pass
+
+# GRAPHIC API SHARING
+ @abstractmethod
+ def has_gl_sharing(self):
+ pass
+ @abstractmethod
+ def has_gl_event_sharing(self):
+ pass
+ @abstractmethod
+ def has_gl_msaa_sharing(self):
+ pass
+ @abstractmethod
+ def has_dx9_sharing(self):
+ pass
+ @abstractmethod
+ def has_dx10_sharing(self):
+ pass
+ @abstractmethod
+ def has_dx11_sharing(self):
+ pass
diff --git a/hysop/backend/device/opencl/__init__.py b/hysop/backend/device/opencl/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..3966ba85a770eb9ead03e3966dfc726c5f277495
--- /dev/null
+++ b/hysop/backend/device/opencl/__init__.py
@@ -0,0 +1,50 @@
+"""
+Everything concerning OpenCL in hysop.
+Some sources are parsed at build to handle several OpenCL features.
+Other sources are generated and optimized at runtime.
+see hysop.backend.device.opencl.opencl_tools.parse_file
+see hysop.backend.device.codegen
+"""
+
+import pyopencl
+import pyopencl.tools
+import pyopencl.array
+import pyopencl.characterize
+import pyopencl.reduction
+import pyopencl.clrandom
+import pyopencl.elementwise
+import pyopencl.scan
+
+from hysop import __DEFAULT_PLATFORM_ID__, __DEFAULT_DEVICE_ID__, __VERBOSE__
+
+KERNEL_DUMP_FOLDER='opencl_generated_kernels'
+"""Default folder to dump debug opencl kernel sources"""
+
+__OPENCL_PROFILE__ = False
+"""Boolean, true to enable OpenCL profiling events to time computations"""
+
+## open cl underlying implementation
+cl = pyopencl
+"""PyOpencl module, underlying OpenCL implementation"""
+
+clTools = pyopencl.tools
+"""PyOpencl tools"""
+
+clArray = pyopencl.array
+"""PyOpenCL arrays"""
+
+clRandom = pyopencl.clrandom
+"""PyOpenCL random"""
+
+clReduction = pyopencl.reduction
+"""PyOpenCL reductions"""
+
+clScan = pyopencl.scan
+"""PyOpenCL scan"""
+
+clElementwise = pyopencl.elementwise
+"""PyOpenCL reductions"""
+
+clCharacterize = pyopencl.characterize
+"""PyOpenCL characterize"""
+
diff --git a/hysop/gpu/cl_src/advection/basic_rk2.cl b/hysop/backend/device/opencl/cl_src/advection/basic_rk2.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/basic_rk2.cl
rename to hysop/backend/device/opencl/cl_src/advection/basic_rk2.cl
diff --git a/hysop/gpu/cl_src/advection/basic_rk2_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/basic_rk2_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/basic_rk2_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/basic_rk2_noVec.cl
diff --git a/hysop/gpu/cl_src/advection/basic_rk4.cl b/hysop/backend/device/opencl/cl_src/advection/basic_rk4.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/basic_rk4.cl
rename to hysop/backend/device/opencl/cl_src/advection/basic_rk4.cl
diff --git a/hysop/gpu/cl_src/advection/basic_rk4_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/basic_rk4_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/basic_rk4_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/basic_rk4_noVec.cl
diff --git a/hysop/gpu/cl_src/advection/builtin_euler_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/builtin_euler_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/builtin_euler_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/builtin_euler_noVec.cl
diff --git a/hysop/gpu/cl_src/advection/builtin_rk2.cl b/hysop/backend/device/opencl/cl_src/advection/builtin_rk2.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/builtin_rk2.cl
rename to hysop/backend/device/opencl/cl_src/advection/builtin_rk2.cl
diff --git a/hysop/gpu/cl_src/advection/builtin_rk2_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/builtin_rk2_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/builtin_rk2_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/builtin_rk2_noVec.cl
diff --git a/hysop/gpu/cl_src/advection/builtin_rk4.cl b/hysop/backend/device/opencl/cl_src/advection/builtin_rk4.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/builtin_rk4.cl
rename to hysop/backend/device/opencl/cl_src/advection/builtin_rk4.cl
diff --git a/hysop/gpu/cl_src/advection/builtin_rk4_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/builtin_rk4_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/builtin_rk4_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/builtin_rk4_noVec.cl
diff --git a/hysop/gpu/cl_src/advection/comm_basic_rk2_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/comm_basic_rk2_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/comm_basic_rk2_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/comm_basic_rk2_noVec.cl
diff --git a/hysop/gpu/cl_src/advection/comm_builtin_rk2_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/comm_builtin_rk2_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/comm_builtin_rk2_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/comm_builtin_rk2_noVec.cl
diff --git a/hysop/gpu/cl_src/advection/velocity_cache.cl b/hysop/backend/device/opencl/cl_src/advection/velocity_cache.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/velocity_cache.cl
rename to hysop/backend/device/opencl/cl_src/advection/velocity_cache.cl
diff --git a/hysop/gpu/cl_src/advection/velocity_cache_noVec.cl b/hysop/backend/device/opencl/cl_src/advection/velocity_cache_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/advection/velocity_cache_noVec.cl
rename to hysop/backend/device/opencl/cl_src/advection/velocity_cache_noVec.cl
diff --git a/hysop/gpu/cl_src/common.cl b/hysop/backend/device/opencl/cl_src/common.cl
similarity index 100%
rename from hysop/gpu/cl_src/common.cl
rename to hysop/backend/device/opencl/cl_src/common.cl
diff --git a/hysop/gpu/cl_src/kernels/advection.cl b/hysop/backend/device/opencl/cl_src/kernels/advection.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/advection.cl
rename to hysop/backend/device/opencl/cl_src/kernels/advection.cl
diff --git a/hysop/gpu/cl_src/kernels/advection_and_remeshing.cl b/hysop/backend/device/opencl/cl_src/kernels/advection_and_remeshing.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/advection_and_remeshing.cl
rename to hysop/backend/device/opencl/cl_src/kernels/advection_and_remeshing.cl
diff --git a/hysop/gpu/cl_src/kernels/advection_and_remeshing_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/advection_and_remeshing_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/advection_and_remeshing_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/advection_and_remeshing_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/advection_euler_and_remeshing_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/advection_euler_and_remeshing_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/advection_euler_and_remeshing_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/advection_euler_and_remeshing_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/advection_euler_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/advection_euler_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/advection_euler_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/advection_euler_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/advection_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/advection_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/advection_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/advection_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/comm_MS_advection_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/comm_MS_advection_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/comm_MS_advection_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/comm_MS_advection_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/comm_advection_MS_and_remeshing_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/comm_advection_MS_and_remeshing_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/comm_advection_MS_and_remeshing_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/comm_advection_MS_and_remeshing_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/comm_advection_and_remeshing_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/comm_advection_and_remeshing_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/comm_advection_and_remeshing_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/comm_advection_and_remeshing_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/comm_advection_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/comm_advection_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/comm_advection_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/comm_advection_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/comm_remeshing_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/comm_remeshing_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/comm_remeshing_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/comm_remeshing_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/copy.cl b/hysop/backend/device/opencl/cl_src/kernels/copy.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/copy.cl
rename to hysop/backend/device/opencl/cl_src/kernels/copy.cl
diff --git a/hysop/gpu/cl_src/kernels/copy_locMem.cl b/hysop/backend/device/opencl/cl_src/kernels/copy_locMem.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/copy_locMem.cl
rename to hysop/backend/device/opencl/cl_src/kernels/copy_locMem.cl
diff --git a/hysop/gpu/cl_src/kernels/copy_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/copy_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/copy_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/copy_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/diffusion.cl b/hysop/backend/device/opencl/cl_src/kernels/diffusion.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/diffusion.cl
rename to hysop/backend/device/opencl/cl_src/kernels/diffusion.cl
diff --git a/hysop/gpu/cl_src/kernels/fine_to_coarse_filter.cl b/hysop/backend/device/opencl/cl_src/kernels/fine_to_coarse_filter.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/fine_to_coarse_filter.cl
rename to hysop/backend/device/opencl/cl_src/kernels/fine_to_coarse_filter.cl
diff --git a/hysop/gpu/cl_src/kernels/multiphase_baroclinic_rhs.cl b/hysop/backend/device/opencl/cl_src/kernels/multiphase_baroclinic_rhs.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/multiphase_baroclinic_rhs.cl
rename to hysop/backend/device/opencl/cl_src/kernels/multiphase_baroclinic_rhs.cl
diff --git a/hysop/gpu/cl_src/kernels/remeshing.cl b/hysop/backend/device/opencl/cl_src/kernels/remeshing.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/remeshing.cl
rename to hysop/backend/device/opencl/cl_src/kernels/remeshing.cl
diff --git a/hysop/gpu/cl_src/kernels/remeshing_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/remeshing_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/remeshing_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/remeshing_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/rendering.cl b/hysop/backend/device/opencl/cl_src/kernels/rendering.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/rendering.cl
rename to hysop/backend/device/opencl/cl_src/kernels/rendering.cl
diff --git a/hysop/gpu/cl_src/kernels/transpose_xy.cl b/hysop/backend/device/opencl/cl_src/kernels/transpose_xy.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/transpose_xy.cl
rename to hysop/backend/device/opencl/cl_src/kernels/transpose_xy.cl
diff --git a/hysop/gpu/cl_src/kernels/transpose_xy_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/transpose_xy_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/transpose_xy_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/transpose_xy_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/transpose_xz.cl b/hysop/backend/device/opencl/cl_src/kernels/transpose_xz.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/transpose_xz.cl
rename to hysop/backend/device/opencl/cl_src/kernels/transpose_xz.cl
diff --git a/hysop/gpu/cl_src/kernels/transpose_xz_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/transpose_xz_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/transpose_xz_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/transpose_xz_noVec.cl
diff --git a/hysop/gpu/cl_src/kernels/transpose_xz_slice.cl b/hysop/backend/device/opencl/cl_src/kernels/transpose_xz_slice.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/transpose_xz_slice.cl
rename to hysop/backend/device/opencl/cl_src/kernels/transpose_xz_slice.cl
diff --git a/hysop/gpu/cl_src/kernels/transpose_xz_slice_noVec.cl b/hysop/backend/device/opencl/cl_src/kernels/transpose_xz_slice_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/kernels/transpose_xz_slice_noVec.cl
rename to hysop/backend/device/opencl/cl_src/kernels/transpose_xz_slice_noVec.cl
diff --git a/hysop/gpu/cl_src/remeshing/basic.cl b/hysop/backend/device/opencl/cl_src/remeshing/basic.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/basic.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/basic.cl
diff --git a/hysop/gpu/cl_src/remeshing/basic_noVec.cl b/hysop/backend/device/opencl/cl_src/remeshing/basic_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/basic_noVec.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/basic_noVec.cl
diff --git a/hysop/gpu/cl_src/remeshing/comm_basic_noVec.cl b/hysop/backend/device/opencl/cl_src/remeshing/comm_basic_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/comm_basic_noVec.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/comm_basic_noVec.cl
diff --git a/hysop/gpu/cl_src/remeshing/private.cl b/hysop/backend/device/opencl/cl_src/remeshing/private.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/private.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/private.cl
diff --git a/hysop/gpu/cl_src/remeshing/private_noVec.cl b/hysop/backend/device/opencl/cl_src/remeshing/private_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/private_noVec.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/private_noVec.cl
diff --git a/hysop/gpu/cl_src/remeshing/weights.cl b/hysop/backend/device/opencl/cl_src/remeshing/weights.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/weights.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/weights.cl
diff --git a/hysop/gpu/cl_src/remeshing/weights_builtin.cl b/hysop/backend/device/opencl/cl_src/remeshing/weights_builtin.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/weights_builtin.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/weights_builtin.cl
diff --git a/hysop/gpu/cl_src/remeshing/weights_noVec.cl b/hysop/backend/device/opencl/cl_src/remeshing/weights_noVec.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/weights_noVec.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/weights_noVec.cl
diff --git a/hysop/gpu/cl_src/remeshing/weights_noVec_builtin.cl b/hysop/backend/device/opencl/cl_src/remeshing/weights_noVec_builtin.cl
similarity index 100%
rename from hysop/gpu/cl_src/remeshing/weights_noVec_builtin.cl
rename to hysop/backend/device/opencl/cl_src/remeshing/weights_noVec_builtin.cl
diff --git a/hysop/fakef2py/__init__.py b/hysop/backend/device/opencl/device_config/__init__.py
similarity index 100%
rename from hysop/fakef2py/__init__.py
rename to hysop/backend/device/opencl/device_config/__init__.py
diff --git a/hysop/backend/device/opencl/device_config/config_cayman.py b/hysop/backend/device/opencl/device_config/config_cayman.py
new file mode 100644
index 0000000000000000000000000000000000000000..a6dd8e322cf1ab6bbdfb2bbf047fccc03bdc8bcd
--- /dev/null
+++ b/hysop/backend/device/opencl/device_config/config_cayman.py
@@ -0,0 +1,176 @@
+"""
+@file config_cayman.py
+
+OpenCL kernels configurations.
+"""
+from hysop.deps import np
+FLOAT_GPU, DOUBLE_GPU = np.float32, np.float64
+
+#build empty dictionaries
+kernels_config = {}
+kernels_config[2] = {FLOAT_GPU: {}, DOUBLE_GPU: {}}
+kernels_config[3] = {FLOAT_GPU: {}, DOUBLE_GPU: {}}
+
+# Copy kernel:
+def copy_space_index_2d(size, t_dim, b_rows, vec):
+ gwi = (int(size[0] / vec), int(b_rows * size[1] / t_dim), 1)
+ lwi = (t_dim / vec, b_rows, 1)
+ return gwi, lwi
+def copy_space_index_3d(size, t_dim, b_rows, vec):
+ gwi = (int(size[0] / vec), int(b_rows * size[1] / t_dim), int(size[2]))
+ lwi = (t_dim / vec, b_rows, 1)
+ return gwi, lwi
+# Configs : sources, tile size, block rows, vector size, index space function
+kernels_config[3][FLOAT_GPU]['copy'] = \
+ ('kernels/copy.cl', 16, 8, 4, copy_space_index_3d)
+kernels_config[3][DOUBLE_GPU]['copy'] = \
+ ('kernels/copy_locMem.cl', 32, 8, 1, copy_space_index_3d)
+kernels_config[2][FLOAT_GPU]['copy'] = \
+ ('kernels/copy.cl', 16, 8, 2, copy_space_index_2d)
+kernels_config[2][DOUBLE_GPU]['copy'] = \
+ ('kernels/copy.cl', 32, 2, 2, copy_space_index_2d)
+
+# Transpositions kernels:
+# XY transposition
+# Settings are taken from destination layout as current layout.
+# gwi is computed form input layout (appears as transposed layout)
+def xy_space_index_2d(size, t_dim, b_rows, vec):
+ gwi = (int(size[1] / vec), int(b_rows * size[0] / t_dim), 1)
+ lwi = (t_dim / vec, b_rows, 1)
+ return gwi, lwi
+def xy_space_index_3d(size, t_dim, b_rows, vec):
+ gwi = (int(size[1] / vec), int(b_rows * size[0] / t_dim), int(size[2]))
+ lwi = (t_dim / vec, b_rows, 1)
+ return gwi, lwi
+# Configs : sources, tile size, block rows, is padding, vector size,
+# index space function
+kernels_config[3][FLOAT_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy.cl', 16, 8, True, 2, xy_space_index_3d)
+kernels_config[3][DOUBLE_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy.cl', 32, 4, True, 4, xy_space_index_3d)
+kernels_config[2][FLOAT_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy.cl', 32, 8, True, 4, xy_space_index_2d)
+kernels_config[2][DOUBLE_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy.cl', 32, 2, True, 4, xy_space_index_2d)
+
+# XZ transposition
+# Settings are taken from destination layout as current layout.
+# gwi is computed form input layout (appears as transposed layout)
+def xz_space_index_3d(size, t_dim, b_rows, b_deph, vec):
+ gwi = (int(size[2] / vec), int(b_rows * size[1] / t_dim), int(b_deph * size[0] / t_dim))
+ lwi = (t_dim / vec, b_rows, b_deph)
+ return gwi, lwi
+# Configs : sources, tile size, block rows, block depth, is padding,
+# vector size, index space function
+kernels_config[3][FLOAT_GPU]['transpose_xz'] = \
+ ('kernels/transpose_xz.cl', 16, 4, 4, True, 1, xy_space_index_3d)
+kernels_config[3][DOUBLE_GPU]['transpose_xz'] = \
+ ('kernels/transpose_xz.cl', 8, 2, 2, False, 1, xy_space_index_3d)
+
+
+def computational_kernels_index_space(size, vec):
+ dim = len(size)
+ if dim == 3:
+ wi = 64
+ if dim == 2:
+ wi = 256
+ # Change work-item regarding problem size
+ if size[0] % wi > 0:
+ if dim == 3:
+ print "Warning : GPU best performances obtained for",
+ print "problem sizes multiples of 64"
+ else:
+ print "Warning : GPU best performances obtained for",
+ print "problem sizes multiples of 256"
+ while(size[0] % wi > 0):
+ wi = wi / 2
+ # Change work-item regarding vector_width
+ if wi * vec > size[0]:
+ if size[0] % vec > 0:
+ raise ValueError(
+ "Resolution ({0}) must be a multiple of {1}".format(
+ size[0], vec))
+ wi = size[0] // vec
+ if dim == 3:
+ gwi = (int(wi), int(size[1]), int(size[2]))
+ lwi = (int(wi), 1, 1)
+ else:
+ gwi = (int(wi), int(size[1]))
+ lwi = (int(wi), 1)
+ return gwi, lwi
+
+# Advection kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache.cl", "advection/builtin_RKN.cl",
+ "kernels/advection.cl"],
+ False, 4, computational_kernels_index_space)
+kernels_config[3][DOUBLE_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache.cl", "advection/builtin_RKN.cl",
+ "kernels/advection.cl"],
+ False, 2, computational_kernels_index_space)
+kernels_config[2][FLOAT_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache.cl", "advection/builtin_RKN.cl",
+ "kernels/advection.cl"],
+ False, 4, computational_kernels_index_space)
+kernels_config[2][DOUBLE_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_noVec.cl"],
+ False, 1, computational_kernels_index_space)
+
+# Remeshing kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_builtin.cl", "remeshing/private.cl",
+ "kernels/remeshing.cl"],
+ False, 4, computational_kernels_index_space)
+kernels_config[3][DOUBLE_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_builtin.cl", "remeshing/private.cl",
+ "kernels/remeshing.cl"],
+ False, 4, computational_kernels_index_space)
+kernels_config[2][FLOAT_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic.cl",
+ "kernels/remeshing.cl"],
+ True, 4, computational_kernels_index_space)
+kernels_config[2][DOUBLE_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic.cl",
+ "kernels/remeshing.cl"],
+ True, 4, computational_kernels_index_space)
+
+# Advection and remeshing kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_builtin.cl", "remeshing/private.cl",
+ "advection/velocity_cache.cl","advection/builtin_RKN.cl",
+ "kernels/advection_and_remeshing.cl"],
+ False, 4, computational_kernels_index_space)
+kernels_config[3][DOUBLE_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_builtin.cl", "remeshing/private.cl",
+ "advection/velocity_cache.cl", "advection/builtin_RKN.cl",
+ "kernels/advection_and_remeshing.cl"],
+ True, 4, computational_kernels_index_space)
+kernels_config[2][FLOAT_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic.cl",
+ "advection/velocity_cache.cl", "advection/builtin_RKN.cl",
+ "kernels/advection_and_remeshing.cl"],
+ True, 8, computational_kernels_index_space)
+kernels_config[2][DOUBLE_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic.cl",
+ "advection/velocity_cache.cl", "advection/builtin_RKN.cl",
+ "kernels/advection_and_remeshing.cl"],
+ True, 4, computational_kernels_index_space)
+
+
+
diff --git a/hysop/backend/device/opencl/device_config/config_default.py b/hysop/backend/device/opencl/device_config/config_default.py
new file mode 100644
index 0000000000000000000000000000000000000000..79f224a7e7204f658bf81113b0c163178eca4c44
--- /dev/null
+++ b/hysop/backend/device/opencl/device_config/config_default.py
@@ -0,0 +1,248 @@
+"""
+@file config_default.py
+
+OpenCL kernels default configurations.
+"""
+from hysop.deps import np
+FLOAT_GPU, DOUBLE_GPU = np.float32, np.float64
+MAX_GWI = (256, 256, 256)
+
+#build empty dictionaries
+kernels_config = {}
+kernels_config[2] = {FLOAT_GPU: {}, DOUBLE_GPU: {}}
+kernels_config[3] = {FLOAT_GPU: {}, DOUBLE_GPU: {}}
+
+def _clamp_max(w, m):
+ while w > m:
+ w /= 2
+ return int(w)
+
+
+def check_max(t_gwi):
+ return tuple([_clamp_max(w, m) for w, m in zip(t_gwi, MAX_GWI)])
+
+# Transpositions kernels:
+# XY transposition
+# Settings are taken from destination layout as current layout.
+# gwi is computed form input layout (appears as transposed layout)
+def xy_space_index_2d(size, t_dim, b_rows, vec):
+ gwi = check_max((size[1] / vec, b_rows * size[0] / t_dim, 1))
+ lwi = (t_dim / vec, b_rows, 1)
+ blocs_nb = ((size[1] / vec) / lwi[0],
+ (b_rows * size[0] / t_dim) / lwi[1], None)
+ return gwi, lwi, blocs_nb
+def xy_space_index_3d(size, t_dim, b_rows, vec):
+ gwi = check_max((size[1] / vec, b_rows * size[0] / t_dim, size[2]))
+ lwi = (t_dim / vec, b_rows, 1)
+ blocs_nb = ((size[1] / vec) / lwi[0],
+ (b_rows * size[0] / t_dim) / lwi[1], None)
+ return gwi, lwi, blocs_nb
+# Configs : sources, tile size, block rows, is padding, vector size,
+# index space function
+kernels_config[3][FLOAT_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 2, True, 1, xy_space_index_3d)
+kernels_config[3][DOUBLE_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 2, True, 1, xy_space_index_3d)
+kernels_config[2][FLOAT_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 2, True, 1, xy_space_index_2d)
+kernels_config[2][DOUBLE_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 2, True, 1, xy_space_index_2d)
+
+# XZ transposition
+# Settings are taken from destination layout as current layout.
+# gwi is computed form input layout (appears as transposed layout)
+def xz_space_index_3d(size, t_dim, b_rows, b_deph, vec):
+ gwi = check_max((size[2] / vec, size[1], b_deph * size[0] / t_dim))
+ lwi = (t_dim / vec, 1, b_deph)
+ blocs_nb = (((size[2]) / vec) / lwi[0], None,
+ (b_deph * (size[0]) / t_dim) / lwi[2])
+ return gwi, lwi, blocs_nb
+# Configs : sources, tile size, block rows, is padding, vector size,
+# index space function
+kernels_config[3][FLOAT_GPU]['transpose_xz'] = \
+ ('kernels/transpose_xz_slice_noVec.cl', 32, 1, 2, True, 1, xz_space_index_3d)
+kernels_config[3][DOUBLE_GPU]['transpose_xz'] = \
+ ('kernels/transpose_xz_slice_noVec.cl', 32, 1, 2, True, 1, xz_space_index_3d)
+
+def computational_kernels_index_space(wi, size, vec):
+ # Change work-item regarding vector_width
+ if wi * vec > size[0]:
+ if size[0] % vec > 0:
+ raise ValueError(
+ "Resolution ({0}) must be a multiple of {1}".format(
+ size[0], vec))
+ wi = size[0] // vec
+
+ if len(size) == 3:
+ gwi = (int(wi),
+ _clamp_max(size[1], MAX_GWI[1]),
+ _clamp_max(size[2], MAX_GWI[2]))
+ lwi = (int(wi), 1, 1)
+ else:
+ gwi = (int(wi), _clamp_max(size[1], MAX_GWI[1]), 1)
+ lwi = (int(wi), 1, 1)
+ return gwi, lwi
+
+def advection_index_space_3d(size, vec):
+ wi = min(max(32, size[0] / 2), 128)
+ return computational_kernels_index_space(wi, size, vec)
+def advection_index_space_2d_SP(size, vec):
+ wi = min(max(32, size[0] / 2), 128)
+ return computational_kernels_index_space(wi, size, vec)
+def advection_index_space_2d_DP(size, vec):
+ wi = min(max(32, size[0] / 2), 128)
+ return computational_kernels_index_space(wi, size, vec)
+
+def remeshing_index_space_3d(size, vec):
+ wi = min(max(32, size[0] / 2), 128)
+ return computational_kernels_index_space(wi, size, vec)
+def remeshing_index_space_2d(size, vec):
+ wi = min(max(32, size[0] / 2), 128)
+ return computational_kernels_index_space(wi, size, vec)
+
+def advection_and_remeshing_index_space(size, vec):
+ wi = min(size[0] / 2, 128)
+ return computational_kernels_index_space(wi, size, vec)
+
+
+# Advection kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['advec'] = \
+ (["common.cl", "advection/velocity_cache_noVec.cl",
+ "advection/builtin_RKN_noVec.cl", "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['advec'] = \
+ (["common.cl", "advection/velocity_cache_noVec.cl",
+ "advection/builtin_RKN_noVec.cl", "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_3d)
+kernels_config[2][FLOAT_GPU]['advec'] = \
+ (["common.cl", "advection/velocity_cache_noVec.cl",
+ "advection/builtin_RKN_noVec.cl", "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_2d_SP)
+kernels_config[2][DOUBLE_GPU]['advec'] = \
+ (["common.cl", "advection/velocity_cache_noVec.cl",
+ "advection/builtin_RKN_noVec.cl", "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_2d_DP)
+
+# Remeshing kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['remesh'] = \
+ (["common.cl", "remeshing/weights_noVec_builtin.cl",
+ "remeshing/basic_noVec.cl", "kernels/remeshing_noVec.cl"],
+ False, 1, remeshing_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['remesh'] = \
+ (["common.cl", "remeshing/weights_noVec_builtin.cl",
+ "remeshing/basic_noVec.cl", "kernels/remeshing_noVec.cl"],
+ False, 1, remeshing_index_space_3d)
+kernels_config[2][FLOAT_GPU]['remesh'] = \
+ (["common.cl", "remeshing/weights_noVec_builtin.cl",
+ "remeshing/basic_noVec.cl", "kernels/remeshing_noVec.cl"],
+ False, 1, remeshing_index_space_2d)
+kernels_config[2][DOUBLE_GPU]['remesh'] = \
+ (["common.cl", "remeshing/weights_noVec_builtin.cl",
+ "remeshing/basic_noVec.cl", "kernels/remeshing_noVec.cl"],
+ False, 1, remeshing_index_space_2d)
+
+
+# Advection and remeshing kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[3][DOUBLE_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[2][FLOAT_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[2][DOUBLE_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+
+
+def diffusion_space_index_3d(size, nb_part, tile):
+ gwi = check_max((size[0], size[1] / nb_part))
+ lwi = (tile, tile / nb_part)
+ blocs_nb = (size[0] / tile, size[1] / tile)
+ return gwi, lwi, blocs_nb
+
+
+kernels_config[3][FLOAT_GPU]['diffusion'] = \
+ (["common.cl", "kernels/diffusion.cl"],
+ 16, 1, 1, diffusion_space_index_3d)
+
+
+kernels_config[3][DOUBLE_GPU]['advec_comm'] = \
+ (['common.cl', 'kernels/comm_advection_noVec.cl'],
+ False, 1, advection_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['advec_MS_comm'] = \
+ (['common.cl', "remeshing/weights_noVec_builtin.cl",
+ 'kernels/comm_MS_advection_noVec.cl'],
+ False, 1, advection_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_remeshing_noVec.cl'],
+ False, 1, remeshing_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['advec_and_remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_advection_and_remeshing_noVec.cl'],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[3][DOUBLE_GPU]['advec_MS_and_remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_advection_MS_and_remeshing_noVec.cl'],
+ False, 1, advection_and_remeshing_index_space)
+
+
+kernels_config[3][FLOAT_GPU]['advec_comm'] = \
+ (['common.cl', 'kernels/comm_advection_noVec.cl'],
+ False, 1, advection_index_space_3d)
+kernels_config[3][FLOAT_GPU]['advec_MS_comm'] = \
+ (['common.cl', "remeshing/weights_noVec_builtin.cl",
+ 'kernels/comm_MS_advection_noVec.cl'],
+ False, 1, advection_index_space_3d)
+kernels_config[3][FLOAT_GPU]['remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_remeshing_noVec.cl'],
+ False, 1, remeshing_index_space_3d)
+kernels_config[3][FLOAT_GPU]['advec_and_remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_advection_and_remeshing_noVec.cl'],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[3][FLOAT_GPU]['advec_MS_and_remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_advection_MS_and_remeshing_noVec.cl'],
+ False, 1, advection_and_remeshing_index_space)
+
+
+def fine_to_coarse_filter_index_space(size, stencil_width):
+ wg = size[0] / (2 * stencil_width)
+ return ((wg, size[1] / stencil_width, size[2] / stencil_width),
+ (wg, 1, 1))
+
+
+kernels_config[3][FLOAT_GPU]['fine_to_coarse_filter'] = \
+ (["common.cl", 'remeshing/weights_noVec.cl',
+ "kernels/fine_to_coarse_filter.cl"],
+ 1, fine_to_coarse_filter_index_space)
+
+
+def multiphase_baroclinic_index_space(size, tile):
+ wg = (tile, tile, 1)
+ ws = (int(size[0]), int(size[1]), 1)
+ return ws, wg
+
+kernels_config[3][FLOAT_GPU]['multiphase_baroclinic'] = \
+ (["common.cl", "kernels/multiphase_baroclinic_rhs.cl"],
+ 8, 1, multiphase_baroclinic_index_space)
diff --git a/hysop/backend/device/opencl/device_config/config_k20m.py b/hysop/backend/device/opencl/device_config/config_k20m.py
new file mode 100644
index 0000000000000000000000000000000000000000..f0d3857ab56b6b337a33f7dcfd1313ecc776ad23
--- /dev/null
+++ b/hysop/backend/device/opencl/device_config/config_k20m.py
@@ -0,0 +1,245 @@
+"""
+@file config_k20m.py
+
+OpenCL kernels configurations.
+"""
+from hysop.deps import np
+FLOAT_GPU, DOUBLE_GPU = np.float32, np.float64
+MAX_GWI = (1024, 1024, 1024)
+
+
+def _clamp_max(w, m):
+ while w > m:
+ w /= 2
+ return int(w)
+
+
+def check_max(t_gwi):
+ return tuple([_clamp_max(w, m) for w, m in zip(t_gwi, MAX_GWI)])
+
+
+#build empty dictionaries
+kernels_config = {}
+kernels_config[2] = {FLOAT_GPU: {}, DOUBLE_GPU: {}}
+kernels_config[3] = {FLOAT_GPU: {}, DOUBLE_GPU: {}}
+
+# Transpositions kernels:
+# XY transposition
+# Settings are taken from destination layout as current layout.
+# gwi is computed form input layout (appears as transposed layout)
+def xy_space_index_2d(size, t_dim, b_rows, vec):
+ gwi = check_max((size[1] / vec, b_rows * size[0] / t_dim, 1))
+ lwi = (t_dim / vec, b_rows, 1)
+ blocs_nb = ((size[1] / vec) / lwi[0],
+ (b_rows * size[0] / t_dim) / lwi[1], None)
+ return gwi, lwi, blocs_nb
+def xy_space_index_3d(size, t_dim, b_rows, vec):
+ gwi = check_max((size[1] / vec, b_rows * size[0] / t_dim, size[2]))
+ lwi = (t_dim / vec, b_rows, 1)
+ block_nb = ((size[1] / vec) / lwi[0],
+ (b_rows * size[0] / t_dim) / lwi[1], None)
+ return gwi, lwi, block_nb
+# Configs : sources, tile size, block rows, is padding, vector size,
+# index space function
+kernels_config[3][FLOAT_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 4, True, 1, xy_space_index_3d)
+kernels_config[3][DOUBLE_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 16, True, 1, xy_space_index_3d)
+kernels_config[2][FLOAT_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 2, True, 1, xy_space_index_2d)
+kernels_config[2][DOUBLE_GPU]['transpose_xy'] = \
+ ('kernels/transpose_xy_noVec.cl', 32, 8, True, 1, xy_space_index_2d)
+
+# XZ transposition
+# Settings are taken from destination layout as current layout.
+# gwi is computed form input layout (appears as transposed layout)
+def xz_space_index_3d(size, t_dim, b_rows, b_deph, vec):
+ gwi = check_max((size[2] / vec, size[1], b_deph * size[0] / t_dim))
+ lwi = (t_dim / vec, 1, b_deph)
+ blocs_nb = ((size[2] / vec) / lwi[0], None,
+ (b_deph * size[0] / t_dim) / lwi[2])
+ return gwi, lwi, blocs_nb
+# Configs : sources, tile size, block rows, is padding, vector size,
+# index space function
+kernels_config[3][FLOAT_GPU]['transpose_xz'] = \
+ ('kernels/transpose_xz_slice_noVec.cl', 32, 1, 8, True, 1, xz_space_index_3d)
+kernels_config[3][DOUBLE_GPU]['transpose_xz'] = \
+ ('kernels/transpose_xz_slice_noVec.cl', 32, 1, 8, True, 1, xz_space_index_3d)
+
+def computational_kernels_index_space(wi, size, vec):
+ # Change work-item regarding vector_width
+ if wi * vec > size[0]:
+ if size[0] % vec > 0:
+ raise ValueError(
+ "Resolution ({0}) must be a multiple of {1}".format(
+ size[0], vec))
+ wi = size[0] // vec
+
+ if len(size) == 3:
+ gwi = (int(wi),
+ _clamp_max(size[1], MAX_GWI[1]),
+ _clamp_max(size[2], MAX_GWI[2]))
+ lwi = (int(wi), 1, 1)
+ else:
+ gwi = (int(wi), _clamp_max(size[1], MAX_GWI[1]))
+ lwi = (int(wi), 1)
+ return gwi, lwi
+
+def advection_index_space_3d(size, vec):
+ wi = min(size[0] / 4, 1024)
+ return computational_kernels_index_space(wi, size, vec)
+def advection_index_space_2d_SP(size, vec):
+ wi = min(size[0] / 8, 1024)
+ return computational_kernels_index_space(wi, size, vec)
+def advection_index_space_2d_DP(size, vec):
+ wi = min(size[0] / 4, 1024)
+ return computational_kernels_index_space(wi, size, vec)
+
+def remeshing_index_space_3d(size, vec):
+ wi = min(size[0] / 2, 1024)
+ return computational_kernels_index_space(wi, size, vec)
+def remeshing_index_space_2d(size, vec):
+ wi = min(size[0] / 4, 1024)
+ return computational_kernels_index_space(wi, size, vec)
+
+def advection_and_remeshing_index_space(size, vec):
+ wi = min(size[0] / 2, 1024)
+ return computational_kernels_index_space(wi, size, vec)
+
+
+# Advection kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_3d)
+kernels_config[2][FLOAT_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_2d_SP)
+kernels_config[2][DOUBLE_GPU]['advec'] = \
+ (["common.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_noVec.cl"],
+ False, 1, advection_index_space_2d_DP)
+
+# Remeshing kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic_noVec.cl",
+ "kernels/remeshing_noVec.cl"],
+ False, 1, remeshing_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic_noVec.cl",
+ "kernels/remeshing_noVec.cl"],
+ False, 1, remeshing_index_space_3d)
+kernels_config[2][FLOAT_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic.cl",
+ "kernels/remeshing.cl"],
+ True, 2, remeshing_index_space_2d)
+kernels_config[2][DOUBLE_GPU]['remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/basic.cl",
+ "kernels/remeshing.cl"],
+ True, 2, remeshing_index_space_2d)
+
+
+# Advection and remeshing kernel
+# Configs sources, is noBC, vector size, index space function
+kernels_config[3][FLOAT_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[3][DOUBLE_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[2][FLOAT_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[2][DOUBLE_GPU]['advec_and_remesh'] = \
+ (["common.cl",
+ "remeshing/weights_noVec_builtin.cl", "remeshing/private_noVec.cl",
+ "advection/velocity_cache_noVec.cl", "advection/builtin_RKN_noVec.cl",
+ "kernels/advection_and_remeshing_noVec.cl"],
+ False, 1, advection_and_remeshing_index_space)
+
+
+def diffusion_space_index_3d(size, nb_part, tile):
+ gwi = check_max((size[0], size[1] / nb_part))
+ lwi = (tile, tile / nb_part)
+ blocs_nb = (size[0] / tile, size[1] / tile)
+ return gwi, lwi, blocs_nb
+
+
+kernels_config[3][DOUBLE_GPU]['diffusion'] = \
+ (["common.cl", "kernels/diffusion.cl"],
+ 16, 4, 1, diffusion_space_index_3d)
+
+
+kernels_config[3][DOUBLE_GPU]['advec_comm'] = \
+ (['common.cl', 'kernels/comm_advection_noVec.cl'],
+ False, 1, advection_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['advec_MS_comm'] = \
+ (['common.cl', "remeshing/weights_noVec_builtin.cl",
+ 'kernels/comm_MS_advection_noVec.cl'],
+ False, 1, advection_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_remeshing_noVec.cl'],
+ False, 1, remeshing_index_space_3d)
+kernels_config[3][DOUBLE_GPU]['advec_and_remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_advection_and_remeshing_noVec.cl'],
+ False, 1, advection_and_remeshing_index_space)
+kernels_config[3][DOUBLE_GPU]['advec_MS_and_remesh_comm'] = \
+ (['common.cl', 'remeshing/weights_noVec.cl',
+ 'kernels/comm_advection_MS_and_remeshing_noVec.cl'],
+ False, 1, advection_and_remeshing_index_space)
+
+
+def fine_to_coarse_filter_index_space(size, stencil_width):
+ wg = size[0] / (2 * stencil_width)
+ return ((wg, size[1] / stencil_width, size[2] / stencil_width),
+ (wg, 1, 1))
+
+
+kernels_config[3][FLOAT_GPU]['fine_to_coarse_filter'] = \
+ (["common.cl", 'remeshing/weights_noVec.cl',
+ "kernels/fine_to_coarse_filter.cl"],
+ 1, fine_to_coarse_filter_index_space)
+kernels_config[3][DOUBLE_GPU]['fine_to_coarse_filter'] = \
+ (["common.cl", 'remeshing/weights_noVec.cl',
+ "kernels/fine_to_coarse_filter.cl"],
+ 1, fine_to_coarse_filter_index_space)
+
+
+
+def multiphase_baroclinic_index_space(size, tile):
+ wg = (tile, tile, 1)
+ ws = (int(size[0]), int(size[1]), 1)
+ return ws, wg
+
+kernels_config[3][FLOAT_GPU]['multiphase_baroclinic'] = \
+ (["common.cl", "kernels/multiphase_baroclinic_rhs.cl"],
+ 8, 1, multiphase_baroclinic_index_space)
+kernels_config[3][DOUBLE_GPU]['multiphase_baroclinic'] = \
+ (["common.cl", "kernels/multiphase_baroclinic_rhs.cl"],
+ 8, 1, multiphase_baroclinic_index_space)
diff --git a/hysop/backend/device/opencl/opencl_allocator.py b/hysop/backend/device/opencl/opencl_allocator.py
new file mode 100644
index 0000000000000000000000000000000000000000..ecda751b46d561e87f477d0f2f086af338077fc8
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_allocator.py
@@ -0,0 +1,108 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.deps import np
+from hysop.backend.device.opencl import cl
+from hysop.core.memory.allocator import AllocatorBase
+from hysop.backend.device.opencl.opencl_buffer import OpenClBuffer
+
+class OpenClAllocator(AllocatorBase):
+ """
+ Base class for OpenCl backend allocators.
+ """
+ __metaclass__=ABCMeta
+
+ def __init__(self, queue, mem_flags=cl.mem_flags.READ_WRITE):
+ self._queue = queue
+ self._mem_flags = mem_flags
+ if mem_flags & cl.mem_flags.COPY_HOST_PTR:
+ raise ValueError('pyopencl.mem_flags.COPY_HOST_PTR cannot be passed ')
+
+ def get_queue(self):
+ return self._queue
+ def get_context(self):
+ return self._queue.context
+ def get_device(self):
+ return self._queue.device
+ def get_mem_flags(self):
+ return self._mem_flags
+ queue = property(get_queue)
+ context = property(get_context)
+ device = property(get_device)
+ mem_flags = property(get_mem_flags)
+
+ def allocate(self, nbytes, alignment=None):
+ """
+ Wraps _allocate_impl to raise an MemoryError if a cl.Error with the
+ is_out_of_memory flag.
+ Should return an hysop.core.memory.buffer.OpenClBuffer
+ """
+ assert alignment is None, 'alignment is not supported for device allocators.'
+ try:
+ return self._allocate_impl(nbytes=nbytes, alignment=alignment)
+ except cl.Error as e:
+ raise MemoryError(str(e))
+
+ def is_on_host(self):
+ """
+ Return true if buffers are allocated in host memory.
+ """
+ return (self.device.type == cl.device_type.CPU)
+
+ @abstractmethod
+ def _allocate_impl(nbytes, alignment):
+ pass
+
+
+class OpenClDeferredAllocator(OpenClAllocator):
+ """
+ Deferred OpenCL allocator, memory is allocated when used on device.
+ """
+ is_deferred = True
+
+ def _allocate_impl(self, nbytes, alignment):
+ return OpenClBuffer(context=self.context, mem_flags=self.mem_flags, size=nbytes)
+
+
+class OpenClImmediateAllocator(OpenClAllocator):
+ """
+ Immediate OpenCL allocator, memory allocation is not deferred.
+ Convenient for memory pools and to catch allocation errors early.
+ """
+ is_deferred = False
+ _zero = np.array([0, 0, 0, 0], dtype=np.int8)
+
+ def _allocate_impl(self, nbytes, alignment):
+ buf = OpenClBuffer(context=self.context, mem_flags=self.mem_flags, size=nbytes)
+
+ # Make sure the buffer gets allocated right here and right now.
+ # This looks (and is) expensive. But immediate allocators
+ # have their main use in memory pools, whose basic assumption
+ # is that allocation is too expensive anyway--but they rely
+ # on exact 'out-of-memory' information.
+
+ try:
+ from pyopencl.cffi_cl import _enqueue_write_buffer
+ _enqueue_write_buffer(
+ self.queue, buf,
+ self._zero[:min(len(self._zero), nbytes)],
+ is_blocking=False)
+ except RuntimeError as e:
+ # pyopencl will throw a RuntimeError (invalid argument)
+ # if buffer could not be allocated
+ raise MemoryError(str(e))
+
+ # No need to wait for completion here. clWaitForEvents (e.g.)
+ # cannot return mem object allocation failures. This implies that
+ # the buffer is faulted onto the device on enqueue.
+
+ return buf
+
+ def memory_pool(self, name, **kwds):
+ """
+ Construct a memory pool from this allocator.
+ """
+ from hysop.backend.device.opencl.opencl_mempool import MemoryPool, OpenClMemoryPool
+ if isinstance(self, MemoryPool):
+ msg='allocator is already a memory pool.'
+ raise RuntimeError(msg)
+ return OpenClMemoryPool(allocator=self, name=name, **kwds)
diff --git a/hysop/backend/device/opencl/opencl_array.py b/hysop/backend/device/opencl/opencl_array.py
new file mode 100644
index 0000000000000000000000000000000000000000..c6ee55b63af932e782dc223398ae8395ece62a69
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_array.py
@@ -0,0 +1,202 @@
+
+
+import numpy as np
+from hysop.backend.device.opencl import clArray, clTools
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+from hysop.backend.device.opencl.opencl_array_backend import OpenClArrayBackend
+from hysop.core.arrays import MemoryType, MemoryOrdering
+from hysop.core.arrays import default_order
+from hysop.core.arrays.array import Array
+
+class OpenClArray(Array):
+ """
+ OpenCl memory array wrapper (pyopencl.array.Array).
+ """
+
+ def __init__(self, handle, backend, **kargs):
+ """
+ Parameters
+ ----------
+ handle: pyopencl.array.Array, implementation of this array
+ kargs: arguments for base classes.
+ """
+
+ if not isinstance(handle, clArray.Array):
+ msg='Handle should be a pyopencl.array.Array but got a {}.'
+ msg=msg.format(handle.__class__)
+ raise ValueError(msg)
+ if not isinstance(backend, OpenClArrayBackend):
+ msg='Backend should be a OpenClArrayBackend but got a {}.'
+ msg=msg.format(handle.__class__)
+ raise ValueError(msg)
+
+ if handle.dtype in [np.float16, np.longdouble, np.bool]:
+ msg='{} unsupported yet for OpenCl arrays.'.format(handle.dtype)
+ raise TypeError(msg)
+
+ backend.check_queue(handle.queue)
+
+ super(OpenClArray,self).__init__(handle=handle, backend=backend, **kargs)
+
+ def get_ndim(self):
+ return self._handle.ndim
+ def get_shape(self):
+ return self._handle.shape
+ def get_size(self):
+ return self._handle.size
+ def get_strides(self):
+ return self._handle.strides
+ def get_data(self):
+ return self._handle.data
+ def get_base(self):
+ return self._handle.base_data
+ def get_offset(self):
+ return self._handle.offset
+ def get_dtype(self):
+ return self._handle.dtype
+ def get_flags(self):
+ return self._handle.flags
+ def get_T(self):
+ return self._return(self._handle.T)
+ def get_imag(self):
+ return self.backend.imag(self)
+ def get_real(self):
+ return self.backend.real(self)
+ def get_nbytes(self):
+ return self._handle.nbytes
+
+ # array properties
+ ndim = property(get_ndim)
+ shape = property(get_shape)
+ offset = property(get_offset)
+ strides = property(get_strides)
+ data = property(get_data)
+ base = property(get_base)
+ dtype = property(get_dtype)
+ flags = property(get_flags)
+ T = property(get_T)
+ imag = property(get_imag)
+ real = property(get_real)
+ size = property(get_size)
+ nbytes = property(get_nbytes)
+
+ def get_base_data(self):
+ return self._handle.base_data
+ def get_offset(self):
+ return self._handle.offset
+ base_data = property(get_base_data)
+ offset = property(get_offset)
+
+ def ctype(self):
+ """
+ Equivalent C type corresponding to the numpy.dtype.
+ """
+ return clTools.dtype_to_ctype(self.dtype)
+
+
+ def get(self, handle=False,
+ queue=None, ary=None, async=False):
+ """
+ Returns a HostArray, view or copy of this array.
+ """
+ self.backend.check_queue(queue)
+ host_array = self._call('get', queue=queue, ary=ary, async=async)
+ if handle:
+ return host_array._handle
+ if (host_array.size == 1):
+ if host_array.ndim == 0:
+ return host_array._handle
+ if host_array.ndim == 1:
+ return host_array._handle[0]
+ return host_array
+
+
+ # event managment
+ def events(self):
+ """
+ A list of pyopencl.Event instances that the current content of this array depends on.
+ User code may read, but should never modify this list directly.
+ To update this list, instead use the following methods.
+ """
+ return self.handle.events
+
+ def add_event(self, evt):
+ """
+ Add evt to events. If events is too long, this method may implicitly wait
+ for a subset of events and clear them from the list.
+ """
+ self._call('add_event', evt=evt)
+
+ def finish(self):
+ """
+ Wait for the entire contents of events, clear it.
+ """
+ self.handle.finish()
+
+ # queue and context facilities
+ def get_context(self):
+ """
+ Get the opencl context associated to this array.
+ """
+ return self.backend.context
+ def get_device(self):
+ """
+ Get the opencl device associated to this array.
+ """
+ return self.backend.device
+ def set_default_queue(self, queue):
+ """
+ Sets the default queue for this array.
+ """
+ self.backend.check_queue(queue)
+ self._handle.queue = queue
+ def reset_default_queue(self):
+ """
+ Resets the default queue for this array.
+ """
+ self._handle.queue = None
+ def get_default_queue(self):
+ """
+ Get the default queue for this array.
+ """
+ return self._handle.queue or self.backend.default_queue
+
+ context = property(get_context)
+ device = property(get_device)
+ default_queue = property(get_default_queue, set_default_queue)
+
+ def with_queue(queue):
+ """
+ Return a copy of self with the default queue set to queue.
+ """
+ self.backend.check_queue(queue)
+ yield self._call('with_queue', queue=queue)
+
+
+ ## Array specific methods
+ def view(self, dtype):
+ """
+ Returns view of array with the same data. If dtype is different from current dtype,
+ the actual bytes of memory will be reinterpreted.
+ """
+ return self._call('view', dtype=dtype)
+
+ def reshape(self, shape, order=default_order):
+ """
+ Returns view of array with the same data. If dtype is different from current dtype,
+ the actual bytes of memory will be reinterpreted.
+ """
+ return self._call('reshape', shape, order=order)
+
+ def astype(self, dtype, queue=None,
+ order=MemoryOrdering.SAME_ORDER,
+ casting='unsafe', subok=True, copy=True):
+ """
+ Copy of the array, cast to a specified type.
+ """
+ self._unsupported_argument('astype', 'order', order, MemoryOrdering.SAME_ORDER)
+ self._unsupported_argument('astype', 'casting', casting, 'unsafe')
+ self._unsupported_argument('astype', 'subok', subok, True)
+ self._unsupported_argument('astype', 'copy', copy, True)
+ self.backend.check_queue(queue)
+ return self._call('astype', dtype=dtype, queue=queue)
diff --git a/hysop/backend/device/opencl/opencl_array_backend.py b/hysop/backend/device/opencl/opencl_array_backend.py
new file mode 100644
index 0000000000000000000000000000000000000000..981cb7ec62bdd9851721f38a1603811d3b4790a8
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_array_backend.py
@@ -0,0 +1,3031 @@
+
+import warnings
+from hysop.deps import re, np, os
+from hysop.tools.types import check_instance, to_tuple
+from hysop.tools.hash import hash_id
+from hysop.tools.numerics import is_complex, get_dtype, float_to_complex_dtype, \
+ complex_to_float_dtype, find_common_dtype
+from hysop.constants import Backend
+from hysop.constants import HYSOP_REAL, HYSOP_INTEGER, HYSOP_INDEX, HYSOP_BOOL
+from hysop.backend.device.opencl import cl, clArray, clTools, clRandom, \
+ clReduction, clElementwise, clScan
+
+from hysop.core.arrays import default_order, transposition_states
+from hysop.core.arrays import MemoryOrdering, MemoryType, QueuePolicy
+
+from hysop.core.arrays.array_backend import ArrayBackend
+from hysop.core.arrays.array import Array
+
+from hysop.core.memory.mempool import MemoryPool
+
+from hysop.backend.device.opencl.opencl_allocator import OpenClAllocator
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+
+from hysop.tools.numerics import is_fp, is_integer, is_signed, is_unsigned,\
+ get_dtype, match_dtype
+from hysop.tools.types import first_not_None
+
+from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+
+
+class _ElementwiseKernel(object):
+ """
+ Evaluating involved expressions on OpenClArray instances by using overloaded
+ operators can be somewhat inefficient, because a new temporary is created for
+ each intermediate result. ElementwiseKernel generate kernels that evaluate
+ multi-stage expressions on one or several operands in a single pass.
+
+ clElementwise.ElementwiseKernel adapted for use with OpenClArrayBackend.elementwise(...)
+ """
+ def __init__(self, context, arguments, operation,
+ name='elementwise', preamble='', options=[],
+ **kargs):
+ self.kernel = clElementwise.ElementwiseKernel(context=context, arguments=arguments,
+ operation=operation, name=name,
+ preamble=preamble, options=options)
+ def __call__(self, wait_for, args, **kargs):
+ return self.kernel.__call__(wait_for=wait_for, *args)
+
+class _ReductionKernel(object):
+ """
+ Generate a kernel that takes a number of scalar or vector arguments
+ (at least one vector argument), performs the map_expr on each entry
+ of the vector argument and then the reduce_expr on the outcome.
+
+ neutral serves as an initial value and is specified as float or
+ integer formatted as string.
+
+ preamble offers the possibility to add preprocessor directives
+ and other code (such as helper functions) to be included before the
+ actual reduction kernel code.
+
+ vectors in map_expr should be indexed by the variable i.
+
+ reduce_expr uses the formal values 'a' and 'b' to indicate
+ two operands of a binary reduction operation.
+
+ If you do not specify a map_expr, in[i] is automatically
+ assumed and treated as the only one input argument.
+
+ dtype_out specifies the numpy.dtype in which the reduction is performed
+ and in which the result is returned.
+
+ clReduction.ReductionKernel adapted for use with OpenClArrayBackend.elementwise(...)
+ """
+ def __init__(self, context, arguments, reduce_expr, map_expr, neutral, dtype,
+ name='reduce', preamble='', options=[],
+ **kargs):
+ # remove output argument from arguments list
+ arguments = arguments.split(',')
+ arguments = ','.join(arguments[1:])
+
+ self.kernel = clReduction.ReductionKernel(ctx=context, dtype_out=dtype,
+ neutral=neutral,
+ reduce_expr=reduce_expr, map_expr=map_expr,
+ arguments=arguments,
+ name=name, preamble=preamble, options=options)
+
+ def __call__(self, wait_for, return_event, iargs, oargs, pargs, queue, **kargs):
+ assert len(oargs)==1
+ assert len(iargs)>=1
+ return self.kernel.__call__(*(iargs+pargs), out=oargs[0],
+ queue=queue, wait_for=wait_for, return_event=return_event,
+ allocator=None,
+ range=None, slice=None)
+
+class _GenericScanKernel(object):
+ """
+ Generates an OpenCL kernel that performs prefix sums ('scans') on arbitrary types,
+ with many possible tweaks.
+
+ Adapted for use with OpenClArrayBackend.elementwise(...)
+
+ Context and devices:
+ - context: context within the code for this kernel will be generated.
+ - devices may be used to restrict the set of devices on which the kernel is meant to
+ run (defaults to all devices in the context ctx).
+
+ Prefix sum configuration:
+ - dtype specifies the numpy.dtype with which the scan will be performed.
+ May be a structured type if that type was registered through
+ clTools.get_or_register_dtype().
+
+ - arguments: An optional string of comma-separated C argument declarations.
+ If arguments is specified, then input_expr must also be specified.
+
+ - input_expr: A C expression, encoded as a string, resulting in the values to which
+ the scan is applied. This may be used to apply a mapping to values stored
+ in arguments before being scanned.
+ The result of this expression must match dtype.
+
+ - scan_expr: The associative, binary operation carrying out the scan,
+ represented as a C string. Its two arguments are available
+ as a and b when it is evaluated. b is guaranteed to be the
+ element being updated, and a is the increment.
+
+ - neutral is the neutral element of scan_expr, obeying scan_expr(a, neutral) == a.
+
+ - output_statement: a C statement that writes the output of the scan.
+ It has access to the scan result as item, the preceding scan result item as
+ prev_item, and the current index as i.
+ prev_item in a segmented scan will be the neutral element i
+ at a segment boundary, not the immediately preceding item.
+
+ Using prev_item in output statement has a small run-time cost.
+ prev_item enables the construction of an exclusive scan.
+
+ For non-segmented scans, output_statement may also reference last_item,
+ which evaluates to the scan result of the last array entry.
+
+ Segmented scans:
+ - is_segment_start_expr: A C expression, encoded as a string, resulting in a C bool
+ value that determines whether a new scan segments starts at index i.
+ If given, makes the scan a segmented scan. Has access to the current index i,
+ the result of input_expr as a, and in addition may use arguments and input_fetch_expr
+ variables just like input_expr.
+
+ If it returns true, then previous sums will not spill over into the item with
+ index i or subsequent items.
+
+ - input_fetch_exprs: a list of tuples (NAME, ARG_NAME, OFFSET).
+ An entry here has the effect of doing the equivalent of the
+ following before input_expr: ARG_NAME_TYPE NAME = ARG_NAME[i+OFFSET];
+
+ OFFSET is allowed to be 0 or -1
+ ARG_NAME_TYPE is the type of ARG_NAME.
+
+ Kernel generation and build options:
+ - name is used for kernel names to ensure recognizability in profiles and logs.
+ - options is a list of compiler options to use when building.
+ - preamble specifies a string of code that is inserted before the actual kernels.
+
+ clScan.GenericScanKernel adapted for use with OpenClArrayBackend.elementwise(...)
+ """
+ def __init__(self, context, dtype, arguments,
+ input_expr, scan_expr, neutral,
+ output_statement,
+ is_segment_start_expr=None, input_fetch_exprs=None,
+ name='generic_scan', options=[], preamble='',
+ devices=None,
+ index_dtype = np.int32,
+ **kargs):
+
+ input_fetch_exprs = input_fetch_exprs or list()
+
+ self.kernel = clScan.GenericScanKernel(ctx=context,
+ dtype=dtype, index_dtype=index_dtype,
+ arguments=arguments, neutral=neutral,
+ scan_expr=scan_expr, input_expr=input_expr, output_statement=output_statement,
+ is_segment_start_expr=is_segment_start_expr,
+ input_fetch_exprs=input_fetch_exprs,
+ name_prefix=name, preamble=preamble, options=options)
+
+ def __call__(self, args, queue, wait_for=None, size=None, **kargs):
+ """
+ Call the kernel with arguments args.
+ size may specify the length of the scan to be carried out.
+ If not given, this length is inferred from the first array argument passed.
+ """
+ return self.kernel.__call__(*args, queue=queue,
+ size=size, wait_for=wait_for)
+
+
+
+class OpenClArrayBackend(ArrayBackend):
+ """
+ Opencl array backend, extending pyopencl.array.Array capabilities.
+
+ By default all methods are using the default opencl device (setup during
+ build in hysop.__init__.py and hysop.backend.device.opencl.__init__.py)
+ and an associated default command queue. An OpenClArrayBackend can be
+ created with any context and default queue through an OpenClEnvironment.
+
+ See hysop.backend.device.opencl.opencl_tools.get_or_create_opencl_env() for more
+ informations on how to create or get an OpenClEnvironment.
+
+ The default allocator is a hysop.backend.device.opencl.opencl_allocator.OpenClImmediateAllocator
+ and the arrays are created within a hysop.core.memory.MemoryPool based on this allocator
+ so that there is no surprise when the array is first used (out of memory).
+ """
+
+ def get_kind(self):
+ return Backend.OPENCL
+ kind = property(get_kind)
+
+ def get_host_array_backend(self):
+ return self._host_array_backend
+ host_array_backend=property(get_host_array_backend)
+
+ def short_description(self):
+ return ':OpenClBackend: id={}, ctx={}, allocator={}[{}], queue={}, HostBackend[id={}, allocator={}[{}]]'.format(
+ self.identifier(),
+ hash_id(self._context),
+ self._allocator.__class__.__name__, hash_id(self._allocator),
+ hash_id(self._default_queue),
+ self.host_array_backend.identifier(),
+ self.host_array_backend.allocator.__class__.__name__,
+ hash_id(self.host_array_backend.allocator))
+
+ def __eq__(self, other):
+ if not other.__class__ == self.__class__:
+ return NotImplemented
+ eq = (self._context is other._context)
+ eq &= (self._default_queue is other._default_queue)
+ eq &= (self._allocator is other._allocator)
+ eq &= (self.host_array_backend is other.host_array_backend)
+ return eq
+ def __ne__(self):
+ return not (self == other)
+ def __hash__(self):
+ return id(self._context) ^ id(self._default_queue) ^ id(self.allocator) ^ id(self.host_array_backend)
+
+ def __init__(self, cl_env=None, queue=None, allocator=None,
+ host_array_backend=None):
+ """
+ Initialize and OpenClArrayBackend with OpenCL environment cl_env.
+
+ If cl_env and queue are not specified, the default environment returned
+ by get_or_create_opencl_env() will be used along with its default queue.
+
+ If cl_env is not specified but a queue is specified, this queue will be
+ used instead along with its associated context.
+
+ If both queue and cl_env are speficied, context should match.
+ Allocator can be used to override cl_env.memory_pool and should also match context.
+
+ Note that allocation queue can be different from default array computation queue.
+ """
+ check_instance(cl_env, OpenClEnvironment, allow_none=True)
+ check_instance(queue, cl.CommandQueue, allow_none=True)
+ check_instance(allocator, OpenClAllocator, allow_none=True)
+
+ if (queue is None):
+ cl_env = cl_env or get_or_create_opencl_env()
+ context = cl_env.context
+ queue = cl_env.default_queue
+ allocator = allocator or cl_env.memory_pool
+ assert allocator.context == context
+ elif (cl_env is None):
+ context = queue.context
+ if (allocator is None):
+ msg='A custom allocator should be given as input '
+ msg+='(cl_env was not specified but queue was).'
+ raise ValueError(msg)
+ else:
+ # cl_env and queue specified
+ context = cl_env.context
+ allocator = allocator or cl_env.memory_pool
+
+ check_instance(allocator, OpenClAllocator)
+ check_instance(context, cl.Context)
+ check_instance(queue, cl.CommandQueue)
+
+ if queue.context != context:
+ msg = 'Queue does not match context:'
+ msg += '\n *Given context is {}.'.format(context)
+ msg += '\n *Command queue context is {}.'.format(queue.context)
+ raise ValueError(msg)
+ if allocator.context != context:
+ msg = 'Allocator does not match context.'
+ msg += '\n *Given context is {}.'.format(context)
+ msg += '\n *Allocator context is {}.'.format(allocator.context)
+ raise ValueError(msg)
+
+ assert len(context.devices)==1, 'Multidevice contexts are not supported.'
+
+ from hysop.core.arrays.all import HostArrayBackend, \
+ default_host_array_backend
+ host_array_backend = host_array_backend or default_host_array_backend
+ check_instance(host_array_backend, HostArrayBackend)
+
+ super(OpenClArrayBackend,self).__init__(allocator=allocator)
+ self._context = context
+ self._default_queue = queue
+ self._host_array_backend = host_array_backend
+
+ def get_default_queue(self):
+ return self._default_queue
+ def get_context(self):
+ return self._context
+ def get_device(self):
+ return self._context.devices[0]
+
+ default_queue = property(get_default_queue)
+ context = property(get_context)
+ device = property(get_device)
+
+
+# BACKEND SPECIFIC METHODS #
+############################
+ def can_wrap(self, handle):
+ """
+ Should return True if handle is an Array or a array handle corresponding
+ this backend.
+ """
+ from hysop.core.arrays.all import OpenClArray
+ return isinstance(handle, (OpenClArray, clArray.Array))
+
+ def wrap(self, handle):
+ """
+ Create an hysop.backend.device.OpenclArray from an pyopencl.array.Array instance.
+ """
+ from hysop.core.arrays.all import OpenClArray
+
+ if isinstance(handle, OpenClArray):
+ return handle
+
+ check_instance(handle, clArray.Array)
+
+ return OpenClArray(backend=self, handle=handle)
+
+ def _arg(self, arg):
+ """
+ Prepare one argument for a call to pyopencl backend.
+ """
+ if isinstance(arg, QueuePolicy):
+ if arg==QueuePolicy.COPY_QUEUE:
+ return clArray._copy_queue
+ elif arg==QueuePolicy.SAME_AS_TRANSFER:
+ return clArray._same_as_transfer
+ elif arg==QueuePolicy.NO_QUEUE:
+ return None
+ else:
+ msg='Unknown queue policy {}.'.format(arg)
+ raise ValueError(msg)
+ else:
+ return super(OpenClArrayBackend,self)._arg(arg)
+
+
+ def copyto(self, dst, src, queue=None, async=False, **kargs):
+ """
+ src is a OpenClArray
+ dst can be everything
+ """
+ from hysop.core.arrays.all import OpenClArray, HostArray
+ self._check_argtype('copyto', 'src', src, OpenClArray)
+
+ if isinstance(dst, OpenClArray) or isinstance(dst, clArray.Array):
+ if isinstance(dst, clArray.Array):
+ dst = self.wrap(dst)
+ if dst.size != src.size:
+ raise TypeError("'dst' has non-matching size")
+ if dst.dtype != src.dtype:
+ raise TypeError("'dst' has non-matching type")
+ if src.size:
+ queue = first_not_None(queue, src.default_queue, dst.default_queue)
+ evt = cl.enqueue_copy(queue=queue,
+ byte_count = src.nbytes,
+ dest=dst.base, src=src.base,
+ dest_offset=dst.offset, src_offset=src.offset)
+ if async:
+ return evt
+ else:
+ evt.wait()
+ elif isinstance(dst, Array):
+ return src.handle.get(queue=queue, ary=dst.handle, async=async)
+ elif isinstance(dst, np.ndarray):
+ return src.handle.get(queue=queue, ary=dst, async=async)
+ else:
+ msg = 'Unknown type to copy to ({}) for array of type {}.'
+ msg = msg.format(dst.__class__.__name__, src.__class__.__name__)
+ raise TypeError(msg)
+
+
+# HELPER FUNCTIONS #
+####################
+
+ def format_kernel_arg(self, arg, argname, const=False, allow_none=False):
+ from hysop.core.arrays.all import OpenClArray
+ const = 'const' if const else ''
+ is_scalar = False
+ if (arg is None):
+ if allow_none:
+ pass
+ else:
+ msg='Got None argument and allow_none is not set.'
+ raise ValueError(msg)
+ elif np.isscalar(arg):
+ dtype = get_dtype(arg)
+ ctype = clTools.dtype_to_ctype(dtype)
+ argument = '{} {} {}'.format(const, ctype, argname)
+ arg = np.asarray(arg, dtype=dtype)
+ is_scalar = True
+ elif isinstance(arg, OpenClArray):
+ dtype = arg.dtype
+ ctype = arg.ctype()
+ argument = '__global {} {}* {}'.format(ctype, const, argname)
+ elif isinstance(arg, Array):
+ msg='Argument \'{}\' is an Array but not an OpenClArray '
+ msg+='(size={}, shape={}, dtype={}).'
+ msg=msg.format(argname, arg.size, arg.shape, arg.dtype)
+ raise TypeError(msg)
+ elif isinstance(arg, np.ndarray):
+ if arg.size==1:
+ dtype = arg.dtype
+ ctype = clTools.dtype_to_ctype(arg.dtype)
+ argument = '{} {} {}'.format(const, ctype, argname)
+ is_scalar = True
+ else:
+ msg='Argument \'{}\' is a non-scalar np.ndarray (size={}, shape={}, dtype={}).'
+ msg=msg.format(argname, arg.size, arg.shape, arg.dtype)
+ raise TypeError(msg)
+ else:
+ msg='Unknown argument type {} (value={}).'.format(arg.__class__, arg)
+ raise TypeError(msg)
+ return arg, argument, is_scalar, dtype
+
+ def format_kernel_args(self, kargs, argprefix, argflags,
+ argcast=None, dtype=None, is_output=False,
+ arguments=None, const=False, filter_expr=None):
+
+ if argflags is not None:
+ assert 'has_fp16' in argflags
+ assert 'has_fp64' in argflags
+ if filter_expr is None:
+ filter_expr = dict()
+ else:
+ self._check_argtype('format_kernel_args', 'filter_expr', filter_expr, dict)
+
+ if not isinstance(argcast, tuple):
+ assert not isinstance(argcast, set) and not isinstance(argcast, list)
+ argcast = (argcast,)*len(kargs)
+ else:
+ if len(argcast)!=len(kargs):
+ msg = 'Allocation dtypes input length mismatch:'
+ msg+='\n\tkargs: {}\n\targcast={}\n'
+ msg=msg.format(kargs, argcast)
+ raise ValueError(msg)
+
+
+ # find common floating point type
+ fdtypes = []
+ for i,arg in enumerate(kargs):
+ if (argcast[i] == 'f') or (argcast[i] == 'c'):
+ cast_dtype = match_dtype(arg, argcast[i])
+ if is_complex(cast_dtype):
+ fdtypes.append(complex_to_float_dtype(cast_dtype))
+ else:
+ fdtypes.append(cast_dtype)
+ if fdtypes:
+ fcast_dtype = find_common_dtype(*tuple(fdtypes))
+ #TODO fix np.float16 and np.longdouble support
+ if fcast_dtype==np.float16:
+ fcast_dtype=np.float32
+ if fcast_dtype==np.longdouble:
+ fcast_dtype=np.float64
+ else:
+ fcast_dtype = np.float64
+ ccast_dtype = float_to_complex_dtype(fcast_dtype)
+ del fdtypes
+
+ if (arguments is None):
+ arguments = [None,] * len(kargs)
+ else:
+ self._check_argtype('format_kernel_args', 'arguments', arguments, list)
+ if len(kargs)!=len(arguments):
+ msg = 'Argument count mismatch:\n\tkargs: {}\n\targuments={}\n'
+ msg=msg.format(kargs, arguments)
+ raise ValueError(msg)
+
+ kargs = list(kargs)
+ for i,arg in enumerate(kargs):
+ argname = '{}{}'.format(argprefix,i)
+ arg, argument, is_scalar, dtype = self.format_kernel_arg(arg,
+ argname=argname, const=const)
+ kargs[i] = arg
+ if (arguments[i] is None):
+ arguments[i] = argument
+ if is_output:
+ affectation = '{}\[i\]\s*=\s*([\s\S]*?)\s*$'.format(argname)
+ affectation = re.compile(affectation)
+ is_cast = (argcast[i] is not None)
+ for (k,v) in filter_expr.iteritems():
+ expr = filter_expr[k]
+ if expr is None:
+ continue
+ argi = argname+'[i]'
+ if is_output: #cast to nearest output value dtype
+ if not is_complex(dtype):
+ ctype = clTools.dtype_to_ctype(dtype)
+ convert = '{}=convert_{}_rte(\\1)'.format(argi,ctype)
+ expr = expr.split(';')
+ for i,subexpr in enumerate(expr):
+ expr[i] = re.sub(affectation,convert,subexpr)
+ expr = ';'.join(expr)
+ elif is_cast: #input variable should be cast
+ if (is_complex(dtype)) or (argcast[i] == 'c'):
+ cast_dtype = ccast_dtype
+ elif (is_fp(dtype)) or (argcast[i] == 'f'):
+ cast_dtype = fcast_dtype
+ else:
+ cast_dtype = match_dtype(dtype, argcast[i])
+ if cast_dtype != dtype:
+ if is_complex(cast_dtype):
+ ftype = complex_to_float_dtype(cast_dtype)
+ ctype = clTools.dtype_to_ctype(ftype)
+ if is_complex(dtype):
+ argc = 'c{}_new({argi}.real,{argi}.imag)'.format(ctype,
+ argi=argi)
+ else:
+ if dtype != ftype:
+ argc = 'convert_{}({})'.format(ctype, argi)
+ else:
+ argc = argi
+ argc = 'c{}_fromreal({})'.format(ctype,argc)
+ expr = expr.replace(argi, argc)
+ else:
+ ctype = clTools.dtype_to_ctype(cast_dtype)
+ argc = 'convert_{}({})'.format(ctype, argi)
+ expr = expr.replace(argi, argc)
+ if is_scalar:
+ expr = expr.replace(argi,argname)
+ filter_expr[k] = expr
+ if argflags is not None:
+ if (dtype == np.float16):
+ argflags['has_fp16'] = True
+ elif (dtype == np.float64) or (dtype == np.complex128):
+ argflags['has_fp64'] = True
+ kargs, _ = self._prepare_args(*kargs)
+ return kargs, arguments
+
+ @classmethod
+ def complex_fn(cls, fname, handle):
+ """
+ Return corresponding complex function name from pyopencl-complex.h
+ matching handle complex datatype.
+ """
+ #see pyopencl/cl/pyopencl-complex.h
+ assert is_complex(handle)
+ if fname not in ['real', 'imag', 'abs', 'abs_squared',
+ 'new', 'fromreal',
+ 'neg', 'conj', 'add', 'addr',
+ 'radd', 'sub', 'mul', 'mulr', 'rdivide',
+ 'divide', 'divider', 'pow', 'powr', 'rpow',
+ 'sqrt', 'exp', 'log', 'sin', 'cos', 'tan',
+ 'sinh', 'cosh', 'tanh']:
+ msg='The function \'{}\' has not been implemented for complex numbers, '
+ msg+='see \'{}/cl/pyopencl-complex.h\' for more informations on '
+ msg+='available methods.'
+ msg = msg.format(fname, os.path.dirname(cl.__file__))
+ raise NotImplementedError(msg)
+
+ dtype = get_dtype(handle)
+ if dtype not in [np.complex64, np.complex128]:
+ msg='{} complex type has not been implemented yet.'
+ msg=msg.format(dtype)
+ raise NotImplementedError(msg)
+ ftype = complex_to_float_dtype(dtype)
+ ctype = clTools.dtype_to_ctype(ftype)
+ prefix='c{}_'.format(ctype)
+
+ return prefix+fname
+
+ @classmethod
+ def binary_complex_fn(cls, fname, x0, x1):
+ assert is_complex(x0) or is_complex(x1)
+ if not is_complex(x0):
+ fname='r'+fname
+ elif not is_complex(x1):
+ fname=fname+'r'
+
+ # rsub and subr do not exist in complex header
+ if (fname == 'subr'):
+ operands_prefix=('','-')
+ elif (fname == 'rsub'):
+ operands_prefix=('', cls.complex_fn('neg',x1))
+ else:
+ operands_prefix=('','')
+
+ ftype = find_common_dtype(x0,x1)
+ cmplx_fname = cls.complex_fn(fname, ftype)
+
+ expr='{}({}(x0[i]), {}(x1[i]))'
+ expr = expr.format(cmplx_fname, *operands_prefix)
+
+ # fix 0^0 and 0^x
+ if fname.find('pow')>=0:
+ default=expr
+ expr0='{}(1)'.format(cls.complex_fn('fromreal', ftype))
+ expr1='{}(0)'.format(cls.complex_fn('fromreal', ftype))
+ expr2='{}(NAN,NAN)'.format(cls.complex_fn('new', ftype))
+ if fname=='rpow':
+ cond0='(x0[i]==0)'
+ cond1='((x1[i].real==0) && (x1[i].imag==0))'
+ elif fname=='powr':
+ cond0='((x0[i].real==0) && (x0[i].imag==0))'
+ cond1='(x1[i]==0)'
+ elif fname=='pow':
+ cond0='((x0[i].real==0) && (x0[i].imag==0))'
+ cond1='(x1[i].imag==0)'
+ cond2='(x1[i].real==0)'
+ expr='({cond0} ? ({cond1} ? ({cond2} ? {expr0} : {expr1}) : {expr2}) : {default})'.format(
+ cond0=cond0, cond1=cond1, cond2=cond2,
+ expr0=expr0, expr1=expr1, expr2=expr2,
+ default=default)
+
+ expr = 'y0[i]={}'.format(expr)
+ return expr
+
+
+ def elementwise(self, ikargs, okargs, extra_kargs=None,
+ input_arguments=None, output_arguments=None, extra_arguments=None,
+ filter_expr=None,
+ dtype=None, infer_dtype=False,
+ queue=None, infer_queue=False,
+ async=False, convert_inputs=None,
+ allocator=None, alloc_shapes=None, alloc_dtypes=None,
+ Kernel=_ElementwiseKernel,
+ kernel_build_kwargs=None, kernel_call_kwargs=None):
+ """
+ Build and call kernel that takes:
+ n read-only scalars or OpenClArray as input arguments xi,
+ m OpenClArray as output arguments yi,
+ k read-only parameters pi
+ and performs an operation specified as a snippet of C99 on these arguments,
+ depending on passed Kernel class and additional arguments passed
+ in kernel_build_kwargs and kernel_call_kwargs.
+
+ This method performs:
+ y0[i],...,ym[i] = f( x0[i],...,xn[i] ; p0,...,pk )
+
+ 1) outputs allocation
+ 2) expression and arguments preprocessing
+ 3) kernel creation and compilation:
+ kernel = Kernel(**kernel_build_kwargs)
+ 4) kernel call:
+ return kernel(**kernel_call_kwargs)
+
+ The OpenCL kernel signature should match something like this:
+ kernel_name(*y0,...,*ym, const *x0,...,const *xn, const p0, ... const pk)
+
+ Kernel arguments:
+ For all input and output arguments, if they are OpenClArray, all shapes
+ and order should match or an error is raised.
+
+ If one of the output arg is set to None, it is allocated by the
+ given allocator, dtype and queue with the global shape and order.
+
+ Allocation shape can be overidden by using the argument 'alloc_shapes' which
+ should be a list of the same size as okargs (output arguments) or None.
+ If alloc_shapes is not None at allocated variable index, this shape is used
+ instead of the common operand shape.
+
+ If infer_dtype is set to True and dtype is None, every None output argument will
+ be allocated with the first OpenClArray input dtype contained in ikargs (input
+ arguments). If there is no input OpenClArray the lookup is extended to okargs
+ (output arguments). This can be overhidden using alloc_dtypes witch should be
+ a list of size of the output argument.
+
+ Default arguments names (generated in opencl kernel) are:
+ x0,x1,...,xn for inputs ( ikargs -> input_arguments)
+ y0,y1,...,ym for outputs ( okargs -> output_arguments)
+ p0,p1,...,pk for parameters (extra_kargs -> extra_arguments)
+ input arguments and extra arguments are read-only.
+
+ input_ arguments (x0,...,xn) can be scalars or OpenClArrays.
+ output arguments (y0,...,ym) can only be OpenClArrays.
+ extra arguments (p0,...,pk) can be anything compatible with pyopencl.
+
+ Expression filtering:
+ filter_expr is the dictionary of expr_name (str) -> expression (str)
+ Expressions in filter_expr are filtered according the following rule:
+ If input xi is a scalar, elementwise access 'x[i]' is replaced by 'x'
+ in given 'expr'.
+ This allows broadcasting of scalars in operators.
+
+ Filterered expressions are added to kernel_build_kwargs entries prior
+ to kernel construction. This implies that kernel_build_kwargs keys and
+ filter_expr keys should not clash.
+
+ Kernel build and kernel call:
+ kernel creation:
+ knl = Kernel(**kernel_build_kwargs)
+ kernel call:
+ knl(**kernel_call_kwargs)
+
+ User supplied 'kernel_build_kwargs' are completed with:
+ - all filtered expressions contained in dictionnary 'filter_expr'
+ - kernel_build_kwargs['context'] = context corresponding to queue
+ - kernel_build_kwargs['arguments'] = preprocessed arguments
+ (output+input+params)
+ - kernel_build_kwargs['dtype'] = dtype
+
+ User supplied 'kernel_call_kwargs' are completed with:
+ - kernel_call_kwargs['queue'] = queue
+ - kernel_call_kwargs['args'] = kargs (okargs+ikargs+extra_kargs), preprocessed.
+ - kernel_call_kwargs['iargs'] = ikargs, preprocessed
+ - kernel_call_kwargs['oargs'] = okargs, preprocessed, allocated if necessary
+ - kernel_call_kwargs['pargs'] = extra_kargs, preprocessed
+
+ Preprocessed arguments are passed through self._prepare_args(...)
+
+ If there is a key clash in those dictionaries, the method will fail.
+
+ Queue priorities:
+ queue (function argument),
+ if infer_queue is set to True:
+ x0.default_queue, ..., xn.default_queue
+ y0.default_queue, ..., ym.default_queue
+ /!\ default_cl_queue is not used in this function.
+
+ Call and events:
+ wait_for specify a list a event to wait prior applying the kernel.
+
+ If async is set to False, this is a blocking opencl call and this functions returns
+ output arguments okargs as a tuple unless there is only one output.
+
+ If async is set to True, this is a non blocking call and an event is returned in
+ addition to the outputs as last argument.
+
+ The returned event may not be used for profiling purposes, because it only
+ covers the last effective kernel call (reductions may use two kernels
+ for example).
+ """
+ from hysop.core.arrays.all import OpenClArray
+
+ extra_kargs = extra_kargs or tuple()
+ kernel_build_kwargs = kernel_build_kwargs or dict()
+ kernel_call_kwargs = kernel_call_kwargs or dict()
+
+ self._check_argtype('elementwise', 'ikargs', ikargs, tuple)
+ self._check_argtype('elementwise', 'okargs', okargs, tuple)
+ self._check_argtype('elementwise', 'extra_kargs', extra_kargs, tuple)
+ self._check_argtype('elementwise', 'kernel_build_kwargs', kernel_build_kwargs, dict)
+ self._check_argtype('elementwise', 'kernel_call_kwargs', kernel_call_kwargs, dict)
+
+ if (alloc_dtypes is None):
+ alloc_dtypes = (None,)*len(okargs)
+ elif isinstance(alloc_dtypes, str):
+ alloc_dtypes = (alloc_dtypes,)*len(okargs)
+ else:
+ self._check_argtype('elementwise', 'alloc_dtype', alloc_dtypes, tuple)
+ if len(alloc_dtypes)!=len(okargs):
+ msg = 'Allocation dtypes input length mismatch:'
+ msg+='\n\tokargs: {}\n\talloc_dtypes={}\n'
+ msg=msg.format(okargs, alloc_dtypes)
+ raise ValueError(msg)
+
+ alloc_shapes = alloc_shapes or (None,)*len(okargs)
+ self._check_argtype('elementwise', 'alloc_shapes', alloc_shapes, tuple)
+
+ order = None
+ shape = None
+ for arg in ikargs+okargs:
+ if isinstance(arg, OpenClArray):
+ if infer_queue:
+ queue = first_not_None(queue, arg.default_queue)
+ if infer_dtype:
+ dtype = first_not_None(dtype, arg.dtype)
+ if (order is None):
+ shape = arg.shape
+ order = arg.order
+ elif arg.shape != shape:
+ msg='{} with shape {} does not match reference shape {}.'
+ msg=msg.format(arg,args.shape,shape)
+ elif arg.order != order:
+ msg='{} with order {} does not match reference order {}.'
+ msg=msg.format(arg,args.order,order)
+ if (shape is None):
+ msg='No OpenClArray argument was found in ikargs and okargs.'
+ raise ValueError(msg)
+
+ alloc_dtypes = tuple([match_dtype(dtype,alloc_dtypes[i]) \
+ for i in xrange(len(okargs))])
+
+ okargs = list(okargs)
+ for i, (arg, _shape, _dtype) in enumerate(zip(okargs,alloc_shapes,alloc_dtypes)):
+ if (arg is None):
+ alloc_shape = first_not_None(_shape, shape)
+ alloc_dtype = first_not_None(_dtype, dtype)
+ if (alloc_dtype is None):
+ msg='Output argument y{} has not been allocated and dtype was'
+ msg+=' not set (dtype={}, infer_dtype={}, alloc_dtypes={}).'
+ msg=msg.format(i,dtype,infer_dtype,alloc_dtypes)
+ raise ValueError(msg)
+ if (order is None):
+ msg='Output argument y{} has not been allocated and order was'
+ msg+=' not set.'
+ msg=msg.format(i)
+ raise ValueError(msg)
+ okargs[i] = self.empty(shape=alloc_shape, dtype=alloc_dtype,
+ queue=queue, order=order)
+ okargs = tuple(okargs)
+
+ argflags = {
+ 'has_fp16': (dtype == np.float16),
+ 'has_fp64': (dtype == np.float64)
+ }
+
+ ikargs, input_arguments = \
+ self.format_kernel_args(kargs=ikargs, argprefix='x', is_output=False,
+ arguments=input_arguments, filter_expr=filter_expr,
+ const=True, argflags=argflags,
+ argcast=convert_inputs, dtype=dtype)
+
+ okargs, output_arguments = \
+ self.format_kernel_args(kargs=okargs, argprefix='y', is_output=True,
+ arguments=output_arguments, filter_expr=filter_expr,
+ const=False, argflags=argflags)
+
+ extra_kargs, extra_arguments = \
+ self.format_kernel_args(kargs=extra_kargs, argprefix='p', is_output=False,
+ arguments=extra_arguments,
+ const=True, argflags=argflags)
+
+ kargs = okargs + ikargs + extra_kargs
+ arguments = output_arguments + input_arguments + extra_arguments
+ arguments = ', '.join(arguments)
+
+ # kernel build keyword arguments
+ assert not set(kernel_build_kwargs.keys()).intersection(filter_expr.keys())
+ kernel_build_kwargs.update(filter_expr)
+
+ blacklist = ['context', 'arguments','dtype','argflags']
+ assert not set(kernel_build_kwargs.keys()).intersection(blacklist)
+
+ kernel_build_kwargs['context'] = queue.context
+ kernel_build_kwargs['arguments'] = arguments
+ kernel_build_kwargs['dtype'] = dtype
+ kernel_build_kwargs['argflags'] = argflags
+
+ # kernel call keyword arguments
+ blacklist = ['queue', 'args','iargs','oargs','pargs']
+ assert not set(kernel_call_kwargs.keys()).intersection(blacklist)
+ kernel_call_kwargs['queue'] = queue
+ kernel_call_kwargs['args'] = kargs
+ kernel_call_kwargs['iargs'] = ikargs
+ kernel_call_kwargs['oargs'] = okargs
+ kernel_call_kwargs['pargs'] = extra_kargs
+
+ try:
+ knl = Kernel(**kernel_build_kwargs)
+ ret = knl(**kernel_call_kwargs)
+ except:
+ def val2str(val):
+ if val.__class__ in [list, tuple, set]:
+ out = '{}[{}]'.format(val.__class__.__name__,
+ ', '.join([val2str(v) for v in val]))
+ elif isinstance(val,Array):
+ out= '{}(shape={}, dtype={}, order={})'
+ out=out.format(val.__class__.__name__, val.shape,
+ val.dtype, val.order)
+ elif val.__class__ in self._registered_backends().keys():
+ out= '{}(shape={}, dtype={})'
+ out=out.format(val.__class__.__name__, val.shape,
+ val.dtype)
+ else:
+ out=val
+ return out
+ def dic2str(dic):
+ entries=[]
+ for k,v in dic.iteritems():
+ e = '{}: {}'.format(k, val2str(v))
+ entries.append(e)
+ return '\n\t'+'\n\t'.join(entries)
+ msg = 'Something went wrong during kernel build or kernel call:'
+ msg+= '\n build kargs:{}'.format(dic2str(kernel_build_kwargs))
+ msg+= '\n call kargs:{}'.format(dic2str(kernel_call_kwargs))
+ msg+= '\n'
+ print msg
+ raise
+
+ if isinstance(ret, tuple):
+ evt = ret[-1]
+ else:
+ evt = ret
+
+ okargs = self._return(okargs)
+
+ if not async:
+ evt.wait()
+ if len(okargs)==1:
+ return okargs[0]
+ else:
+ return okargs
+ else:
+ if len(okargs)==1:
+ return okargs[0], evt
+ else:
+ return okargs, evt
+
+ def nary_op(self, ikargs, okargs, operation,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None, output_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ alloc_shapes=None, alloc_dtypes=None,
+ async=False, wait_for=None,
+ convert_inputs=None,
+ name='nary_op', options=[], preamble=''):
+ """
+ A kernel that takes n vector as input and outputs m vectors.
+ The operation is specified as a snippet of C99 on these arguments.
+ Default arguments names are x0,x1,...,xn and y0,y1,...,ym.
+
+ Queue priorities: queue (function argument),
+ if infer_queue:
+ x0.default_queue, ..., xn.default_queue,
+ y0.default_queue, ..., yn.default_queue,
+
+ For all input and output arguments, if they are OpenClArray, all shapes should match.
+ If out is None, it is allocated to input shape with specified dtype.
+
+ y0[i] = f( x0[i],...,xn[i] ; p0,...,pk )
+ <=>
+ y0[i] = ElementwiseKernel(const x0[i],...,const xn[i], const p0,..., const pk)
+
+ If async is set to True, evt is returned as last argument.
+ If out and dtype is None it is set to xi.dtype where xi is the first OpenClArray
+
+ options are opencl kernel build options.
+ preamble is appended unmodified in source code before kernel declaration.
+ """
+ Kernel = _ElementwiseKernel
+ kernel_build_kwargs = {
+ 'options': options,
+ 'preamble': preamble,
+ 'name': name
+ }
+ kernel_call_kwargs = {
+ 'wait_for': wait_for
+ }
+ filter_expr = {
+ 'operation': operation
+ }
+ return self.elementwise(ikargs=ikargs, okargs=okargs,
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ filter_expr=filter_expr,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ async=async,
+ allocator=allocator, convert_inputs=convert_inputs,
+ alloc_shapes=alloc_shapes, alloc_dtypes=alloc_dtypes,
+ Kernel=Kernel,
+ kernel_build_kwargs= kernel_build_kwargs,
+ kernel_call_kwargs = kernel_call_kwargs)
+
+ def unary_op(self, x0, expr, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None, output_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ convert_inputs=None,
+ allocator=None,
+ alloc_shapes=None, alloc_dtypes=None,
+ async=False, wait_for=None,
+ name='unary_op', options=[], preamble=''):
+
+ return self.nary_op(ikargs=(x0,), okargs=(out,), operation=expr,
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ allocator=allocator, convert_inputs=convert_inputs,
+ alloc_shapes=alloc_shapes, alloc_dtypes=alloc_dtypes,
+ async=async, wait_for=wait_for,
+ name=name, options=options, preamble=preamble)
+
+ def binary_op(self, x0, x1, expr, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None, output_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ convert_inputs=None,
+ allocator=None,
+ alloc_shapes=None, alloc_dtypes=None,
+ async=False, wait_for=None,
+ name='binary_op', options=[], preamble=''):
+
+ return self.nary_op(ikargs=(x0,x1), okargs=(out,), operation=expr,
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ allocator=allocator, convert_inputs=convert_inputs,
+ alloc_shapes=alloc_shapes, alloc_dtypes=alloc_dtypes,
+ async=async, wait_for=wait_for,
+ name=name, options=options, preamble=preamble)
+
+
+ def reduce(self, kargs, neutral, reduce_expr, map_expr='x0[i]',
+ axis=None, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None, output_arguments=None,
+ convert_inputs=None, alloc_dtypes=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ async=False, wait_for=None,
+ name='reduction', options=[], preamble=''):
+ """
+ Reduce arrays elements over the whole array.
+ kargs = kernel array or scalar arguments (tuple)
+ y0 = ReductionKernel( MAP_EXPR(const x0[i],...,const xn[i], const p0,..., const pk) )
+ """
+ from hysop.core.arrays.all import OpenClArray
+
+ if dtype is None:
+ if any([is_signed(k) for k in kargs]):
+ dtype=np.int64
+ elif any([is_unsigned(k) for k in kargs]):
+ dtype=np.uint64
+ else:
+ pass
+
+ map_expr = map_expr.strip()
+ reduce_expr = reduce_expr.strip()
+
+ input_dtype = find_common_dtype(*kargs)
+ if is_complex(input_dtype):
+ map_ops = {
+ 'a+b': 'add',
+ 'a-b': 'sub',
+ 'a*b': 'mul',
+ }
+ if reduce_expr in map_ops:
+ neutral= '{}({})'.format(self.complex_fn('fromreal',input_dtype), neutral)
+ reduce_expr = '{}(a,b)'.format( self.complex_fn(map_ops[reduce_expr], input_dtype))
+
+ self._unsupported_argument('reduce','axis',axis)
+ if (out is not None):
+ self._check_argtype('reduce', 'out', out, OpenClArray)
+ dtype = out.dtype
+ assert out.size==1
+ out = out.handle
+
+ Kernel=_ReductionKernel
+ kernel_build_kwargs = {
+ 'name': name,
+ 'options': options,
+ 'preamble': preamble,
+ 'reduce_expr': reduce_expr,
+ 'neutral': neutral,
+ }
+ kernel_call_kwargs = {
+ 'return_event': True,
+ 'wait_for': wait_for,
+ }
+ filter_expr = {
+ 'map_expr': map_expr
+ }
+ return self.elementwise(ikargs=kargs, okargs=(out,),
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ filter_expr=filter_expr,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ async=async,
+ convert_inputs=convert_inputs, alloc_dtypes=alloc_dtypes,
+ allocator=allocator, alloc_shapes=((1,),),
+ Kernel=Kernel,
+ kernel_build_kwargs= kernel_build_kwargs,
+ kernel_call_kwargs = kernel_call_kwargs)
+
+
+ def nanreduce(self, kargs, neutral, reduce_expr, map_expr='x0[i]',
+ axis=None, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None, output_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ convert_inputs=None,
+ async=False, wait_for=None,
+ name='nan_reduction', options=[], preamble=''):
+ """
+ Reduce arrays elements over the whole array, replacing mapped expr NaNs by the neutral.
+ dtype should be a floating point type.
+ kargs = kernel args as a scalar or tuple
+ """
+ if any([is_complex(k) for k in kargs]):
+ ctype = find_common_dtype(*kargs)
+ nan_map_expr = '((isnan({expr}.real) || isnan({expr}.imag)) ? {neutral} : {expr})'
+ nan_map_expr = nan_map_expr.format(expr=map_expr,
+ neutral='{}({})'.format(self.complex_fn('fromreal',ctype), neutral))
+ elif any([is_fp(k) for k in kargs]):
+ nan_map_expr = '(isnan({expr}) ? {neutral} : {expr})'
+ nan_map_expr = nan_map_expr.format(expr=map_expr, neutral=neutral)
+ else:
+ nan_map_expr = map_expr
+
+ return self.reduce(kargs=kargs, neutral=neutral, convert_inputs=convert_inputs,
+ reduce_expr=reduce_expr, map_expr=nan_map_expr,
+ axis=axis, out=out, extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ dtype=dtype, infer_dtype=infer_dtype, queue=queue, infer_queue=infer_queue,
+ allocator=allocator, async=async, wait_for=wait_for,
+ name=name, options=options, preamble=preamble)
+
+ def generic_scan(self, kargs, neutral, scan_expr, output_statement,
+ input_expr='x0[i]', size=None,
+ is_segment_start_expr=None, input_fetch_exprs=None,
+ axis=None, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None, output_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ convert_inputs=None,
+ async=False, wait_for=None,
+ name='generic_scan', options=[], preamble=''):
+ """
+ Scan arrays elements over the whole array.
+ kargs = kernel array or scalar arguments (tuple)
+ """
+ from hysop.core.arrays.all import OpenClArray
+
+ self._unsupported_argument('generic_scan','axis',axis)
+
+ if dtype is None:
+ if any([is_signed(k) for k in kargs]):
+ dtype=np.int64
+ elif any([is_unsigned(k) for k in kargs]):
+ dtype=np.uint64
+ # numpy does not force np.float16 / np.float32 to np.float64
+
+
+ scan_expr = scan_expr.strip()
+ input_dtype = find_common_dtype(*kargs)
+ if is_complex(input_dtype):
+ if input_dtype == np.complex128:
+ define='#define PYOPENCL_DEFINE_CDOUBLE'
+ else:
+ define=''
+ include = '#include <pyopencl-complex.h>\n'+preamble
+ preamble='{}\n{}\n{}'.format(define,include,preamble)
+
+ map_ops = {
+ 'a+b': 'add',
+ 'a-b': 'sub',
+ 'a*b': 'mul',
+ }
+ if scan_expr in map_ops:
+ neutral= '{}({})'.format(self.complex_fn('fromreal',input_dtype), neutral)
+ scan_expr = '{}(a,b)'.format( self.complex_fn(map_ops[scan_expr], input_dtype))
+
+ Kernel=_GenericScanKernel
+ kernel_build_kwargs = {
+ 'name': name,
+ 'options': options,
+ 'preamble': preamble,
+ 'scan_expr': scan_expr,
+ 'neutral': neutral,
+ 'input_fetch_exprs': input_fetch_exprs
+ }
+
+ kernel_call_kwargs = {
+ 'wait_for': wait_for,
+ 'size': size
+ }
+ filter_expr = {
+ 'input_expr': input_expr,
+ 'output_statement': output_statement,
+ 'is_segment_start_expr': is_segment_start_expr,
+ }
+ return self.elementwise(ikargs=kargs, okargs=(out,),
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ filter_expr=filter_expr,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ async=async,
+ allocator=allocator, alloc_shapes=None,
+ convert_inputs=convert_inputs,
+ Kernel=Kernel,
+ kernel_build_kwargs= kernel_build_kwargs,
+ kernel_call_kwargs = kernel_call_kwargs)
+
+ def inclusive_scan(self, kargs, neutral, scan_expr,
+ input_expr='x0[i]', size=None,
+ axis=None, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ convert_inputs=None,
+ async=False, wait_for=None,
+ name='inclusive_scan', options=[], preamble=''):
+
+ output_arguments = None
+ output_statement = 'y0[i] = item'
+
+ return self.generic_scan(kargs=kargs, neutral=neutral, scan_expr=scan_expr,
+ input_expr=input_expr, output_statement=output_statement,
+ size=size, axis=axis, out=out,
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ allocator=allocator, convert_inputs=convert_inputs,
+ async=async, wait_for=wait_for,
+ name=name, options=options, preamble=preamble)
+
+ def exclusive_scan(self, kargs, neutral, scan_expr,
+ input_expr='x0[i]', size=None,
+ axis=None, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ async=False, wait_for=None,
+ name='exclusive_scan', options=[], preamble=''):
+
+ output_arguments = None
+ output_statement = 'y0[i] = prev_item'
+
+ return self.generic_scan(ikargs=kargs, neutral=neutral, scan_expr=scan_expr,
+ input_expr=input_expr, output_statement=output_statement,
+ size=size, axis=axis, out=out,
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments, output_arguments=output_arguments,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ allocator=allocator,
+ async=async, wait_for=wait_for,
+ name=name, options=options, preamble=preamble)
+
+ def inclusive_nanscan(self, kargs, neutral, scan_expr,
+ input_expr='x0[i]', size=None,
+ axis=None, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ async=False, wait_for=None,
+ name='inclusive_nanscan', options=[], preamble=''):
+
+ if any([is_complex(k) for k in kargs]):
+ ctype = find_common_dtype(*kargs)
+ nan_input_expr = '((isnan({expr}.real) || isnan({expr}.imag)) ? {neutral} : {expr})'
+ nan_input_expr = nan_input_expr.format(expr=input_expr,
+ neutral='{}({})'.format(self.complex_fn('fromreal',ctype), neutral))
+ elif any([is_fp(k) for k in kargs]):
+ nan_input_expr = '(isnan({expr}) ? {neutral} : {expr})'
+ nan_input_expr = nan_input_expr.format(expr=input_expr, neutral=neutral)
+ else:
+ nan_input_expr = input_expr
+
+ return self.inclusive_scan(kargs=kargs, neutral=neutral, scan_expr=scan_expr,
+ input_expr=nan_input_expr,
+ size=size, axis=axis, out=out,
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ allocator=allocator,
+ async=async, wait_for=wait_for,
+ name=name, options=options, preamble=preamble)
+
+ def exclusive_nanscan(self, kargs, neutral, scan_expr,
+ input_expr='x0[i]', size=None,
+ axis=None, out=None,
+ extra_kargs=None, extra_arguments=None,
+ input_arguments=None,
+ dtype=None, infer_dtype=True,
+ queue=None, infer_queue=True,
+ allocator=None,
+ async=False, wait_for=None,
+ name='exclusive_nanscan', options=[], preamble=''):
+
+ if any([is_complex(k) for k in kargs]):
+ ctype = find_common_dtype(*kargs)
+ nan_input_expr = '((isnan({expr}.real) || isnan({expr}.imag)) ? {neutral} : {expr})'
+ nan_input_expr = nan_input_expr.format(expr=input_expr,
+ neutral='{}({})'.format(self.complex_fn('fromreal',ctype), neutral))
+ elif any([is_fp(k) for k in kargs]):
+ nan_input_expr = '(isnan({expr}) ? {neutral} : {expr})'
+ nan_input_expr = nan_input_expr.format(expr=input_expr, neutral=neutral)
+ else:
+ nan_input_expr = input_expr
+
+ return self.exclusive_scan(kargs=kargs, neutral=neutral, scan_expr=scan_expr,
+ input_expr=nan_input_expr,
+ size=size, axis=axis, out=out,
+ extra_kargs=extra_kargs, extra_arguments=extra_arguments,
+ input_arguments=input_arguments,
+ dtype=dtype, infer_dtype=infer_dtype,
+ queue=queue, infer_queue=infer_queue,
+ allocator=allocator,
+ async=async, wait_for=wait_for,
+ name=name, options=options, preamble=preamble)
+
+ def check_queue(self, queue):
+ if (queue is None):
+ return
+ if queue.context != self.context:
+ msg='Given queue does not match backend context.'
+ raise RuntimeError(msg)
+
+###########################
+# ARRAY CREATION ROUTINES #
+
+ def array(self, shape, dtype=HYSOP_REAL, order=default_order,
+ queue=None, min_alignment=None,
+ buf=None, offset=0,
+ strides=None, events=None):
+ """
+ Create an OpenClArray, see pyopencl.array.Array constructor.
+ If a queue is specified, it is set as default queue,
+ else it will be backend.default_queue.
+ """
+ #FIXME OpenCL half float support
+ if dtype == np.float16:
+ dtype=np.float32
+ msg='OpenClArrayBackend promoted float16 to float32 in array allocation of shape {}.'
+ msg=msg.format(shape)
+ warnings.warn(RuntimeWarning(msg))
+ #FIXME OpenCL long double support
+ if dtype == np.longdouble:
+ msg='OpenClArrayBackend demoted {} to float64 in array allocation of shape {}.'
+ msg=msg.format(dtype, shape)
+ dtype = np.float64
+ warnings.warn(RuntimeWarning(msg))
+ #FIXME OpenCL bool support
+ if dtype == np.bool:
+ dtype=HYSOP_BOOL
+ msg='OpenClArrayBackend promoted np.bool to {} in array allocation of shape {}.'
+ msg=msg.format(dtype, shape)
+ warnings.warn(RuntimeWarning(msg))
+
+ shape = to_tuple(shape)
+
+ queue = queue or self.default_queue
+ self.check_queue(queue)
+
+ if buf is None:
+ assert offset==0
+ assert strides is None
+ allocator = self.allocator
+ if min_alignment < self.allocator.device.mem_base_addr_align:
+ alignment=1
+ dtype = np.dtype(dtype)
+ size = np.prod(shape)*dtype.itemsize
+ else:
+ (size,nbytes,alignment) = self.get_alignment_and_size(shape=shape,
+ dtype=dtype, min_alignment=min_alignment)
+ buf = allocator.allocate_aligned(size, alignment=alignment)
+
+
+ handle = self._call(clArray.Array, cq=queue, shape=shape, dtype=dtype, order=order,
+ allocator=None, data=buf, offset=offset,
+ strides=strides, events=events)
+ return self.wrap(handle)
+
+ def asarray(self, a, queue=None, async=False,
+ dtype=None, order=default_order, array_queue=QueuePolicy.SAME_AS_TRANSFER):
+ """
+ Convert the input to an OpenClArray.
+ Queue is set as default queue.
+ """
+ from hysop.backend.device.opencl.opencl_array import Array, OpenClArray
+ from hysop.backend.host.host_array import HostArray
+ acls = a.__class__.__name__
+ self.check_queue(queue)
+
+ queue = queue or self.default_queue
+
+ if (dtype is not None):
+ pass
+ if isinstance(a, Array):
+ dtype = a.dtype
+ elif hasattr(a, 'dtype'):
+ dtype = a.dtype
+ else:
+ msg='Could not extract dtype from type {} and argument not set (dtype).'
+ msg=msg.format(acls)
+ raise ValueError(msg)
+
+ if isinstance(a, OpenClArray):
+ array = a
+ elif isinstance(a, clArray.Array):
+ array = self.wrap(handle=handle)
+ elif a.__class__ in [list, tuple, set, np.ndarray, HostArray]:
+ if a.__class__ in [list, tuple, set]:
+ a = np.asarray(a)
+ elif isinstance(a, HostArray):
+ a = a.handle
+
+ array = self._call(clArray.to_device, queue=queue, ary=a,
+ async=async, array_queue=array_queue)
+ else:
+ msg='Unknown type to convert from {}.'
+ msg=msg.format(acls)
+ raise TypeError(msg)
+
+ return array.view(dtype)
+
+ def copy(self, a, order=MemoryOrdering.SAME_ORDER, queue=None):
+ """
+ Return an array copy of the given object.
+ """
+ self._unsupported_argument('copy','order',order,MemoryOrdering.SAME_ORDER)
+ self.check_queue(queue)
+ return self._call(a.handle.copy, queue=queue)
+
+# Filling
+ def fill(self, a, value, queue=None, wait_for=None):
+ """
+ Fill the array with given value
+ """
+ self.check_queue(queue)
+ a.handle.fill(value=value, queue=queue, wait_for=wait_for)
+
+# Ones and zeros
+ def empty(self, shape, dtype=HYSOP_REAL, order=default_order, queue=None):
+ """
+ Return a new array of given shape and type, without initializing entries.
+ If queue is specified, the queue becomes the default queue, else
+ backend.default_queue is used instead.
+ """
+ return self.array(shape=shape, dtype=dtype, order=order, queue=queue)
+
+ def full(self, shape, fill_value, dtype=HYSOP_REAL, order=default_order, queue=None):
+ """
+ Return a new array of given shape and type, filled with fill_value.
+ Queue is set as default queue.
+ """
+ a = self.empty(shape=shape, dtype=dtype, order=order, queue=queue)
+ self.fill(a=a, value=fill_value, queue=queue)
+ return a
+ def zeros(self, shape, dtype=HYSOP_REAL, order=default_order, queue=None):
+ """
+ Return a new array of given shape and type, filled with zeros.
+ Queue is set as default queue.
+ """
+ return self.full(shape=shape, dtype=dtype, order=order, queue=queue,
+ fill_value=0)
+ def ones(self, shape, dtype=HYSOP_REAL, order=default_order, queue=None):
+ """
+ Return a new array of given shape and type, filled with ones.
+ Queue is set as default queue.
+ """
+ return self.full(shape=shape, dtype=dtype, order=order, queue=queue,
+ fill_value=1)
+
+
+ def empty_like(self, a, dtype=None, order=None, subok=True, queue=None):
+ """
+ Return a new array with the same shape and type as a given array.
+ Queue is set as default queue.
+ """
+ return self.array(shape=a.shape, queue=queue,
+ dtype = first_not_None(dtype, a.dtype),
+ order = first_not_None(order, a.order))
+ def full_like(self, a, fill_value, dtype=None, order=None, subok=True, queue=None):
+ """
+ Return a new array with the same shape and type as a given array.
+ Queue is set as default queue.
+ """
+ a = self.empty_like(a=a, dtype=dtype, order=order, subok=subok,
+ queue=queue)
+ self.fill(a, value=fill_value, queue=queue)
+ return a
+ def zeros_like(self, a, dtype=None, order=None, subok=True, queue=None):
+ """
+ Return an array of zeros with the same shape and type as a given array.
+ Queue is set as default queue.
+ """
+ return self.full_like(a=a,fill_value=0,dtype=dtype,order=order,subok=subok,
+ queue=queue)
+ def ones_like(self, a, dtype=None, order=None, subok=True, queue=None):
+ """
+ Return an array of ones with the same shape and type as a given array.
+ Queue is set as default queue.
+ """
+ return self.full_like(a=a,fill_value=1,dtype=dtype,order=order,subok=subok,
+ queue=queue)
+
+ def arange(self, *args, **kargs):
+ """
+ Return evenly spaced values within a given interval.
+ """
+ assert 'allocator' not in kargs
+ if 'queue' not in kargs:
+ queue = self.default_queue
+ else:
+ queue = kargs.pop('queue')
+ if 'dtype' not in kargs:
+ kargs['dtype'] = HYSOP_INTEGER
+ return self.wrap(clArray.arange(queue, *args, allocator=self.allocator, **kargs))
+
+
+# BINARY OPERATIONS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.bitwise.html
+#####################
+
+# Elementwise bit operations
+ def bitwise_and(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Compute the bit-wise AND of two arrays element-wise.
+ """
+ expr = 'y0[i] = (x0[i] & x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def bitwise_or(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Compute the bit-wise OR of two arrays element-wise.
+ """
+ expr = 'y0[i] = (x0[i] | x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def bitwise_xor(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Compute the bit-wise XOR of two arrays element-wise.
+ """
+ expr = 'y0[i] = (x0[i] ^ x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+
+ def invert(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Compute bit-wise inversion, or bit-wise NOT, element-wise.
+ """
+ expr = 'y0[i] = (~x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def left_shift(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Shift the bits of an integer to the left.
+ """
+ expr = 'y0[i] = (x0[i] << x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def right_shift(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Shift the bits of an integer to the right.
+ """
+ expr = 'y0[i] = (x0[i] >> x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+
+
+# LOGIC FUNCTIONS #
+###################
+## See https://docs.scipy.org/doc/numpy/reference/routines.logic.html
+
+#Truth value testing
+ def any(self, a, axis=None, out=None, queue=None, dtype=HYSOP_BOOL):
+ """
+ Test whether any array elements along a given axis evaluate to True.
+ """
+ return self.reduce(kargs=(a,), axis=axis, dtype=dtype, out=out, queue=queue,
+ neutral='false', reduce_expr='a||b')
+ def all(self, a, axis=None, out=None, queue=None, dtype=HYSOP_BOOL):
+ """
+ Test whether all array elements along a given axis evaluate to True.
+ """
+ return self.reduce(kargs=(a,), axis=axis, dtype=dtype, out=out, queue=queue,
+ neutral='true', reduce_expr='a&&b')
+
+#Array contents
+ def isfinite(self, x, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Test element-wise for finiteness (not infinity or not Not a Number).
+ """
+ if is_fp(x):
+ expr = 'y0[i] = (!isinf(x0[i])) && (!isnan(x0[i]))'
+ elif is_complex(x):
+ expr = 'y0[i] = ((!isinf(x0[i].real)) && (!isnan(x0[i].real))'
+ expr+= '&& (!isinf(x0[i].imag)) && (!isnan(x0[i].imag)))'
+ else:
+ expr = 'y0[i] = 1'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def isinf(self, x, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Test element-wise for positive or negative infinity.
+ """
+ if is_fp(x):
+ expr = 'y0[i] = isinf(x0[i])'
+ elif is_complex(x):
+ expr = 'y0[i] = (isinf(x0[i].real) || isinf(x0[i].imag))'
+ else:
+ expr = 'y0[i] = 0'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def isnan(self, x, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Test element-wise for NaN and return result as a boolean array.
+ """
+ if is_fp(x):
+ expr = 'y0[i] = isnan(x0[i])'
+ elif is_complex(x):
+ expr = 'y0[i] = (isnan(x0[i].real) || isnan(x0[i].imag))'
+ else:
+ expr = 'y0[i] = 0'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def isneginf(self, x, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Test element-wise for negative infinity, return result as bool array.
+ """
+ assert not is_complex(x)
+ if is_fp(x):
+ expr = 'y0[i] = signbit(x0[i]) && isinf(x0[i])'
+ elif is_complex(x):
+ expr = 'y0[i] = ((signbit(x0[i].real) && isinf(x0[i].real))'
+ expr += '|| (signbit(x0[i].imag) && isinf(x0[i].imag)))'
+ else:
+ expr = 'y0[i] = 0'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def isposinf(self, x, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Test element-wise for positive infinity, return result as bool array.
+ """
+ assert not is_complex(x)
+ if is_fp(x):
+ expr = 'y0[i] = (!signbit(x0[i])) && isinf(x0[i])'
+ elif is_complex(x):
+ expr = 'y0[i] = ((!signbit(x0[i].real) && isinf(x0[i].real))'
+ expr += '|| (!signbit(x0[i].imag) && isinf(x0[i].imag)))'
+ else:
+ expr = 'y0[i] = 0'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+
+#Logical operations
+ def logical_and(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Compute the truth value of x1 AND x2 element-wise.
+ """
+ expr = 'y0[i] = (x0[i] && x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def logical_or(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Compute the truth value of x1 OR x2 element-wise.
+ """
+ expr = 'y0[i] = (x0[i] || x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def logical_not(self, x, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Compute the truth value of NOT x element-wise.
+ """
+ expr = 'y0[i] = (!x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def logical_xor(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Compute the truth value of x1 XOR x2, element-wise.
+ """
+ expr = 'y0[i] = (x0[i] ? (!x1[i]) : x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+
+#Comparisson
+ def allequal(self, a, b, equal_nan=False,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Returns True if two arrays are element-wise equal within a tolerance.
+ """
+ x0,x1 = a,b
+ map_expr ='( x0[i]==x1[i] )'
+ if is_fp(x0) and is_fp(x1) and equal_nan:
+ map_expr += ' || ( isnan(x0[i]) && isnan(x1[i]) )'
+ return self.reduce(kargs=(x0,x1), neutral='true', reduce_expr='a&&b',
+ queue=queue, dtype=dtype,
+ map_expr=map_expr,
+ arguments=arguments)
+ def allclose(self, a, b, rtol=1e-05, atol=1e-08, equal_nan=False,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Returns True if two arrays are element-wise equal within a tolerance.
+ """
+ if is_complex(a) or is_complex(b):
+ map_expr = '({fabs}({sub}(x0[i],x1[i])) <= (atol + rtol*{fabs}(x1[i])))'
+ common_dtype = find_common_dtype(a,b)
+ map_expr = map_expr.format(fabs=self.complex_fn('abs',common_dtype),
+ sub=self.complex_fn('sub',common_dtype))
+ convert_inputs='c'
+ else:
+ map_expr = '(fabs(x0[i]-x1[i]) <= (atol + rtol*fabs(x1[i])))'
+ convert_inputs='f'
+ return self.reduce(kargs=(a,b), neutral='true', reduce_expr='a&&b',
+ queue=queue, dtype=dtype,
+ map_expr=map_expr,
+ extra_kargs=(np.float64(rtol), np.float64(atol)),
+ extra_arguments=['const double rtol', 'const double atol'],
+ convert_inputs=convert_inputs, alloc_dtypes='f')
+ def isclose(self, a, b, rtol=1e-05, atol=1e-08, equal_nan=False,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Returns a boolean array where two arrays are element-wise equal within a tolerance.
+ """
+ if is_complex(a) or is_complex(b):
+ map_expr = '({fabs}({sub}(x0[i],x1[i])) <= (atol + rtol*{fabs}(x1[i])))'
+ common_dtype = find_common_dtype(a,b)
+ map_expr = map_expr.format(fabs=self.complex_fn('abs',common_dtype),
+ sub=self.complex_fn('sub',common_dtype))
+ convert_inputs='c'
+ else:
+ map_expr = '(fabs(x0[i]-x1[i]) <= (atol + rtol*fabs(x1[i])))'
+ convert_inputs='f'
+ return self.binary_op(x0=a, x1=b, expr=expr, out=out,
+ extra_kargs=(np.float64(rtol), np.float64(atol)),
+ extra_arguments=['double rtol', 'double atol'],
+ queue=queue, dtype=dtype,
+ convert_inputs=convert_inputs)
+ def array_equal(self, a1, a2,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ True if two arrays have the same shape and elements, False otherwise.
+ """
+ return (a1.shape==a2.shape) and \
+ self.all_equal(x1=a1,x2=a2,queue=queue,dtype=HYSOP_BOOL)
+
+ @staticmethod
+ def _make_comparisson_expr(x1,x2,comp):
+ iseq = (comp == '==')
+ expr = 'y0[i] = (({}) || (({}) && ({})))'
+ if is_complex(x1) and is_complex(x2):
+ expr = expr.format(
+ 'false' if iseq else 'x0[i].real {comp} x1[i].real',
+ 'x0[i].real == x1[i].real',
+ 'x0[i].imag {comp} x1[i].imag')
+ elif is_complex(x1):
+ expr = expr.format(
+ 'false' if iseq else 'x0[i].real {comp} x1[i]',
+ 'x0[i].real == x1[i]',
+ 'x0[i].imag {comp} 0')
+ elif is_complex(x2):
+ expr = expr.format(
+ 'false' if iseq else 'x0[i] {comp} x1[i].real',
+ 'x0[i] == x1[i].real',
+ '0 {comp} x1[i].imag')
+ else:
+ expr = expr.format(
+ 'false' if iseq else 'x0[i] {comp} x1[i]',
+ 'x0[i] == x1[i]',
+ '0 {comp} 0')
+ return expr.format(comp=comp)
+
+ def greater(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Return the truth value of (x1 > x2) element-wise.
+ """
+ expr = self._make_comparisson_expr(x1,x2,'>')
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def greater_equal(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Return the truth value of (x1 >= x2) element-wise.
+ """
+ expr = self._make_comparisson_expr(x1,x2,'>=')
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def less(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Return the truth value of (x1 < x2) element-wise.
+ """
+ expr = self._make_comparisson_expr(x1,x2,'<')
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def less_equal(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Return the truth value of (x1 =< x2) element-wise.
+ """
+ expr = self._make_comparisson_expr(x1,x2,'<=')
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def equal(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Return (x1 == x2) element-wise.
+ """
+ expr = self._make_comparisson_expr(x1,x2,'==')
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def not_equal(self, x1, x2, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Return (x1 != x2) element-wise.
+ """
+ expr = self._make_comparisson_expr(x1,x2,'!=')
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+
+
+# MATHEMATICAL FUNCTIONS #
+##########################
+## See https://docs.scipy.org/doc/numpy/reference/routines.math.html
+
+ def _flt_or_cplx_unary_op(self, x, fname, **kargs):
+ assert 'expr' not in kargs
+ assert 'x0' not in kargs
+ assert 'convert_inputs' not in kargs
+ assert 'alloc_dtypes' not in kargs
+ expr='y0[i] = {}(x0[i])'
+ if is_complex(x):
+ expr = expr.format(self.complex_fn(fname, x))
+ convert_inputs='c'
+ alloc_dtypes='c'
+ else:
+ expr = expr.format(fname)
+ convert_inputs='f'
+ alloc_dtypes='f'
+ return self.unary_op(expr=expr, x0=x, convert_inputs=convert_inputs,
+ alloc_dtypes=alloc_dtypes, **kargs)
+
+ def _flt_or_map_cplx_unary_op(self, x, fname, **kargs):
+ assert 'expr' not in kargs
+ assert 'x0' not in kargs
+ if is_complex(x):
+ expr='y0[i] = {}({fn}(x0[i].real), {fn}(x0[i].imag))'
+ expr = expr.format(self.complex_fn('new', x), fn=fname)
+ _convert_inputs=None
+ _alloc_dtypes=(x.dtype,)
+ else:
+ expr='y0[i] = {}(x0[i])'
+ expr = expr.format(fname)
+ _convert_inputs='f'
+ _alloc_dtypes='f'
+ alloc_dtypes = kargs.pop('alloc_dtypes', None) or _alloc_dtypes
+ convert_inputs = kargs.pop('convert_inputs', None) or _convert_inputs
+ return self.unary_op(expr=expr, x0=x, convert_inputs=convert_inputs,
+ alloc_dtypes=alloc_dtypes, **kargs)
+
+ def _cplx_binary_op(self, x0, x1, fname, **kargs):
+ assert is_complex(x0) or is_complex(x1)
+ assert 'expr' not in kargs
+ assert 'convert_inputs' not in kargs
+ assert 'alloc_dtypes' not in kargs
+
+ convert_inputs='f'
+ alloc_dtypes='c'
+ expr = self.binary_complex_fn(fname,x0,x1)
+
+ return self.binary_op(expr=expr, x0=x0, x1=x1,
+ convert_inputs=convert_inputs,
+ alloc_dtypes=alloc_dtypes, **kargs)
+
+
+# Trigonometric functions
+ def sin(self, x, out=None, queue=None,
+ dtype=None):
+ """
+ Trigonometric sine, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'sin', out=out,
+ queue=queue, dtype=dtype)
+ def cos(self, x, out=None, queue=None, dtype=None):
+ """
+ Cosine element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'cos', out=out,
+ queue=queue, dtype=dtype)
+ def tan(self, x, out=None, queue=None, dtype=None):
+ """
+ Compute tangent element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'tan', out=out,
+ queue=queue, dtype=dtype)
+
+ def arcsin(self, x, out=None, queue=None, dtype=None):
+ """
+ Inverse sine, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'asin', out=out,
+ queue=queue, dtype=dtype)
+ def arccos(self, x, out=None, queue=None, dtype=None):
+ """
+ Trigonometric inverse cosine, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'acos', out=out,
+ queue=queue, dtype=dtype)
+ def arctan(self, x, out=None, queue=None, dtype=None):
+ """
+ Trigonometric inverse tangent, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'atan', out=out,
+ queue=queue, dtype=dtype)
+ def arctan2(self, x1, x2, out=None, queue=None, dtype=None):
+ """
+ Element-wise arc tangent of x1/x2 choosing the quadrant correctly.
+ """
+ expr='y0[i] = atan2(x0[i],x1[i])'
+ assert not is_complex(x1) and not is_complex(x2)
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+
+ def hypot(self, x1, x2, out=None, queue=None, dtype=None):
+ """
+ Given the legs of a right triangle, return its hypotenuse.
+ """
+ assert not is_complex(x1) and not is_complex(x2)
+ expr='y0[i] = hypot(x0[i],x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ #def unwrap(self, p, discont=3.141592653589793, axis=-1):
+ #"""
+ #Unwrap by changing deltas between values to 2*pi complement.
+ #"""
+ #self.unary_op(x0=x, expr='y0[i] = unwrap(x0[i])', out=out,
+ #queue=queue, dtype=dtype,
+ # convert_inputs='f', alloc_dtypes='f')
+ def deg2rad(self, x, out=None, queue=None, dtype=None):
+ """
+ Convert angles from degrees to radians.
+ """
+ assert not is_complex(x)
+ return self.unary_op(x0=x, expr='y0[i] = x0[i] * M_PI/180.0', out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ def rad2deg(self, x, out=None, queue=None, dtype=None):
+ """
+ Convert angles from radians to degrees.
+ """
+ assert not is_complex(x)
+ return self.unary_op(x0=x, expr='y0[i] = x0[i] * 180.0/M_PI', out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+
+# Hyperbolic functions
+ def sinh(self, x, out=None, queue=None, dtype=None):
+ """
+ Hyperbolic sine, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'sinh', out=out,
+ queue=queue, dtype=dtype)
+ def cosh(self, x, out=None, queue=None, dtype=None):
+ """
+ Hyperbolic cosine, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'cosh', out=out,
+ queue=queue, dtype=dtype)
+ def tanh(self, x, out=None, queue=None, dtype=None):
+ """
+ Compute hyperbolic tangent element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'tanh', out=out,
+ queue=queue, dtype=dtype)
+
+ def arcsinh(self, x, out=None, queue=None, dtype=None):
+ """
+ Inverse hyperbolic sine element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'asinh', out=out,
+ queue=queue, dtype=dtype)
+ def arccosh(self, x, out=None, queue=None, dtype=None):
+ """
+ Inverse hyperbolic cosine, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'acosh', out=out,
+ queue=queue, dtype=dtype)
+ def arctanh(self, x, out=None, queue=None, dtype=None):
+ """
+ Inverse hyperbolic tangent element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'atanh', out=out,
+ queue=queue, dtype=dtype)
+
+# Rounding
+ def around(self, a, decimals=0, out=None,
+ queue=None, dtype=None):
+ """
+ Round an array to the given number of decimals.
+ """
+ self._unsupported_argument('round','decimals',decimals,0)
+ if is_complex(dtype):
+ convert_inputs = (np.complex128,)
+ else:
+ convert_inputs = None
+ alloc_dtypes=(a.dtype,)
+ return self._flt_or_map_cplx_unary_op(a, 'round', out=out,
+ queue=queue, dtype=dtype,
+ alloc_dtypes=alloc_dtypes,
+ convert_inputs=convert_inputs)
+
+ def fix(self, x, y=None, out=None,
+ queue=None, dtype=None):
+ """
+ Round to nearest integer towards zero.
+ """
+ assert not is_complex(x)
+ return self.unary_op(x0=x, expr='y0[i] = trunc(x0[i])', out=y,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ def rint(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Round elements of the array to the nearest integer.
+ """
+ return self._flt_or_map_cplx_unary_op(x, 'rint', out=out,
+ queue=queue, dtype=dtype)
+ def floor(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the floor of the input, element-wise.
+ """
+ assert not is_complex(x)
+ if x.is_fp():
+ expr='y0[i] = floor(x0[i])'
+ else:
+ expr='y0[i] = x0[i]'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ def ceil(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the ceiling of the input, element-wise.
+ """
+ assert not is_complex(x)
+ return self.unary_op(x0=x, expr='y0[i] = ceil(x0[i])', out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ def trunc(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the truncated value of the input, element-wise.
+ """
+ assert not is_complex(x)
+ return self.unary_op(x0=x, expr='y0[i] = trunc(x0[i])', out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+
+
+# Sums, product, differences
+ def sum(self, a, axis=None, dtype=None, out=None, queue=None):
+ """
+ Sum of array elements over a given axis.
+ """
+ return self.reduce(kargs=(a,), axis=axis, dtype=dtype, out=out, queue=queue,
+ neutral='0', reduce_expr='a+b')
+
+ def prod(self, a, axis=None, dtype=None, out=None, queue=None):
+ """
+ Return the product of array elements over a given axis.
+ """
+ return self.reduce(kargs=(a,), axis=axis, dtype=dtype, out=out, queue=queue,
+ neutral='1', reduce_expr='a*b')
+
+ def nansum(self, a, axis=None, dtype=None, out=None, queue=None):
+ """
+ Return the sum of array elements over a given axis treating Not a Numbers (NaNs)
+ as zeros.
+ """
+ return self.nanreduce(kargs=(a,), axis=axis, dtype=dtype, out=out, queue=queue,
+ neutral='0', reduce_expr='a+b')
+
+ def nanprod(self, a, axis=None, dtype=None, out=None, queue=None):
+ """
+ Return the product of array elements over a given axis treating
+ Not a Numbers (NaNs) as ones.
+ """
+ return self.nanreduce(kargs=(a,), axis=axis, dtype=dtype, out=out, queue=queue,
+ neutral='1', reduce_expr='a*b')
+
+ def cumprod(self, a, axis=None, dtype=None, out=None,
+ queue=None):
+ """
+ Return the cumulative product of elements along a given axis.
+ /!\ precision loss because of operation ordering
+ """
+ return self.inclusive_scan(kargs=(a,), axis=axis, dtype=dtype, out=out,
+ neutral='1', scan_expr='a*b', queue=queue)
+ def cumsum(self, a, axis=None, dtype=None, out=None,
+ queue=None):
+ """
+ Return the cumulative sum of the elements along a given axis.
+ """
+ return self.inclusive_scan(kargs=(a,), axis=axis, dtype=dtype, out=out,
+ neutral='0', scan_expr='a+b', queue=queue)
+ def nancumprod(self, a, axis=None, dtype=None, out=None,
+ queue=None):
+ """
+ Return the cumulative product of array elements over a given axis treating
+ Not a Numbers (NaNs) as one.
+ /!\ precision loss because of operation ordering
+ """
+ return self.inclusive_nanscan(kargs=(a,), axis=axis, dtype=dtype, out=out,
+ neutral='1', scan_expr='a*b', queue=queue)
+ def nancumsum(self, a, axis=None, dtype=None, out=None,
+ queue=None):
+ """
+ Return the cumulative sum of array elements over a given axis treating
+ Not a Numbers (NaNs) as zero.
+ """
+ return self.inclusive_nanscan(kargs=(a,), axis=axis, dtype=dtype, out=out,
+ neutral='0', scan_expr='a+b', queue=queue)
+ def diff(self, a, n=1, axis=-1):
+ """
+ Calculate the n-th discrete difference along given axis.
+ """
+ self._not_implemented_yet('diff')
+ def ediff1d(self, ary, to_end=None, to_begin=None):
+ """
+ The differences between consecutive elements of an array.
+ """
+ self._not_implemented_yet('ediff1d')
+ def gradient(self, f, *varargs, **kwargs):
+ """
+ Return the gradient of an N-dimensional array.
+ """
+ self._not_implemented_yet('gradient')
+ def cross(self, a, b, axisa=-1, axisb=-1, axisc=-1, axis=None):
+ """
+ Return the cross product of two (arrays of) vectors.
+ """
+ self._not_implemented_yet('cross')
+ def trapz(self, y, x=None, dx=1.0, axis=-1):
+ """
+ Integrate along the given axis using the composite trapezoidal rule.
+ """
+ self._not_implemented_yet('trapz')
+
+#Exponents and logarithms
+ def exp(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Calculate the exponential of all elements in the input array.
+ """
+ return self._flt_or_cplx_unary_op(x, 'exp',out=out,
+ queue=queue, dtype=dtype)
+ def exp2(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Calculate 2**p for all p in the input array.
+ """
+ expr='y0[i] = exp2(x0[i])'
+ return self._flt_or_cplx_unary_op(x, 'exp2',out=out,
+ queue=queue, dtype=dtype)
+ def expm1(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Calculate exp(x) - 1 for all elements in the array.
+ """
+ expr='y0[i] = expm1(x0[i])'
+ return self._flt_or_cplx_unary_op(x, 'expm1',out=out,
+ queue=queue, dtype=dtype)
+
+ def log(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Natural logarithm, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'log',out=out,
+ queue=queue, dtype=dtype)
+ def log2(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Base-2 logarithm of x.
+ """
+ return self._flt_or_cplx_unary_op(x, 'log2',out=out,
+ queue=queue, dtype=dtype)
+ def log10(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the base 10 logarithm of the input array, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'log10',out=out,
+ queue=queue, dtype=dtype)
+ def log1p(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the natural logarithm of one plus the input array, element-wise.
+ """
+ expr='y0[i] = log1p(x0[i])'
+ return self._flt_or_cplx_unary_op(x, 'log1p',out=out,
+ queue=queue, dtype=dtype)
+
+ def logaddexp(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Logarithm of the sum of exponentiations of the inputs.
+ """
+ assert not is_complex(x1) and not is_complex(x2)
+ expr='y0[i] = log(exp(x0[i]) + exp(x1[i]))'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ def logaddexp2(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Logarithm of the sum of exponentiations of the inputs in base-2.
+ """
+ assert not is_complex(x1) and not is_complex(x2)
+ expr='y0[i] = log2(pow(2,x0[i]) + pow(2,x1[i]))'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+
+ #Other special functions
+ def i0(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Modified Bessel function of the first kind, order 0.
+ """
+ self._not_implemented_yet('i0',
+ convert_inputs='f', alloc_dtypes='f')
+ def sinc(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the sinc function.
+ """
+ assert not is_complex(x)
+ expr='y0[i] = sin(M_PI*x0[i]) / (M_PI*x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+
+ #Floating point routines
+ def signbit(self, x, out=None,
+ queue=None, dtype=HYSOP_BOOL):
+ """
+ Returns element-wise True where signbit is set (less than zero).
+ """
+ assert not is_complex(x)
+ expr='y0[i] = signbit(x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f')
+ def copysign(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Change the sign of x1 to that of x2, element-wise.
+ """
+ assert not is_complex(x1) and not is_complex(x2)
+ expr='y0[i] = copysign(x0[i], x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ def frexp(self, x, out1=None, out2=None,
+ queue=None):
+ """
+ Decompose the elements of x into mantissa and twos exponent.
+ """
+ assert not is_complex(x)
+ expr='int buf; y0[i] = frexp(x0[i], &buf); y1[i]=buf;'
+ return self.nary_op(ikargs=(x,), okargs=(out1,out2), operation=expr,
+ queue=queue,
+ convert_inputs='f', alloc_dtypes=('f',np.int32))
+ def ldexp(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Returns x1 * 2**x2, element-wise.
+ """
+ expr='y0[i] = ldexp(x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+
+
+# Arithmetic operations
+ def add(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Add arguments element-wise.
+ """
+ if is_complex(x1) or is_complex(x2):
+ return self._cplx_binary_op(x1,x2,'add',
+ out=out,queue=queue,dtype=dtype,)
+ else:
+ expr = 'y0[i] = (x0[i] + x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def reciprocal(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the reciprocal of the argument, element-wise.
+ """
+ dt = get_dtype(x)
+ if is_complex(x):
+ expr = 'y0[i] = {}(1,x0[i])'.format(self.complex_fn('rdivide',x))
+ elif is_integer(x):
+ info = np.iinfo(dt)
+ if (dt==np.int32) or (dt==np.int64): # to match numpy output
+ suffix = 'u' if is_unsigned(x) else ''
+ suffix += 'L' if (dt==np.int64) else ''
+ imin='{}{}'.format(info.min,suffix)
+ if dt==np.int64:
+ imin='{}{}'.format(info.min+1,suffix) #...
+ expr = 'y0[i] = (x0[i]==0 ? {imin} : (1{suffix}/x0[i]))'
+ expr = expr.format(imin=imin,suffix=suffix)
+ else:
+ expr = 'y0[i] = (x0[i]==0 ? 0 : (1/x0[i]))'
+ else:
+ expr = 'y0[i] = (1.0/x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def negative(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Numerical negative, element-wise.
+ """
+ if is_complex(x):
+ expr = 'y0[i] = {}(x0[i])'.format(self.complex_fn('neg',x))
+ else:
+ expr = 'y0[i] = (-x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def multiply(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Multiply arguments element-wise.
+ """
+ if is_complex(x1) or is_complex(x2):
+ return self._cplx_binary_op(x1,x2,'mul',
+ out=out,queue=queue,dtype=dtype,)
+ else:
+ expr = 'y0[i] = (x0[i] * x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def divide(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Divide arguments element-wise.
+ """
+ if is_complex(x1) or is_complex(x2):
+ return self._cplx_binary_op(x1,x2,'divide',
+ out=out,queue=queue,dtype=dtype)
+ elif is_integer(x2):
+ expr = 'y0[i] = (x1[i]==0 ? 0 : floor(x0[i] / x1[i]))'
+ convert_inputs = np.float64
+ else:
+ expr = 'y0[i] = (x0[i] / x1[i])'
+ convert_inputs = None
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs=convert_inputs)
+ def power(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ First array elements raised to powers from second array, element-wise.
+ """
+ if is_complex(x1) or is_complex(x2):
+ return self._cplx_binary_op(x1,x2,'pow',
+ out=out,queue=queue,dtype=dtype,)
+ else:
+ expr = 'pow(x0[i], x1[i])'
+ expr='y0[i] = ' + expr
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f')
+ def subtract(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Subtract arguments, element-wise.
+ """
+ if is_complex(x1) or is_complex(x2):
+ return self._cplx_binary_op(x1,x2,'sub',
+ out=out,queue=queue,dtype=dtype,)
+ else:
+ expr = 'y0[i] = (x0[i] - x1[i])'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def true_divide(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Returns a true division of the inputs, element-wise.
+ """
+ if is_complex(x1) or is_complex(x2):
+ return self._cplx_binary_op(x1,x2,'divide',
+ out=out,queue=queue,dtype=dtype)
+ else:
+ expr = 'y0[i] = (x0[i] / x1[i])'
+ convert_inputs=None
+ if is_integer(x1) and is_integer(x2):
+ dtype=(dtype or HYSOP_REAL)
+ convert_inputs=dtype
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs=convert_inputs)
+ def floor_divide(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Return the largest integer smaller or equal to the division of the inputs.
+ Returns y = floor(x1/x2)
+
+ Special floating point values are handled this way:
+
+ x1 x2 output
+ nan *** nan
+ *** nan nan
+ inf *** nan
+ --- inf 0 if (x1 and x2 have same sign) else -1
+ --- --- floor(x1/x2)
+
+ Note: inf means +inf or -inf.
+ """
+ if is_complex(x1) or is_complex(x2):
+ self._not_implemented_yet('floor_divide.')
+ elif is_integer(x1):
+ expr = 'y0[i] = (x1[i]==0 ? 0 : floor(x0[i]/x1[i]))'
+ convert_inputs=(np.float64,None)
+ else:
+ expr = 'y0[i] = ((isnan(x0[i])||isnan(x1[i])||isinf(x0[i]))?NAN:(isinf(x1[i])?((signbit(x0[i])^signbit(x1[i]))?-1:0):floor(x0[i]/x1[i])))'
+ convert_inputs='f'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs=convert_inputs)
+ def fmod(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Return the element-wise remainder of division (REM).
+ Remainder has the same sign as the dividend x1.
+ This should not be confused with the Python modulus operator x1 % x2.
+ Returns x - y*trunc(x/y)
+ """
+ assert not is_complex(x1) and not is_complex(x2)
+ if is_fp(x1) or is_fp(x2):
+ # expr = 'y0[i] = x0[i] - x1[i]*trunc(x0[i]/x1[i])'
+ expr = 'y0[i] = fmod(x0[i],x1[i])'
+ else:
+ expr = 'y0[i] = (x1[i] == 0 ? 0 : (x0[i] % x1[i]))'
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def mod(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Return element-wise remainder of division (MOD).
+ Remainder has the same sign as the divisor x2.
+ Match Python modulus operator x1 % x2.
+ Returns x - y*floor(x/y)
+
+ Special floating point values are handled this way:
+
+ x1 x2 output
+ nan *** nan
+ *** nan nan
+ inf inf nan
+ inf --- x2 if (x1 and x2 have same sign) else x1
+ --- --- x1 - x2 * floor(x1/x2)
+
+ Note: inf means +inf or -inf.
+ """
+ assert not is_complex(x1) and not is_complex(x2)
+ expr = 'x0[i] - x1[i]*floor(x0[i]/x1[i])'
+ convert_inputs=None
+ if is_integer(x1):
+ expr = '(x1[i]==0 ? 0 : {})'.format(expr)
+ convert_inputs=(np.float64,None)
+ if is_fp(x1) or is_fp(x2):
+ expr = '(isnan(x0[i])||isnan(x1[i])?NAN:(isinf(x1[i])?(isinf(x0[i])?NAN:(signbit(x0[i])^signbit(x1[i])?x1[i]:x0[i])):{}))'.format(expr)
+ convert_inputs='f'
+ expr='y0[i] = '+expr
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs=convert_inputs)
+ def modf(self, x, out1=None, out2=None,
+ queue=None, dtype=None):
+ """
+ Return the fractional and integral parts of an array, element-wise.
+ The fractional and integral parts are negative if the given number is negative.
+ => they have the same sign as the input argument.
+ out1 = fractional part
+ out2 = integral part
+ """
+ assert not is_complex(x)
+ if x.is_fp():
+ expr = 'y0[i] = modf(x0[i], &y1[i])'
+ else:
+ expr = 'y0[i] = 0; y1[i] = x0[i];'
+ return self.nary_op(ikargs=(x,), okargs=(out1,out2), operation=expr,
+ queue=queue, dtype=dtype, alloc_dtypes='f')
+
+# Handling complex numbers
+ def angle(self, z, deg=False,
+ queue=None, dtype=None):
+ """
+ Return the angle of the complex argument.
+ """
+ if deg:
+ fact = 180/np.pi
+ else:
+ fact = 1.0
+ if is_complex(z):
+ zimag = z.imag
+ zreal = z.real
+ else:
+ zimag = 0
+ zreal = z
+ return self.arctan2(zimag, zreal, queue=queue) * fact
+
+ def real(self, val, queue=None, out=None, dtype=None):
+ """
+ Return the real part of the elements of the array.
+ """
+ if is_complex(val):
+ expr = 'y0[i] = x0[i].real'
+ dtype = dtype or complex_to_float_dtype(val.dtype)
+ return self.unary_op(x0=val, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ else:
+ return val
+ def imag(self, val):
+ """
+ Return the imaginary part of the elements of the array.
+ """
+ return self.wrap(val.handle.imag)
+ def conj(self, x, out=None):
+ """
+ Return the complex conjugate, element-wise.
+ """
+ return self.wrap(x.handle.conj())
+
+# Miscellanous
+ def convolve(self, a, v, mode='full',
+ queue=None, dtype=None):
+ """
+ Returns the discrete, linear convolution of two one-dimensional sequences.
+ """
+ self._not_implemented_yet('convolve')
+ def clip(self, a, a_min, a_max, out=None,
+ queue=None, dtype=None):
+ """
+ Clip (limit) the values in an array.
+ """
+ if is_fp(a):
+ expr = 'y0[i] = (isnan(x0[i]) ? NAN : clamp(x0[i], p0, p1))'
+ elif is_complex(a):
+ expr = 'y0[i] = ({cond0} ? {expr0} : ({cond1} ? {expr1} : {default}))'
+ cond0='({xr}<{p0r} || ({xr}=={p0r} && {xi}<{p0i}))'
+ cond1='({xr}>{p1r} || ({xr}=={p1r} && {xi}>{p1i}))'
+ expr0='p0'
+ expr1='p1'
+ default='x0[i]'
+ expr = expr.format(cond0=cond0, cond1=cond1, expr0=expr0, expr1=expr1, default=default)
+ expr = expr.format(xr = 'x0[i].real', p0r = 'p0.real', p1r='p1.real',
+ xi = 'x0[i].imag', p0i = 'p0.imag', p1i='p1.imag')
+ else:
+ expr = 'y0[i] = clamp(x0[i], p0, p1)'
+ atype = a.dtype
+ atype = a.dtype
+ a_min = np.asarray(a_min, dtype=atype)
+ a_max = np.asarray(a_max, dtype=atype)
+ assert a_min <= a_max
+ return self.unary_op(x0=a, expr=expr, out=out, extra_kargs=(a_min, a_max),
+ queue=queue, dtype=dtype)
+
+ def clip_components(self, a, a_min, a_max, out=None,
+ queue=None, dtype=None):
+ """
+ Clip (limit) the real and imaginary part of a complex number independantly.
+ ie:
+ a.real = clip(a.real, a_min.real, a_max.real)
+ a.imag = clip(a.imag, a_min.imag, a_max.imag)
+ """
+ assert is_complex(a) and is_complex(a_min) and is_complex(a_max)
+ assert a_min.real <= a_max.real
+ assert a_min.imag <= a_max.imag
+ a_min = np.asarray(a_min, dtype=a.dtype)
+ a_max = np.asarray(a_max, dtype=a.dtype)
+ expr0 = 'y0[i].real = (isnan(x0[i].real) ? NAN : clamp(x0[i].real, p0.real, p1.real));'
+ expr1 = 'y0[i].imag = (isnan(x0[i].imag) ? NAN : clamp(x0[i].imag, p0.imag, p1.imag));'
+ expr = expr0+expr1
+ return self.unary_op(x0=a, expr=expr, out=out, extra_kargs=(a_min, a_max),
+ queue=queue, dtype=dtype)
+
+ def sqrt(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the positive square-root of an array, element-wise.
+ """
+ return self._flt_or_cplx_unary_op(x, 'sqrt', out=out,
+ queue=queue, dtype=dtype)
+ def cbrt(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the cube-root of an array, element-wise.
+ """
+ assert not is_complex(x)
+ expr = 'y0[i] = cbrt(x0[i])'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f', alloc_dtypes='f')
+ def square(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Return the element-wise square of the input.
+ """
+ expr = 'y0[i] = x0[i]*x0[i]'
+ if is_complex(x):
+ return self._cplx_binary_op(x,x,'mul',
+ queue=queue, dtype=dtype, out=out)
+ else:
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def nan_to_num(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Replace nan with zero and inf with finite numbers.
+ """
+
+ if is_fp(x) or is_complex(x):
+ dtype = dtype or x.dtype
+ if is_complex(dtype):
+ ftype=complex_to_float_dtype(dtype)
+ else:
+ ftype=dtype
+ info = np.finfo(ftype)
+ max_val = np.asarray(info.max, dtype=ftype)
+ min_val = np.asarray(info.min, dtype=ftype)
+ if is_fp(x):
+ expr = 'y0[i] = (isnan(x0[i]) ? 0 : (isinf(x0[i]) ? (signbit(x0[i]) ? p0 : p1) : x0[i]))'
+ elif is_complex(x):
+ real = '(isnan(x0[i].real) ? 0 : (isinf(x0[i].real) ? (signbit(x0[i].real) ? p0 : p1) : x0[i].real))'
+ imag = '(isnan(x0[i].imag) ? 0 : (isinf(x0[i].imag) ? (signbit(x0[i].imag) ? p0 : p1) : x0[i].imag))'
+ expr = 'y0[i] = {new}({real},{imag})'.format(real=real, imag=imag,
+ new=self.complex_fn('new', dtype))
+ return self.unary_op(x0=x, expr=expr, out=out,
+ extra_kargs=(min_val, max_val),
+ queue=queue, dtype=dtype)
+ elif out:
+ out.copyfrom(x)
+ else:
+ return x.astype(dtype=dtype or x.dtype, queue=queue)
+ def real_if_close(self, a, tol=100, queue=None):
+ """
+ If complex input returns a real array if complex parts are close to zero.
+ """
+ if is_complex(a):
+ if tol > 1:
+ from numpy.core import getlimits
+ f = getlimits.finfo(a.dtype.type)
+ tol = f.eps * tol
+
+ if self.reduce(kargs=(a,), neutral='true', reduce_expr='a&&b',
+ map_expr='(fabs(x0[i].imag) < tol)',
+ queue=queue, dtype=HYSOP_BOOL,
+ extra_kargs=(np.float64(tol),),
+ extra_arguments=['const double tol']).get():
+ return a.real
+ else:
+ return a
+ else:
+ return a
+
+ def maximum(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Element-wise maximum of array elements, priority to NaNs.
+ """
+ if is_fp(x1) and is_fp(x2):
+ expr = '(isnan(x0[i]) ? NAN : (isnan(x1[i]) ? NAN : max(x0[i], x1[i])))'
+ elif is_fp(x1):
+ expr = '(isnan(x0[i]) ? NAN : max(x0[i], x1[i]))'
+ elif is_fp(x2):
+ expr = '(isnan(x1[i]) ? NAN : max(x0[i], x1[i]))'
+ elif is_complex(x1) and is_complex(x2):
+ default = '(((x0[i].real>x1[i].real) || ((x0[i].real==x1[i].real) && (x0[i].imag>x1[i].imag))) ? x0[i] : x1[i])'
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', 'x0[i]',
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', 'x1[i]',
+ default)
+ elif is_complex(x1):
+ fromreal=self.complex_fn('fromreal', x1)
+ default = '(((x0[i].real>x1[i]) || ((x0[i].real==x1[i]) && (x0[i].imag>0))) ? x0[i] : {}(x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', 'x0[i]',
+ 'isnan(x1[i])', '{}(NAN)'.format(fromreal),
+ default)
+ elif is_complex(x2):
+ fromreal=self.complex_fn('fromreal', x2)
+ default = '(((x0[i]>x1[i].real) || ((x0[i]==x1[i].real) && (0>x1[i].imag))) ? {}(x0[i]) : x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ 'isnan(x0[i])', '{}(x0[i])'.format(fromreal),
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', 'x1[i]',
+ default)
+ else:
+ expr = 'max(x0[i], x1[i])'
+ expr='y0[i] = '+expr
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def minimum(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Element-wise minimum of array elements, priority to NaNs.
+ """
+ if is_fp(x1) and is_fp(x2):
+ expr = '(isnan(x0[i]) ? NAN : (isnan(x1[i]) ? NAN : min(x0[i], x1[i])))'
+ elif is_fp(x1):
+ expr = '(isnan(x0[i]) ? NAN : min(x0[i], x1[i]))'
+ elif is_fp(x2):
+ expr = '(isnan(x1[i]) ? NAN : min(x0[i], x1[i]))'
+ elif is_complex(x1) and is_complex(x2):
+ default = '(((x0[i].real<x1[i].real) || ((x0[i].real==x1[i].real) && (x0[i].imag<x1[i].imag))) ? x0[i] : x1[i])'
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', 'x0[i]',
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', 'x1[i]',
+ default)
+ elif is_complex(x1):
+ fromreal=self.complex_fn('fromreal', x1)
+ default = '(((x0[i].real<x1[i]) || ((x0[i].real==x1[i]) && (x0[i].imag<0))) ? x0[i] : {}(x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', 'x0[i]',
+ 'isnan(x1[i])', '{}(x1[i])'.format(fromreal),
+ default)
+ elif is_complex(x2):
+ fromreal=self.complex_fn('fromreal', x2)
+ default = '(((x0[i]<x1[i].real) || ((x0[i]==x1[i].real) && (0<x1[i].imag))) ? {}(x0[i]) : x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ 'isnan(x0[i])', '{}(x0[i])'.format(fromreal),
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', 'x1[i]',
+ default)
+ else:
+ expr = 'min(x0[i], x1[i])'
+ expr='y0[i] = '+expr
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def fmax(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Element-wise maximum of array elements, ignoring NaNs.
+ """
+ if is_fp(x1) and is_fp(x2):
+ expr = '(isnan(x0[i]) ? x1[i] : (isnan(x1[i]) ? x0[i] : max(x0[i], x1[i])))'
+ elif is_fp(x1):
+ expr = '(isnan(x0[i]) ? x1[i] : max(x0[i], x1[i]))'
+ elif is_fp(x2):
+ expr = '(isnan(x1[i]) ? x0[i] : max(x0[i], x1[i]))'
+ elif is_complex(x1) and is_complex(x2):
+ default = '(((x0[i].real>x1[i].real) || ((x0[i].real==x1[i].real) && (x0[i].imag>x1[i].imag))) ? x0[i] : x1[i])'
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', 'x1[i]',
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', 'x0[i]',
+ default)
+ elif is_complex(x1):
+ fromreal=self.complex_fn('fromreal', x1)
+ default = '(((x0[i].real>x1[i]) || ((x0[i].real==x1[i]) && (x0[i].imag>0))) ? x0[i] : {}(x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', '{}(x1[i])'.format(fromreal),
+ 'isnan(x1[i])', 'x0[i]',
+ default)
+ elif is_complex(x2):
+ fromreal=self.complex_fn('fromreal', x2)
+ default = '(((x0[i]>x1[i].real) || ((x0[i]==x1[i].real) && (0>x1[i].imag))) ? {}(x0[i]) : x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ 'isnan(x0[i])', 'x1[i]',
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', '{}(x0[i])'.format(fromreal),
+ default)
+ else:
+ expr = 'max(x0[i], x1[i])'
+ expr = 'y0[i] = ' + expr
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def fmin(self, x1, x2, out=None,
+ queue=None, dtype=None):
+ """
+ Element-wise minimum of array elements, ignoring NaNs.
+ """
+ if is_fp(x1) and is_fp(x2):
+ expr = '(isnan(x0[i]) ? x1[i] : (isnan(x1[i]) ? x0[i] : min(x0[i], x1[i])))'
+ elif is_fp(x1):
+ expr = '(isnan(x0[i]) ? x1[i] : min(x0[i], x1[i]))'
+ elif is_fp(x2):
+ expr = '(isnan(x1[i]) ? x0[i] : min(x0[i], x1[i]))'
+ elif is_complex(x1) and is_complex(x2):
+ default = '(((x0[i].real<x1[i].real) || ((x0[i].real==x1[i].real) && (x0[i].imag<x1[i].imag))) ? x0[i] : x1[i])'
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', 'x1[i]',
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', 'x0[i]',
+ default)
+ elif is_complex(x1):
+ fromreal=self.complex_fn('fromreal', x1)
+ default = '(((x0[i].real<x1[i]) || ((x0[i].real==x1[i]) && (x0[i].imag<0))) ? x0[i] : {}(x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ '(isnan(x0[i].real) || isnan(x0[i].imag))', '{}(x1[i])'.format(fromreal),
+ 'isnan(x1[i])', 'x0[i]',
+ default)
+ elif is_complex(x2):
+ fromreal=self.complex_fn('fromreal', x2)
+ default = '(((x0[i]<x1[i].real) || ((x0[i]==x1[i].real) && (0<x1[i].imag))) ? {}(x0[i]) : x1[i])'.format(fromreal)
+ expr = '({} ? {} : ({} ? {} : {}))'.format(
+ 'isnan(x0[i])', 'x1[i]',
+ '(isnan(x1[i].real) || isnan(x1[i].imag))', '{}(x0[i])'.format(fromreal),
+ default)
+ else:
+ expr = 'min(x0[i], x1[i])'
+ expr = 'y0[i] = ' + expr
+ return self.binary_op(x0=x1, x1=x2, expr=expr, out=out,
+ queue=queue, dtype=dtype)
+ def fabs(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Calculate the absolute value element-wise, outputs real values unless out or dtype
+ is set.
+ """
+ assert not is_complex(x)
+ if is_fp(x):
+ expr = 'y0[i] = fabs(x0[i])'
+ else:
+ expr = 'y0[i] = abs(x0[i])'
+ alloc_dtypes = 'f'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ alloc_dtypes=alloc_dtypes)
+ def absolute(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Calculate the absolute value element-wise, ouputs values as input type
+ unless out or dtype is set.
+ """
+ if is_complex(x):
+ expr = 'y0[i] = {}(x0[i])'.format(self.complex_fn('abs',x))
+ alloc_dtypes=(complex_to_float_dtype(x),)
+ elif is_fp(x):
+ expr = 'y0[i] = fabs(x0[i])'
+ alloc_dtypes=None
+ else:
+ expr = 'y0[i] = abs(x0[i])'
+ alloc_dtypes=None
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype, alloc_dtypes=alloc_dtypes)
+
+ def sign(self, x, out=None,
+ queue=None, dtype=None):
+ """
+ Returns an element-wise indication of the sign of a number.
+ NaNs values are kept to NaNs to comply with numpy.
+ """
+ if is_fp(x):
+ expr = 'y0[i] = (isnan(x0[i]) ? NAN : sign(x0[i]))'
+ elif is_complex(x):
+ expr = 'y0[i] = {}(isnan(x0[i].real) ? NAN : sign(x0[i].real))'
+ expr = expr.format(self.complex_fn('fromreal', x))
+ else:
+ expr = 'y0[i] = (sign(x0[i]))'
+ return self.unary_op(x0=x, expr=expr, out=out,
+ queue=queue, dtype=dtype,
+ convert_inputs='f')
+
+
+# RANDOM SAMPLING #
+###################
+## See https://docs.scipy.org/doc/numpy/reference/routines.random.html
+
+# Simple random data
+ def rand(self, shape=None, queue=None,
+ order=default_order, dtype=HYSOP_REAL,
+ out=None, a=0.0, b=1.0, generator=None):
+ """
+ Return samples from the uniform distribution [a,b].
+ Default generator is clRandom.PhiloxGenerator.
+ """
+ self._check_argtype('rand', 'shape', shape, tuple)
+ self.check_queue(queue)
+ if (generator is None):
+ generator = clRandom.PhiloxGenerator(context=self.context)
+ if (out is None):
+ out = self.empty(shape=shape, dtype=dtype, order=order, queue=queue)
+ generator.fill_uniform(ary=out.handle, a=a, b=b, queue=queue)
+ return out
+
+ def randn(self, shape=None, queue=None,
+ order=default_order, dtype=HYSOP_REAL,
+ out=None, mu=0.0, sigma=1.0, generator=None,
+ *args):
+ """
+ Return samples from the standard normal distribution [mu,sigma].
+ Default generator is clRandom.PhiloxGenerator.
+ """
+ self.check_queue(queue)
+ self._check_argtype('randn', 'shape', shape, tuple)
+ if (generator is None):
+ generator = clRandom.PhiloxGenerator(context=self.context)
+ if (out is None):
+ out = self.empty(shape=shape, dtype=dtype, order=order, queue=queue)
+ generator.fill_normal(ary=out.handle, mu=mu, sigma=sigma, queue=queue)
+ return out
+
+
+# STATISTICS #
+##############
+## See https://docs.scipy.org/doc/numpy/reference/routines.sort.html
+
+#Order statistics
+ def amin(self, a, axis=None, out=None, queue=None):
+ """
+ Return the minimum of an array.
+ """
+ return self.reduce(a=a, neutral='x[0]', reduce_expr='min(a,b)',
+ axis=axis, out=out, queue=queue)
+
+ def amax(self, a, axis=None, out=None, slice=None, queue=None):
+ """
+ Return the maximum of an array.
+ """
+ return self.reduce(a=a, neutral='x[0]', reduce_expr='max(a,b)',
+ axis=axis, out=out, queue=queue)
+
+ def average(self, a, axis=None, weights=None, returned=False, queue=None):
+ """
+ Compute the weighted average along the specified axis.
+ """
+ self._unsupported_argument('average','returned', returned, False)
+ if (weights is None):
+ return self.mean(a=a, axis=axis, queue=queue)
+ else:
+ arguments = '__global {ctype} const* x0, __global {ctype} const* w0'
+ arguments = arguments.format(ctype=a.ctype())
+ return self.reduce(kargs=a, neutral='0', reduce_expr='a+b',
+ axis=axis, out=out, queue=queue, dtype=dtype,
+ map_expr='w0[i]*x0[i]',
+ arguments=arguments) / float(a.size)
+
+ def mean(self, a, axis=None, dtype=None, out=None, queue=None):
+ """
+ Compute the arithmetic mean along the specified axis.
+ """
+ return a.sum(a=a, axis=axis, dtype=dtype, out=out, queue=queue) / float(a.size)
+
+ def std(self, a, axis=None, dtype=None, out=None, ddof=0, queue=None):
+ """
+ Compute the standard deviation along the specified axis.
+ """
+ self._not_implemented_yet('std')
+
+ def var(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the variance along the specified axis.
+ """
+ self._not_implemented_yet('var')
+
+ def nanmedian(self, a, axis=None, out=None, overwrite_input=False):
+ """
+ Compute the median along the specified axis, while ignoring NaNs.
+ """
+ self._not_implemented_yet('nanmedian')
+ def nanmean(self, a, axis=None, dtype=None, out=None):
+ """
+ Compute the arithmetic mean along the specified axis, ignoring NaNs.
+ """
+ self._not_implemented_yet('nanmean')
+ def nanstd(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the standard deviation along the specified axis, while ignoring NaNs.
+ """
+ self._not_implemented_yet('nanstd')
+ def nanvar(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the variance along the specified axis, while ignoring NaNs.
+ """
+ self._not_implemented_yet('nanvar')
+
+ @staticmethod
+ def build_codegen_argument(args, name, typegen, ctype,
+ itype='unsigned long',
+ const=False, ptr=True, **kargs):
+
+ from hysop.backend.device.codegen.base.utils import ArgDict
+ from hysop.backend.device.codegen.base.variables import CodegenVariable
+ check_instance(args, ArgDict)
+
+ base = '{}_base'.format(name)
+ offset = '{}_offset'.format(name)
+ assert base not in args
+ assert offset not in args
+
+ assert 'nl' not in kargs
+ assert 'add_impl_const' not in kargs
+ assert 'init' not in kargs
+
+ args[base] = CodegenVariable(name=base, typegen=typegen,
+ ctype=ctype, ptr=ptr, const=const,
+ add_impl_const=True, nl=False, **kargs)
+
+ args[offset] = CodegenVariable(name=offset,
+ typegen=typegen, ctype=itype,
+ add_impl_const=True, nl=True)
+
+ char_alias = args[base].full_ctype(ctype='char', cast=True, align=True)
+ ctype_alias = args[base].full_ctype(cast=True, align=True)
+ init = '({})(({})({})+{})'.format(ctype_alias, char_alias, base, offset)
+
+ var = CodegenVariable(name=name, typegen=typegen,
+ ctype=ctype, ptr=ptr, const=const,
+ add_impl_const=True, nl=False,
+ init=init, **kargs)
+
+ return var
+
+
+ArrayBackend._register_backend(clArray.Array, OpenClArrayBackend)
diff --git a/hysop/backend/device/opencl/opencl_buffer.py b/hysop/backend/device/opencl/opencl_buffer.py
new file mode 100644
index 0000000000000000000000000000000000000000..715ee6b3c29bbb829d9cc93b1a94944db044f4fb
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_buffer.py
@@ -0,0 +1,53 @@
+
+from hysop.core.memory.buffer import PooledBuffer
+from hysop.backend.device.device_buffer import DeviceBuffer
+from hysop.backend.device.opencl import cl
+
+class OpenClBuffer(cl.Buffer, DeviceBuffer):
+
+ """
+ OpenCL buffer object.
+ Simple wrapper of a pyopencl.Buffer.
+ """
+ def __init__(self, context, mem_flags, size=0, hostbuf=None):
+ super(OpenClBuffer,self).__init__(context=context, flags=mem_flags,
+ size=size, hostbuf=hostbuf)
+
+ @classmethod
+ def from_int_ptr(cls, int_ptr_value, retain=True):
+ """
+ Creates an OpenClBuffer from a raw opencl pointer (as an int).
+ """
+ obj = cl.Buffer.from_int_ptr(int_ptr_value=int_ptr_value, retain=retain)
+ obj.__class__ = OpenClBuffer
+ return obj
+
+ @classmethod
+ def from_cl_buffer(cls, cl_buffer):
+ """
+ Creates an OpenClBuffer from a cl_buffer.
+ """
+ assert isinstance(cl_buffer, cl.Buffer)
+ return cls.from_int_ptr(cl_buffer.int_ptr, retain=True)
+
+ def get_int_ptr(self):
+ return self.int_ptr
+
+ def ref_count(self):
+ return self.reference_count
+
+ def aligned_view(self, alignment, size=None):
+ assert alignment>0
+ assert not (alignment & (alignment-1)), 'alignment is not a power of 2.'
+ ptr = self.get_int_ptr()
+ offset = -ptr % alignment
+ if (size is None):
+ size = self.size-offset
+ else:
+ assert self.size >= (offset+size)
+ return self[offset:offset+size]
+
+class OpenClPooledBuffer(PooledBuffer, cl.MemoryObjectHolder):
+ def get_ptr(self):
+ return self._bufview.ptr
+ ptr = property(get_ptr)
diff --git a/hysop/backend/device/opencl/opencl_device.py b/hysop/backend/device/opencl/opencl_device.py
new file mode 100644
index 0000000000000000000000000000000000000000..19925e276df64a7ad07d8a286dd123a2315f2886
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_device.py
@@ -0,0 +1,798 @@
+
+from hysop import hprint
+from hysop.deps import re, np
+from hysop.backend.device.opencl import cl
+from hysop.constants import DeviceType, CacheType, MemoryType, FpConfig
+from hysop.tools.units import bytes2str, freq2str, time2str
+from hysop.backend.device import LogicalDevice, UnknownDeviceAttribute
+from hysop.tools.string_utils import prepend
+
+def opencl_version_atleast(major,minor,returned=UnknownDeviceAttribute()):
+ def decorator(f):
+ def wrap(*args, **kargs):
+ self = args[0]
+ (version_major, version_minor) = self.opencl_version()
+ if (version_major > major) or \
+ (version_major==major and version_minor >= minor):
+ return f(*args, **kargs)
+ else:
+ return returned
+ return wrap
+ return decorator
+
+def cl2hysop_device_type(cl_dev_type):
+ entries = {
+ cl.device_type.ACCELERATOR: DeviceType.ACCELERATOR,
+ cl.device_type.ALL: DeviceType.ALL,
+ cl.device_type.CPU: DeviceType.CPU,
+ cl.device_type.DEFAULT: DeviceType.DEFAULT,
+ cl.device_type.GPU: DeviceType.GPU
+ }
+ if hasattr(cl.device_type, 'CUSTOM'):
+ entries[cl.device_type.CUSTOM] = DeviceType.CUSTOM
+
+ if cl_dev_type not in entries:
+ msg = 'Unknown opencl device type {}.'.format(cl_dev_type)
+ raise ValueError(msg)
+ return entries[cl_dev_type]
+
+
+def cl2hysop_mem_type(cl_mem_type):
+ if cl_mem_type == cl.device_local_mem_type.LOCAL:
+ return MemoryType.LOCAL_MEMORY
+ elif cl_mem_type == cl.device_local_mem_type.GLOBAL:
+ return MemoryType.GLOBAL_MEMORY
+ else:
+ msg = 'Unknown memory type {}.'.format(cl_mem_type)
+ raise ValueError(msg)
+
+def cl2hysop_cache_type(cl_cache_type):
+ ct = cl.device_mem_cache_type
+ if cl_cache_type == ct.NONE:
+ return CacheType.NONE
+ elif cl_cache_type == ct.READ_ONLY_CACHE:
+ return CacheType.READ_ONLY_CACHE
+ elif cl_cache_type == ct.READ_WRITE_CACHE:
+ return CacheType.READ_WRITE_CACHE
+ else:
+ msg = 'Unknown cache type {}.'.format(cl_cache_type)
+ raise ValueError(msg)
+
+def cl2hysop_fpconfig(cl_fpconfig):
+ entries = {
+ FpConfig.DENORM: bool(cl_fpconfig & 0x01),
+ FpConfig.INF_NAN: bool(cl_fpconfig & 0x02),
+ FpConfig.ROUND_TO_NEAREST: bool(cl_fpconfig & 0x04),
+ FpConfig.ROUND_TO_ZERO: bool(cl_fpconfig & 0x08),
+ FpConfig.ROUND_TO_INF: bool(cl_fpconfig & 0x10),
+ FpConfig.FMA: bool(cl_fpconfig & 0x20),
+ FpConfig.SOFT_FLOAT: bool(cl_fpconfig & 0x40),
+ FpConfig.CORRECTLY_ROUNDED_DIVIDE_SQRT: bool(cl_fpconfig & 0x80)
+ }
+ if cl_fpconfig>0xff:
+ msg='Unknown bit field entry \'{:04x}\'.'.format(cl_fpconfig)
+ msg+='\nSee opencl header to add missing entries (cl_device_fp_config).'
+ raise ValueError(msg)
+ return entries
+
+class OpenClDevice(LogicalDevice):
+
+ @classmethod
+ def handle_cls(cls):
+ return cl.Device
+
+ def __init__(self, device_handle, **kargs):
+ version = device_handle.version
+ regexp = re.compile('OpenCL ([0-9]+)\.([0-9]+)')
+ match = re.match(regexp, version)
+ assert match, 'Could not match opencl version from \'{}\'.'.format(version)
+ major, minor = int(match.group(1)), int(match.group(2))
+ self._cl_version = (major,minor)
+
+ super(OpenClDevice,self).__init__(device_handle=device_handle,**kargs)
+
+ def _match_physical_device(self, hardware_topo):
+ if self.type() == DeviceType.CPU:
+ # if its a cpu, we can only match mono socket architectures
+ packages = hardware_topo.cpu_packages()
+ if len(packages)>1:
+ hprint(' -Multi socket architecture, could not match opencl cpu.')
+ return None
+ else:
+ hprint(' -Matched opencl device \'{}\' to cpu package 0.'.format(self.name()))
+ return packages[0]
+
+ # if it is not a device of type CPU, it may be a pci device
+ # first we match only by vendor id
+ pci_devices = hardware_topo.pci_devices(vendor_id=self.vendor_id())
+
+ # if there is only one such device we are lucky
+ if len(pci_devices)==1:
+ device = pci_devices[0]
+ msg=' -Matched opencl device \'{}\' by vendor id to pci bus id {}'
+ msg=msg.format(self.name(), device.pci_busid())
+ hprint(msg)
+ return device
+ # else we may try to look to pci bus id
+ # at this time, this is only available for nvidia and amd via opencl extensions
+ else:
+ pci_bus_id = self.pci_bus_id()
+ pci_devices = dict(zip([dev.pci_busid() for dev in pci_devices],pci_devices))
+ if not isinstance(pci_bus_id, str):
+ hprint(' -Could not get opencl pci device bus id.')
+ return None
+ elif pci_bus_id not in pci_devices.keys():
+ hprint(' -Could get opencl pci device bus id ({}), but it did not match '.format(pci_bus_id)
+ +'any in hardware topology.')
+ return None
+ else:
+ hprint(' -Matched opencl device \'{}\' to pci bus id {}'.format(self.name(), pci_bus_id))
+
+ return pci_devices[pci_bus_id]
+
+ def device_id(self):
+ if self.type() == DeviceType.CPU:
+ return None
+ elif (self.physical_device() is not None):
+ return self.physical_device().device_id()
+ else:
+ return None
+
+ def device_summary(self):
+ def _device_id():
+ did = self.device_id()
+ if (did is not None):
+ return '[0x{:04x}]'.format(did)
+ else:
+ return ''
+ msg = \
+'''General informations:
+ *name: {} {}
+ *vendor: {} [0x{:04x}]
+ *device type: {}
+ *opencl version: {}
+ *opencl C version: {}
+
+ *address bits: {}bit
+ *little endian: {}
+ *ECC enabled: {}
+ *max clock frequency: {}
+
+ *device available: {}
+ *compiler available: {}
+ *linker available: {}
+ *spir support: {}
+'''.format(
+self.name(), _device_id(),
+self.vendor(), self.vendor_id(),
+self.type(),
+self._handle.version, self.opencl_c_version(),
+self.address_bits(), self.little_endian(),
+self.error_correction_support(),
+freq2str(self.max_clock_frequency()),
+self.available(), self.compiler_available(),
+self.linker_available(), self.has_spir_support())
+ return msg
+
+ def memory_summary(self):
+ msg = \
+'''
+Global memory:
+ *size: {}
+ *max alloc size: {}
+ *cache size: {}
+ *cacheline size: {}
+ *cache type: {}
+
+Local memory
+ *total size: {}
+ *usable size: {}
+ *cache type: {}
+'''.format(
+bytes2str(self.global_mem_size()),
+bytes2str(self.max_global_alloc_size()),
+bytes2str(self.global_mem_cache_size(), decimal=False),
+bytes2str(self.global_mem_cacheline_size(), decimal=False),
+self.global_mem_cache_type(),
+bytes2str(self.local_mem_size(), decimal=False),
+bytes2str(self.usable_local_mem_size(), decimal=False),
+self.local_mem_type())
+ return msg
+
+ def kernel_summary(self):
+ msg = \
+'''
+Kernel execution capabilities:
+ *max grid size: {}
+ *max block size: {} (dim={})
+ *max threads: {}
+
+ *simd lane size: {}
+ *max constant args: {}
+ *max constant buffer size: {}
+ *max global variable size: {}
+'''.format(
+self.max_grid_size(),
+self.max_block_size(), self.max_block_dim(),
+self.max_threads_per_block(),
+self.simd_lane_size(),
+self.max_constant_args(),
+bytes2str(self.max_constant_buffer_size(), decimal=False),
+bytes2str(self.max_global_variable_size(), decimal=False))
+ return msg
+
+ def fp_support_summary(self):
+
+ def fmt(bits, has_fp, get_fp_flags):
+ if not has_fp:
+ support = '\n *fp{} support: None'.format(bits)
+ else:
+ support = '\n *fp{} support:'.format(bits)
+ flags = get_fp_flags()
+ support += '\n -'+'\n -'.join(sorted([str(k) for k in flags.keys() if flags[k]]))
+ support += '\n'
+
+ return support
+
+ msg=\
+'''
+Floating point support:{}{}{}
+'''.format(
+fmt(16, self.has_fp16(), self.fp16_config),
+fmt(32, self.has_fp32(), self.fp32_config),
+fmt(64, self.has_fp64(), self.fp64_config))
+ return msg[:-1]
+
+ def vectors_summary(self):
+ has_native = self.opencl_version()[0]>1 or self.opencl_version()[1]>=1
+ def fmt(string):
+ return ('/'+str(string) if has_native else '')
+ msg=\
+'''
+Vector sizes (preferred{}):
+ *char: {}{}
+ *short: {}{}
+ *int: {}{}
+ *long: {}{}
+
+ *half: {}{}
+ *float: {}{}
+ *double: {}{}
+'''.format(
+ fmt('native'),
+ self.preferred_vector_width_char(), fmt(self.native_vector_width_char()),
+ self.preferred_vector_width_short(), fmt(self.native_vector_width_short()),
+ self.preferred_vector_width_int(), fmt(self.native_vector_width_int()),
+ self.preferred_vector_width_long(), fmt(self.native_vector_width_long()),
+ self.preferred_vector_width_half(), fmt(self.native_vector_width_half()),
+ self.preferred_vector_width_float(), fmt(self.native_vector_width_float()),
+ self.preferred_vector_width_double(), fmt(self.native_vector_width_double()))
+ return msg
+
+ def image_summary(self):
+ if not self.has_image_support():
+ return '\nImage support: None\n'
+
+ def fmt(has_read_support, has_write_support, max_size_fn):
+ if not has_read_support:
+ return 'unsupported'
+ if has_write_support:
+ mode = 'read/write'
+ else:
+ mode = 'read only'
+ max_size = max_size_fn()
+ return '{:<20} {}'.format(tuple(max_size), mode)
+
+ def fmt_array(has_support, max_size_fn):
+ if not has_support:
+ return 'unsupported'
+ else:
+ max_size = max_size_fn()
+ return '{}'.format(tuple(max_size))
+
+ msg=\
+'''
+Image support:
+ *max image args: {}
+ *max write image args: {}
+ *max samplers args: {}
+
+ *1D image: {}
+ *2D image: {}
+ *3D image: {}
+
+ *1D image array: {}
+ *2D image array: {}
+
+ *1D image from buffer: {}
+ *2D image from buffer: {}
+ *3D image from buffer: {}
+'''.format(
+ self.max_image_args(),
+ self.max_write_image_args(),
+ self.max_samplers(),
+ fmt(self.has_1d_image_support(), self.has_1d_image_write_support(), self.max_1d_image_size),
+ fmt(self.has_2d_image_support(), self.has_2d_image_write_support(), self.max_2d_image_size),
+ fmt(self.has_3d_image_support(), self.has_3d_image_write_support(), self.max_3d_image_size),
+ fmt_array(self.has_1d_image_array_support(), self.max_1d_image_array_size),
+ fmt_array(self.has_2d_image_array_support(), self.max_2d_image_array_size),
+ self.has_1d_image_from_buffer_support(),
+ self.has_2d_image_from_buffer_support(),
+ self.has_3d_image_from_buffer_support())
+ return msg
+
+ def atomics_summary(self):
+ def fmt(glob, local , mixed):
+ return '{}/{}/{}'.format(int(glob),int(local),int(mixed))
+ msg=\
+'''
+Atomics capabilities (global/local/mixed support):
+ *int32/uint32: {}
+ *int64/uint64: {}
+ *float32: {}
+ *float64: {}
+
+ *int32 hardware counters: {}
+ *int64 hardware counters: {}
+'''.format(
+ fmt(self.has_global_int32_atomics(), self.has_local_int32_atomics(), self.has_mixed_int32_atomics()),
+ fmt(self.has_global_int64_atomics(), self.has_local_int64_atomics(), self.has_mixed_int64_atomics()),
+ fmt(self.has_global_float32_atomics(), self.has_local_float32_atomics(), self.has_mixed_float32_atomics()),
+ fmt(self.has_global_float64_atomics(), self.has_local_float64_atomics(), self.has_mixed_float64_atomics()),
+ self.has_int32_hardware_atomic_counters(),
+ self.has_int64_hardware_atomic_counters())
+ return msg
+
+ def misc_summary(self):
+ if self.has_printf_support():
+ pbs = self.printf_buffer_size()
+ pbs = 'up to {}'.format(bytes2str(pbs)) if isinstance(pbs,(int,long)) else 'unknown buffer size'
+ msg=\
+'''
+Miscellaneous:
+ *device splitting: {}
+ *printf: {}
+ *queue priority: {}
+ *profiling level: {}
+'''.format(
+ 'yes, up to {} subdevices'.format(self.max_subdevices()) if self.has_device_partition_support() else 'no',
+ 'yes, {}'.format(pbs) if self.has_printf_support() else 'no',
+ 'yes' if self.has_queue_priority_support() else 'no',
+ 'yes, resolution is {}'.format(time2str(self.profiling_time_resolution()).strip())
+)
+ return msg
+
+ def extensions_summary(self):
+ return '\nExtensions:\n *'+'\n *'.join(sorted(self.extensions()))
+
+ def __str__(self):
+ return \
+'''
+== OpenClDevice ==
+{}{}{}{}{}{}{}{}{}
+==================
+'''.format(
+prepend(self.device_summary(), ' '),
+prepend(self.memory_summary(), ' '),
+prepend(self.kernel_summary(), ' '),
+prepend(self.fp_support_summary(), ' '),
+prepend(self.vectors_summary(), ' '),
+prepend(self.image_summary(), ' '),
+prepend(self.atomics_summary(), ' '),
+prepend(self.misc_summary(), ' '),
+prepend(self.extensions_summary(), ' '))
+
+
+# OPENCL DEVICE SPECIFIC
+ def opencl_version(self):
+ return self._cl_version
+ def has_extension(self, extension):
+ return (extension in self.extensions())
+ def has_spir_support(self):
+ return self.has_extension('cl_khr_spir')
+ def pci_bus_id(self):
+ """
+ Return the PCI bus id of this device if possible.
+ Format is '0000:bus:device.function' 8+5+3 = 16 bits
+ Example: 0000:01:00.0
+ """
+ if self.type() == DeviceType.CPU:
+ return None
+ else:
+ if self.has_extension('cl_nv_device_attribute_query'):
+ bus_id = self._handle.pci_bus_id_nv
+ slot_id = self._handle.pci_slot_id_nv
+ dev_id = (slot_id >> 3)
+ fn_id = (slot_id & 0x07)
+ bus_id0 = (bus_id >> 8 ) # not sure if usefull
+ bus_id1 = (bus_id & 0xff)
+ return '{:04x}:{:02x}:{:02x}.{:01x}'.format(bus_id0,bus_id1,dev_id,fn_id)
+ elif self.has_extension('cl_amd_device_topology'):
+ topo = self._handle.topology_amd
+ bus_id = topo.pcie.bus
+ dev_id = topo.pcie.device
+ fn_id = topo.pcie.function
+ bus_id0 = (bus_id >> 8 ) # not sure if usefull
+ bus_id1 = (bus_id & 0xff)
+ return '{:04x}:{:02x}:{:02x}.{:01x}'.format(bus_id0,bus_id1,dev_id,fn_id)
+ else:
+ return UnknownDeviceAttribute()
+
+
+ def extensions(self):
+ return [ext.strip() for ext in self._handle.extensions.split(' ') if ext.strip() != '']
+ def available(self):
+ return bool(self._handle.available)
+ def compiler_available(self):
+ return bool(self._handle.compiler_available)
+ def host_unified_memory(self):
+ return self._handle.host_unified_memory
+ def opencl_c_version(self):
+ return self._handle.opencl_c_version.strip()
+
+ @opencl_version_atleast(1,1)
+ def native_vector_width_char(self):
+ return self._handle.native_vector_width_char
+ @opencl_version_atleast(1,1)
+ def native_vector_width_short(self):
+ return self._handle.native_vector_width_short
+ @opencl_version_atleast(1,1)
+ def native_vector_width_int(self):
+ return self._handle.native_vector_width_int
+ @opencl_version_atleast(1,1)
+ def native_vector_width_long(self):
+ return self._handle.native_vector_width_long
+ @opencl_version_atleast(1,1)
+ def native_vector_width_float(self):
+ return self._handle.native_vector_width_float
+ @opencl_version_atleast(1,1)
+ def native_vector_width_double(self):
+ return self._handle.native_vector_width_double
+ @opencl_version_atleast(1,1)
+ def native_vector_width_half(self):
+ return self._handle.native_vector_width_half
+
+ @opencl_version_atleast(1,2)
+ def builtin_kernels(self):
+ return self._handle.builtin_kernels
+ @opencl_version_atleast(1,2)
+ def linker_available(self):
+ return bool(self._handle.linker_available)
+ @opencl_version_atleast(1,2)
+ def partition_properties(self):
+ return self._handle.partition_properties
+ @opencl_version_atleast(1,2)
+ def partition_affinity_domain(self):
+ return self._handle.partition_affinity_domain
+ @opencl_version_atleast(1,2)
+ def partition_type(self):
+ return self._handle.partition_type
+
+ @opencl_version_atleast(2,0)
+ def pipe_max_active_reservations(self):
+ return self._handle.pipe_max_active_reservations
+ @opencl_version_atleast(2,0)
+ def pipe_max_packet_size(self):
+ return self._handle.pipe_max_packet_size
+ @opencl_version_atleast(2,0)
+ def queue_on_device_max_size(self):
+ return self._handle.queue_on_device_max_size
+ @opencl_version_atleast(2,0)
+ def queue_on_device_preferred_size(self):
+ return self._handle.queue_on_device_preferred_size
+ @opencl_version_atleast(2,0)
+ def queue_on_host_properties(self):
+ return self._handle.queue_on_host_properties
+ @opencl_version_atleast(2,0)
+ def spir_versions(self):
+ return self._handle.spir_versions
+ @opencl_version_atleast(2,0)
+ def svm_capabilities(self):
+ return self._handle.svm_capabilities
+ @opencl_version_atleast(2,0)
+ def terminate_capability_hkr(self):
+ return self._handle.terminate_capability_hkr
+ @opencl_version_atleast(2,0)
+ def max_global_variable_size(self):
+ return self._handle.max_global_variable_size
+
+ @opencl_version_atleast(2,1)
+ def subgroup_independent_forward_progress(self):
+ return self._handle.subgroup_independent_forward_progress
+
+#DEVICE
+ def name(self):
+ return self._handle.name.strip()
+ def platform_name(self):
+ return self._handle.platform.strip()
+ def type(self):
+ return cl2hysop_device_type(self._handle.type)
+ def vendor(self):
+ return self._handle.vendor.strip()
+ def vendor_id(self):
+ return self._handle.vendor_id
+ def max_clock_frequency(self):
+ return self._handle.max_clock_frequency*1e6
+ def address_bits(self):
+ return self._handle.address_bits
+ def little_endian(self):
+ return bool(self._handle.endian_little)
+ def error_correction_support(self):
+ return bool(self._handle.error_correction_support)
+
+#KERNEL
+ def max_grid_dim(self):
+ return self._handle.max_work_item_dimensions
+ def max_grid_size(self):
+ return UnknownDeviceAttribute()
+ def max_block_dim(self):
+ return self._handle.max_work_item_dimensions
+ def max_block_size(self):
+ return np.asarray(self._handle.max_work_item_sizes)
+ def max_threads_per_block(self):
+ return self._handle.max_work_group_size
+ def simd_lane_size(self):
+ return cl.characterize.get_simd_group_size(self._handle, np.int32)
+
+ def max_constant_args(self):
+ return self._handle.max_constant_args
+ def max_constant_buffer_size(self):
+ return self._handle.max_constant_buffer_size
+
+#MEMORY
+ def global_mem_size(self):
+ return self._handle.global_mem_size
+ def global_mem_cache_size(self):
+ return self._handle.global_mem_cache_size
+ def global_mem_cacheline_size(self):
+ return self._handle.global_mem_cacheline_size
+ def global_mem_cache_type(self):
+ return cl2hysop_cache_type(self._handle.global_mem_cache_type)
+ def max_global_alloc_size(self):
+ return self._handle.max_mem_alloc_size
+
+ def local_mem_size(self):
+ return self._handle.local_mem_size
+ def local_mem_type(self):
+ return cl2hysop_mem_type(self._handle.local_mem_type)
+ def usable_local_mem_size(self):
+ return cl.characterize.usable_local_mem_size(self._handle)
+
+#DEVICE SPLITTING
+ def has_device_partition_support(self):
+ cl_version = self.opencl_version()
+ if cl_version == (1,0) or cl_version == (1,1):
+ return self.has_extension('cl_ext_device_fission')
+ else:
+ return self.max_subdevices()>1
+ def max_subdevices(self):
+ return self._handle.partition_max_sub_devices
+ def partition_device(self, n):
+ assert self.has_device_partition_support()
+ assert n>1
+ assert self.max_subdevices() >= n
+ raise NotImplementedError()
+
+# QUEUES
+ @opencl_version_atleast(2,0,False)
+ def has_queue_priority_support(self):
+ return True
+
+#FP SUPPORT
+ def has_fp16(self):
+ return self.has_extension('cl_khr_fp16')
+ def has_fp32(self):
+ return True
+ def has_fp64(self):
+ return self.has_extension('cl_khr_fp64') or \
+ self.has_extension('cl_amd_fp64')
+ def fp16_config(self):
+ assert self.has_fp16()
+ return cl2hysop_fpconfig(self._handle.half_fp_config)
+ def fp32_config(self):
+ assert self.has_fp32()
+ return cl2hysop_fpconfig(self._handle.single_fp_config)
+ def fp64_config(self):
+ assert self.has_fp64()
+ return cl2hysop_fpconfig(self._handle.double_fp_config)
+
+#IMAGES
+ def has_image_support(self):
+ return bool(self._handle.image_support)
+ def max_image_args(self):
+ assert self.has_image_support()
+ return self._handle.max_read_image_args
+ def max_read_image_args(self):
+ assert self.has_image_support()
+ return self._handle.max_read_image_args
+ def max_write_image_args(self):
+ assert self.has_image_support()
+ return self._handle.max_write_image_args
+ def max_samplers(self):
+ assert self.has_image_support()
+ return self._handle.max_samplers
+
+ def has_1d_image_support(self):
+ return self.has_image_support()
+ def has_2d_image_support(self):
+ return self.has_image_support()
+ def has_3d_image_support(self):
+ return self.has_image_support()
+
+ def has_1d_image_write_support(self):
+ return (self.max_write_image_args()>0)
+ def has_2d_image_write_support(self):
+ return (self.max_write_image_args()>0)
+ def has_3d_image_write_support(self):
+ return (self.max_write_image_args()>0) and \
+ self.has_extension('cl_khr_3d_image_writes')
+
+ @opencl_version_atleast(1,2,False)
+ def has_1d_image_array_support(self):
+ return self.has_image_support()
+ @opencl_version_atleast(1,2,False)
+ def has_2d_image_array_support(self):
+ return self.has_image_support()
+
+ def image_max_array_size(self):
+ assert self.has_1d_image_array_support() or \
+ self.has_2d_image_array_support()
+ return self._handle.image_max_array_size
+
+ def max_1d_image_size(self):
+ assert self.has_1d_image_support()
+ return np.asarray([self._handle.image2d_max_width])
+ def max_1d_image_array_size(self):
+ assert self.has_1d_image_array_support()
+ return np.asarray([
+ self.image_max_array_size(),
+ self._handle.image2d_max_width])
+
+ def max_2d_image_size(self):
+ assert self.has_2d_image_support()
+ return np.asarray([
+ self._handle.image2d_max_height,
+ self._handle.image2d_max_width])
+ def max_2d_image_array_size(self):
+ assert self.has_2d_image_array_support()
+ return np.asarray([
+ self.image_max_array_size(),
+ self._handle.image2d_max_height,
+ self._handle.image2d_max_width])
+
+ def max_3d_image_size(self):
+ assert self.has_3d_image_support()
+ return np.asarray([
+ self._handle.image3d_max_depth,
+ self._handle.image3d_max_height,
+ self._handle.image3d_max_width])
+
+ @opencl_version_atleast(1,2,False)
+ def has_1d_image_from_buffer_support(self):
+ return self.has_image_support()
+
+ def has_2d_image_from_buffer_support(self):
+ if self.opencl_version()[0] >= 2:
+ return self.has_image_support()
+ else:
+ return self.has_extension('cl_khr_image2d_from_buffer')
+
+ def has_3d_image_from_buffer_support(self):
+ return False
+
+ @opencl_version_atleast(2,0,False)
+ def has_2d_image_from_image_support(self):
+ return self.has_image_support()
+
+ def image_max_buffer_size(self):
+ assert self.has_1d_image_from_buffer_support() or \
+ self.has_2d_image_from_buffer_support()
+ return self._handle.max_buffer_size
+ def image_base_address_alignment(self):
+ assert self.has_2d_image_from_buffer_support()
+ return self._handle.image_vase_address_alignment
+ def image_pitch_aligment(self):
+ assert self.has_2d_image_from_buffer_support()
+ return self._handle.image_pitch_alignment
+
+
+
+#ATOMICS
+ def has_global_int32_atomics(self):
+ if self.opencl_version() == (1,0):
+ return self.has_extension('cl_khr_global_int32_base_atomics')
+ else:
+ return True
+ def has_global_int64_atomics(self):
+ return self.has_extension('cl_khr_int64_base_atomics')
+ def has_global_float32_atomics(self):
+ return (self.opencl_version()[0] >= 2)
+ def has_global_float64_atomics(self):
+ return (self.opencl_version()[0] >= 2)
+
+ def has_local_int32_atomics(self):
+ if self.opencl_version() == (1,0):
+ return self.has_extension('cl_khr_local_int32_base_atomics')
+ else:
+ return True
+ def has_local_int64_atomics(self):
+ return self.has_extension('cl_khr_int64_base_atomics')
+ def has_local_float32_atomics(self):
+ return (self.opencl_version()[0] >= 2)
+ def has_local_float64_atomics(self):
+ return (self.opencl_version()[0] >= 2)
+
+ def has_mixed_int32_atomics(self):
+ return False
+ def has_mixed_int64_atomics(self):
+ return False
+ def has_mixed_float32_atomics(self):
+ return False
+ def has_mixed_float64_atomics(self):
+ return False
+
+ def has_int32_hardware_atomic_counters(self):
+ return self.has_extension('cl_ext_atomic_counters_32')
+ def has_int64_hardware_atomic_counters(self):
+ return self.has_extension('cl_ext_atomic_counters_64')
+
+ @opencl_version_atleast(2,0,returned=1)
+ def preferred_platform_atomic_alignment(self):
+ return self._handle.preffered_platform_atomic_alignment
+ @opencl_version_atleast(2,0,returned=1)
+ def preferred_local_atomic_alignment(self):
+ return self._handle.preferred_local_atomic_alignment
+ @opencl_version_atleast(2,0,returned=1)
+ def preferred_global_atomic_alignment(self):
+ return self._handle.preferred_global_atomic_alignment
+
+# PROFILING
+ def has_profiling_support(self):
+ return True
+ def profiling_time_resolution(self):
+ assert self.has_profiling_support()
+ if self._handle.profiling_timer_resolution == 0:
+ return 'unknown'
+ else:
+ return self._handle.profiling_timer_resolution*1e-9
+
+# PRINTF
+ @opencl_version_atleast(1,2,returned=False)
+ def has_printf_support(self):
+ return True
+ def printf_buffer_size(self):
+ assert self.has_printf_support()
+ try:
+ return self._handle.printf_buffer_size
+ except:
+ return UnknownDeviceAttribute()
+
+# VECTORS
+ def preferred_vector_width_char(self):
+ return self._handle.preferred_vector_width_char
+ def preferred_vector_width_short(self):
+ return self._handle.preferred_vector_width_short
+ def preferred_vector_width_int(self):
+ return self._handle.preferred_vector_width_int
+ def preferred_vector_width_long(self):
+ return self._handle.preferred_vector_width_long
+ def preferred_vector_width_half(self):
+ return self._handle.preferred_vector_width_half
+ def preferred_vector_width_float(self):
+ return self._handle.preferred_vector_width_float
+ def preferred_vector_width_double(self):
+ return self._handle.preferred_vector_width_double
+
+# GRAPHIC API INTEROPS
+ def has_gl_sharing(self):
+ return self.has_extension('cl_khr_gl_sharing')
+ def has_gl_event_sharing(self):
+ return self.has_extension('cl_khr_gl_event')
+ def has_gl_msaa_sharing(self):
+ return self.has_extension('cl_khr_gl_msaa_sharing')
+ def has_dx9_sharing(self):
+ return self.has_extension('cl_khr_dx9_media_sharing')
+ def has_dx10_sharing(self):
+ return self.has_extension('cl_khr_d3d10_sharing')
+ def has_dx11_sharing(self):
+ return self.has_extension('cl_khr_d3d11_sharing')
diff --git a/hysop/backend/device/opencl/opencl_discrete.py b/hysop/backend/device/opencl/opencl_discrete.py
new file mode 100644
index 0000000000000000000000000000000000000000..e8763c321f3bff111facfb2360b86137e17a5c2d
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_discrete.py
@@ -0,0 +1,93 @@
+"""Discrete field defined on device (GPU)
+"""
+from hysop import __VERBOSE__
+from hysop.constants import HYSOP_ORDER, HYSOP_REAL, DirectionLabels
+from hysop.fields.discrete import DiscreteField
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher, OpenClKernelListLauncher
+
+from hysop.tools.numpywrappers import npw
+from hysop.backend.device.opencl.opencl_array_backend import OpenClArrayBackend
+
+
+class OpenClDiscreteField(DiscreteField):
+ """GPU Discrete vector field implementation.
+ Allocates OpenCL device memory for the field.
+ """
+ def __init__(self, cl_env, name, is_vector=False, topology=None):
+ """GPU Discrete vector field implementation.
+ Allocates OpenCL device memory for the field.
+
+ Parameters
+ ----------
+
+ queue : OpenCL queue
+ topology : :class:`~hysop.core.mpi.topology.Cartesian`, optional
+ mpi topology and local meshes info
+ is_vector: boolean, optional
+ true if parent field is a vector field, default=False
+ name : string, optional
+ Field name
+ """
+ # init base class
+ super(OpenClDiscreteField, self).__init__(topology, is_vector, name)
+
+ # OpenCL environment
+ self.cl_env = cl_env
+ self.npcl = OpenClArrayBackend(cl_env=cl_env)
+
+ # OpenCL arrays
+ self.gpu_data = [None] * self.nb_components
+
+ # True if device allocations have been done,
+ self.gpu_allocated = False
+
+ # OpenCL Events list modifying this field
+ self.events = []
+
+ # Get the ids of processes involved in the field discretisation.
+ # Default = all, otherwise, get info from input topology if given.
+ if topology is None:
+ from hysop.core.mpi import main_rank
+ self._rank = main_rank
+ else:
+ self._rank = topology.rank
+
+ @classmethod
+ def from_field(cls, cl_env, vfield):
+ if not isinstance(vfield, OpenClDiscreteField):
+ vfield.__class__ = cls
+ OpenClDiscreteField.__init__(
+ vfield, cl_env,
+ vfield.topology, vfield.nb_components > 1, vfield.name)
+
+ def allocate(self):
+ """Device blocking memory allocations."""
+ queue = self.cl_env.default_queue()
+ if not self.gpu_allocated:
+ self.gpu_data = [ self.npcl.asarray(array) for array in self.data ]
+
+ def wait(self):
+ """
+ Waiting for all events completion in the field list.
+ Resets the events list.
+ """
+ if __VERBOSE__:
+ print "{" + str(self._rank) + "}", "Wait events :", self.name
+ for e in self.events:
+ e.wait()
+ self.events = []
+
+
+ def to_device(self):
+ pass
+
+ def to_host(self):
+ pass
+
+ def initialize(self):
+ pass
+ def finalize(self):
+ pass
+ def get_profiling_info(self):
+ pass
diff --git a/hysop/backend/device/opencl/opencl_env.py b/hysop/backend/device/opencl/opencl_env.py
new file mode 100644
index 0000000000000000000000000000000000000000..400bec091037edbcd13c2c4dcd1ab9e351c9c29c
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_env.py
@@ -0,0 +1,578 @@
+
+
+from hysop import vprint
+from hysop import __VERBOSE__, __KERNEL_DEBUG__, __DEFAULT_PLATFORM_ID__, __DEFAULT_DEVICE_ID__
+from hysop.deps import hashlib, np, os
+from hysop.constants import Precision, DeviceType
+from hysop.tools.io_utils import IO
+from hysop.tools.units import bytes2str
+
+from hysop.backend.device.opencl import cl, clTools, __OPENCL_PROFILE__, KERNEL_DUMP_FOLDER
+from hysop.backend.device.opencl.opencl_tools import convert_device_type, convert_precision
+from hysop.backend.device.opencl.opencl_tools import get_platform, get_context, get_device, \
+ create_queue, parse_opencl_file
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+from hysop.backend.device.opencl.opencl_allocator import OpenClImmediateAllocator
+
+
+class OpenClEnvironment(object):
+ """
+ OpenCL environment.
+ """
+ def __init__(self, comm=None,
+ platform_id = __DEFAULT_PLATFORM_ID__,
+ device_id = __DEFAULT_DEVICE_ID__,
+ precision = Precision.DEFAULT,
+ device_type = DeviceType.ALL,
+ gl_sharing=False,
+ name=None,
+ **kwds):
+ """Initialize an OpenCL environment
+
+ Parameters
+ ----------
+ platform_id : int
+ chosen platform id.
+ device_id : int
+ chosen device id.
+ device_type : string
+ chosen device type.
+ precision : int
+ required precision for real data.
+ gl_sharing : bool, optional
+ True to build a context shared between OpenGL and OpenCL.
+ Default=False.
+ comm : mpi communicator, optional
+ Communicator which handles the OpenCL env.
+ Default = :data:`~hysop.core.mpi.main_comm`
+ name : str, optional
+ Name used for memory pool logging.
+ Defaults to device name.
+ kwds: dict
+ Extra arguments for memory pool creation.
+
+ Notes
+ -----
+ See hysop.backend.device.opencl.opencl_tools.get_or_create_opencl_env() to
+ create an OpenClEnvironment that will persist and thus maximize memory pool
+ memory reuse on target device.
+ """
+
+ msg=\
+'''== Creating OpenCL environment ==
+ name: {}
+ platform_id: {}
+ device_id: {}
+ precision: {} ({})
+ device_type: {}
+ gl_sharing: {}
+ communicator size: {}
+'''.format(name, platform_id, device_id, precision, convert_precision(precision).__name__,
+ device_type, gl_sharing, comm.Get_size() if (comm is not None) else '1 (no communicator passed)')
+ vprint(msg)
+
+
+ if precision in [Precision.LONG_DOUBLE, Precision.QUAD, Precision.SAME]:
+ msg='Precision {} is not supported for OpenCl environment.'
+ msg=msg.format(precision)
+ raise ValueError(msg)
+
+ device_type = convert_device_type(device_type)
+ precision = convert_precision(precision)
+ self.precision = precision
+
+ # OpenCL platform
+ platform = get_platform(platform_id)
+ # OpenCL device
+ device = get_device(platform, device_id, device_type)
+ # OpenCL context
+ context = get_context(device, gl_sharing)
+ # OpenCL default queue
+ self._queues = { 'default_queue': create_queue(context) }
+ queue = self.default_queue
+ # OpenCL allocator
+ allocator = OpenClImmediateAllocator(queue=queue,
+ mem_flags=cl.mem_flags.READ_WRITE)
+ # OpenCL memory pool
+ name = name or device.name
+ mempool = allocator.memory_pool(name=name, **kwds)
+
+ self._platform = platform
+ self._device = device
+ self._context = context
+ self._allocator = allocator
+ self._mempool = mempool
+
+ msg=\
+''' -- Platform --
+ *plat id: {}
+ *name: {}
+ *version: {}
+
+ -- Device --
+ *dev id: {}
+ *name: {}
+ *type: {}
+ *version: {}
+ *global mem size: {}
+'''.format(
+platform_id, platform.name, platform.version,
+device_id, device.name, cl.device_type.to_string(device.type),
+device.opencl_c_version, bytes2str(device.global_mem_size))
+ if context.properties:
+ msg+='\n -- Context --'
+ msg+='\n *properties: {}'.format(context.properties)
+ msg+='\n'
+ if queue.properties:
+ msg+='\n -- Queue --'
+ msg+='\n *properties: {}'.format(queue.properties)
+ msg+='\n'
+ vprint(msg)
+
+
+ # Floating point codegeneration mode
+ _kargs = {'device':device, 'context':context, 'platform':platform }
+ if __KERNEL_DEBUG__:
+ _kargs['float_dump_mode'] = 'dec'
+ else:
+ _kargs['float_dump_mode'] = 'hex'
+
+ # Floating point precision
+ if precision == np.float16:
+ _kargs['fbtype'] = 'half'
+ elif precision == np.float32:
+ _kargs['fbtype'] = 'float'
+ elif precision == np.float64:
+ _kargs['fbtype'] = 'double'
+ else:
+ raise ValueError('Unknown floating point precision {}!'.format(precision))
+
+ typegen = OpenClTypeGen(**_kargs)
+
+ self.typegen = typegen
+ self.prec_size = typegen.FLT_BYTES[typegen.fbtype]
+
+ self.default_build_opts = []
+
+ if __OPENCL_PROFILE__ and self.device.vendor.find('NVIDIA') >= 0:
+ self.default_build_opts.append('-cl-nv-verbose')
+
+ self.default_build_opts += self._get_precision_opts()
+
+ self.macros = {}
+
+ # Kernels configuration dictionary
+ if self.device.name == 'Cayman':
+ from hysop.backend.device.opencl.device_config.config_cayman import kernels_config as _kernel_cfg
+ elif self.device.name in ['Tesla K20m', 'Tesla K20Xm']:
+ from hysop.backend.device.opencl.device_config.config_k20m import kernels_config as _kernel_cfg
+ else:
+ vprint('/!\\ Get a default kernels config for {}'.format(self.device.name.strip()))
+ from hysop.backend.device.opencl.device_config.config_default import kernels_config as _kernel_cfg
+ self.kernels_config = _kernel_cfg
+
+ vprint('=================================\n')
+
+ self._comm = comm
+ if (comm is not None):
+ self.is_master = (comm.Get_rank()==0)
+ self.is_multi_device = (comm.Get_size()>1)
+ self._check_comm_devices()
+ else:
+ self.is_master = True
+ self.is_multi_device = False
+
+ def extensions(self):
+ return [ext.strip() for ext in self._device.extensions.split(' ') if ext.strip() != '']
+ def has_extension(self, extension):
+ return (extension in self.extensions())
+ def pci_bus_id(self):
+ """
+ Return the PCI bus id of this device if possible.
+ Format is '0000:bus:device.function' 8+5+3 = 16 bits
+ Example: 0000:01:00.0
+ """
+ if self.has_extension('cl_nv_device_attribute_query'):
+ bus_id = self.device.pci_bus_id_nv
+ slot_id = self.device.pci_slot_id_nv
+ dev_id = (slot_id >> 3)
+ fn_id = (slot_id & 0x07)
+ bus_id0 = (bus_id >> 8 )
+ bus_id1 = (bus_id & 0xff)
+ return '{:04x}:{:02x}:{:02x}.{:01x}'.format(bus_id0,bus_id1,dev_id,fn_id)
+ elif self.has_extension('cl_amd_device_topology'):
+ topo = self.device.topology_amd
+ bus_id = topo.pcie.bus
+ dev_id = topo.pcie.device
+ fn_id = topo.pcie.function
+ bus_id0 = (bus_id >> 8 ) # not sure if usefull
+ bus_id1 = (bus_id & 0xff)
+ return '{:04x}:{:02x}:{:02x}.{:01x}'.format(bus_id0,bus_id1,dev_id,fn_id)
+ else:
+ return 'unknown'
+
+ def device_identifier(self):
+ from hysop.core.mpi import processor_name
+ processor_name = processor_name.lower().strip().replace(' ','_')
+ vendor = self.device.vendor.lower().strip().replace(' ','_')
+ device = self.device.name.lower().strip().replace(' ','_')
+ pci_bus_id = self.pci_bus_id()
+ identifier = '{}__{}__{}__{}'.format(processor_name, vendor, device, pci_bus_id)
+ return identifier
+
+ def _check_comm_devices(self):
+ identifier = self.device_identifier()
+ self.comm.gather((self.rank, identifier) ,root=0)
+
+ def get_platform(self):
+ return self._platform
+ def get_context(self):
+ return self._context
+ def get_device(self):
+ return self._device
+ def get_queues(self):
+ return self._queues
+ def get_allocator(self):
+ return self._allocator
+ def get_memory_pool(self):
+ return self._mempool
+ def get_default_queue(self):
+ return self.queue('default_queue')
+ def get_comm(self):
+ return self._comm
+ def get_rank(self):
+ return self._comm.Get_rank()
+
+ platform = property(get_platform)
+ context = property(get_context)
+ device = property(get_device)
+ queues = property(get_queues)
+ allocator = property(get_allocator)
+ memory_pool = property(get_memory_pool)
+ default_queue = property(get_default_queue)
+ comm = property(get_comm)
+ rank = property(get_rank)
+
+ def queue(self, name):
+ return self._queues[name]
+
+ def create_queue(self, name):
+ """Create OpenCL queue from current context
+ """
+ assert name not in self._queues
+ queue = create_queue(self.context())
+ self._queues[name] = queue
+ return queue
+
+ def _get_precision_opts(self):
+ """
+ Check if device is capable to work with given precision
+ and returns build options considering this precision
+ """
+ opts = []
+
+ # Precision supported
+ fp32_rounding_flag = True
+ if (self.precision == np.float16):
+ if self.device.half_fp_config <= 0:
+ raise ValueError('Half precision is not supported on device.')
+ Prec = 'half'
+ elif (self.precision == np.float32):
+ opts .append('-cl-single-precision-constant')
+ prec = 'single'
+ elif (self.precision == np.float64):
+ if self.device.double_fp_config <=0:
+ raise ValueError('Double Precision is not supported on device')
+ prec = 'double'
+
+
+ vprint(' -- Precision capabilities --')
+ for v in ['DENORM', 'INF_NAN',
+ 'ROUND_TO_NEAREST', 'ROUND_TO_ZERO', 'ROUND_TO_INF',
+ 'FMA', 'CORRECTLY_ROUNDED_DIVIDE_SQRT', 'SOFT_FLOAT']:
+ try:
+ if eval('(self.device.' + prec + '_fp_config &' +
+ ' cl.device_fp_config.' +
+ v + ') == cl.device_fp_config.' + v):
+ vprint(' *{}'.format(v))
+ else:
+ if v is 'CORRECTLY_ROUNDED_DIVIDE_SQRT':
+ fp32_rounding_flag = False
+ except AttributeError as ae:
+ if v is 'CORRECTLY_ROUNDED_DIVIDE_SQRT':
+ fp32_rounding_flag = False
+ vprint(v, 'is not supported in OpenCL C 1.2.\n',
+ ' Exception catched : ', ae)
+
+ if fp32_rounding_flag:
+ opts.append('-cl-fp32-correctly-rounded-divide-sqrt')
+ return opts
+
+
+ def _create_cl_program(self, file_list,
+ vector_width=4,
+ nb_remesh_components=1,
+ build_options='',
+ force_verbose=None, force_debug=None):
+ """Build OpenCL sources
+
+ Parameters
+ ----------
+ files : string or list of strings
+ user defined files names
+ vector_width : int, optional
+ OpenCL vector type width, default=4
+ nb_remesh_components : int, optional
+ number of remeshed components, default=1
+ build_options: string
+ additional OpenCL compile flags
+ force_verbose: bool, optional, default=None
+ force verbose mode
+ force_debug: bool, optional, default=None
+ force debug mode (kernel source dumping and preprocessing)
+
+ Returns OpenCL kernel
+ Parse the sources to handle single and double precision.
+ """
+ VERBOSE = __VERBOSE__ if (force_verbose is None) else force_verbose
+ DEBUG = __KERNEL_DEBUG__ if (force_debug is None) else force_debug
+
+ gpu_src = ""
+ if cl.device_type.to_string(self.device.type) == 'GPU' and \
+ self.precision is DOUBLE_GPU:
+ gpu_src += '#pragma OPENCL EXTENSION cl_khr_fp64: enable \n'
+
+ if isinstance(files, list):
+ file_list = files
+ else:
+ file_list = [files]
+
+ if VERBOSE:
+ print('=== Kernel sources compiling ===')
+ for sd in file_list:
+ print(' - ', sf)
+
+ for sf in file_list:
+ # search and open cl file.
+ try:
+ f = open(sf, 'r')
+ except IOError as ioe:
+ if ioe.errno == 2:
+ # path to cl files inside hysop.gpu package
+ f = open(OPENCL_SRC + sf, 'r')
+ else:
+ raise ioe
+ gpu_src += "".join(
+ self.parse_file(f, vector_width, nb_remesh_components))
+ f.close()
+
+ # print gpu_src
+ if self.macros is not None:
+ for k in self.macros:
+ gpu_src = gpu_src.replace(k, str(self.macros[k]))
+
+ if self.precision is FLOAT_GPU:
+ # Rexexp to add 'f' suffix to float constants
+ # Match 1.2, 1.234, 1.2e3, 1.2E-05
+ float_replace = re.compile(r'(?P<float>\d\.\d+((e|E)-?\d+)?)')
+ gpu_src = float_replace.sub(r'\g<float>f', gpu_src)
+ else:
+ gpu_src = gpu_src.replace('float', 'double')
+
+ # Log final opencl generated code for debug purposes
+ if DEBUG:
+ kernel_name = (file_list[-1].split('/')[-1]).replace('.cl','_parsed')
+ def listformat(L):
+ if isinstance(L,str):
+ L=L.replace('-D ','').split(' ')
+ L=list(L)
+ for empty in ['', ' ']:
+ if empty in L:
+ L.remove(empty)
+ return '\n\t\t'+'\n\t\t'.join(L)
+ dump_prefix = \
+'''
+/*
+Dumped OpenCL Kernel '{}'
+ vector_width: {}
+ nb_remesh_components: {}
+ source_files: {}
+ default_build_opts: {}
+ all build_options: {}
+*/
+'''.format(kernel_name,
+ vector_width,
+ nb_remesh_components,
+ listformat(file_list),
+ listformat(self.default_build_opts),
+ listformat(build_options))
+
+
+ dumped_src = dump_prefix + gpu_src
+
+ dump_folder=IO.default_path()+'/'+KERNEL_DUMP_FOLDER
+ dump_file_prefix=dump_folder+'/'+kernel_name
+ tmp_dump_file=dump_file_prefix+'.c'
+ dump_file=dump_file_prefix+'.cl'
+ if not os.path.exists(dump_folder):
+ os.makedirs(dump_folder)
+ with open(tmp_dump_file, 'w+') as f:
+ f.write(dumped_src)
+
+ try:
+ #try to preprocess sources
+ import subprocess
+ opts = build_options
+ opts = re.sub('-cl-([a-z0-9]+-?)+ ','',opts)
+ cmd = ['gcc',opts,'-E','-c',tmp_dump_file,'-o',dump_file_prefix+'_preprocessed.cl']
+ subprocess.check_call(' '.join(cmd), shell=True);
+ finally:
+ os.rename(tmp_dump_file,dump_file)
+
+ if VERBOSE:
+ msg = 'OpenCL kernel {} source dumped to {}.'.format(kernel_name, dump_file)
+ print(msg)
+
+ # OpenCL program
+ prg = cl.Program(self.context, gpu_src)
+ return prg
+
+
+
+ def build_src(self, files,
+ build_options='',
+ vector_width=4,
+ nb_remesh_components=1):
+ """Build OpenCL sources
+
+ Parameters
+ ----------
+ files : string or list of strings
+ user defined file names
+ build_options : string, optional
+ Compiler options, default=""
+ vector_width : int, optional
+ OpenCL vector type width, default=4
+ nb_remesh_components : int, optional
+ number of remeshed components, default=1
+ force_verbose: bool, optional
+ force verbose mode
+ force_debug: bool, optional
+ force debug mode (kernel dumping)
+
+ Returns OpenCL binaries
+
+ Parse the sources to handle single and double precision.
+ """
+
+ if isinstance(files, list):
+ file_list = files
+ else:
+ file_list = [files]
+
+ vprint("=== Kernel sources compiling ===")
+ for sf in file_list:
+ vprint(" - ", sf)
+
+ # --- create kernel from cl files ---
+ prg = self._create_cl_program(files=file_list,
+ build_options=build_options,
+ vector_width=vector_width,
+ nb_remesh_components=nb_remesh_components,
+ force_verbose=force_verbose,
+ force_debug=force_debug)
+
+ # --- Build kernel ---
+ try:
+ build = prg.build(build_options)
+ except Exception, e:
+ print("Build files : ")
+ for sf in file_list:
+ print(" - ", sf)
+ print("Build options : ", build_options)
+ print("Vectorization : ", vector_width)
+ raise e
+
+ # display post-build info
+ vprint("Build options : ",
+ build.get_build_info(
+ self.device, cl.program_build_info.OPTIONS))
+ vprint("Compiler status : ",
+ build.get_build_info(
+ self.device, cl.program_build_info.STATUS))
+ vprint("Compiler log : ",
+ build.get_build_info(self.device,
+ cl.program_build_info.LOG))
+ vprint("===\n")
+ return build
+
+
+
+ def build_raw_src(self, src, build_options=[],
+ kernel_name=None,
+ force_verbose=None, force_debug=None):
+ """Build raw OpenCL sources
+
+ Parameters
+ ----------
+ src : string
+ OpenCL source code
+ build_options : string
+ Compiler options to use for building
+ Returns OpenCL binaries
+ """
+ assert isinstance(build_options, (str,list,set,tuple))
+ if not isinstance(build_options, str):
+ build_opts = ' '.join(set(self.default_build_opts).update(build_options))
+ else:
+ build_opts = ' '.join(self.default_build_opts) + ' ' + build_options
+ VERBOSE = __VERBOSE__ if (force_verbose is None) else force_verbose
+ DEBUG = __KERNEL_DEBUG__ if (force_debug is None) else force_debug
+
+ gpu_src = src
+
+ src_hash = hashlib.sha1(gpu_src).hexdigest()
+ if (kernel_name is None):
+ kernel_name = src_hash
+ else:
+ kernel_name += '_{}'.format(src_hash[:4])
+
+ if VERBOSE:
+ print('=== Kernel raw source compiling ===')
+ prg = cl.Program(self.context, gpu_src)
+
+
+ dump_folder=IO.default_path()+'/'+KERNEL_DUMP_FOLDER
+ if not os.path.exists(dump_folder):
+ os.makedirs(dump_folder)
+
+ # Build OpenCL program
+ try:
+ build = prg.build(build_opts)
+ except Exception, e:
+ # always dump source when build fails
+ dump_file=dump_folder+'/'+'{}_build_fail.cl'.format(kernel_name)
+ with open(dump_file, 'w+') as f:
+ f.write(gpu_src)
+ vprint('Build options : ', build_opts)
+ vprint('Build Failed: dumped source to {}.'.format(dump_file))
+ raise e
+
+ if VERBOSE:
+ vprint('Build options: ',
+ build.get_build_info(self.device, cl.program_build_info.OPTIONS))
+ vprint('Compiler status: ',
+ build.get_build_info(self.device, cl.program_build_info.STATUS))
+ vprint('Compiler log: ',
+ build.get_build_info(self.device, cl.program_build_info.LOG))
+ if DEBUG:
+ # dump kernel source while in debug mode
+ dump_file=dump_folder+'/'+'{}_dump.cl'.format(kernel_name)
+ print('Dumping kernel src at \'{}\'.'.format(dump_file))
+ with open(dump_file, 'w+') as f:
+ f.write(gpu_src)
+
+ if VERBOSE:
+ print("===\n")
+
+ return build
diff --git a/hysop/backend/device/opencl/opencl_kernel.py b/hysop/backend/device/opencl/opencl_kernel.py
new file mode 100644
index 0000000000000000000000000000000000000000..332c8338b68da4519a9947ba1fe6a1f99ade2bcc
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_kernel.py
@@ -0,0 +1,177 @@
+"""
+"""
+from hysop import __VERBOSE__, __DEBUG__
+from hysop.constants import DirectionLabels
+from hysop.backend.device.opencl import cl, __OPENCL_PROFILE__
+from hysop.tools.decorators import debug
+from hysop.tools.profiler import FProfiler
+
+
+class OpenClKernelListLauncher(object):
+ """OpenCL kernel list launcher.
+
+ Manage launching of OpenCL kernels as a list.
+ """
+ @debug
+ def __init__(self, kernel, queue, gsize, lsize=None):
+ """Create a kernel list launcher.
+
+ Parameters
+ ----------
+
+ kernel : list
+ queue : OpenCL command queue
+ gsize : int
+ OpenCL global size index.
+ lsize : int, optional
+ OpenCL local size index.
+ """
+ ## OpenCL Kernel list
+ self.kernel = kernel
+ #print [k.function_name for k in self.kernel]
+ ## OpenCL command queue
+ self.queue = queue
+ ## OpenCL global size index.
+ self.global_size = gsize
+ ## OpenCL local size index.
+ self.local_size = lsize
+ if __OPENCL_PROFILE__:
+ if len(self.kernel) == 1:
+ try:
+ self.profile = [FProfiler("OpenCL_" + k.function_name)
+ for k in self.kernel]
+ except AttributeError:
+ self.profile = [FProfiler("OpenCL_" + k.__name__)
+ for k in self.kernel]
+ else:
+ self.profile = [
+ FProfiler("OpenCL_" + k.function_name + DirectionLabels[d])
+ for d, k in enumerate(self.kernel)]
+ else:
+ self.profile = []
+
+ @debug
+ def __call__(self, d, *args, **kwargs):
+ """
+ Launch a kernel.
+
+ OpenCL global size and local sizes are not given in
+ args. Class member are used.
+
+ @param d : kernel index in kernel list.
+ @param args : kernel arguments.
+ @return OpenCL Event
+ """
+ return OpenClKernelListLauncher.launch_sizes_in_args(
+ self, d, self.global_size[d], self.local_size[d], *args, **kwargs)
+
+ def _kernel_name(self,d):
+ try:
+ kname = self.kernel[d].function_name
+ except AttributeError:
+ kname = self.kernel[d].__name__
+ return kname
+
+
+ @debug
+ def launch_sizes_in_args(self, d, *args, **kwargs):
+ """
+ Launch a kernel.
+
+ Opencl global and local sizes are given in args.
+
+ @param d : kernel index in kernel list.
+ @param args : kernel arguments.
+ @return OpenCL Event.
+ """
+ if __VERBOSE__:
+ try:
+ print ' ',self.kernel[d].function_name, d, args[0], args[1]
+ # print "\targs: ",args[2:]
+ # print "\tkwargs: ", kwargs
+ except AttributeError:
+ print ' ', self.kernel[d].__name__
+ evt = self.kernel[d](self.queue, *args, **kwargs)
+ if __OPENCL_PROFILE__:
+ evt.wait()
+ self.profile[d] += (evt.profile.end - evt.profile.start) * 1e-9
+ if __VERBOSE__:
+ try:
+ evt.wait()
+ status = evt.command_execution_status
+ if status < 0:
+ msg='\n/!\ Execution error {} while waiting kernel {} to finish /!\\\n'.format(status,self._kernel_name(d))
+ raise RuntimeError(msg)
+ except Exception, e:
+ msg='\n/!\ Unknown execution error while waiting kernel {} to finish /!\\\n'.format(self._kernel_name(d))
+ print msg
+ raise e
+
+
+ return evt
+
+ def function_name(self, d=None):
+ """Prints OpenCL Kernels function names informations"""
+ if d is not None:
+ kernel = self.kernel[d]
+ try:
+ name = kernel.function_name
+ except:
+ name = kernel.__name__
+ return name
+ else:
+ return [self.function_name(d)
+ for d in xrange(len(self.kernel))]
+
+
+class OpenClKernelLauncher(OpenClKernelListLauncher):
+ """
+ OpenCL kernel launcher.
+
+ Manage launching of one OpenCL kernel as a OpenClKernelListLauncher
+ with a list of one kernel.
+ """
+ @debug
+ def __init__(self, kernel, queue, gsize=None, lsize=None):
+ """
+ Create a OpenClKernelLauncher.
+
+ Create a OpenClKernelListLauncher with a list of one kernel.
+
+ @param kernel : kernel.
+ @param queue : OpenCL command queue.
+ @param gsize : OpenCL global size index.
+ @param lsize : OpenCL local size index.
+ """
+ OpenClKernelListLauncher.__init__(self, [kernel], queue, [gsize], [lsize])
+
+ @debug
+ def launch_sizes_in_args(self, *args, **kwargs):
+ """
+ Launch the kernel.
+
+ Opencl global and local sizes are given in args.
+
+ @param args : kernel arguments.
+ @return OpenCL Event.
+ """
+ return OpenClKernelListLauncher.launch_sizes_in_args(
+ self, 0, *args, **kwargs)
+
+ @debug
+ def __call__(self, *args, **kwargs):
+ """
+ Launch the kernel.
+
+ OpenCL global size and local sizes are not given in args.
+ Class member are used.
+
+ @param args : kernel arguments.
+ @return OpenCL Event
+ """
+ return OpenClKernelListLauncher.__call__(self, 0, *args, **kwargs)
+
+ def function_name(self):
+ """Prints OpenCL Kernel function name informations"""
+ res = OpenClKernelListLauncher.function_name(self, 0)
+ return res
diff --git a/hysop/backend/device/opencl/opencl_mempool.py b/hysop/backend/device/opencl/opencl_mempool.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ad21b5fd2ee91225c7709f30401061bf4688ce8
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_mempool.py
@@ -0,0 +1,20 @@
+
+from hysop.tools.types import check_instance
+from hysop.backend.device.opencl.opencl_allocator import OpenClAllocator
+from hysop.backend.device.opencl.opencl_buffer import OpenClPooledBuffer
+from hysop.core.memory.mempool import MemoryPool
+
+class OpenClMemoryPool(MemoryPool,OpenClAllocator):
+
+ def __init__(self, allocator, **kwds):
+ check_instance(allocator, OpenClAllocator)
+ super(OpenClMemoryPool,self).__init__(allocator=allocator, queue=allocator.queue,
+ mem_flags=0, **kwds)
+
+ def _wrap_buffer(self, buf, alloc_sz, size, alignment):
+ return OpenClPooledBuffer(pool=self, buf=buf, alloc_sz=alloc_sz,
+ size=size, alignment=alignment)
+
+ def _allocate_impl(self):
+ msg='This should not have been called.'
+ raise RuntimeError(msg)
diff --git a/hysop/backend/device/opencl/opencl_operator.py b/hysop/backend/device/opencl/opencl_operator.py
new file mode 100644
index 0000000000000000000000000000000000000000..e641c8aa65c55d7571c27a6cdd56d6b002018172
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_operator.py
@@ -0,0 +1,225 @@
+"""Abstract class providing a common interface to all
+discrete operators working on the OpenCl backend.
+
+* :class:`~hysop.backend.device.opencl.opencl_operator.OpenClOperator` is an abstract class
+ used to provide a common interface to all discrete operators working with the
+ opencl backend.
+"""
+from abc import ABCMeta
+
+from hysop.constants import Precision, Backend
+from hysop.tools.decorators import debug
+from hysop.tools.types import check_instance, first_not_None
+from hysop.backend.device.codegen.structs.mesh_info import MeshInfoStruct
+from hysop.backend.device.kernel_config import KernelConfig
+from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+from hysop.core.mpi.topology import Topology
+from hysop.core.mpi.topology_descriptor import TopologyDescriptor
+from hysop.core.graph.computational_operator import ComputationalGraphOperator
+
+class OpenClOperator(ComputationalGraphOperator):
+ """
+ Abstract class for discrete operators working on opencl backend.
+ """
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, cl_env=None, **kwds):
+ """
+ Create the common attributes of all OpenCL operators.
+ See handle_method() and setup().
+
+ All input and output variable topologies should be of kind
+ Backend.OPENCL and share the same OpenClEnvironment.
+
+ Attributes
+ ----------
+ cl_env: OpenClEnvironment
+ OpenCL environment shared accross all topologies.
+
+ Notes
+ -----
+ About method keys:
+ KernelConfig: user build options, defines, precision
+ and autotuner configuration
+ """
+
+ super(OpenClOperator, self).__init__(**kwds)
+
+ cl_env = cl_env or get_or_create_opencl_env(self.mpi_params.comm)
+ check_instance(cl_env, OpenClEnvironment)
+ self.cl_env = cl_env
+ assert cl_env.comm == self.mpi_params.comm
+
+ def supported_backends(self):
+ """
+ return the backends that this operator's topologies can support.
+ """
+ return set([Backend.OPENCL])
+
+ @debug
+ def handle_method(self, method):
+ """
+ Extract device configuration and precision from KernelConfig.
+ """
+ super(OpenClOperator,self).handle_method(method)
+
+ assert KernelConfig in method
+
+ kernel_config = method.pop(KernelConfig)
+ autotuner_config = kernel_config.autotuner_config
+
+ precision = kernel_config.precision
+
+ if precision == Precision.SAME:
+ precision = self.cl_env.precision
+ elif precision in [Precision.LONG_DOUBLE, Precision.QUAD]:
+ msg='Precision {} is not supported for OpenCl environment.'
+ msg=msg.format(precision)
+ raise ValueError(msg)
+ else:
+ from hysop.backend.device.opencl.opencl_tools import convert_precision
+ precision = convert_precision(precision)
+
+ self.precision = precision
+ self.autotuner_config = autotuner_config
+
+ self._initialize_cl_build_options(kernel_config.user_build_options)
+ self._initialize_cl_size_constants(kernel_config.user_size_constants)
+
+ def check(self):
+ super(OpenClOperator, self).check()
+ self._check_cl_env()
+
+ @debug
+ def get_field_requirements(self):
+ """
+ called just after handle_method(), ie self.method has been set.
+ topology requirements are:
+ 1) min and max ghosts for each input and output variables
+ 2) allowed splitting directions for cartesian topologies
+ 3) required local and global transposition state, if any.
+ and more
+ they are stored in self.input_field_requirements and
+ self.output_field_requirements.
+
+ keys are continuous fields and values are of type
+ hysop.fields.field_requirement.discretefieldrequirements
+
+ default is backend.opencl, no min or max ghosts, basis.cartesian and no specific
+ transposition state for each input and output variables.
+ """
+
+ # by default we create OPENCL (gpu) TopologyDescriptors
+ for field, topo_descriptor in self.input_vars.iteritems():
+ topo_descriptor = TopologyDescriptor.build_descriptor(
+ backend=Backend.OPENCL,
+ operator=self,
+ field=field,
+ handle=topo_descriptor,
+ cl_env=self.cl_env)
+ self.input_vars[field] = topo_descriptor
+
+ for field, topo_descriptor in self.output_vars.iteritems():
+ topo_descriptor = TopologyDescriptor.build_descriptor(
+ backend=Backend.OPENCL,
+ operator=self,
+ field=field,
+ handle=topo_descriptor,
+ cl_env=self.cl_env)
+ self.output_vars[field] = topo_descriptor
+
+ return super(OpenClOperator, self).get_field_requirements()
+
+ @debug
+ def discretize(self):
+ """
+ Builds all opencl mesh info used for code generation.
+ """
+ super(OpenClOperator,self).discretize()
+ self._build_cl_mesh_info()
+
+ def build_options(self):
+ """
+ Build and return opencl build option string from
+ self._cl_build_options and self._cl_defines.
+ """
+ build_options = self._cl_build_options
+ defines = set()
+ for define,value in self._cl_defines.iteritems():
+ if (value is not None):
+ define = '{}={}'.format(define.strip(), value.strip())
+ else:
+ define = define.strip()
+ defines.update(define)
+ return ' '.join(build_options) + ' -D'.join(defines)
+
+ @debug
+ def _check_cl_env(self):
+ """
+ Check if all topologies are on OpenCL backend and check that all opencl environments
+ match.
+ """
+ topo = (self.input_vars.values()+self.output_vars.values())[0]
+ assert isinstance(topo, Topology)
+ assert topo.backend.kind == Backend.OPENCL
+ ref_env = self.cl_env
+
+ for topo in set(self.input_vars.values()+self.output_vars.values()):
+ assert isinstance(topo, Topology)
+ assert topo.backend.kind == Backend.OPENCL
+ assert topo.cl_env == ref_env
+
+ @debug
+ def _initialize_cl_build_options(self, user_options):
+ """
+ Initialize OpenCl build options.
+ """
+ check_instance(user_options, list)
+ build_options = set()
+ build_options.update(self.cl_env.default_build_opts)
+ build_options.update(user_options)
+ self._cl_build_options = build_options
+
+ @debug
+ def _initialize_cl_size_constants(self, user_size_constants):
+ """
+ Initialize compile time constants (preprocessor defines) for kernels.
+ """
+ check_instance(user_size_constants, list)
+ cl_defines = {}
+ for usc in user_size_constants:
+ if isinstance(usc, tuple):
+ assert len(usc)==2
+ cl_defines[usc[0]] = usc[1]
+ else:
+ cl_defines[usc[0]] = None
+ self._cl_defines = cl_defines
+
+
+ @debug
+ def _build_cl_mesh_info(self):
+ """
+ Build mesh info structures for each input and output variables.
+ """
+
+ input_mesh_info = {}
+ for field, topo in self.input_vars.iteritems():
+ mesh = topo.mesh
+ input_mesh_info[field] = MeshInfoStruct.create_from_mesh(
+ name='{}_in_field_mesh_info'.format(field.name),
+ cl_env=self.cl_env,
+ mesh=mesh)[1]
+
+ output_mesh_info = {}
+ for field, topo in self.output_vars.iteritems():
+ dfield = field.discrete_fields[topo]
+ mesh = topo.mesh
+ output_mesh_info[field] = MeshInfoStruct.create_from_mesh(
+ name='{}_out_field_mesh_info'.format(field.name),
+ cl_env=self.cl_env,
+ mesh=mesh)[1]
+
+ self.input_mesh_info = input_mesh_info
+ self.output_mesh_info = output_mesh_info
diff --git a/hysop/backend/device/opencl/opencl_platform.py b/hysop/backend/device/opencl/opencl_platform.py
new file mode 100644
index 0000000000000000000000000000000000000000..b528b80bf7fd9320f86f58f857f40a5027967b37
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_platform.py
@@ -0,0 +1,17 @@
+
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.device import OpenClDevice
+from hysop.backend._platform import Platform
+
+class OpenClPlatform(Platform):
+
+ @classmethod
+ def handle_cls(cls):
+ return cl.Platform
+
+ def _discover_devices(self, hardware_topo):
+ for device in self.handle().get_devices():
+ obj = OpenClDevice(platform=self,
+ device_handle=device,
+ hardware_topo=hardware_topo)
+ self._logical_devices.append(obj)
diff --git a/hysop/backend/device/opencl/opencl_printer.py b/hysop/backend/device/opencl/opencl_printer.py
new file mode 100644
index 0000000000000000000000000000000000000000..b635575d6ec6654e20a9a897c7973aa373c8abc3
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_printer.py
@@ -0,0 +1,151 @@
+
+
+import sympy as sm
+from sympy.printing.ccode import CCodePrinter
+from hysop.tools.types import check_instance
+from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+
+# /!\ TODO complete known_functions list with OpenCL builtins
+# - keys are sympy function names (beware to capital letters)
+# - values are either strings or list of tuples (predicate(inputs),string)
+# that corresponds to OpenCL function builtins.
+# Here are some attributes that can be checked in predicates:
+# is_zero
+# is_finite is_integer
+# is_negative is_positive
+# is_rational is_real
+known_functions = {
+ 'Abs': [(lambda x: x.is_integer, 'abs'),'fabs'],
+ 'min': [(lambda x,y: x.is_integer and y.is_integer, 'min'),'fmin'],
+ 'max': [(lambda x,y: x.is_integer and y.is_integer, 'max'),'fmax'],
+ 'sqrt': 'sqrt',
+ 'gamma': 'tgamma',
+
+ 'sin': 'sin',
+ 'cos': 'cos',
+ 'tan': 'tan',
+ 'asin': 'asin',
+ 'acos': 'acos',
+ 'atan': 'atan',
+ 'atan2': 'atan2',
+
+ 'sinh': 'sinh',
+ 'cosh': 'cosh',
+ 'tanh': 'tanh',
+ 'asinh': 'asinh',
+ 'acosh': 'acosh',
+ 'atanh': 'atanh',
+
+ 'exp': 'exp',
+ 'log': 'log',
+ 'erf': 'erf',
+ 'floor': 'floor',
+ 'ceiling': 'ceil',
+}
+
+# OpenCl 2.2 reserved keywords (see opencl documentation)
+reserved_words = [
+
+ # C++14 keywords
+ 'alignas', 'continue', 'friend', 'register', 'true',
+ 'alignof', 'decltype', 'goto', 'reinterpret_cast', 'try',
+ 'asm', 'default', 'if', 'return', 'typedef',
+ 'auto', 'delete', 'inline', 'short', 'typeid',
+ 'bool', 'do', 'int', 'signed', 'typename',
+ 'break', 'double', 'long', 'sizeof', 'union',
+ 'case', 'dynamic_cast', 'mutable', 'static', 'unsigned',
+ 'catch', 'else', 'namespace', 'static_assert', 'using',
+ 'char', 'enum', 'new', 'static_cast', 'virtual',
+ 'char16_t', 'explicit', 'noexcept', 'struct', 'void',
+ 'char32_t', 'export', 'nullptr', 'switch', 'volatile',
+ 'class', 'extern', 'operator', 'template', 'wchar_t',
+ 'const', 'false', 'private', 'this', 'while',
+ 'constexpr', 'float', 'protected', 'thread_local',
+ 'const_cast', 'for', 'public', 'throw'
+ 'override', 'final',
+
+ # OpenCl data types
+ 'uchar', 'ushort', 'uint', 'ulong', 'half',
+ 'bool2', 'char2', 'uchar2', 'short2', 'ushort2', 'int2', 'uint2', 'long2', 'ulong2', 'half2', 'float2', 'double2',
+ 'bool3', 'char3', 'uchar3', 'short3', 'ushort3', 'int3', 'uint3', 'long3', 'ulong3', 'half3', 'float3', 'double3',
+ 'bool4', 'char4', 'uchar4', 'short4', 'ushort4', 'int4', 'uint4', 'long4', 'ulong4', 'half4', 'float4', 'double4',
+ 'bool8', 'char8', 'uchar8', 'short8', 'ushort8', 'int8', 'uint8', 'long8', 'ulong8', 'half8', 'float8', 'double8',
+ 'bool16', 'char16', 'uchar16', 'short16', 'ushort16', 'int16', 'uint16', 'long16', 'ulong16', 'half16', 'float16', 'double16',
+
+ # function qualifiers
+ 'kernel', '__kernel',
+
+ # access qualifiers
+ 'read_only', 'write_only', 'read_write',
+ '__read_only', '__write_only', '__read_write',
+]
+
+
+class OpenClPrinter(CCodePrinter):
+ """
+ A printer to convert sympy expressions to strings of opencl code
+ """
+ printmethod = '_clcode'
+ language = 'OpenCL'
+
+ _default_settings = {
+ 'order': None,
+ 'full_prec': 'auto',
+ 'precision': None,
+ 'user_functions': {},
+ 'human': True,
+ 'contract': True,
+ 'dereference': set(),
+ 'error_on_reserved': True,
+ 'reserved_word_suffix': None,
+ }
+
+ def __init__(self, typegen, symbol2vars=None, **settings):
+ check_instance(typegen, OpenClTypeGen)
+ check_instance(symbol2vars, dict, keys=sm.Symbol, allow_none=True)
+
+ super(OpenClPrinter,self).__init__(settings=settings)
+
+ self.known_functions = dict(known_functions)
+ self.reserved_words = set(reserved_words)
+ self.typegen = typegen
+ self.symbol2vars = symbol2vars
+
+ def dump_symbol(self, expr):
+ symbol2vars = self.symbol2vars
+ if expr in symbol2vars:
+ return self._print(symbol2vars[expr])
+ else:
+ return super(OpenClPrinter,self)._print_Symbol(expr)
+ def dump_rational(self, expr):
+ return self.typegen.dump(expr)
+ def dump_float(self, expr):
+ return self.typegen.dump(expr)
+
+
+ def _print_Symbol(self, expr):
+ return self.dump_symbol(expr)
+ def _print_Rational(self, expr):
+ return self.dump_rational(expr)
+ def _print_PythonRational(self, expr):
+ return self.dump_rational(expr)
+ def _print_Fraction(self, expr):
+ return self.dump_rational(expr)
+ def _print_mpq(self, expr):
+ return self.dump_rational(expr)
+ def _print_Float(self, expr):
+ return self.dump_float(expr)
+
+ # last resort printer (if _print_CLASS is not found)
+ def emptyPrinter(self,expr):
+ return self.typegen.dump(expr)
+
+def dump_clcode(expr, typegen, **kargs):
+ """Return OpenCL representation of the given expression as a string."""
+ p = OpenClPrinter(typegen=typegen, **kargs)
+ s = p.doprint(expr)
+ return s
+
+def print_clcode(expr, typegen, **kargs):
+ """Prints OpenCL representation of the given expression."""
+ print dump_clcode(expr,typegen=typegen,**kargs)
diff --git a/hysop/backend/device/opencl/opencl_tools.py b/hysop/backend/device/opencl/opencl_tools.py
new file mode 100644
index 0000000000000000000000000000000000000000..7bf64a26fe340845864a3c426d7265b14eb21396
--- /dev/null
+++ b/hysop/backend/device/opencl/opencl_tools.py
@@ -0,0 +1,446 @@
+"""Classes and tools used to handle the OpenCL backend.
+
+* :class:`~hysop.gpu.tools.OpenClEnvironment`:
+ object handling opencl platform, device ... info.
+* :func:`~hysop.gpu.tools.get_opengl_shared_environment`:
+ build or get an OpenCL environment with openGL properties.
+* :func:`~hysop.gpu.tools.get_opencl_environment`:
+ build or get an OpenCL environment.
+* :func:`~hysop.gpu.tools.explore`
+ explore system and display platform, devices, memory ... info.
+
+
+
+"""
+from hysop.deps import os, re, itertools, hashlib, pickle, gzip, hashlib
+
+from hysop import __VERBOSE__, __KERNEL_DEBUG__, \
+ __DEFAULT_PLATFORM_ID__, __DEFAULT_DEVICE_ID__
+from hysop import vprint
+
+from hysop.backend.device.opencl import cl, __OPENCL_PROFILE__
+from hysop.constants import np, Precision, DeviceType, HYSOP_REAL
+from hysop.core.mpi import MPI, main_comm
+from hysop.tools.io_utils import IO
+from hysop.tools.decorators import static_vars
+from hysop.tools.types import check_instance
+
+
+class KernelError(Exception):
+ """
+ Custom exception for kernel errors.
+ """
+ def __init__(msg, err):
+ super(KernelError,self).__init__(msg)
+ self.msg = msg
+ self.err = err
+
+ def __str__(self):
+ return self.err + ': ' + self.msg
+
+
+def explore():
+ """Scan system and print OpenCL environment details"""
+ print("OpenCL exploration : ")
+ platforms = cl.get_platforms()
+ platforms_info = ["name", "version", "vendor", "profile", "extensions"]
+ devices_info = ["name",
+ "version",
+ "vendor",
+ "profile",
+ "extensions",
+ "available",
+ "type",
+ "compiler_available",
+ "double_fp_config",
+ "single_fp_config",
+ "global_mem_size",
+ "global_mem_cache_type",
+ "global_mem_cache_size",
+ "global_mem_cacheline_size",
+ "local_mem_size",
+ "local_mem_type",
+ "max_clock_frequency",
+ "max_compute_units",
+ "max_constant_buffer_size",
+ "max_mem_alloc_size",
+ "max_work_group_size",
+ "max_work_item_dimensions",
+ "max_work_item_sizes",
+ "preferred_vector_width_double",
+ "preferred_vector_width_float",
+ "preferred_vector_width_int"]
+ for pltfm in platforms:
+ print("Platform:", pltfm.name)
+ for pltfm_info in platforms_info:
+ print(" |-", pltfm_info, ':', eval("pltfm." + pltfm_info))
+ devices = pltfm.get_devices()
+ for dvc in devices:
+ print(" |- Device:", dvc.name)
+ for dvc_info in devices_info:
+ print(" |-", dvc_info, ':', eval("dvc." + dvc_info))
+
+
+def convert_device_type(device_type):
+ """
+ Converts a hysop device type to corresponding opencl device type.
+ """
+ if (device_type is None):
+ return None
+ check_instance(device_type, DeviceType)
+
+ conversion = {
+ DeviceType.ALL: cl.device_type.ALL,
+ DeviceType.ACCELERATOR: cl.device_type.ACCELERATOR,
+ DeviceType.CPU: cl.device_type.CPU,
+ DeviceType.GPU: cl.device_type.GPU,
+ #DeviceType.CUSTOM: cl.device_type.CUSTOM,
+ DeviceType.DEFAULT: cl.device_type.DEFAULT,
+ }
+
+ if device_type not in conversion.keys():
+ msg = 'Unknown device type {}.'.format(device_type)
+ raise ValueError(msg)
+
+ return conversion[device_type]
+
+def convert_precision(precision):
+ """
+ Converts a hysop precision to corresponding numpy dtype.
+ """
+ if (precision is None):
+ return None
+ check_instance(precision, Precision)
+
+ if precision == Precision.SAME:
+ msg='Cannot convert Precision.SAME to numpy dtype.'
+ raise ValueError(msg)
+ if precision == Precision.QUAD:
+ msg= 'Numpy does not support the 128-bit IEEE quad precision data type.'
+ raise RuntimeError(msg)
+
+ #TODO when long double will be supported check if device has np.float96 or np.float128 long doubles
+ # (ie padded to 3*32bits or 2*64bits)
+ conversion = {
+ Precision.DEFAULT: HYSOP_REAL,
+ Precision.LONG_DOUBLE: np.longdouble,
+ Precision.DOUBLE: np.float64,
+ Precision.FLOAT: np.float32,
+ Precision.HALF: np.float16,
+ }
+
+ if precision not in conversion.keys():
+ msg = 'Unknown precision {}.'.format(precision)
+ raise ValueError(msg)
+
+ return conversion[precision]
+
+
+@static_vars(opencl_environments=dict())
+def get_or_create_opencl_env(comm=None,
+ platform_id = __DEFAULT_PLATFORM_ID__,
+ device_id = __DEFAULT_DEVICE_ID__,
+ device_type = DeviceType.ALL,
+ precision = Precision.DEFAULT,
+ gl_sharing=False,
+ **kargs):
+ """
+ Create or an OpenClEnvironment from given parameters if it does not already exists.
+ All environements are kept alive (cached) in a dictionary local to this
+ function (ie. all opencl operators can share the same OpenClEnvironment).
+ """
+
+ check_instance(platform_id, int)
+ check_instance(device_id, int)
+ check_instance(device_type, DeviceType, allow_none=True)
+ check_instance(precision, Precision)
+ check_instance(gl_sharing, bool)
+
+ key = (platform_id, device_id, device_type, gl_sharing,)
+ if (comm is not None):
+ key += (comm.Get_name(), comm.Get_rank(), comm.Get_size(),)
+
+ opencl_envs = get_or_create_opencl_env.opencl_environments
+ if key in opencl_envs:
+ return opencl_envs[key]
+
+ from hysop.backend.device.opencl.opencl_env import OpenClEnvironment
+ env = OpenClEnvironment(platform_id=platform_id, device_id=device_id,
+ device_type=device_type, gl_sharing=gl_sharing, comm=comm,
+ precision=precision, **kargs)
+
+ opencl_envs[key] = env
+
+ return env
+
+
+def create_queue(ctx, props=None):
+ """
+ Returns OpenCL queue from context
+ ctx : OpenCL context
+ """
+ if (props is not None):
+ queue = cl.CommandQueue(ctx, props)
+ elif __OPENCL_PROFILE__:
+ props = cl.command_queue_properties.PROFILING_ENABLE
+ queue = cl.CommandQueue(ctx, properties=props)
+ else:
+ queue = cl.CommandQueue(ctx)
+
+ return queue
+
+
+
+def get_work_items(resolution, vector_width=1):
+ """Set the optimal work-item number and OpenCL space index.
+
+ Parameters
+ ----------
+ resolution : tuple
+ local mesh resolution
+ vector_width : int
+ OpenCL vector types width
+
+ Returns
+ -------
+ int : work-item number
+ tuple : global space index
+ tuple : local space index
+
+ Use 64 work-items in 3D and 256 in 2D.
+ Use Both the number from device capability
+ The problem must be a multiple of and greater
+ than work-item number * vector_width
+ """
+ # Optimal work item number
+ if len(resolution) == 3:
+ workItemNumber = 64 if min(resolution) >= 64 \
+ else min(resolution)
+ else:
+ workItemNumber = 256 if min(resolution) >= 256 \
+ else min(resolution)
+ # Change work-item regarding problem size
+ if resolution[0] % workItemNumber > 0:
+ if len(resolution) == 3:
+ print("Warning : GPU best performances obtained for",)
+ print("problem sizes multiples of 64")
+ else:
+ print("Warning : GPU best performances obtained for",)
+ print("problem sizes multiples of 256")
+ while resolution[0] % workItemNumber > 0:
+ workItemNumber = workItemNumber / 2
+ # Change work-item regarding vector_width
+ if workItemNumber * vector_width > resolution[0]:
+ if resolution[0] % vector_width > 0:
+ raise ValueError(
+ "Resolution ({0}) must be a multiple of {1}".format(
+ resolution[0], vector_width))
+ workItemNumber = resolution[0] // vector_width
+ if len(resolution) == 3:
+ gwi = (int(workItemNumber),
+ int(resolution[1]), int(resolution[2]))
+ lwi = (int(workItemNumber), 1, 1)
+ else:
+ gwi = (int(workItemNumber),
+ int(resolution[1]))
+ lwi = (int(workItemNumber), 1)
+ return workItemNumber, gwi, lwi
+
+
+
+def get_platform(platform_id):
+ """Returns an OpenCL platform
+ :param platform_id : OpenCL platform id
+
+ """
+ assert (platform_id is not None)
+ try:
+ # OpenCL platform
+ platform = cl.get_platforms()[platform_id]
+ except IndexError:
+ plist = cl.get_platforms()
+ platform = plist[0]
+ msg= ' Incorrect platform_id : {}'.format(platform_id)
+ msg+=' Only {} are available.'.format(len(plist))
+ msg+=' --> getting default platform {}.'.format(platform.name)
+ vprint(msg)
+ return platform
+
+
+
+def get_device(platform, device_id, device_type):
+ """Returns an OpenCL device
+
+ Parameters
+ ----------
+ platform_id : int
+ chosen platform id.
+ device_id : int
+ chosen device id.
+ device_type : string
+ chosen device type.
+
+ Try to use given parameters and in case of fails, use pyopencl context
+ creation function.
+ """
+ display = False
+ try:
+ if device_type != cl.device_type.ALL:
+ device_type_id = cl.device_type.__getattribute__(cl.device_type,
+ str(device_type.upper()))
+ device = platform.get_devices(device_type_id)[device_id]
+ else:
+ device = platform.get_devices()[device_id]
+ except IndexError:
+ msg = '\nIncorrect device_id {}'.format(device_id)
+ msg += '\nThere is only {} devices available.'.format(len(platform.get_devices()))
+ msg += '\nGetting first device of type {}.'.format(device_type)
+ vprint(msg)
+ device = platform.get_devices()[0]
+ except:
+ msg = '\nCould not get a device of type {}'.format(device_type)
+ msg += '\nGetting first device in platform.'
+ vprint(msg)
+ device = platform.get_devices()[0]
+
+ return device
+
+
+
+def get_context(device, gl_sharing):
+ """Returns OpenCL context
+
+ Parameters
+ ----------
+ device : OpenCL device
+ which handles the context.
+ gl_sharing : bool
+ True to build a context shared between OpenGL and OpenCL.
+ Default=False.
+
+ """
+ props = None
+ if gl_sharing:
+ from pyopencl.tools import get_gl_sharing_context_properties
+ import sys
+ if sys.platform == 'darwin':
+ props = get_gl_sharing_context_properties()
+ else:
+ # Some OSs prefer clCreateContextFromType, some prefer
+ # clCreateContext. Try both.
+ props = \
+ [(cl.context_properties.PLATFORM, self.platform)] \
+ + get_gl_sharing_context_properties()
+ ctx = cl.Context(properties=props, devices=[device])
+ else:
+ ctx = cl.Context(devices=[device])
+ return ctx
+
+
+
+
+def parse_opencl_file(f, n=8, nb_remesh_components=1):
+ """Parse a file containing OpenCL sources.
+
+ Parameters
+ ----------
+ f : string
+ file name
+ n : int, optional
+ vector width, default=8
+ nb_remesh_components : int
+ number of remeshed components
+
+ Returns
+ -------
+ string, the parsed sources.
+
+ Notes
+ -----
+ * __N__ is expanded as an integer corresponding to vector width.
+ * __NN__ instruction is duplicated to operate on each vector component:
+
+ * if line ends with ';', the whole instruciton is
+ duplicated.
+ * if line ends with ',' and contains
+ '(float__N__)(', the float element is duplicated
+
+ * Remeshing fields components are expanded as follows :
+ All code between '__RCOMPONENT_S__' and
+ '__RCOMPONENT_E__' flags are duplicated n times with n
+ the number of components to compute. In this duplicated code, the
+ flag '__ID__' is replaced by index of a range of lenght
+ the number of components. A flag '__RCOMPONENT_S__P__'
+ may be used and the duplicated elements are separated with ','
+ (for function parameters expanding).
+
+ Examples with a 4-width vector code::
+
+ float__N__ x; -> float4 x;
+
+ x.s__NN__ = 1.0f; -> x.s0 = 1.0f;
+ x.s1 = 1.0f;
+ x.s2 = 1.0f;
+ x.s3 = 1.0f;
+
+ x = (int__N__)(__NN__, -> x = (int4)(0,
+ ); 1,
+ 2,
+ 3,
+ );
+
+ Examples with a 2 components expansion code::
+
+ __RCOMP_P __global const float* var__ID__,
+ -> __global const float* var0,__global const float* var1,
+
+ __RCOMP_I var__ID__[i] = 0.0;
+ -> var0[i] = 0.0;var1[i] = 0.0;
+
+ aFunction(__RCOMP_P var__ID__, __RCOMP_P other__ID__);
+ -> aFunction(var0, var1, other0, other1);
+
+ """
+ src = ""
+ # replacement for floatN elements
+ vec_floatn = re.compile(r'\(float__N__\)\(')
+ vec_nn = re.compile('__NN__')
+ vec_n = re.compile('__N__')
+ for l in f.readlines():
+ # Expand floatN items
+ if vec_floatn.search(l) and vec_nn.search(l) and \
+ l[-2] == ',':
+ sl = l.split("(float__N__)(")
+ l = sl[0] + "(float" + str(n) + ")("
+ el = sl[1].rsplit(',', 1)[0]
+ for i in xrange(n):
+ l += vec_nn.sub(str(i), el) + ','
+ l = l[:-1] + '\n'
+ # Expand floatN elements access
+ elif vec_nn.search(l) and l[-2] == ';':
+ el = ""
+ for i in xrange(n):
+ el += vec_nn.sub(str(i), l)
+ l = el
+ # Replace vector length
+ src += vec_n.sub(str(n), l)
+
+ # Replacement for remeshed components
+ re_instr = re.compile(r'__RCOMP_I([\w\s\.,()\[\]+*/=-]+;)')
+ # __RCOMP_I ...;
+
+ def repl_instruction(m):
+ return ''.join(
+ [m.group(1).replace('__ID__', str(i))
+ for i in xrange(nb_remesh_components)])
+ # __RCOMP_P ..., ou __RCOMP_P ...)
+ re_param = re.compile(r'__RCOMP_P([\w\s\.\[\]+*/=-]+(?=,|\)))')
+
+ def repl_parameter(m):
+ return ', '.join(
+ [m.group(1).replace('__ID__', str(i))
+ for i in xrange(nb_remesh_components)])
+
+ src = re_instr.sub(repl_instruction, src)
+ src = re_param.sub(repl_parameter, src)
+ return src
diff --git a/hysop/codegen/base/types.py b/hysop/backend/device/opencl/opencl_types.py
similarity index 57%
rename from hysop/codegen/base/types.py
rename to hysop/backend/device/opencl/opencl_types.py
index 2767f38294ec41585f8c5e72cf791313d0045f78..dc1820806759cd8763ef7b9f3085b6afd0287b03 100644
--- a/hysop/codegen/base/types.py
+++ b/hysop/backend/device/opencl/opencl_types.py
@@ -1,18 +1,10 @@
-from gmpy2 import mpq,mpfr,f2q
-import pyopencl as cl
-import numpy as np
-import itertools as it
-import string
+from hysop import __KERNEL_DEBUG__
+from hysop.deps import sm, np, it, string, re
+from hysop.backend.device.opencl import cl, clArray
+from hysop.tools.numerics import MPZ, MPQ, MPFR, F2Q
-from pyopencl import array
-from hysop import __VERBOSE__, __DEBUG__
-
-MPQ = mpq(0).__class__
-MPFR = mpfr(0).__class__
-F2Q = f2q(0).__class__
-
-vsizes = [1,2,3,4,8,16]
+vsizes = [1,2,3,4,8,16]
base_types = ['float','signed','unsigned']
float_base_types = ['half','float','double']
signed_base_types = ['char','short','int','long']
@@ -101,7 +93,9 @@ def float_to_hex_str(f,fbtype):
mant_dig = FLT_MANT_DIG[fbtype]
literal = FLT_LITERAL [fbtype]
- nhex = (mant_dig-1+3)//4 + 2 # +2= leading one or zero and decimal point characters (1.abde... or 0.abcde...)
+
+ nhex = (mant_dig-1+3)//4 + 2
+ # +2= leading one or zero and decimal point characters (1.abde... or 0.abcde...)
sf[0] = ('+' if sf[0] == '' else sf[0])+'0x'
sf[1] = mantissa[:nhex]
@@ -109,28 +103,47 @@ def float_to_hex_str(f,fbtype):
return ''.join(sf)
def float_to_dec_str(f,fbtype):
+
sf = float(f).__repr__().split('.')
- offset = (1 if sf[0][0] in ['-','+'] else 0)
- sf[1] = sf[1][:FLT_DIG[fbtype]-len(sf[0])+offset+1]
- return ('+' if f>0 else '') + '.'.join(sf)+FLT_LITERAL[fbtype]
+ sf += (3-len(sf))*[None]
+
+ buf = sf[1].split('e')
+ mantissa = buf[0]
+ exponent = buf[1] if len(buf)>1 else None
+ dig = FLT_DIG[fbtype]
+ literal = FLT_LITERAL [fbtype]
+
+ sig = len(sf[0].replace('+','').replace('-','').lstrip('0'))
+ sf[0] = ('+' if (sf[0] == '') else sf[0] + '.')
+ sf[1] = mantissa[:dig-sig+1]
+ sf[2] = 'e'+exponent+literal if (exponent is not None) else literal
+ return ''.join(sf)
#pyopencl specific
-cla = cl.array.vec
+vec = clArray.vec
def npmake(dtype):
return lambda scalar: np.array([scalar], dtype=dtype)
-vtype_int = [np.int32, cla.int2, cla.int3, cla.int4, cla.int8, cla.int16 ]
-vtype_uint = [np.uint32, cla.uint2, cla.uint3, cla.uint4, cla.uint8, cla.uint16 ]
-vtype_simple = [np.float32, cla.float2, cla.float3, cla.float4, cla.float8, cla.float16 ]
-vtype_double = [np.float64, cla.double2, cla.double3, cla.double4, cla.double8, cla.double16 ]
-
-make_int = [npmake(np.int32), cla.make_int2, cla.make_int3, cla.make_int4, cla.make_int8, cla.make_int16 ]
-make_uint = [npmake(np.uint32), cla.make_uint2, cla.make_uint3, cla.make_uint4, cla.make_uint8, cla.make_uint16 ]
-make_simple = [npmake(np.float32), cla.make_float2, cla.make_float3, cla.make_float4, cla.make_float8, cla.make_float16 ]
-make_double = [npmake(np.float64), cla.make_double2, cla.make_double3, cla.make_double4, cla.make_double8, cla.make_double16 ]
+vtype_int = [np.int32, vec.int2, vec.int3, vec.int4, vec.int8, vec.int16 ]
+vtype_uint = [np.uint32, vec.uint2, vec.uint3, vec.uint4, vec.uint8, vec.uint16 ]
+vtype_simple = [np.float32, vec.float2, vec.float3, vec.float4, vec.float8, vec.float16 ]
+vtype_double = [np.float64, vec.double2, vec.double3, vec.double4, vec.double8, vec.double16 ]
+
+make_int = [npmake(np.int32), vec.make_int2, vec.make_int3,
+ vec.make_int4, vec.make_int8,
+ vec.make_int16 ]
+make_uint = [npmake(np.uint32), vec.make_uint2, vec.make_uint3,
+ vec.make_uint4, vec.make_uint8,
+ vec.make_uint16 ]
+make_simple = [npmake(np.float32), vec.make_float2, vec.make_float3,
+ vec.make_float4, vec.make_float8,
+ vec.make_float16 ]
+make_double = [npmake(np.float64), vec.make_double2, vec.make_double3,
+ vec.make_double4, vec.make_double8,
+ vec.make_double16 ]
def simplen(n):
if n==1: return np.float32
@@ -157,13 +170,14 @@ _typen = {
'uint' : uintn
}
+
def typen(btype,n):
return _typen[btype](n)
+
def cl_type_to_dtype(cl_type):
btype = basetype(cl_type)
N = components(cl_type)
return typen(btype,N)
-
def make_simplen(vals,n,dval=0):
vals = (vals,) if np.isscalar(vals) else tuple(vals)
@@ -212,32 +226,61 @@ class TypeGen(object):
raise ValueError('Unknown float_dump_mode \'{}\''.format(float_dump_mode))
def dump(self, val):
- if val.__class__ in [list,tuple,dict,np.ndarray]:
+ if isinstance(val, (list,tuple,dict,np.ndarray)):
raise ValueError('Value is not a scalar, got {}.'.format(val))
- if val.__class__ in [float,np.float16,np.float32,np.float64]:
- return self.float_to_str(val, self.fbtype)
- elif val.__class__ in [int,np.int8,np.int16,np.int32,np.int64]:
- sign = ('' if val==0 else ('' if val>0 else '-'))
- sval = str(val)
+ if isinstance(val, (float,np.floating,MPFR)):
+ sval = self.float_to_str(val, self.fbtype)
+ return '({})'.format(sval)
+ elif isinstance(val, (np.integer,int,long,MPZ)):
+ sign = ('' if val==0 else ('+' if val>0 else '-'))
+ sval = str(val)
if val<0:
- sval = sval[1:]
+ sval=sval[1:]
+ if val!=0:
sval = '({}{})'.format(sign,sval)
else:
- sval = '{}{}'.format(sign,sval)
+ sval = '0'
return sval
- elif val.__class__ in [bool,np.bool_]:
+ elif isinstance(val, (bool,np.bool_)):
return 'true' if val else 'false'
- elif isinstance(val, MPQ):
- if __DEBUG__ or __VERBOSE__:
- return '({}.0{f}/{}.0{f})'.format(val.numerator,val.denominator,f=FLT_LITERAL[self.fbtype])
- else:
+ elif isinstance(val, (MPQ, sm.Rational)):
+ if not __KERNEL_DEBUG__:
return self.dump(float(val))
+ if isinstance(val, MPQ):
+ if val.denominator==1:
+ return str(val.numerator)
+ else:
+ return '({}.0{f}/{}.0{f})'.format(val.numerator,val.denominator,
+ f=FLT_LITERAL[self.fbtype])
+ elif isinstance(val, sm.Rational):
+ if val.q == 1:
+ return str(val.p)
+ else:
+ return '({}.0{f}/{}.0{f})'.format(val.p,val.q,
+ f=FLT_LITERAL[self.fbtype])
else:
return val.__str__()
+
+# struct type generation (type size and struct field offsets) is different for each device
+# depending on architecture and compiler implementation and features.
+# /!\ do not use the same opencl typegen instance for two different devices that are
+# not equivalent.
class OpenClTypeGen(TypeGen):
- def __init__(self,fbtype='float', float_dump_mode='dec'):
+ @staticmethod
+ def devicelessTypegen():
+ """
+ Sometimes we do not need structs and code generation is device independent.
+ """
+ return OpenClTypeGen(device=None,context=None,platform=None);
+
+ def __init__(self, device, context, platform,
+ fbtype='float', float_dump_mode='dec'):
super(OpenClTypeGen,self).__init__(fbtype,float_dump_mode)
+
+ self.device = device
+ self.context = context
+ self.platform = platform
self.vsizes = vsizes
self.signed_base_types = signed_base_types
@@ -283,11 +326,12 @@ class OpenClTypeGen(TypeGen):
elif fbtype == 'double':
self.floatn = doublen
self.make_floatn = make_doublen
+ # elif fbtype == 'half':
+ # self.floatn = halfn
+ # self.make_floatn = make_halfn
else:
- self.floatn = None
- self.make_floatn = None
- #else:
- #raise ValueError('Unknown fbtype \'{}\''.format(fbtype))
+ raise ValueError('Unknown fbtype \'{}\''.format(fbtype))
+
def device_has_ftype(self,device):
dev_exts = device.extensions.split(' ')
@@ -296,10 +340,47 @@ class OpenClTypeGen(TypeGen):
def cl_requirements(self):
return [self.float_base_type_require[self.fbtype]];
+ def opencl_version_greater(self, major, minor):
+ (cl_major, cl_minor) = self.opencl_version()
+ if cl_major < major:
+ return False
+ if (cl_major == major) and (cl_minor <= minor):
+ return False
+ return True
+
+ def opencl_version(self):
+ assert (self.device is not None)
+ sversion = self.device.version.strip()
+ _regexp='OpenCL\s+(\d)\.(\d)'
+ regexp=re.compile(_regexp)
+ match=re.match(regexp,sversion)
+ if not match:
+ msg='Could not extract OpenCL version from device returned version \'{}\' '
+ msg += 'and regular expression \'{}\'.'
+ msg=msg.format(sversion,_regexp)
+ raise RuntimeError(msg)
+ major = match.group(1)
+ minor = match.group(2)
+ return (major,minor)
+
def dtype_from_str(self,stype):
stype = stype.replace('ftype', self.fbtype).replace('fbtype',self.fbtype)
btype = basetype(stype)
N = components(stype)
return typen(btype,N)
-
+
+ def dump_expr(self, expr, symbol2vars=None, **printer_settings):
+ """
+ Print sympy expression expr as OpenCL code.
+ Sympy symbols may be replaced using symbol2vars dictionnary.
+ This dumper uses OpenClTypeGen.dump for floats and quotients.
+ See hysop.backend.device.opencl.opencl_printer.OpenClPrinter
+ """
+ from hysop.backend.device.opencl.opencl_printer import OpenClPrinter
+ printer = OpenClPrinter(typegen=self,symbol2vars=symbol2vars,**printer_settings)
+ return printer.doprint(expr)
+
+ def __repr__(self):
+ return '{}_{}_{}_{}'.format(self.platform.name,self.device.name,
+ self.fbtype,self.float_dump_mode)
diff --git a/hysop/gpu/tests/__init__.py b/hysop/backend/device/opencl/operator/__init__.py
similarity index 100%
rename from hysop/gpu/tests/__init__.py
rename to hysop/backend/device/opencl/operator/__init__.py
diff --git a/hysop/mpi/tests/__init__.py b/hysop/backend/device/opencl/operator/directional/__init__.py
similarity index 100%
rename from hysop/mpi/tests/__init__.py
rename to hysop/backend/device/opencl/operator/directional/__init__.py
diff --git a/hysop/backend/device/opencl/operator/directional/advection_dir.py b/hysop/backend/device/opencl/operator/directional/advection_dir.py
new file mode 100644
index 0000000000000000000000000000000000000000..b2a3cebbdfa7e6d596e3fcd7971105612bedc29e
--- /dev/null
+++ b/hysop/backend/device/opencl/operator/directional/advection_dir.py
@@ -0,0 +1,380 @@
+
+from hysop import Field
+from hysop.deps import np
+from hysop.tools.numpywrappers import npw
+from hysop.constants import BoundaryCondition
+from hysop.tools.decorators import debug
+from hysop.tools.types import check_instance
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+from hysop.core.graph.graph import not_initialized, initialized, discretized, ready
+
+from hysop.backend.device.kernel_config import KernelConfig
+from hysop.backend.device.opencl.operator.directional.opencl_directional_operator import OpenClDirectionalOperator
+
+from hysop.tools.types import InstanceOf
+from hysop.numerics.remesh.remesh import RemeshKernel
+from hysop.methods import Interpolation, Precision, TimeIntegrator, Remesh
+
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta, Euler, RK2, RK3, RK4
+from hysop.backend.device.codegen.kernels.directional_advection import \
+ DirectionalAdvectionKernel
+from hysop.backend.device.codegen.kernels.directional_remesh import \
+ DirectionalRemeshKernel
+from hysop.core.memory.memory_request import MemoryRequest
+from hysop.backend.device.codegen.structs.mesh_info import MeshInfoStruct
+
+class OpenClDirectionalAdvection(OpenClDirectionalOperator):
+
+ __default_method = {
+ TimeIntegrator: Euler,
+ Interpolation: Interpolation.LINEAR,
+ Remesh: Remesh.L2_1,
+ KernelConfig: KernelConfig()
+ }
+
+ __available_methods = {
+ TimeIntegrator: InstanceOf(ExplicitRungeKutta),
+ Interpolation: Interpolation.LINEAR,
+ Remesh: (InstanceOf(Remesh), InstanceOf(RemeshKernel)),
+ KernelConfig: InstanceOf(KernelConfig)
+ }
+
+ @debug
+ def __init__(self, velocity,
+ advected_fields, advected_fields_out, variables, velocity_cfl,
+ force_atomics=False, relax_min_particles=False, remesh_criteria_eps=None,
+ **kwds):
+ """
+ Particular advection of field(s) in a given direction,
+ on opencl backend, without remeshing.
+
+ OpenCL kernels are build once per dimension in order to handle
+ directional splitting with resolution non uniform in directions.
+
+ Parameters
+ ----------
+ velocity: Field
+ Continuous velocity field (all components)
+ advected_fields: Field or array like of Fields
+ Instance or list of continuous fields to be advected.
+ advected_fields_out: Field or array like of Field
+ Where input fields are remeshed
+ variables: dict
+ Dictionary of continuous fields as keys and topologies as values.
+ velocity_cfl: float
+ Velocity cfl in given direction.
+ force_atomics: bool
+ If set, only use atomic accumulators for remesh.
+ Default: autotuner will automatically figure out the best strategy
+ between using atomic operations and remeshing multiple particles at
+ a time.
+ relax_min_particles: bool
+ Relax the minimum particles required for correct accumulation of remeshed
+ quantities in cache when not using atomic operations.
+ If this is set to True, the minimum number will be reset to 2.
+ The minimum number of particles to be remeshed at a time, when
+ by a work_item is 2*ceil(scalar_cfl) because of maximum potential
+ particles superposition after the advection step.
+ remesh_criteria_eps: int
+ Minimum number of epsilons (in specified precision) that will trigger
+ remeshing. By default every non zero value is remeshed.
+ kwds:
+ Extra parameters passed to generated directional operators.
+
+ Attributes
+ ----------
+ velocity: Field
+ Continuous velocity field (all components)
+ advected_fields_in: list
+ List of continuous fields to be advected.
+ advected_fields_out: list
+ List of output continuous fields.
+ """
+
+ check_instance(velocity, Field)
+ check_instance(advected_fields, list, values=Field)
+ check_instance(advected_fields_out, list, values=Field)
+ check_instance(variables, dict, keys=Field, values=CartesianDescriptors)
+ assert (len(advected_fields)==len(advected_fields_out))
+
+ input_vars = { velocity: variables[velocity] }
+ output_vars = {}
+
+ is_inplace = True
+
+ for field in advected_fields:
+ input_vars[field] = variables[field]
+ for field in advected_fields_out:
+ output_vars[field] = variables[field]
+ if input_vars[field] == output_vars[field]:
+ assert is_inplace, 'Cannot mix in place and out of place remesh.'
+ else:
+ is_inplace = False
+
+ super(OpenClDirectionalAdvection,self).__init__(input_vars=input_vars,
+ output_vars=output_vars, **kwds)
+
+ self.velocity = velocity
+ self.first_scalar = advected_fields[0]
+ self.advected_fields_in = advected_fields
+ self.advected_fields_out = advected_fields_out
+
+ self.velocity_cfl = velocity_cfl
+ self.is_inplace = is_inplace
+
+ self.force_atomics = force_atomics
+ self.relax_min_particles = relax_min_particles
+ self.remesh_criteria_eps = remesh_criteria_eps
+
+ @debug
+ def handle_method(self,method):
+ super(OpenClDirectionalAdvection,self).handle_method(method)
+
+ remesh_kernel = method.pop(Remesh)
+ if isinstance(remesh_kernel, Remesh):
+ remesh_kernel = RemeshKernel.from_enum(remesh_kernel)
+
+ self.remesh_kernel = remesh_kernel
+ self.interp = method.pop(Interpolation)
+ self.time_integrator = method.pop(TimeIntegrator)
+
+ @debug
+ def get_field_requirements(self):
+ requirements = super(OpenClDirectionalAdvection, self).get_field_requirements()
+
+ direction = self.direction
+ is_inplace = self.is_inplace
+
+ velocity = self.velocity
+ velocity_cfl = self.velocity_cfl
+ v_topo, v_requirements = requirements.get_input_requirement(velocity)
+ v_dx = v_topo.mesh.space_step
+
+ advection_ghosts = int(np.ceil(velocity_cfl * v_dx[direction]))
+ min_velocity_ghosts = npw.integer_zeros(v_dx.shape)
+ min_velocity_ghosts[self.direction] = advection_ghosts
+ v_requirements.min_ghosts = min_velocity_ghosts
+
+ scalar = self.first_scalar
+ s_topo, _ = requirements.get_input_requirement(scalar)
+ s_dx = s_topo.mesh.space_step
+ scalar_cfl = advection_ghosts * (v_dx[direction] / s_dx[direction])
+
+ remesh_ghosts = DirectionalRemeshKernel.scalars_out_cache_ghosts(scalar_cfl,
+ self.remesh_kernel)
+ min_scalar_ghosts = npw.integer_zeros(s_dx.shape)
+ min_scalar_ghosts[self.direction] = remesh_ghosts
+
+ for sfield in self.advected_fields_out:
+ _s_topo, _s_requirements = requirements.get_output_requirement(sfield)
+ _s_dx = _s_topo.mesh.space_step
+ assert (_s_dx == s_dx).all()
+ _s_requirements.min_ghosts = min_scalar_ghosts
+
+ if is_inplace:
+ for sfield in self.advected_fields_in:
+ _s_topo, _s_requirements = requirements.get_input_requirement(sfield)
+ _s_dx = _s_topo.mesh.space_step
+ assert (_s_dx == s_dx).all()
+ _s_requirements.min_ghosts = min_scalar_ghosts
+
+ self.scalar_cfl = scalar_cfl
+
+ return requirements
+
+ @debug
+ def discretize(self):
+ super(OpenClDirectionalAdvection,self).discretize()
+ dvelocity = self.input_discrete_fields[self.velocity]
+ velocity_mesh_info = self.input_mesh_info[self.velocity]
+
+ # field -> discrete_field
+ dadvected_fields_in = {field: self.input_discrete_fields[field]
+ for field in self.advected_fields_in}
+ dadvected_fields_out = {field: self.output_discrete_fields[field]
+ for field in self.advected_fields_out}
+
+ # field -> dfield_mesh_info
+ dfields_in_mesh_info = { field : self.input_mesh_info[field]
+ for field in self.advected_fields_in }
+ dfields_out_mesh_info = { field : self.output_mesh_info[field]
+ for field in self.advected_fields_out }
+
+ fdx = dfields_in_mesh_info.values()[0].vars['dx'][0]
+ xmin = dfields_in_mesh_info.values()[0].vars['global_mesh'].vars['xmin'][0]
+ for mesh_info in dfields_in_mesh_info.values() + dfields_out_mesh_info.values():
+ assert mesh_info.vars['dx'][0] == fdx
+ assert mesh_info.vars['global_mesh'].vars['xmin'][0] == xmin
+
+ self.dvelocity = dvelocity
+ self.dadvected_fields_in = dadvected_fields_in
+ self.dadvected_fields_out = dadvected_fields_out
+
+ self.velocity_mesh_info = velocity_mesh_info
+ self.dfields_in_mesh_info = dfields_in_mesh_info
+ self.dfields_out_mesh_info = dfields_out_mesh_info
+
+ @debug
+ def get_work_properties(self):
+ requests = super(OpenClDirectionalAdvection,self).get_work_properties()
+ precision = self.cl_env.precision
+
+ request, mesh = MemoryRequest.dfield_like(a=self.dadvected_fields_in.values()[0],
+ dtype=precision, ghosts=None, ncomponents=1)
+ requests.push_mem_request('position', request)
+
+ self.position_mesh_info = MeshInfoStruct.create_from_mesh('position_mesh_info',
+ self.cl_env, mesh)[1]
+
+ return requests
+
+ @debug
+ def setup(self, work):
+ super(OpenClDirectionalAdvection,self).setup(work)
+ self._device_buffer_allocations(work)
+ self._collect_kernels()
+
+ def _device_buffer_allocations(self, work):
+ """
+ Allocate OpenCL buffers for advected particle positions and
+ advected fields on particles.
+ """
+ if (work is None):
+ raise ValueError('work is None.')
+
+ self.dposition = work.get_buffer(self, 'position')
+
+ def _collect_kernels(self):
+ # self._collect_advection_kernel()
+ self._collect_remesh_kernel()
+
+ def _collect_advection_kernel(self):
+ velocity = self.dvelocity
+ position = self.dposition
+
+ velocity_mesh_info = self.velocity_mesh_info
+ position_mesh_info = self.position_mesh_info
+
+ cfl = self.cfl
+ precision = self.precision
+ time_integrator = self.time_integrator
+ direction = self.direction
+
+ cl_env = self.cl_env
+ build_options = self.build_options()
+ autotuner_config = self.autotuner_config
+
+ (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistic, cached_bytes) = \
+ DirectionalAdvectionKernel.autotune(
+ direction=direction,
+ cfl=cfl,
+ cl_env=cl_env,
+ precision=precision,
+ velocity=velocity,
+ position=position,
+ velocity_mesh_info = velocity_mesh_info,
+ position_mesh_info = position_mesh_info,
+ time_integrator=time_integrator,
+ build_opts=build_options,
+ autotuner_config=autotuner_config)
+
+
+ def _collect_remesh_kernel(self):
+ position = self.dposition
+
+ position_mesh_info = self.position_mesh_info
+
+ scalar_cfl = self.scalar_cfl
+ precision = self.precision
+ time_integrator = self.time_integrator
+ direction = self.direction
+
+ cl_env = self.cl_env
+ build_options = self.build_options()
+ autotuner_config = self.autotuner_config
+
+ remesh_kernel = self.remesh_kernel
+
+ remesh_criteria_eps = self.remesh_criteria_eps
+ force_atomics = self.force_atomics
+ relax_min_particles = self.relax_min_particles
+
+ position = {self.dposition : self.position_mesh_info}
+ scalars_in = self.dadvected_fields_in
+ scalars_out = self.dadvected_fields_out
+ scalars_in_mesh_info = self.dfields_in_mesh_info
+ scalars_out_mesh_info = self.dfields_out_mesh_info
+ is_inplace = self.is_inplace
+
+ (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistic, cached_bytes) = \
+ DirectionalRemeshKernel.autotune(cl_env=cl_env,
+ precision=precision,
+ direction=direction,
+ scalar_cfl=scalar_cfl,
+ remesh_kernel=remesh_kernel,
+ remesh_criteria_eps=remesh_criteria_eps,
+ position=position,
+ scalars_in=scalars_in,
+ scalars_out=scalars_out,
+ scalars_in_mesh_info=scalars_in_mesh_info,
+ scalars_out_mesh_info=scalars_out_mesh_info,
+ is_inplace=is_inplace,
+ autotuner_config=autotuner_config,
+ build_opts=build_options,
+ force_atomics=force_atomics,
+ relax_min_particles=relax_min_particles,
+ dump_src=False,
+ symbolic_mode=False)
+
+
+ @debug
+ def apply(self,**kargs):
+ super(OpenClDirectionalAdvection,self).apply(**kargs)
+
+ ## Backend methods
+ # ComputationalNode
+ @classmethod
+ def default_method(cls):
+ return cls.__default_method
+
+ @classmethod
+ def available_methods(cls):
+ return cls.__available_methods
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return False
+
+ @classmethod
+ def supports_mpi(cls):
+ return False
+
+ # DirectionalOperator
+ @classmethod
+ def supported_dimensions(cls):
+ return [1,2,3]
+
+ # ComputationalGraphNode
+ @classmethod
+ def supports_multiscale(cls):
+ return False
+ @classmethod
+ def supports_multiple_advected_topologies(cls):
+ return False
+
+
+ def _do_compute(self,simulation,dt_coeff,**kargs):
+ dt = simulation.time_step * dt_coeff
+ self._do_compute_impl(dt=dt,**kargs)
+
+ def _do_compute_monoscale(self, dt):
+ raise NotImplementedError()
+ def _do_compute_multiscale(self, dt):
+ raise NotImplementedError()
+ def _do_compute_monoscale_comm(self, dt):
+ raise NotImplementedError()
+ def _do_compute_multiscale_comm(self, dt):
+ raise NotImplementedError()
+
diff --git a/hysop/backend/device/opencl/operator/directional/opencl_directional_operator.py b/hysop/backend/device/opencl/operator/directional/opencl_directional_operator.py
new file mode 100644
index 0000000000000000000000000000000000000000..c02201edab5610d39cc23a61f61c43f981c5207a
--- /dev/null
+++ b/hysop/backend/device/opencl/operator/directional/opencl_directional_operator.py
@@ -0,0 +1,54 @@
+
+from hysop.tools.decorators import debug
+from hysop.backend.device.opencl.opencl_operator import OpenClOperator
+from hysop.constants import DirectionLabels, transposition_states
+
+class OpenClDirectionalOperator(OpenClOperator):
+
+ @debug
+ def __init__(self,direction,splitting_dim,**kargs):
+ """
+ Directional operator in a given direction, OpenCl version.
+
+ OpenCL kernels are build once per dimension in order to handle
+ directional splitting with resolution non uniform in directions.
+
+ Parameters
+ ----------
+ direction: int
+ Direction of this operator.
+ splitting_dim:
+ The dimension of the splitting.
+
+ Attributes
+ ----------
+ direction: int
+ Direction of this operator.
+ splitting_dim:
+ The dimension of the splitting.
+ """
+ super(OpenClDirectionalOperator,self).__init__(**kargs)
+ dim = splitting_dim
+ self.direction = direction
+ self.splitting_dim = splitting_dim
+
+ if (direction<0) or (direction >= dim):
+ msg = "Bad direction '{}' for dimension {}.".format(direction,dim)
+ raise ValueError(msg)
+
+ @debug
+ def get_field_requirements(self):
+ requirements = super(OpenClDirectionalOperator, self).get_field_requirements()
+
+ direction = self.direction
+ dim = self.splitting_dim
+
+ sdir = DirectionLabels[direction]
+ tstates = transposition_states[dim].all
+ tstates = [ tstate for tstate in tstates if str(tstate)[-1]==sdir ]
+
+ for field,td,req in requirements.iter_input_requirements():
+ req.transposition_states = set(tstates)
+
+ return requirements
+
diff --git a/hysop/backend/device/opencl/operator/directional/stretching_dir.py b/hysop/backend/device/opencl/operator/directional/stretching_dir.py
new file mode 100644
index 0000000000000000000000000000000000000000..cf3f7267e3e43e5e8586ef7bcb252ab87867fad6
--- /dev/null
+++ b/hysop/backend/device/opencl/operator/directional/stretching_dir.py
@@ -0,0 +1,213 @@
+
+from hysop import Field, TopologyDescriptor
+from hysop.deps import np
+from hysop.tools.decorators import debug
+from hysop.tools.types import check_instance
+from hysop.core.graph.graph import not_initialized, initialized, discretized, ready
+from hysop.constants import StretchingFormulation
+
+from hysop.backend.device.kernel_config import KernelConfig
+from hysop.backend.device.opencl.operator.directional.opencl_directional_operator import OpenClDirectionalOperator
+
+from hysop.tools.types import InstanceOf
+from hysop.methods import Interpolation, TimeIntegrator, Remesh, SpaceDiscretization
+
+from hysop.constants import StretchingFormulation
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta, Euler, RK2, RK3, RK4
+
+from hysop.backend.device.codegen.kernels.directional_stretching import \
+ DirectionalStretchingKernel
+
+class OpenClDirectionalStretching(OpenClDirectionalOperator):
+
+ __default_method = {
+ KernelConfig: KernelConfig(),
+ TimeIntegrator: Euler,
+ StretchingFormulation: StretchingFormulation.GRAD_UW,
+ SpaceDiscretization: SpaceDiscretization.FDC4
+ }
+
+ __available_methods = {
+ KernelConfig: InstanceOf(KernelConfig),
+ TimeIntegrator: InstanceOf(ExplicitRungeKutta),
+ StretchingFormulation: InstanceOf(StretchingFormulation),
+ SpaceDiscretization: InstanceOf(SpaceDiscretization)
+ }
+
+ @debug
+ def __init__(self, velocity, vorticity, vorticity_out,
+ variables, **kwds):
+ """
+ Directionnal stretching of vorticity in a given direction
+ on opencl backend.
+
+ OpenCL kernels are build once per dimension in order to handle
+ directional splitting with resolution non uniform in directions.
+
+ Parameters
+ ----------
+ velocity: Field
+ Continuous velocity field (all components)
+ vorticity: Field
+ Input vorticity field.
+ vorticity_out: Field, optional
+ Output vorticity field.
+ variables: dict
+ Dictionary of continuous fields as keys and topologies as values.
+ kwds:
+ Extra parameters passed to generated directional operators.
+
+ Attributes
+ ----------
+ velocity: Field
+ Continuous velocity field (all components)
+ vorticity_in: list
+ Input vorticity field.
+ vorticity_out: list
+ Output vorticity field.
+ """
+
+ check_instance(velocity, Field)
+ check_instance(vorticity, Field)
+ check_instance(vorticity_out, Field)
+ check_instance(variables, dict, keys=Field, values=TopologyDescriptor)
+
+ input_vars = { velocity: variables[velocity], vorticity: variables[vorticity] }
+ output_vars = { vorticity_out: variables[vorticity_out] }
+
+ super(OpenClDirectionalStretching,self).__init__(input_vars=input_vars,
+ output_vars=output_vars, **kwds)
+
+ self.velocity = velocity
+ self.vorticity_in = vorticity
+ self.vorticity_out = vorticity_out
+
+ # point _do_compute_impl function to the right implementation
+ # if self._is_distributed:
+ # if is_multi_scale:
+ # impl = self._do_compute_multiscale_comm
+ # else:
+ # impl = self._do_compute_monoscale_comm
+ # else:
+ # if is_multi_scale:
+ # impl = self._do_compute_multiscale
+ # else:
+ # impl = self._do_compute_monoscale
+ # self._do_compute_impl = impl
+
+ @debug
+ def handle_method(self,method):
+ super(OpenClDirectionalStretching,self).handle_method(method)
+ self.time_integrator = method.pop(TimeIntegrator)
+ self.stretching_formulation = method.pop(StretchingFormulation)
+ self.space_discretization = method.pop(SpaceDiscretization)
+
+ @debug
+ def discretize(self):
+ super(OpenClDirectionalStretching,self).discretize()
+ dvelocity = self.input_discrete_fields[self.velocity]
+ dvorticity_in = self.input_discrete_fields[self.vorticity_in]
+ dvorticity_out = self.output_discrete_fields[self.vorticity_out]
+ assert dvorticity_in.topology == dvorticity_out.topology
+
+ vorticity_mesh_info_in = self.input_mesh_info[self.vorticity_in]
+ vorticity_mesh_info_out = self.output_mesh_info[self.vorticity_out]
+ assert vorticity_mesh_info_in[0] == vorticity_mesh_info_out[0]
+
+ self.dvelocity = dvelocity
+ self.dvorticity_in = dvorticity_in
+ self.dvorticity_out = dvorticity_out
+
+ self.velocity_mesh_info = self.input_mesh_info[self.velocity]
+ self.vorticity_mesh_info = vorticity_mesh_info_in
+
+ @debug
+ def setup(self, work):
+ super(OpenClDirectionalStretching,self).setup(work)
+ self._collect_kernels()
+
+ def _collect_kernels(self):
+ self._collect_stretching_kernel()
+
+ def _collect_stretching_kernel(self):
+
+ velocity = self.dvelocity
+ vorticity_in = self.dvorticity_in
+ vorticity_out = self.dvorticity_out
+
+ velocity_mesh_info = self.velocity_mesh_info[1]
+ vorticity_mesh_info = self.vorticity_mesh_info[1]
+
+ direction = self.direction
+ formulation = self.stretching_formulation
+ discretization = self.space_discretization
+ time_integrator = self.time_integrator
+
+ cl_env = self.cl_env
+ precision = self.precision
+ build_options = self.build_options()
+ autotuner_config = self.autotuner_config
+
+ (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistic, cached_bytes) = \
+ DirectionalStretchingKernel.autotune(
+ cl_env=cl_env,
+ precision=precision,
+ build_options=build_options,
+ autotuner_config=autotuner_config,
+ direction=direction,
+ time_integrator=time_integrator,
+ formulation=formulation,
+ discretization=discretization,
+ velocity=velocity,
+ vorticity_in=vorticity_in,
+ vorticity_out=vorticity_out,
+ velocity_mesh_info=velocity_mesh_info,
+ vorticity_mesh_info=vorticity_mesh_info)
+
+ @debug
+ def apply(self,**kargs):
+ super(OpenClDirectionalStretching,self).apply(**kargs)
+
+ ## Backend methods
+ # ComputationalNode
+ @classmethod
+ def default_method(cls):
+ return cls.__default_method
+
+ @classmethod
+ def available_methods(cls):
+ return cls.__available_methods
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return False
+
+ @classmethod
+ def supports_mpi(cls):
+ return False
+
+ # DirectionalOperator
+ @classmethod
+ def supported_dimensions(cls):
+ return [3]
+
+ # ComputationalGraphNode
+ @classmethod
+ def supports_multiscale(cls):
+ return False
+
+ def _do_compute(self,simulation,dt_coeff,**kargs):
+ dt = simulation.time_step * dt_coeff
+ self._do_compute_impl(dt=dt,**kargs)
+
+ def _do_compute_monoscale(self, dt):
+ raise NotImplementedError()
+ def _do_compute_multiscale(self, dt):
+ raise NotImplementedError()
+ def _do_compute_monoscale_comm(self, dt):
+ raise NotImplementedError()
+ def _do_compute_multiscale_comm(self, dt):
+ raise NotImplementedError()
+
+
diff --git a/hysop/backend/device/opencl/operators.py b/hysop/backend/device/opencl/operators.py
new file mode 100644
index 0000000000000000000000000000000000000000..a36e1a142282c60802bd7b9e57ccaf540d58b8e1
--- /dev/null
+++ b/hysop/backend/device/opencl/operators.py
@@ -0,0 +1,5 @@
+
+from hysop.backend.device.opencl.operator.directional.advection_dir import \
+ OpenClDirectionalAdvection
+from hysop.backend.device.opencl.operator.directional.stretching_dir import \
+ OpenClDirectionalStretching
diff --git a/hysop/numerics/tests/__init__.py b/hysop/backend/device/opencl/tests/__init__.py
similarity index 100%
rename from hysop/numerics/tests/__init__.py
rename to hysop/backend/device/opencl/tests/__init__.py
diff --git a/hysop/backend/discover.py b/hysop/backend/discover.py
new file mode 100644
index 0000000000000000000000000000000000000000..c699c0375fde243730b2c94d0bd45bc4eb975639
--- /dev/null
+++ b/hysop/backend/discover.py
@@ -0,0 +1,16 @@
+
+from hysop import hprint
+from hysop.backend.hardware.pci_ids import PCIIds
+from hysop.backend.hardware.hwinfo import Topology
+
+from hysop.core.mpi import shm_rank, shm_size
+
+# Parse all PCI vendors and device data
+
+hprint('*Detecting hardware and software environment...')
+hprint('*Parsing pci database...')
+pciids = PCIIds()
+
+# Use lstopo xml output (hwinfo) to get local hardware topology
+hprint('*Parsing hardware topology...')
+topology = Topology.parse(pciids)
diff --git a/hysop/operator/tests/__init__.py b/hysop/backend/hardware/__init__.py
similarity index 100%
rename from hysop/operator/tests/__init__.py
rename to hysop/backend/hardware/__init__.py
diff --git a/hysop/backend/hardware/cpu.py b/hysop/backend/hardware/cpu.py
new file mode 100644
index 0000000000000000000000000000000000000000..0082eea9b5467e23acf49247b71133f990251a0c
--- /dev/null
+++ b/hysop/backend/hardware/cpu.py
@@ -0,0 +1,101 @@
+
+from hysop.backend.hardware.hwinfo import TopologyObject
+
+class ProcessingUnit(TopologyObject):
+ """
+ The smallest physical execution unit that hwloc recognizes.
+ For example, there may be multiple PUs on a core (e.g., hardware threads).
+ """
+ def __init__(self, parent, pu):
+ super(ProcessingUnit, self).__init__(parent, pu)
+
+ def _parsed_type(self):
+ return 'PU'
+
+ def _parse_object(self, it):
+ raise ValueError('Unknown object type {}.'.format(_type))
+
+class PhysicalCore(TopologyObject):
+ """
+ A single, physical processing unit which may still contain multiple logical processors,
+ such as hardware threads.
+ """
+ def __init__(self, parent, core):
+ self._processing_units = []
+ super(PhysicalCore,self).__init__(parent, core)
+
+ def processing_units(self):
+ return sorted(self._processing_units, key=lambda x: x.os_index())
+ def processing_units_count(self):
+ return len(self._processing_units)
+
+ def _parsed_type(self):
+ return 'Core'
+
+ def _parse_object(self, it):
+ _type = it.attrib['type']
+ if _type=='PU':
+ obj = ProcessingUnit(self, it)
+ self._processing_units.append(obj)
+ else:
+ raise ValueError('Unknown object type {}.'.format(_type))
+
+ def __str__(self):
+ return 'core {}: {}'.format(self.os_index(), self.cpu_mask())
+
+class CpuPackage(TopologyObject):
+ """
+ A physical package or chip, that goes into a package,
+ it is a grouping of one or more processors.
+ """
+ def __init__(self, parent, package):
+ self._physical_cores = []
+ super(CpuPackage,self).__init__(parent, package)
+
+ def physical_cores(self):
+ return sorted(self._physical_cores, key=lambda x: x.os_index())
+ def family_number(self):
+ return self.attribute('cpu_family_number', 0, int)
+ def stepping(self):
+ return self.attribute('cpu_stepping', 0, int)
+ def vendor(self):
+ return self.attribute('cpu_vendor')
+ def model(self):
+ return self.attribute('cpu_model')
+
+ def physical_cores_count(self):
+ return len(self._physical_cores)
+ def processing_units_count(self):
+ return sum(x.processing_units_count() for x in self._physical_cores)
+
+ def __str__(self):
+ header = '::Package {}::'.format(self.os_index())
+ content = \
+'''
+vendor: {}
+model: {}
+family: {}
+stepping: {}
+phys. cores: {}
+proc. units: {}
+
+cpuset: {}
+'''.format(self.vendor(), self.model(),
+ self.family_number(), self.stepping(),
+ self.physical_cores_count(), self.processing_units_count(),
+ self.cpu_mask())
+ for core in self.physical_cores():
+ content+=str(core)+'\n'
+ return header + self.indent(content)
+
+ def _parsed_type(self):
+ return 'Package'
+
+ def _parse_object(self, it):
+ _type = it.attrib['type']
+ if _type == 'Core':
+ obj = PhysicalCore(self, it)
+ self._physical_cores.append(obj)
+ else:
+ raise ValueError('Unknown object type {}.'.format(_type))
+
diff --git a/hysop/backend/hardware/hardware_backend.py b/hysop/backend/hardware/hardware_backend.py
new file mode 100644
index 0000000000000000000000000000000000000000..8a5bdb88ffdf4d7616e9c2bac49b430f8e552df6
--- /dev/null
+++ b/hysop/backend/hardware/hardware_backend.py
@@ -0,0 +1,20 @@
+
+from hysop.backend.handle import Handle
+
+from abc import ABCMeta, abstractmethod
+
+class HardwareBackend(object):
+
+ __metaclass__ = ABCMeta
+
+ def __init__(self, hardware_topo, **kargs):
+ super(HardwareBackend,self).__init__(**kargs)
+ self._platforms = []
+ self._discover_platforms(hardware_topo)
+
+ def platforms(self):
+ return self._platforms
+
+ @abstractmethod
+ def _discover_platforms(self, hardware_topo):
+ pass
diff --git a/hysop/backend/hardware/hwinfo.py b/hysop/backend/hardware/hwinfo.py
new file mode 100644
index 0000000000000000000000000000000000000000..c14b1ab0981bd46ec21264819c7f7d9606e3b514
--- /dev/null
+++ b/hysop/backend/hardware/hwinfo.py
@@ -0,0 +1,313 @@
+
+from xml.etree import cElementTree as ElementTree
+
+from hysop import vprint
+from hysop.backend import __HAS_OPENCL_BACKEND__
+from hysop.deps import abstractmethod, ABCMeta
+from hysop.deps import subprocess, math, np, it, copy
+
+from hysop.tools.enum import EnumFactory
+from hysop.tools.decorators import requires_cmd
+from hysop.tools.contexts import printoptions
+from hysop.tools.string_utils import prepend, camel2snake
+from hysop.tools.units import bytes2str
+
+from hysop.backend.hardware.pci_ids import PCIIds
+from hysop.core.mpi import is_multihost, interhost_comm, host_rank
+
+class TopologyObject(object):
+ """
+ XML parser base to parse lstopo (hardware info) xml output.
+ See hwloc(7) and lstopo(1) man.
+ """
+
+ __metaclass__ = ABCMeta
+
+ _print_indent = ' '*2
+
+ def __init__(self, parent, element, pciids=None):
+ self.parent = parent
+ self.pciids = pciids or parent.pciids
+
+ if element.tag=='topology':
+ self._attributes = None
+ elif element.tag=='object':
+ self._attributes = self._parse_attributes(element.attrib)
+ else:
+ raise ValueError('Unknown initialization tag {}.'.format(tag))
+
+ for child in element:
+ self._handle_child(child)
+ self._post_init()
+
+ def indent(self, string, extra_spaces=0):
+ return prepend(string, self._print_indent + ' '*extra_spaces)
+
+ def pop_attr(self, name):
+ return self._attributes.pop(name)
+
+ def attributes(self):
+ return self._attributes
+
+ def attribute(self, name, default=None, cast=lambda x:x):
+ if name in self._attributes:
+ return cast(self._attributes[name])
+ else:
+ return default
+
+ def update_attributes(self, attr):
+ self._attributes.update(attr)
+
+ def cpu_set(self):
+ return self.attribute('cpuset')
+
+ def full_cpu_set(self):
+ if self._parsed_type() in ['Machine']:
+ return self.cpu_set()
+ else:
+ return self.parent.full_cpu_set()
+
+ def cpu_mask(self):
+ cpuset = self.cpu_set()
+ mask_length = int(math.ceil(math.log(self.full_cpu_set(),2)))
+ _cpuset = '|{0:0{length}b}|'.format(cpuset, length=mask_length)
+ _cpuset = _cpuset.replace('0','.').replace('1', 'x')
+ _cpuset += ' 0x{0:0{length}x}'.format(cpuset, length=mask_length/4)
+ return _cpuset
+
+ def all_cpu_set(self):
+ return '0x{:x} (complete=0x{:x}, online=0x{:x}, allowed=0x{:x})'.format(
+ self.attribute('cpuset'),
+ self.attribute('complete_cpuset'),
+ self.attribute('online_cpuset'),
+ self.attribute('allowed_cpuset'),
+ )
+
+ def os_index(self):
+ return self.attribute('os_index')
+
+ def print_attributes(self):
+ print '{} attributes:'.format(self.__class__.__name__)
+ for k,v in self.attributes().iteritems():
+ print ' {} -> {}'.format(k,v)
+ print
+
+ def _post_init(self):
+ pass
+
+ def _handle_child(self, child):
+ tag = child.tag
+ attr = child.attrib
+ if tag == 'info':
+ self._parse_info(attr)
+ elif tag == 'object':
+ self._parse_object(child)
+ elif tag == 'distances':
+ self._parse_distances(child)
+ elif tag == 'page_type':
+ self._parse_page_type(attr)
+ else:
+ raise ValueError('Unknown tag {}.'.format(tag))
+
+ @abstractmethod
+ def _parsed_type(self):
+ pass
+
+ @abstractmethod
+ def _parse_object(self, it):
+ pass
+
+ def _parse_attributes(self, attributes):
+ info = {}
+ _type = attributes.pop('type')
+ if not _type == self._parsed_type():
+ msg='Type \'{}\' does not match parsed type \'{}\'.'
+ msg=msg.format(_type, self._parsed_type())
+ raise ValueError(msg)
+ for k,v in attributes.iteritems():
+ if (k.find('cpuset')>=0) or (k.find('nodeset')>=0):
+ info[k] = int(v,16)
+ elif k in ['local_memory','os_index','osdev_type']:
+ info[k] = int(v)
+ elif k in ['pci_link_speed']:
+ info[k] = float(v)
+ elif k in ['bridge_pci', 'bridge_type', 'depth',
+ 'pci_type', 'pci_busid', 'name']:
+ info[k] = v.strip()
+ else:
+ raise ValueError('Unknown key {} with value {}.'.format(k,v))
+ return info
+
+ def _parse_info(self, info):
+ name = info['name']
+ value = info['value']
+ name = camel2snake(name.replace('DMI',''))
+ self._attributes[name] = value
+
+ def _parse_page_type(self, page_type):
+ pass
+
+ def _parse_distances(self, child):
+ distances = child.attrib
+ nbobjs = int(distances['nbobjs'])
+ assert nbobjs>1
+
+ values = []
+ for v in child:
+ assert v.tag == 'latency'
+ val = v.attrib['value']
+ values.append(val)
+
+ assert len(values) == nbobjs*nbobjs
+ self._attributes['distances'] = np.reshape(np.asarray(values, dtype=np.float32),(nbobjs,nbobjs,))
+
+
+class HostStatistics(object):
+ def __init__(self, topo=None):
+ self.hosts = 0
+ self.numa_nodes=[]
+ self.memory_per_node=[]
+ self.packages=[]
+ self.physical_cores=[]
+ self.processing_units=[]
+ self.has_opencl=[]
+ self.has_cuda=[]
+ if (topo is not None):
+ machine = topo.machine()
+ self.hosts+=1
+ self.numa_nodes.append(machine.numa_nodes_count())
+ for node in machine.numa_nodes():
+ self.memory_per_node.append(node.local_memory())
+ self.packages.append(node.cpu_packages_count())
+ self.physical_cores.append(node.physical_cores_count())
+ self.processing_units.append(node.processing_units_count())
+ self.has_opencl.append(topo.has_opencl())
+ self.has_cuda.append(topo.has_cuda())
+
+ def copy(self):
+ return copy.deepcopy(self)
+
+ def __add__(self, other):
+ stats = self.copy()
+ stats.hosts += other.hosts
+ stats.numa_nodes += other.numa_nodes
+ stats.memory_per_node += other.memory_per_node
+ stats.packages += other.packages
+ stats.physical_cores += other.physical_cores
+ stats.processing_units += other.processing_units
+ stats.has_opencl += other.has_opencl
+ stats.has_cuda += other.has_cuda
+ return stats
+
+ def minmax(self, values, op=lambda x: x, dtype=np.int32):
+ return 'mean={}, min={}, max={}'.format(op(np.mean(values).astype(dtype)),
+ op(np.min(values).astype(dtype)),
+ op(np.max(values).astype(dtype)))
+ def pct(self, values):
+ return '{}%'.format(np.sum(values)*100.0/len(values))
+
+ def __str__(self):
+ msg=\
+'''
+Cluster statistics:
+ hosts: {}
+ numa nodes: {}
+ memory per node: {}
+ packages: {}
+ physical cores: {}
+ processing units: {}
+ opencl support: {}
+ cuda support: {}
+'''.format(
+self.hosts,
+self.minmax(self.numa_nodes),
+self.minmax(self.memory_per_node, op=bytes2str, dtype=np.float32),
+self.minmax(self.packages),
+self.minmax(self.physical_cores),
+self.minmax(self.processing_units),
+self.pct(self.has_opencl),
+self.pct(self.has_cuda))
+ return msg
+
+
+class Topology(TopologyObject):
+
+ @classmethod
+ @requires_cmd('lstopo')
+ def parse(cls, pciids = PCIIds()):
+ topology = subprocess.check_output(['lstopo', '-l', '-v', '--no-caches', '--cpuset', '--of', 'xml'])
+ topology = ElementTree.fromstring(topology)
+ return Topology(parent=None, topo=topology, pciids=pciids)
+
+ def __init__(self, parent, topo, pciids):
+ self._machine = None
+ self._opencl_backend = None
+ self._cuda_backend = None
+ self._stats = None
+ super(Topology,self).__init__(parent, topo, pciids)
+
+
+ def _post_init(self):
+
+ vprint('*Looking for logical devices...')
+ self._find_logical_devices()
+
+ vprint('*Getting distant nodes topology...')
+ self._get_distant_topology()
+
+ vprint('*Dumping everything...\n\n{}\n{}'.format(self.machine(),self._backend_report()))
+ if is_multihost:
+ vprint(self.cluster_statistics())
+
+ def _backend_report(self):
+ return 'Backends: None'
+
+ def machine(self):
+ return self._machine
+
+ def host_stats(self):
+ return HostStatistics(self)
+ def has_opencl(self):
+ return (self._opencl_backend is not None)
+ def has_cuda(self):
+ return (self._cuda_backend is not None)
+
+ def cluster_statistics(self):
+ return self._stats
+
+ def _parsed_type(self):
+ return 'Machine'
+
+ def _parse_object(self, it):
+ from hysop.backend.hardware.machine import Machine
+ _type = it.attrib['type']
+ if _type=='Machine':
+ assert (self._machine is None)
+ self._machine = Machine(self,it)
+ else:
+ raise ValueError('Unknown object type {} obtained during Topology parsing.'.format(_type))
+
+ def _find_logical_devices(self):
+ """
+ Look for logical devices exposed by various backends
+ and bind them to physical devices
+ """
+ if host_rank==0:
+ if __HAS_OPENCL_BACKEND__:
+ from hysop.backend.device.opencl.backend import OpenClArrayBackend
+ self._opencl_backend = OpenClArrayBackend(self.machine())
+ else:
+ self._opencl_backend = None
+
+ def _get_distant_topology(self):
+ # if not is_multihost:
+ # return
+ if host_rank==0:
+ self._stats = interhost_comm.allreduce(self.host_stats())
+
+
+if __name__ == '__main__':
+ pciids = PCIIds()
+ topo = Topology.parse(pciids)
+ machine = topo.machine()
+ print machine.to_string(expand_pci_tree=True)
diff --git a/hysop/backend/hardware/machine.py b/hysop/backend/hardware/machine.py
new file mode 100644
index 0000000000000000000000000000000000000000..9d8f438c3095a3ff3882b95ee1d94afe560afed4
--- /dev/null
+++ b/hysop/backend/hardware/machine.py
@@ -0,0 +1,285 @@
+
+from hysop.deps import platform
+from hysop.constants import System
+from hysop.deps import it, math
+from hysop.tools.units import bytes2str
+from hysop.backend.hardware.hwinfo import TopologyObject
+from hysop.backend.hardware.cpu import CpuPackage
+from hysop.backend.hardware.pci import PciBridge
+
+class NumaNode(TopologyObject):
+ """
+ A set of processors around memory which the processors can directly access.
+ """
+ def __init__(self, parent, node, package=None, bridge=None):
+ if (node is not None):
+ self._packages = []
+ self._bridges = []
+ super(NumaNode, self).__init__(parent, node)
+ else:
+ assert (package is not None)
+ self._attributes = {}
+ self._packages = [package]
+ self._bridges = [bridge]
+ self.parent = parent
+
+ def packages(self):
+ return sorted(self._packages, key=lambda x: x.os_index())
+ def bridges(self):
+ return sorted(self._bridges, key=lambda x: x.os_index())
+
+ def local_memory(self):
+ return self.attribute('local_memory')
+ def node_set(self):
+ return self.attribute('nodeset')
+ def node_mask(self):
+ nodeset = self.node_set()
+ mask_length = int(math.ceil(math.log(self.parent.full_node_set(),2)))
+ _nodeset = '|{0:0{length}b}|'.format(nodeset, length=mask_length)
+ _nodeset = _nodeset.replace('0','.').replace('1', 'x')
+ _nodeset += ' 0x{0:0{length}x}'.format(nodeset, length=mask_length/4)
+ return _nodeset
+
+
+ def cpu_packages_count(self):
+ return len(self._packages)
+ def physical_cores_count(self):
+ return sum(x.physical_cores_count() for x in self._packages)
+ def processing_units_count(self):
+ return sum(x.processing_units_count() for x in self._packages)
+
+ def pci_bridge_count(self):
+ return len(self._bridges)
+ def pci_devices_count(self):
+ return sum(x.pci_device_count() for x in self._bridges)
+
+ def cpu_packages(self):
+ return self.packages()
+ def pci_devices(self):
+ return it.chain.from_iterable([x.leaf_pci_devices() for x in self.bridges()])
+
+ def __str__(self):
+ return self.to_string()
+
+ def to_string(self, expand_pci_tree=True):
+ header = '-- NUMA Node {} --'.format(self.os_index())
+ content =\
+'''
+nodeset: {}
+cpuset: {}
+node memory: {}
+
+'''.format(self.node_mask(), self.cpu_mask(),
+ bytes2str(self.local_memory(), decimal=True))
+ for package in self.packages():
+ content += str(package)
+ if self.pci_bridge_count()>0:
+ content+='\n::PCI bus topology::\n'
+ for bridge in self.bridges():
+ content += self.indent(bridge.to_string(expand_pci_tree=expand_pci_tree))
+ return header + self.indent(content)
+
+ def _parsed_type(self):
+ return 'NUMANode'
+
+ def _parse_object(self, it):
+ _type = it.attrib['type']
+ if _type == 'Package':
+ obj = CpuPackage(self, it)
+ self._packages.append(obj)
+ elif _type == 'Bridge':
+ obj = PciBridge(self, it)
+ self._bridges.append(obj)
+ else:
+ raise ValueError('Unknown object type {}.'.format(_type))
+
+ @classmethod
+ def from_package(cls, parent, package, bridge, attributes):
+ """
+ Build a virtual NUMA node when there is only one socket.
+ """
+ node = NumaNode(node=None, parent=parent, package=package, bridge=bridge)
+ node.update_attributes(attributes)
+ return node
+
+
+
+class Machine(TopologyObject):
+ """
+ Class describing a physical machine (a set of processors and memory).
+ """
+
+ def __init__(self, parent, machine):
+ if platform.system() == 'Windows':
+ system = System.WINDOWS
+ elif platform.system() == 'Darwin':
+ system = System.DARWIN
+ elif platform.system() == 'Linux':
+ system = System.LINUX
+ else:
+ msg='Unknown platform system {}.'.format(platform.system())
+ raise ValueError(msg)
+
+ self._system = system
+ self._bridge, self._package = None, None
+ self._numa_nodes = []
+
+ super(Machine,self).__init__(parent, machine)
+
+ def _post_init(self):
+ if self._package:
+ self._attributes['nodeset'] = 1
+ attr = {'local_memory': self.pop_attr('local_memory'),
+ 'os_index': self.pop_attr('os_index'),
+ 'cpuset': self.cpu_set(),
+ 'nodeset': 1}
+ self._numa_nodes = [ NumaNode.from_package(parent=self, attributes=attr,
+ package=self._package, bridge=self._bridge) ]
+ elif self._numa_nodes:
+ pass
+ else:
+ raise RuntimeError('Something went wrong during parsing.')
+
+ def _parsed_type(self):
+ return 'Machine'
+
+ def _handle_child(self, child):
+ if child.tag=='page_type':
+ self._parse_page_type(child)
+ else:
+ super(Machine,self)._handle_child(child)
+
+ def _parse_page_type(self, it):
+ pass
+
+ def _parse_object(self, it):
+ _type = it.attrib['type']
+ if _type=='Package':
+ assert (self._package is None) and (not self._numa_nodes)
+ self._package = CpuPackage(self,it)
+ elif _type=='Bridge':
+ assert (self._bridge is None) and (not self._numa_nodes)
+ self._bridge = PciBridge(self,it)
+ elif _type=='NUMANode':
+ assert (self._package is None) and (self._bridge is None)
+ self._numa_nodes.append(NumaNode(self,it))
+ else:
+ raise ValueError('Unknown object type {} obtained during Machine parsing.'.format(_type))
+
+
+ ## Machine information
+ def system(self):
+ return self._system
+
+ def numa_nodes(self):
+ return sorted(self._numa_nodes, key=lambda x: x.os_index())
+ def numa_nodes_count(self):
+ return len(self._numa_nodes)
+
+ def distances(self):
+ if 'distances' in self._attributes:
+ return self.attribute('distances')
+ else:
+ return None
+
+ def node_set(self):
+ return self.attribute('nodeset')
+ def full_node_set(self):
+ return self.node_set()
+
+ def total_memory(self):
+ return sum(x.local_memory() for x in self._numa_nodes)
+ def cpu_packages_count(self):
+ return sum(x.cpu_packages_count() for x in self._numa_nodes)
+ def physical_cores_count(self):
+ return sum(x.physical_cores_count() for x in self._numa_nodes)
+ def processing_units_count(self):
+ return sum(x.processing_units_count() for x in self._numa_nodes)
+
+ def pci_devices_count(self):
+ return sum(x.pci_device_count() for x in self._numa_nodes)
+
+ def cpu_packages(self):
+ return [cpu for cpu in it.chain.from_iterable([x.cpu_packages() for x in self.numa_nodes()])]
+ def pci_devices(self, vendor_id=None, device_id=None):
+ devices = it.chain.from_iterable([x.pci_devices() for x in self.numa_nodes()])
+ if (vendor_id is not None):
+ devices = it.ifilter(lambda x: x.pci_system_vendor_id() == vendor_id, devices)
+ if (device_id is not None):
+ devices = it.ifilter(lambda x: x.pci_system_device_id() == device_id, devices)
+ return [dev for dev in devices]
+
+ def architecture(self):
+ return self.attribute('architecture')
+
+ def backend(self):
+ return '{} {}'.format(
+ self.attribute('backend'),
+ self.attribute('architecture'))
+
+ def os(self):
+ return '{} {} ({})'.format(
+ self.attribute('os_name'),
+ self.attribute('os_release'),
+ self.attribute('os_version'))
+
+ def bios(self):
+ return '{} v.{} ({})'.format(
+ self.attribute('bios_vendor'),
+ self.attribute('bios_version'),
+ self.attribute('bios_date'))
+
+ def board(self):
+ return '{} {} {}'.format(
+ self.attribute('board_vendor'),
+ self.attribute('board_name'),
+ self.attribute('board_version'))
+
+
+ def hwinfo_version(self):
+ return '{} (hwinfo) v.{}'.format(
+ self.attribute('process_name'),
+ self.attribute('hwloc_version'))
+
+ def __str__(self):
+ return self.to_string()
+
+ def to_string(self, expand_pci_tree=True):
+ header = '== Physical Hardware Report =='
+ content = \
+'''
+bios: {}
+board: {}
+backend: {}
+OS: {}
+nodeset: 0x{:x}
+cpuset: 0x{:x}
+
+NUMA nodes: {}
+CPU packages: {}
+physical cores: {}
+processing units: {}
+physical memory: {}
+'''.format(self.bios(), self.board(), self.backend(), self.os(),
+ self.node_set(), self.cpu_set(),
+ self.numa_nodes_count(),
+ self.cpu_packages_count(),
+ self.physical_cores_count(),
+ self.processing_units_count(),
+ bytes2str(self.total_memory(),decimal=True))
+
+ for node in self.numa_nodes():
+ content += '\n'+node.to_string(expand_pci_tree=expand_pci_tree)+'\n'
+
+ distances = self.distances()
+ if (distances is not None):
+ content += '\nRelative latency matrix between NUMA nodes:'
+ with printoptions(precision=2):
+ content += '\n{}'.format(distances)
+ content += '\n'
+
+ content += '\nHardware info gathered with {}'.format(self.hwinfo_version())
+
+ footer = '\n===================='
+
+ return header + self.indent(content) + footer
diff --git a/hysop/backend/hardware/pci.py b/hysop/backend/hardware/pci.py
new file mode 100644
index 0000000000000000000000000000000000000000..3969e79e5e5271137d66102e212e7937b77a5d19
--- /dev/null
+++ b/hysop/backend/hardware/pci.py
@@ -0,0 +1,373 @@
+from hysop.deps import re, it
+from hysop.tools.enum import EnumFactory
+from hysop.tools.string_utils import prepend
+from hysop.backend.hardware.hwinfo import TopologyObject
+
+OperatingSystemDeviceType = EnumFactory.create('OperatingSystemDeviceType', {
+ 'BLOCK_DEVICE': 0x0, #Operating system block device.
+ #For instance "sda" on Linux.
+
+ 'GPU_DEVICE': 0x1, #Operating system GPU device.
+ #For instance ":0.0" for a GL display, "card0" for a Linux DRM dev.
+
+ 'NETWORK_DEVICE': 0x2, #Operating system network device.
+ #For instance the "eth0" interface on Linux.
+
+ 'OPENFABRICS_DEVICE': 0x3, #Operating system openfabrics device.
+ #For instance the "mlx4_0" InfiniBand HCA device on Linux.
+
+ 'DMA_DEVICE': 0x4, #Operating system dma engine device.
+ #For instance the "dma0chan0" DMA channel on Linux.
+
+ 'COPROCESSOR_DEVICE': 0x5 #Operating system co-processor device.
+ #For instance "mic0" for a Xeon Phi (MIC) on Linux,
+ # "opencl0d0" for a OpenCL device, "cuda0" for a CUDA device.
+})
+"""
+Type of an Operating System device (pci device function).
+See hwloc documentation on type 'hwloc_obj_osdev_type_e'.
+"""
+
+
+class OperatingSystemDevice(TopologyObject):
+ def __init__(self, parent, device):
+ super(OperatingSystemDevice,self).__init__(parent, device)
+
+ def _parsed_type(self):
+ return 'OSDev'
+ def _parse_object(self, it):
+ raise ValueError('Unknown object type {}.'.format(_type))
+
+ def name(self):
+ return self.attribute('name')
+ def osdev_type(self):
+ return self.attribute('osdev_type', 0, int)
+
+ # type 0 specific
+ def type(self):
+ assert self.osdev_type()==0
+ if 'type' in self._attributes:
+ return self.attribute('type')
+ else:
+ return ''
+ def model(self):
+ assert self.osdev_type()==0
+ if 'model' in self._attributes:
+ return self.attribute('model')
+ else:
+ return ''
+ def serial_number(self):
+ assert self.osdev_type()==0
+ return self.attribute('serial_number')
+ def linux_device_id(self):
+ assert self.osdev_type()==0
+ return self.attribute('linux_device_id')
+
+ # type 2 specific
+ def address(self):
+ assert self.osdev_type()==2
+ return self.attribute('address')
+
+ # type 6 specific
+ def backend(self):
+ assert self.osdev_type()==5
+ return self.attribute('backend')
+
+ def backend_info(self):
+ assert self.osdev_type()==5
+ if self.backend()=='CUDA':
+ self.print_attributes()
+ multi_processors = self.attribute('cuda_multi_processors', 0, int)
+ cores_per_mp = self.attribute('cuda_cores_per_mp', 0, int)
+ global_mem = self.attribute('cuda_global_memory_size', (0,)),
+ shared_mem_per_mp = self.attribute('cuda_shared_memory_size_per_mp', (0,)),
+ l2_cache_size = self.attribute('cudal2_cache_size',(0,)),
+ return {
+ 'multi_processors': multi_processors,
+ 'cores_per_mp': cores_per_mp,
+ 'cores': cores_per_mp*multi_processors,
+ 'global_memory_size': ', '.join(tuple(bytes2str(int(mem)*1024*1024/1000) for mem in global_mem)),
+ 'shared_memory_size_per_mp': ', '.join(tuple(bytes2str(int(mem)*1000) for mem in shared_mem_per_mp)),
+ 'l2_cache_size': ', '.join(tuple(bytes2str(int(mem)*1000) for mem in l2_cache_size)),
+ }
+ else:
+ return None
+
+
+ def __str__(self):
+ _type = self.osdev_type()
+ osdev_type = OperatingSystemDeviceType[_type]
+ if (osdev_type == OperatingSystemDeviceType.BLOCK_DEVICE):
+ return 'block_device: {} {} /dev/{}'.format(self.type(), self.model(), self.name())
+ elif (osdev_type == OperatingSystemDeviceType.GPU_DEVICE):
+ return 'gpu_device: {}'.format(self.name())
+ elif (osdev_type == OperatingSystemDeviceType.NETWORK_DEVICE):
+ return 'network_device: {} {}'.format(self.name(), self.address())
+ elif (osdev_type == OperatingSystemDeviceType.OPENFABRICS_DEVICE):
+ return 'openfabrics_device: {} node_guid={}'.format(self.name(),
+ self.attribute('node_guid'))
+ elif (osdev_type == OperatingSystemDeviceType.DMA_DEVICE):
+ return 'dma_device: PRINTING_NOT_IMPLEMENTED'
+ elif (osdev_type == OperatingSystemDeviceType.COPROCESSOR_DEVICE):
+ header = 'coprocessor /dev/{} on backend {}'.format(self.name(), self.backend())
+ backend_info = self.backend_info()
+ if backend_info:
+ content=''
+ for k,v in backend_info.iteritems():
+ content += '\n*{}: {}'.format(k,v)
+ return header+self.indent(content)
+ else:
+ return 'coprocessor_device: PRINTING_NOT_IMPLEMENTED'
+ else:
+ self.print_attributes()
+ raise ValueError('Unimplemented osdev printing for type {} ({}).'.format(
+ osdev_type, _type))
+ return content
+
+class PciDevice(TopologyObject):
+ def __init__(self, parent, device):
+ self._os_devices = []
+ super(PciDevice,self).__init__(parent, device)
+
+ def leaf_pci_devices(self):
+ return [self]
+
+ def _post_init(self):
+ pci_type = self.pci_type()
+ regexp = '([a-f0-9]{4})\s+\[([a-f0-9]{4}):([a-f0-9]{4})\]\s+'
+ regexp += '\[([a-f0-9]{4}):([a-f0-9]{4})\]\s+([a-f0-9]{2})'
+ regexp = re.compile(regexp)
+ match = re.match(regexp, pci_type)
+ if not match:
+ msg='Could not match pci device type \'{}\'.'
+ msg=msg.format(pci_type)
+ raise ValueError(msg)
+
+ pci_device_class_id = match.group(1)
+
+ vendor_id = match.group(2)
+ device_id = match.group(3)
+
+ subvendor_id = match.group(4)
+ subdevice_id = match.group(5)
+
+ revision = match.group(6)
+
+ pci_device_class = self.pciids.find_device_class_by_id(pci_device_class_id)
+
+ vendor = self.pciids.find_vendor(vendor_id)
+ if not vendor:
+ vendor = vendor_id
+ device = None
+ else:
+ device = vendor.find_device(device_id, subdevice_id)
+ if not device:
+ device = '[{}:{}]'.format(vendor_id, device_id)
+
+ subvendor = self.pciids.find_vendor(subvendor_id)
+ if not subvendor:
+ subvendor = subvendor_id
+ subdevice = None
+ else:
+ subdevice = subvendor.find_device(subdevice_id)
+ if not subdevice:
+ subdevice = '[{}:{}]'.format(subvendor_id, subdevice_id)
+
+ self._attributes['pci_device_class_sid'] = pci_device_class_id
+ self._attributes['pci_system_vendor_sid'] = vendor_id
+ self._attributes['pci_system_device_sid'] = device_id
+ self._attributes['pci_subsystem_vendor_sid'] = subvendor_id
+ self._attributes['pci_subsystem_device_sid'] = subdevice_id
+ self._attributes['pci_device_revision_string'] = revision
+
+ self._attributes['pci_device_class_id'] = int(pci_device_class_id,16)
+ self._attributes['pci_system_vendor_id'] = int(vendor_id, 16)
+ self._attributes['pci_system_device_id'] = int(device_id, 16)
+ self._attributes['pci_subsystem_vendor_id'] = int(subvendor_id, 16)
+ self._attributes['pci_subsystem_device_id'] = int(subdevice_id, 16)
+ self._attributes['pci_device_revision_value'] = int(revision, 16)
+
+ self._attributes['pci_device_class'] = pci_device_class
+ self._attributes['pci_system_vendor'] = vendor
+ self._attributes['pci_system_device'] = device
+ self._attributes['pci_subsystem_vendor'] = subvendor
+ self._attributes['pci_subsystem_device'] = subdevice
+
+ def pci_link_speed(self):
+ return self.attribute('pci_link_speed')
+ def pci_busid(self):
+ return self.attribute('pci_busid')
+ def pci_type(self):
+ return self.attribute('pci_type')
+
+ def vendor(self):
+ return self.pci_system_vendor()
+ def device(self):
+ return self.pci_system_device()
+ def vendor_id(self):
+ return self.pci_system_vendor_id()
+ def device_id(self):
+ return self.pci_system_device_id()
+
+ def subdevices(self):
+ return self.operating_system_devices()
+ def subdevices_count(self):
+ return self.operating_system_devices_count()
+
+ def pci_device_class_id(self):
+ return self.attribute('pci_device_class_id')
+ def pci_device_class_sid(self):
+ return self.attribute('pci_device_class_sid')
+ def pci_device_class(self):
+ return self.attribute('pci_device_class')
+
+ def pci_device_revision_val(self):
+ return self.attribute('pci_device_revision_value')
+ def pci_device_revision_str(self):
+ return self.attribute('pci_device_revision_string')
+
+ def pci_system_vendor_id(self):
+ return self.attribute('pci_system_vendor_id')
+ def pci_system_vendor_sid(self):
+ return self.attribute('pci_system_vendor_sid')
+ def pci_system_vendor(self):
+ return self.attribute('pci_system_vendor')
+
+ def pci_system_device_id(self):
+ return self.attribute('pci_system_device_id')
+ def pci_system_device_sid(self):
+ return self.attribute('pci_system_device_sid')
+ def pci_system_device(self):
+ return self.attribute('pci_system_device')
+
+ def pci_subsystem_vendor_id(self):
+ return self.attribute('pci_subsystem_vendor_id')
+ def pci_subsystem_vendor_sid(self):
+ return self.attribute('pci_subsystem_vendor_sid')
+ def pci_subsystem_vendor(self):
+ return self.attribute('pci_subsystem_vendor')
+
+ def pci_subsystem_device_id(self):
+ return self.attribute('pci_subsystem_device_id')
+ def pci_subsystem_device_sid(self):
+ return self.attribute('pci_subsystem_device_sid')
+ def pci_subsystem_device(self):
+ return self.attribute('pci_subsystem_device')
+
+ def operating_system_devices_count(self):
+ return len(self._os_devices)
+ def operating_system_devices(self):
+ return self._os_devices
+
+ def to_string(self, expand_pci_tree=True, **kargs):
+ if expand_pci_tree:
+ header = '{} {}'.format(self.pci_busid(), self.pci_device_class())
+ content = '\nvendor: {}'.format(self.pci_system_vendor())
+ content += '\ndevice: {}'.format(self.pci_system_device())
+ if self.pci_system_vendor_id() != self.pci_subsystem_vendor_id():
+ content += '\nsubvendor: {}'.format(self.pci_subsystem_vendor())
+ content += '\nsubdevice: {}'.format(self.pci_subsystem_device())
+ content += '\nrevision: 0x{}'.format(self.pci_device_revision_str())
+ if self.subdevices_count()>0:
+ subcontent=''
+ for osdev in self.subdevices():
+ subcontent += '\n> {}'.format(osdev)
+ content += prepend(subcontent,2*' ')
+ content += '\n'
+ return header + prepend(content, 5*' ')
+ else:
+ return '{} {} ({})'.format(self.pci_busid(),
+ self.device(),
+ self.pci_device_class().name)
+
+ def __str__(self):
+ return self.to_string()
+
+ def _parsed_type(self):
+ return 'PCIDev'
+ def _parse_object(self, it):
+ _type = it.attrib['type']
+ if _type == 'OSDev':
+ obj = OperatingSystemDevice(self, it)
+ self._os_devices.append(obj)
+ else:
+ raise ValueError('Unknown object type {}.'.format(_type))
+
+class PciBridge(TopologyObject):
+ def __init__(self, parent, bridge):
+ self._pci_devices = []
+ super(PciBridge, self).__init__(parent, bridge)
+
+ def pci_devices(self, split=False):
+ devs = sorted(self._pci_devices, key=lambda x: x.os_index())
+ if split:
+ devices = [dev for dev in devs if isinstance(dev,PciBridge)]
+ devices +=[dev for dev in devs if isinstance(dev,PciDevice)]
+ return devices
+ else:
+ return devs
+ def pci_devices_count(self):
+ return len(self._pci_devices)
+ def leaf_pci_devices(self):
+ return it.chain.from_iterable([x.leaf_pci_devices() for x in self._pci_devices])
+
+ def bridge_pci(self):
+ return self.attribute('bridge_pci')
+ def bridge_type(self):
+ return self.attribute('bridge_type')
+ def bridge_depth(self):
+ return self.attribute('depth', 0, int)
+
+ def __str__(self):
+ return self.to_string()
+
+ def to_string(self, expand_pci_tree=True, is_last=False):
+ header = 'Bridge {}'.format(self.bridge_pci())
+ content=''
+ devices = self.pci_devices(split=True)
+
+ is_root = (self.bridge_depth()==0)
+ if is_root:
+ prefix = 'x-'
+ else:
+ prefix = ''
+
+ if (not is_root) and (is_last):
+ extra_pad = 3
+ else:
+ extra_pad = 0
+
+ if expand_pci_tree and self.pci_devices_count()==1:
+ extra_bar = '|\n'
+ else:
+ extra_bar = ''
+
+ for dev_id, pci_device in enumerate(devices[:-1]):
+ pci_device = pci_device.to_string(expand_pci_tree)
+ pci_device = pci_device.split('\n')
+ pci_device[0] = '|--'+pci_device[0]
+ for i in xrange(1,len(pci_device)):
+ pci_device[i] = '| '+pci_device[i]
+ if (dev_id==0) and expand_pci_tree:
+ pci_device = ['|']+pci_device
+ pci_device='\n'.join(pci_device)
+ branch = self.indent(pci_device, len(prefix))
+ content += '\n'+branch
+ pci_device = devices[-1].to_string(expand_pci_tree, is_last=True)
+ branch = self.indent('{}|__{}'.format(extra_bar, pci_device), extra_pad+len(prefix))
+ content += '\n'+branch
+ return prefix + header + content
+
+ def _parsed_type(self):
+ return 'Bridge'
+
+ def _parse_object(self, it):
+ _type = it.attrib['type']
+ if _type == 'PCIDev':
+ obj = PciDevice(self, it)
+ self._pci_devices.append(obj)
+ elif _type == 'Bridge':
+ obj = PciBridge(self, it)
+ self._pci_devices.append(obj)
+ else:
+ raise ValueError('Unknown object type {}.'.format(_type))
diff --git a/hysop/backend/hardware/pci_ids.py b/hysop/backend/hardware/pci_ids.py
new file mode 100644
index 0000000000000000000000000000000000000000..2a322e0916c22038fa08f913da458da808e7450d
--- /dev/null
+++ b/hysop/backend/hardware/pci_ids.py
@@ -0,0 +1,380 @@
+
+import os, gzip, bz2, urllib2, re
+
+class PciVendor(object):
+ _regexp = re.compile('([0-9a-f]{4})\s+(.*)')
+
+ def __init__(self, vendor):
+ """
+ Class initializes with the raw line from pci.ids
+ """
+
+ vendor = vendor.strip()
+ match = re.match(self._regexp, vendor)
+ if not match:
+ msg='PCI vendor could not match regexp: {}.'
+ msg=msg.format(vendor)
+ raise ValueError(msg)
+ else:
+ self.sid = match.group(1)
+ self.id = int(self.sid, 16)
+ self.name = match.group(2)
+ self.devices = {}
+
+
+ def find_device(self, device_id, subdevice_id=None):
+ if (device_id is None) or (device_id not in self.devices):
+ return None
+
+ device = self.devices[device_id]
+ if (subdevice_id is None) or (subdevice_id not in device.subdevices):
+ return device
+
+ subdevice = device.subdevices[subdevice_id]
+ return subdevice
+
+ def _parse_device(self, device):
+ """
+ Parse a device and adds it to self.devices
+ Input is a raw line from pci.ids
+ Returns the parsed device_id.
+ """
+ device = PciDevice(device, vendor=self)
+ device_id = device.id
+ device_sid = device.sid
+ if (device_id not in self.devices):
+ self.devices[device_id] = device
+ self.devices[device_sid] = device
+ return device_id
+
+ def __str__(self):
+ return self.name
+
+class PciDevice(object):
+ _regexp = re.compile('([0-9a-f]{4})\s+(.*)')
+
+ def __init__(self, device, vendor):
+ device = device.strip()
+ match = re.match(self._regexp, device)
+ if not match:
+ msg='pci device could not match regexp: {}.'
+ msg=msg.format(device)
+ raise valueerror(msg)
+
+ self.vendor = vendor
+ self.sid = match.group(1)
+ self.id = int(self.sid, 16)
+ self.name = match.group(2)
+ self.subdevices = {}
+
+ def __str__(self):
+ return self.name
+
+ def _parse_sub_device(self, subdevice):
+ """
+ parse a subdevice and adds it to self.subdevices.
+ input is a raw line from pci.ids
+ returns the parsed subdevice_id.
+ """
+ subdevice = PciSubDevice(subdevice,device=self,vendor=self.vendor)
+ subdevice_id = subdevice.subdevice_id
+ subdevice_sid = subdevice.subdevice_sid
+ if (subdevice_id not in self.subdevices):
+ self.subdevices[subdevice_id] = subdevice
+ self.subdevices[subdevice_sid] = subdevice
+ return subdevice_id
+
+ def __str__(self):
+ return self.name
+
+class PciSubDevice(object):
+ _regexp = re.compile('([0-9a-f]{4})\s+([0-9a-f]{4})\s+(.*)')
+ def __init__(self, subdevice, device, vendor):
+ subdevice = subdevice.strip()
+ match = re.match(self._regexp, subdevice)
+ if not match:
+ msg='PCI device could not match regexp: {}.'
+ msg=msg.format(subdevice)
+ raise ValueError(msg)
+
+ self.vendor = vendor
+ self.device = device
+ self.subvendor_sid = match.group(1)
+ self.subvendor_id = int(self.subvendor_sid, 16)
+ self.subdevice_sid = match.group(2)
+ self.subdevice_id = int(self.subdevice_sid, 16)
+ self.name = match.group(3)
+
+ def __str__(self):
+ return self.name
+
+class PciDeviceClass(object):
+ _regexp = re.compile('C\s+([0-9a-f]{2})\s+(.*)')
+
+ def __init__(self, device_class):
+ device_class = device_class.strip()
+ match = re.match(self._regexp, device_class)
+ if not match:
+ msg='Pci device class could not match regexp: {}.'
+ msg=msg.format(device_class)
+ raise ValueError(msg)
+
+ self.sid = match.group(1)
+ self.id = int(self.sid, 16)
+ self.name = match.group(2)
+ self.device_subclasses = {}
+
+ def _parse_sub_class(self, subclass):
+ """
+ parse a subdevice and adds it to self.subdevices.
+ input is a raw line from pci.ids
+ returns the parsed subdevice_id.
+ """
+ subclass = PciDeviceSubClass(subclass, device_class=self)
+ subclass_id = subclass.id
+ subclass_sid = subclass.sid
+ if (subclass_id not in self.device_subclasses):
+ self.device_subclasses[subclass_id] = subclass
+ self.device_subclasses[subclass_sid] = subclass
+ return subclass_id
+
+ def __str__(self):
+ return self.name
+
+class PciDeviceSubClass(object):
+ _regexp = re.compile('([0-9a-f]{2})\s+(.*)')
+
+ def __init__(self, device_subclass, device_class):
+ device_subclass = device_subclass.strip()
+ match = re.match(self._regexp, device_subclass)
+ if not match:
+ msg='Pci device subclass could not match regexp: {}.'
+ msg=msg.format(device_subclass)
+ raise ValueError(msg)
+
+ self.device_class = device_class
+ self.sid = match.group(1)
+ self.id = int(self.sid, 16)
+ self.name = match.group(2)
+ self.programming_interfaces = {}
+
+ def _parse_programming_interface(self, interface):
+ interface = PciProgrammingInterface(interface, device_subclass=self, device_class=self.device_class)
+ interface_id = interface.id
+ interface_sid = interface.sid
+ if (interface_id not in self.programming_interfaces):
+ self.programming_interfaces[interface_id] = interface
+ self.programming_interfaces[interface_sid] = interface
+ return interface_id
+
+ def __str__(self):
+ return '{} ({})'.format(self.name, self.device_class.name)
+
+class PciProgrammingInterface(object):
+ _regexp = re.compile('([0-9a-f]{2})\s+(.*)')
+
+ def __init__(self, interface, device_subclass, device_class):
+ interface = interface.strip()
+ match = re.match(self._regexp, interface)
+ if not match:
+ msg='Pci device interface could not match regexp: {}.'
+ msg=msg.format(interface)
+ raise ValueError(msg)
+
+ self.device_class = device_class
+ self.device_subclass = device_subclass
+ self.sid = match.group(1)
+ self.id = int(self.sid, 16)
+ self.name = match.group(2)
+
+ def __str__(self):
+ return self.name
+
+class PCIIds(object):
+ """
+ Class used to parse all pci.ids entries.
+ This file should contains up to date PCI vendors and device ids.
+
+ The default path that is looked is '/usr/share/hwdata/pci.ids'
+ See http://pciids.sourceforge.net/ to get urls.
+
+ It can be updated using the command 'update-pciids',
+ or by providing a custom source file or url in constructor.
+
+ Usage:
+ from hysop.backend.topology import PCIIds
+ pciids = PCIIds(filepath or url)
+
+ #PCI DEVICES
+ pciids.vendors[vendor_id]
+ .devices[device_id]
+ .subdevices[subdevice_id]
+
+ #PCI DEVICE CLASSES
+ pciids.device_classes[class_id]
+ .device_subclasses[subclass_id]
+ .programming_interfaces[interface_id]
+
+ All ids can be given as hexadecimal strings or as integers.
+ """
+
+ def __init__(self, path='/usr/share/hwdata/pci.ids',
+ url=None):
+ """
+ Loads and parse a pci.ids file.
+ The file may be compressed in gzip or bzip2 format.
+ url has priority over path.
+ """
+
+ self.vendors = {}
+ self.device_classes = {}
+ self._parsed = False
+
+ if (url is not None):
+ self.load_from_url(url=url)
+ elif (path is not None):
+ self.load_from_path(path=path)
+
+ def load_from_url(self, url):
+ response = urllib2.urlopen(url)
+ content = response.read()
+ self._parse(content)
+
+ def load_from_path(self, path):
+ if not os.path.isfile(path):
+ msg='File \'{}\' does not exist.'.format(path)
+ raise ValueError(msg)
+
+ if path.endswith('.ids'):
+ with open(path, 'ro') as f:
+ content = f.read()
+ elif path.endswith('.ids.gz'):
+ with gzip.open(path, 'ro') as f:
+ content = f.read()
+ elif path.endswith('.ids.bz2'):
+ with bz2.BZ2File(path, 'r') as f:
+ content = f.read()
+ else:
+ msg='File \'{}\' has an unknown extensions, valid ones are {}.'
+ msg=msg.format(path, ['*.ids', '*.ids.gz', '*.ids.bz2'])
+ raise ValueError(msg)
+
+ self._parse(content)
+
+ def find_vendor(self, vendor_id):
+ assert self._parsed
+ if (vendor_id is None) or (vendor_id not in self.vendors):
+ return None
+ else:
+ return self.vendors[vendor_id]
+
+ def find_device(self, vendor_id, device_id, subdevice_id=None):
+ vendor = self.find_vendor(vendor_id)
+ if (vendor is None):
+ return None
+ return vendor.find_device(device_id, subdevice_id)
+
+ def find_device_by_id(self, id):
+ if isinstance(id,str):
+ id = int(id,16)
+ if id>0xffffffffffff:
+ raise ValueError(id)
+ elif id>0xffffffff:
+ vendor_id = (id & 0xffff00000000) >> (2*16)
+ device_id = (id & 0x0000ffff0000) >> (1*16)
+ subdevice_id = (id & 0x00000000ffff) >> (0*16)
+ elif id>0xffff:
+ vendor_id = (id & 0xffff0000) >> (1*16)
+ device_id = (id & 0x0000ffff) >> (0*16)
+ subdevice_id = None
+ else:
+ vendor_id = (id & 0xffff) >> (0*4)
+ device_id = None
+ subdevice_id = None
+
+ return self.find_device(vendor_id, device_id, subdevice_id)
+
+ def find_device_class(self, device_class_id, device_subclass_id=None, programming_interface=None):
+ assert self._parsed
+ if (device_class_id is None) or (device_class_id not in self.device_classes):
+ return None
+
+ device_class = self.device_classes[device_class_id]
+ if (device_subclass_id is None) or (device_subclass_id not in device_class.device_subclasses):
+ return device_class
+
+ device_subclass = device_class.device_subclasses[device_subclass_id]
+ if (programming_interface is None) or (programming_interface not in device_subclass.programming_interfaces):
+ return device_subclass
+
+ programming_interface = device_subclass.programming_interfaces[programming_interface]
+ return programming_interface
+
+ def find_device_class_by_id(self, id):
+ if isinstance(id,str):
+ id = int(id,16)
+ if id>0xffffff:
+ raise ValueError(id)
+ elif id>0xffff:
+ device_class_id = (id & 0xff0000) >> (2*8)
+ device_subclass_id = (id & 0x00ff00) >> (1*8)
+ programming_interface_id = (id & 0x0000ff) >> (0*8)
+ elif id>0xff:
+ device_class_id = (id & 0xff00) >> (1*8)
+ device_subclass_id = (id & 0x00ff) >> (0*8)
+ programming_interface_id = None
+ else:
+ device_class_id = (id & 0xff) >> (8*0)
+ device_subclass_id = None
+ programming_interface_id = None
+
+ return self.find_device_class(device_class_id, device_subclass_id, programming_interface_id)
+
+ def _parse(self, content):
+ msg='Something went wrong during parsing.'
+ for line in content.split('\n'):
+ if (line.strip()=='') or (line[0] == '#'):
+ continue
+ elif line.find('\t\t') == 0:
+ if parse_vendor:
+ self.vendors[vendor_id].devices[device_id]._parse_sub_device(line)
+ elif parse_device_class:
+ self.device_classes[device_class_id].device_subclasses[device_subclass_id]._parse_programming_interface(line)
+ else:
+ raise RuntimeError(msg)
+ elif line.find('\t') == 0:
+ if parse_vendor:
+ device_id = self.vendors[vendor_id]._parse_device(line)
+ elif parse_device_class:
+ device_subclass_id = self.device_classes[device_class_id]._parse_sub_class(line)
+ else:
+ raise RuntimeError(msg)
+ elif line.strip()[0]=='C':
+ device_class_id = self._parse_device_class(line)
+ parse_device_class = True
+ parse_vendor = False
+ else:
+ vendor_id = self._parse_vendor(line)
+ parse_device_class = False
+ parse_vendor = True
+ self._parsed = True
+
+
+ def _parse_vendor(self, line):
+ vendor = PciVendor(line)
+ vendor_id = vendor.id
+ vendor_sid = vendor.sid
+ if vendor_id not in self.vendors:
+ self.vendors[vendor_id] = vendor
+ self.vendors[vendor_sid] = vendor
+ return vendor_id
+
+ def _parse_device_class(self, line):
+ device_class = PciDeviceClass(line)
+ device_class_id = device_class.id
+ device_class_sid = device_class.sid
+ if device_class_id not in self.device_classes:
+ self.device_classes[device_class_id] = device_class
+ self.device_classes[device_class_sid] = device_class
+ return device_class_id
+
diff --git a/hysop/problem/tests/__init__.py b/hysop/backend/host/__init__.py
similarity index 100%
rename from hysop/problem/tests/__init__.py
rename to hysop/backend/host/__init__.py
diff --git a/hysop/backend/host/cpp/__init__.py b/hysop/backend/host/cpp/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/backend/host/cpp/cpp_operators.py b/hysop/backend/host/cpp/cpp_operators.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/backend/host/fortran/__init__.py b/hysop/backend/host/fortran/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc
--- /dev/null
+++ b/hysop/backend/host/fortran/__init__.py
@@ -0,0 +1 @@
+
diff --git a/hysop/backend/host/fortran/fortran_operators.py b/hysop/backend/host/fortran/fortran_operators.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/backend/host/fortran/operator/__init__.py b/hysop/backend/host/fortran/operator/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/backend/host/fortran/operator/diffusion.py b/hysop/backend/host/fortran/operator/diffusion.py
new file mode 100644
index 0000000000000000000000000000000000000000..891c19dc6b53a69a937885707513512dd517c778
--- /dev/null
+++ b/hysop/backend/host/fortran/operator/diffusion.py
@@ -0,0 +1,104 @@
+
+from hysop.backend.host.fortran.operator.fortran_fftw import FortranFFTWOperator, fftw2py
+from hysop.tools.types import check_instance, InstanceOf
+from hysop.tools.decorators import debug
+from hysop.tools.numpywrappers import npw
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+
+class DiffusionFFTW(FortranFFTWOperator):
+
+ __default_method = {}
+ __available_methods = {}
+
+ def __init__(self, input_field, output_field, viscosity, variables, **kargs):
+ """Diffusion operator using FFTW in Fortran.
+
+ Parameters
+ ----------
+ input_field : :class:`~hysop.fields.continuous.Field
+ output_field: :class:`~hysop.fields.continuous.Field`
+ variables: dictionary of fields:topology
+ viscosity : double
+ constant viscosity value
+ kargs :
+ base class parameters.
+
+ Notes:
+ *Equations:
+ dW/dt = K*Laplacian(W)
+ in = Win
+ out = Wout
+ """
+
+ check_instance(input_field, Field)
+ check_instance(output_field, Field)
+ check_instance(variables, dict, keys=Field, values=CartesianDescriptors)
+
+ assert variables[input_field] == variables[output_field], \
+ 'input and output topology mismatch'
+ assert input_field.domain is output_field.domain,\
+ 'input and output domain mismatch'
+
+ input_vars = { input_field: variables[input_field] }
+ output_vars = { output_field: variables[output_field] }
+ super(DiffusionFFTW,self).__init__(input_vars=input_vars, output_vars=output_vars,
+ **kargs)
+
+ self.input_field = input_field
+ self.output_field = output_field
+ self.viscosity = viscosity
+
+
+ def initialize(self, **kwds):
+ super(DiffusionFFTW,self).initialize(**kwds)
+ dim = self.dim
+ if (dim==2):
+ self._solve = self._solve_2d
+ elif (dim==3):
+ self._solve = self._solve_3d
+ else:
+ raise AttributeError(dim + "D case not yet implemented.")
+
+
+ @debug
+ def discretize(self):
+ if self.discretized:
+ return
+ super(DiffusionFFTW,self).discretize()
+ self.din = self.input_field.discrete_fields[self.topology]
+ self.dout = self.output_field.discrete_fields[self.topology]
+
+ @debug
+ def apply(self, simulation=None, **kargs):
+ super(DiffusionFFTW,self).apply(simulation=simulation,**kargs)
+ self._solve(simulation)
+
+ def _solve_2d(self, simulation):
+ """ Solve 2D diffusion problem
+ """
+ dt = simulation.time_step
+ ghosts = self.topology.ghosts()
+ self.dout.data =\
+ fftw2py.solve_diffusion_2d(self.viscosity * dt, self.din.data, ghosts)
+
+ def _solve_3d(self,simulation):
+ """ Solve 3D diffusion problem
+ """
+ dt = simulation.time_step
+ ghosts = self.topology.ghosts
+ self.dout.data = \
+ fftw2py.solve_diffusion_3d(self.viscosity * dt,
+ self.din.data[0],
+ self.din.data[1],
+ self.din.data[2],
+ ghosts)
+
+ def available_methods(self):
+ return self.__available_methods
+ def default_method(self):
+ return self.__default_method
+ def handle_method(self, method):
+ pass
+
+
diff --git a/hysop/backend/host/fortran/operator/fortran_fftw.py b/hysop/backend/host/fortran/operator/fortran_fftw.py
new file mode 100644
index 0000000000000000000000000000000000000000..b2aa556efc95704a2ccbf2518b7611c5d0e4f699
--- /dev/null
+++ b/hysop/backend/host/fortran/operator/fortran_fftw.py
@@ -0,0 +1,118 @@
+
+try:
+ from hysop.f2hysop import fftw2py
+except ImportError:
+ msg = 'HySoP fortran fftw bindings are not available for your hysop install.'
+ msg += 'Try to recompile HySoP with WITH_FFTW=ON'
+ raise ImportError(msg)
+
+from hysop.constants import HYSOP_ORDER
+from hysop.tools.numpywrappers import npw
+from hysop.tools.decorators import debug
+from hysop.tools.types import check_instance
+from hysop.core.graph.computational_operator import ComputationalGraphOperator
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+from hysop.fields.continuous import Field
+
+class FortranFFTWOperator(ComputationalGraphOperator):
+
+ @debug
+ def __init__(self, input_vars, output_vars, **kwds):
+ super(FortranFFTWOperator, self).__init__(input_vars=input_vars,
+ output_vars=output_vars, **kwds)
+
+ check_instance(input_vars, dict, keys=Field, values=CartesianDescriptors)
+ check_instance(output_vars, dict, keys=Field, values=CartesianDescriptors)
+
+ domain = self.input_vars.keys()[0].domain
+ self.dim = domain.dimension
+ self.domain = domain
+
+ def handle_topologies(self):
+ super(FortranFFTWOperator,self).handle_topologies()
+
+ topology = self.input_vars.values()[0]
+ domain = self.domain
+ for (field,topo) in self.input_vars.iteritems():
+ assert topo is topology, 'topology mismatch'
+ assert field.domain is domain, 'domain mismatch'
+ for (field,topo) in self.output_vars.iteritems():
+ assert topo is topology, 'topology mismatch'
+ assert field.domain is domain, 'domain mismatch'
+ self.topology = topology
+
+ @debug
+ def get_field_requirements(self):
+ requirements = super(FortranFFTWOperator, self).get_field_requirements()
+
+ # set can_split to True in all directions except the contiguous one
+ # for inputs and outputs and impose no ghosts
+ for is_input, (field, td, req) in requirements.iter_requirements():
+ can_split = req.can_split
+ can_split[0] = False
+ req.can_split = can_split
+ req.min_ghosts = npw.zeros_like(req.min_ghosts)
+ req.max_ghosts = npw.zeros_like(req.min_ghosts)
+
+ return requirements
+
+ @debug
+ def discretize(self):
+ if self.discretized:
+ return
+ super(FortranFFTWOperator,self).discretize()
+
+ self._fftw_discretize()
+
+ @debug
+ def get_work_properties(self):
+ return super(FortranFFTWOperator,self).get_work_properties()
+
+ @debug
+ def setup(self, work=None):
+ super(FortranFFTWOperator,self).setup(work=work)
+
+ @debug
+ def finalize(self, clean_fftw_solver=False, **kwds):
+ super(FortranFFTWOperator,self).finalize(**kwds)
+ if clean_fftw_solver:
+ fftw2py.clean_fftw_solver(self.dim)
+
+ def _fftw_discretize(self):
+ """
+ fftw specific way to discretize variables for a given
+ 'reference' resolution.
+ It is assumed that in fft case, only one topology must be used
+ for all variables of all fortran fftw operators.
+ """
+
+ self._set_domain_and_tasks()
+ topo = self.topology
+ comm = self.mpi_params.comm
+ size = self.mpi_params.size
+
+ msg = 'input topology is not compliant with fftw.'
+ assert topo.dimension == 1, msg
+
+ if HYSOP_ORDER == 'C':
+ assert topo.shape[0] == size, msg
+ else:
+ assert topo.shape[-1] == size, msg
+
+ resolution = npw.asintegerarray(topo.mesh.discretization.resolution)
+
+ localres, global_start = fftw2py.init_fftw_solver(
+ resolution, topo.domain.length, comm=comm.py2f())
+
+ assert (topo.mesh.resolution == localres).all(), 'Local resolution mismatch.'
+ assert (topo.mesh.start() == global_start).all(), 'Global start mismatch.'
+ msg = 'Ghosts points not yet implemented for fortran fftw operators.'
+ assert (topo.ghosts == 0).all(), msg
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return False
+
+ @classmethod
+ def supports_mpi(cls):
+ return True
diff --git a/hysop/backend/host/fortran/operator/poisson.py b/hysop/backend/host/fortran/operator/poisson.py
new file mode 100644
index 0000000000000000000000000000000000000000..a583f0fa5e92b9751d205698d5ed42917ad92105
--- /dev/null
+++ b/hysop/backend/host/fortran/operator/poisson.py
@@ -0,0 +1,140 @@
+
+from hysop.tools.types import check_instance, InstanceOf
+from hysop.tools.decorators import debug
+from hysop.tools.numpywrappers import npw
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+from hysop.constants import FieldProjection
+from hysop.backend.host.fortran.operator.fortran_fftw import fftw2py, FortranFFTWOperator
+
+class PoissonFFTW(FortranFFTWOperator):
+
+ __default_method = {
+ FieldProjection: FieldProjection.NONE,
+ }
+
+ __available_methods = {
+ FieldProjection: [InstanceOf(FieldProjection), InstanceOf(int)]
+ }
+
+ def __init__(self, velocity, vorticity, variables, **kwds):
+ """Poisson operator to solve incompressible flows using FFTW in Fortran.
+
+ Parameters
+ ----------
+ velocity : :class:`~hysop.fields.continuous.Field
+ solution field
+ vorticity: :class:`~hysop.fields.continuous.Field`
+ right-hand side
+ variables: dict
+ dictionary of fields as keys and topologies as values.
+ kwds :
+ base class parameters.
+
+ Notes
+ -----
+ * About the method parameter:
+ - FieldProjection: frequency hint to project velocity div(U) = 0.
+ """
+
+
+ check_instance(velocity, Field)
+ check_instance(vorticity, Field)
+ check_instance(variables, dict, keys=Field, values=CartesianDescriptors)
+
+ assert velocity.domain is vorticity.domain, 'only one domain is supported'
+ assert variables[velocity] is variables[vorticity], 'only one topology is supported'
+
+ topology = variables[velocity]
+ input_vars = { vorticity: topology }
+ output_vars = { velocity: topology }
+
+ super(PoissonFFTW,self).__init__(input_vars=input_vars, output_vars=output_vars,
+ **kwds)
+
+ self.velocity = velocity
+ self.vorticity = vorticity
+
+ def initialize(self, **kwds):
+ super(PoissonFFTW,self).initialize(**kwds)
+ dim = self.dim
+ if (dim==2):
+ self._solve = self._solve_2d
+ elif (dim==3):
+ self._solve = self._solve_3d
+
+ if (dim!=3) and (self.projection!=FieldProjection.NONE):
+ raise ValueError('Velocity reprojection only available in 3D.')
+
+ def available_methods(self):
+ return PoissonFFTW.__available_methods
+ def default_method(self):
+ return PoissonFFTW.__default_method
+
+ @debug
+ def handle_method(self, method):
+ super(PoissonFFTW,self).handle_method(method)
+ projection = method.pop(FieldProjection)
+
+ if projection == FieldProjection.NONE:
+ self._do_project = lambda simu: False
+ elif projection == FieldProjection.EVERY_STEP:
+ self._do_project = lambda simu: True
+ else: # projection is an integer representing frenquency
+ freq = projection
+ assert freq>=1
+ self._do_project = lambda simu: ((simu.current_iteration % freq)==0)
+ self.projection = projection
+ assert not method, 'Unused method keywords {}.'.format(method.keys())
+
+ @debug
+ def discretize(self):
+ if self.discretized:
+ return
+ super(PoissonFFTW,self).discretize()
+ self.dvelocity = self.velocity.discrete_fields[self.topology]
+ self.dvorticity = self.vorticity.discrete_fields[self.topology]
+
+ @debug
+ def apply(self, simulation=None, **kargs):
+ super(PoissonFFTW,self).apply(simulation=simulation,**kargs)
+ if self._do_project(simulation):
+ self._project(simulation)
+ self._solve(simulation)
+
+ def _solve_2d(self, simu=None):
+ """ Solve 2D poisson problem, no projection, no correction.
+ """
+ ghosts_v = self.variables[self.velocity].ghosts()
+ ghosts_w = self.variables[self.vorticity].ghosts()
+ self.dvelocity.data =\
+ fftw2py.solve_poisson_2d(self.dvorticity.data[0],
+ self.dvelocity.data[0],
+ self.dvelocity.data[1],
+ ghosts_w, ghosts_v)
+
+ def _solve_3d(self,simu=None):
+ """ Solve 3D poisson problem, no projection, no correction
+ """
+ # Solves Poisson equation using usual dvorticity
+ ghosts_v = self.output_vars[self.velocity].ghosts
+ ghosts_w = self.input_vars[self.vorticity].ghosts
+ self.dvelocity.data =\
+ fftw2py.solve_poisson_3d(self.dvorticity.data[0],
+ self.dvorticity.data[1],
+ self.dvorticity.data[2],
+ self.dvelocity.data[0],
+ self.dvelocity.data[1],
+ self.dvelocity.data[2],
+ ghosts_w, ghosts_v)
+
+ def _project(self, simulation):
+ """
+ Apply projection on velocity such that div(U)=0.
+ """
+ assert self.dim==3
+ ghosts_w = self.variables[self.vorticity].ghosts()
+ self.dvorticity.data =\
+ fftw2py.projection_om_3d(self.dvorticity.data[0],
+ self.dvorticity.data[1],
+ self.dvorticity.data[2], ghosts_w)
diff --git a/hysop/backend/host/host_allocator.py b/hysop/backend/host/host_allocator.py
new file mode 100644
index 0000000000000000000000000000000000000000..3a7630962e63d9f93336fd7e843e46b2d93b4b6e
--- /dev/null
+++ b/hysop/backend/host/host_allocator.py
@@ -0,0 +1,32 @@
+
+from hysop.deps import cpuinfo
+from hysop.constants import default_order
+from hysop.core.memory.allocator import AllocatorBase
+from hysop.backend.host.host_buffer import HostBuffer
+
+class HostAllocator(AllocatorBase):
+ """
+ Allocator that allocates HostBuffers
+ """
+
+ def allocate(self, nbytes):
+ return HostBuffer(size=nbytes)
+
+ def is_on_host(self):
+ """
+ Return true if buffers are allocated in host memory.
+ """
+ return True
+
+ def memory_pool(self, name, **kwds):
+ """
+ Construct a memory pool from this allocator.
+ """
+ from hysop.backend.host.host_mempool import MemoryPool, HostMemoryPool
+ if isinstance(self, MemoryPool):
+ msg='allocator is already a memory pool.'
+ raise RuntimeError(msg)
+ return HostMemoryPool(allocator=self, name=name, **kwds)
+
+default_host_allocator = HostAllocator()
+default_host_mempool = default_host_allocator.memory_pool(name=cpuinfo.cpuinfo.get_cpu_info()['brand'])
diff --git a/hysop/backend/host/host_array.py b/hysop/backend/host/host_array.py
new file mode 100644
index 0000000000000000000000000000000000000000..397107691f3628cc78e47ffbc8286aa32cf7288c
--- /dev/null
+++ b/hysop/backend/host/host_array.py
@@ -0,0 +1,171 @@
+
+from hysop.deps import np
+from hysop.core.arrays import MemoryType, MemoryOrdering
+from hysop.core.arrays import default_order
+from hysop.core.arrays.array import Array
+from hysop.backend.host.host_array_backend import HostArrayBackend
+
+class HostArray(Array):
+ """
+ Host memory array wrapper.
+ An HostArray is a numpy.ndarray work-alike that stores its data and performs
+ its computations on CPU with numpy.
+ """
+
+ def __init__(self, handle, backend, **kwds):
+ """
+ Build an HostArray instance.
+
+ Parameters
+ ----------
+ handle: numpy.ndarray
+ implementation of this array
+ backend: HostArrayBackend
+ backend used to build this handle
+ kwds:
+ arguments for base classes.
+ Notes
+ -----
+ This should never be called directly by the user.
+ Arrays should be constructed using array backend facilities, like zeros or empty.
+ The parameters given here refer to a low-level method for instantiating an array.
+ """
+
+ if not isinstance(handle, np.ndarray):
+ msg='Handle should be a np.ndarray but got a {}.'
+ msg=msg.format(handle.__class__.__name__)
+ raise ValueError(msg)
+ if not isinstance(backend, HostArrayBackend):
+ msg='Backend should be a HostArrayBackend but got a {}.'
+ msg=msg.format(handle.__class__.__name__)
+ raise ValueError(msg)
+
+ if handle.dtype in [np.bool]:
+ msg='{} unsupported yet, use HYSOP_BOOL={} instead.'.format(handle.dtype,
+ HYSOP_BOOL)
+ raise TypeError(msg)
+
+ super(HostArray,self).__init__(handle=handle, backend=backend, **kwds)
+
+ # array interface
+ self.__array_interface__ = handle.__array_interface__
+
+ def get_ndim(self):
+ return self.handle.ndim
+ def get_shape(self):
+ return self.handle.shape
+ def get_size(self):
+ return self.handle.size
+ def get_strides(self):
+ return self.handle.strides
+ def get_offset(self):
+ return self.handle.offset
+ def get_data(self):
+ return self.handle.data
+ def get_base(self):
+ return self.handle.base
+ def get_dtype(self):
+ return self.handle.dtype
+ def get_flags(self):
+ return self.handle.flags
+ def get_imag(self):
+ return self.handle.imag
+ def get_real(self):
+ return self.handle.real
+ def get_ctypes(self):
+ return self.handle.ctypes
+ def get_T(self):
+ return self.handle.T
+ def get_size(self):
+ return self.handle.size
+ def get_itemsize(self):
+ return self.handle.itemsize
+ def get_nbytes(self):
+ return self.handle.nbytes
+
+ # array properties
+ ndim = property(get_ndim)
+ shape = property(get_shape)
+ offset = property(get_offset)
+ strides = property(get_strides)
+ data = property(get_data)
+ base = property(get_base)
+ dtype = property(get_dtype)
+ flags = property(get_flags)
+ T = property(get_T)
+ imag = property(get_imag)
+ real = property(get_real)
+ ctypes = property(get_ctypes)
+ size = property(get_size)
+ itemsize = property(get_itemsize)
+ nbytes = property(get_nbytes)
+
+ def get(self, handle=False):
+ """
+ Returns equivalent array on host device, ie. self.
+ """
+ if handle or (self.ndim==0):
+ return self._handle
+ else:
+ return self
+
+
+ def lock(self):
+ """
+ Set tab as a non-writeable array
+ """
+ self.handle.flags.writeable = False
+ return self
+
+ def unlock(self):
+ """
+ set tab as a writeable array
+ """
+ self.handle.flags.writeable = True
+ return self
+
+
+ def tofile(self, fid, sep='', format='%s'):
+ """
+ Write array to a file as text or binary (default).
+ This is a convenience function for quick storage of array data.
+ Information on endianness and precision is lost.
+ """
+ self.handle.tofile(fid=fid,sep=sep,format=format)
+ return self
+ def tolist(self):
+ """
+ Return the array as a possibly nested list.
+ """
+ return self.handle.tolist()
+ def tostring(self, order=MemoryOrdering.SAME_ORDER):
+ """
+ Construct Python bytes containing the raw data bytes in the array.
+ """
+ return self.handle.tostring()
+ def put(self, indices, values, mode='raise'):
+ """
+ Set a.flatn = valuesn for all n in indices.
+ """
+ self.handle.put(indices=indices, values=values, mode=mode)
+ return self
+ def take(self, indices, axis=None, out=None, mode='raise'):
+ """
+ Return an array formed from the elements of a at the given indices.
+ """
+ handle = self.handle.take(indices=indices, axis=axis, out=out, mode=mode)
+ return self.wrap(handle)
+ def astype(self, dtype, order=MemoryOrdering.SAME_ORDER,
+ casting='unsafe', subok=True, copy=True):
+ """
+ Copy of the array, cast to a specified type.
+ """
+ handle = self.handle.astype(dtype=dtype, order=order, casting=casting,
+ subok=subok, copy=copy)
+ return self.wrap(handle)
+ def view(self, dtype):
+ """
+ New view of array with the same data.
+ """
+ handle = self.handle.view(dtype=dtype)
+ return self.wrap(handle)
diff --git a/hysop/backend/host/host_array_backend.py b/hysop/backend/host/host_array_backend.py
new file mode 100644
index 0000000000000000000000000000000000000000..604ae3076252c0f21ea5781addd0787e59a72a6c
--- /dev/null
+++ b/hysop/backend/host/host_array_backend.py
@@ -0,0 +1,2554 @@
+
+from hysop.deps import np
+from hysop.constants import Backend
+from hysop.constants import HYSOP_REAL, HYSOP_INTEGER, HYSOP_BOOL
+from hysop.tools.decorators import wraps
+from hysop.tools.numerics import is_complex
+from hysop.tools.types import check_instance, to_tuple
+from hysop.tools.misc import get_default_args, args2kargs, kargs2args, get_argnames
+from hysop.tools.hash import hash_id
+from hysop.core.arrays import default_order, transposition_states, MemoryOrdering, MemoryType
+from hysop.core.arrays.array_backend import ArrayBackend
+from hysop.core.memory.allocator import AllocatorBase
+from hysop.backend.host.host_buffer import HostBuffer
+
+def numpy_method(f):
+ @wraps(f)
+ def wrapper(*args, **kwargs):
+ from hysop.backend.host.host_array import HostArray
+
+ # build full args dictionnary
+ kargs = get_default_args(f)
+ kargs.update(kwargs)
+ kargs.update(args2kargs(f,args))
+
+ argnames, varargs = get_argnames(f)
+
+ has_args = ('args' in varargs) if varargs else False
+ has_kwargs = ('kwargs' in varargs) if varargs else False
+
+ if has_args or has_kwargs:
+ msg='Wrapper does not support varargs and kwargs signatures for function {}:{}.'
+ msg=msg.format(args[0].__name__,f.__name__)
+ raise RuntimeError(msg)
+
+ for k in kargs.keys():
+ if k not in argnames:
+ msg='Unknown argument {} in function {}::{}(), possible ones are {}.'
+ msg=msg.format(k, args[0].__name__, f.__name__, argnames)
+ raise ValueError(msg)
+
+ # format input arguments for numpy
+ backend = kargs.pop('self')
+ assert isinstance(backend, HostArrayBackend)
+ _,kargs = backend._prepare_args(**kargs)
+
+ backend._alloc_outputs(fname=f.__name__, kargs=kargs)
+
+ # numpy has some functions with badly documented and/or
+ # inacessible keywords so we go back to ordered args
+ args = kargs2args(f, kargs, remove=['self'])
+
+ if hasattr(np, f.__name__):
+ g = getattr(np, f.__name__)
+ ret = g(*args)
+ else:
+ raise RuntimeError('numpy does not define function {}.'.format(f.__name__))
+
+ # wrap output
+ return backend._return(ret)
+ return wrapper
+
+
+class HostArrayBackend(ArrayBackend):
+ """
+ Host array backend.
+ """
+
+ def __init__(self, allocator, **kwds):
+ check_instance(allocator, AllocatorBase)
+ assert allocator.is_on_host(), 'allocator does not allocate buffers on host.'
+ super(HostArrayBackend,self).__init__(allocator=allocator, **kwds)
+
+ def get_kind(self):
+ return Backend.HOST
+ kind = property(get_kind)
+
+ def get_host_array_backend(self):
+ return self
+ host_array_backend=property(get_host_array_backend)
+
+ def short_description(self):
+ return ':HostBackend: id={}, allocator={}[{}]'.format(
+ self.identifier(), self.allocator.__class__.__name__, hash_id(self.allocator))
+
+
+############################
+# BACKEND SPECIFIC METHODS #
+
+
+ def can_wrap(self, handle):
+ """
+ Should return True if handle is an Array or a array handle corresponding
+ this backend.
+ """
+ from hysop.core.arrays.all import HostArray
+ return isinstance(handle, (HostArray, np.ndarray))
+
+ def wrap(self, handle):
+ """
+ Create a HostArray from an np.ndarray instance.
+ """
+ from hysop.core.arrays.all import HostArray
+
+ if isinstance(handle, HostArray):
+ return handle
+
+ check_instance(handle, np.ndarray)
+
+ if handle.dtype==np.bool:
+ import warnings
+ msg='HostArrayBackend: numpy np.bool array converted to HYSOP_BOOL={}.'.format(HYSOP_BOOL.__name__)
+ warnings.warn(msg, UserWarning)
+ return HostArray(backend=self, handle=handle.astype(HYSOP_BOOL))
+ else:
+ return HostArray(backend=self, handle=handle)
+
+ def copyto(self, dst, src):
+ """
+ src is a HostArray
+ dst can be everything
+ """
+ from hysop.core.arrays.all import HostArray, OpenClArray
+ check_instance(src, HostArray)
+
+ assert src.size == dst.size
+
+ if isinstance(dst, HostArray):
+ dst.handle[...] = src.handle.reshape(dst.shape)
+ elif isinstance(dst, OpenClArray):
+ self.not_implemented_yet('cpu2gpu')
+ elif isinstance(dst, np.ndarray):
+ dst[...] = src.handle.reshape(dst.shape)
+ else:
+ msg = 'Unknown type to copy to ({}) for array of type {}.'
+ msg = msg.format(dst.__class__, src.__class__)
+ raise TypeError(msg)
+
+
+###########################
+# ARRAY CREATION ROUTINES #
+## See https://docs.scipy.org/doc/numpy/reference/routines.array-creation.html
+
+
+## ALLOCATED WITH BACKEND ALLOCATOR ##
+
+ def array(self, shape, dtype=HYSOP_REAL, order=default_order,
+ min_alignment=None, buf=None, offset=0):
+ """
+ Create a HostArray, see np.ndarray constructor.
+ If buf is None, a new one is allocated from backend allocator.
+ """
+
+ order = self._arg(order)
+ shape = to_tuple(shape)
+
+ if dtype==np.bool:
+ dtype=HYSOP_BOOL
+ import warning
+ msg='HostArrayBackend: numpy bool array converted to hysop_bool={}.'.format(dtype)
+ warning.warn(msg, userwarning)
+
+ if (buf is None):
+ assert offset==0
+ allocator = self.allocator
+ dtype = np.dtype(dtype)
+ (size,nbytes,alignment) = self.get_alignment_and_size(shape=shape,
+ dtype=dtype, min_alignment=min_alignment)
+ alloc = allocator.allocate_aligned(size, alignment=alignment)
+ handle = HostBuffer(buffer=alloc, shape=shape, dtype=dtype, order=order,
+ offset=0, strides=None, size=None)
+ array = self.wrap(handle=handle)
+ else:
+ handle = np.frombuffer(buf, offset=offset, dtype=dtype)
+ handle = handle.reshape(shape=shape, order=order)
+ array = self.wrap(handle=handle)
+ return array
+
+ def empty(self, shape, dtype=HYSOP_REAL,
+ order=default_order, min_alignment=None):
+ """
+ Return a new array of given shape and type, without initializing entries.
+ Data is allocated from backend allocator.
+ """
+ return self.array(shape=shape, dtype=dtype,
+ order=order, min_alignment=min_alignment)
+
+
+ def full(self, shape, fill_value, dtype=HYSOP_REAL,
+ order=default_order, min_alignment=None):
+ """
+ Return a new array of given shape and type, filled with fill_value.
+ Data is allocated from backend allocator.
+ """
+ a = self.empty(shape=shape, dtype=dtype,
+ order=order, min_alignment=min_alignment)
+ self.fill(a=a, value=fill_value)
+ return a
+
+ def zeros(self, shape, dtype=HYSOP_REAL,
+ order=default_order, min_alignment=None):
+ """
+ Return a new array of given shape and type, filled with zeros.
+ Data is allocated from backend allocator.
+ """
+ return self.full(shape=shape, dtype=dtype, order=order,
+ fill_value=0, min_alignment=min_alignment)
+
+ def ones(self, shape, dtype=HYSOP_REAL,
+ order=default_order, min_alignment=None):
+ """
+ Return a new array of given shape and type, filled with ones.
+ Data is allocated from backend allocator.
+ """
+ return self.full(shape=shape, dtype=dtype, order=order,
+ fill_value=1, min_alignment=min_alignment)
+
+
+
+ def empty_like(self, a, dtype=None, order=None, subok=True):
+ """
+ Return a new array with the same shape and type as a given array.
+ Data is allocated from backend allocator.
+ """
+ self._unsupported_argument('empty_like', 'subok', subok, True)
+ if (order == MemoryOrdering.SAME_ORDER) or (order is None):
+ order = a.order
+ return self.empty(
+ shape = a.shape,
+ dtype = dtype or a.dtype,
+ order = order)
+
+ def full_like(self, a, fill_value, dtype=None, order=None, subok=True):
+ """
+ Return a new array with the same shape and type as a given array.
+ Data is allocated from backend allocator.
+ """
+ a = self.empty_like(a=a, dtype=dtype, order=order, subok=subok)
+ self.fill(a, value=fill_value)
+ return a
+
+ def zeros_like(self, a, dtype=None, order=None, subok=True):
+ """
+ Return an array of zeros with the same shape and type as a given array.
+ Data is allocated from backend allocator.
+ """
+ return self.full_like(a=a,fill_value=0,dtype=dtype,order=order,subok=subok)
+
+ def ones_like(self, a, dtype=None, order=None, subok=True):
+ """
+ Return an array of ones with the same shape and type as a given array.
+ Data is allocated from backend allocator.
+ """
+ return self.full_like(a=a,fill_value=1,dtype=dtype,order=order,subok=subok)
+
+# Filling facility
+ def fill(self, a, value):
+ """
+ Fill the array with given value.
+ """
+ a.handle.fill(value)
+
+
+#### ALLOCATED FROM WITHIN NUMPY ####
+# Ones and zeros
+ @numpy_method
+ def eye(self, N, M, k, dtype=None):
+ """
+ Return a 2-D array with ones on the diagonal and zeros elsewhere.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def identity(self, n, dtype=None):
+ """
+ Return the identity array.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ def copy(self, a, order=MemoryOrdering.SAME_ORDER):
+ """
+ Return an array copy of the given object.
+ """
+ b = self.empty_like(a, order=order)
+ b[...] = a[...]
+ return b
+
+ @numpy_method
+ def asarray(self, a, dtype=None, order=default_order):
+ """
+ Convert the input to an HostArray.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def asanyarray(self, a, dtype=None, order=default_order):
+ """
+ Convert the input to an ndarray, but pass ndarray subclasses through.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def asmatrix(self, data, dtype=None):
+ """
+ Interpret the input as a matrix.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def frombuffer(self, afer, dtype=HYSOP_REAL, count=-1, offset=0):
+ """
+ Interpret a afer as a 1-dimensional array.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def fromfile(self, file, dtype=HYSOP_REAL, count=-1, sep=''):
+ """
+ Construct an array from data in a text or binary file.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def fromfunction(self, function, shape, dtype=HYSOP_REAL):
+ """
+ Construct an array by executing a function over each coordinate.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def fromiter(self, iterable, dtype=HYSOP_REAL, count=-1):
+ """
+ Create a new 1-dimensional array from an iterable object.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def fromstring(self, string, dtype=HYSOP_REAL, count=-1, sep=''):
+ """
+ A new 1-D array initialized from raw binary or text data in a string.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def loadtxt(self, fname, dtype=HYSOP_REAL, comments='#', delimiter=None,
+ converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0):
+ """
+ Load data from a text file.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+
+#Numerical ranges
+
+ def arange(self, *args, **kargs):
+ """
+ Return evenly spaced values within a given interval.
+ Data is *not* allocated from backend allocator.
+ """
+ if 'dtype' not in kargs:
+ kargs['dtype'] = HYSOP_INTEGER
+ handle = np.arange(*args,**kargs)
+ return self.wrap(handle)
+
+ @numpy_method
+ def linspace(self, start, stop, num=50, endpoint=True, retstep=False, dtype=HYSOP_REAL):
+ """
+ Return evenly spaced numbers over a specified interval.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def logspace(self, start, stop, num=50, endpoint=True, base=10.0, dtype=HYSOP_REAL):
+ """
+ Return numbers spaced evenly on a log scale.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def geomspace(self, start, stop, num=50, endpoint=True, dtype=HYSOP_REAL):
+ """
+ Return numbers spaced evenly on a log scale (a geometric progression).
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def meshgrid(self, *xi, **kwargs):
+ """
+ Return coordinate matrices from coordinate vectors.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+
+#Building matrices
+ @numpy_method
+ def diag(self, v, k=0):
+ """
+ Extract a diagonal or construct a diagonal array.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def diagflat(self, v, k=0):
+ """
+ Create a two-dimensional array with the flattened input as a diagonal.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def tri(self, N, M=None, k=0, dtype=HYSOP_REAL):
+ """
+ An array with ones at and below the given diagonal and zeros elsewhere.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def tril(self, m, k):
+ """
+ Lower triangle of an array.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def triu(self, m, k=0):
+ """
+ Upper triangle of an array.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+ @numpy_method
+ def vander(self, x, N=None, increasing=False):
+ """
+ Generate a Vandermonde matrix.
+ Data is *not* allocated from backend allocator.
+ """
+ pass
+
+
+###############################
+# ARRAY MANIPULATION ROUTINES #
+## See https://docs.scipy.org/doc/numpy/reference/routines.array-manipulation.html
+
+#Changing array shape
+ @numpy_method
+ def reshape(self, a, newshape, order=default_order):
+ """
+ Gives a new shape to an array without changing its data.
+ """
+ pass
+ @numpy_method
+ def ravel(self, a, order=MemoryOrdering.SAME_ORDER):
+ """
+ Return a contiguous flattened array.
+ """
+ pass
+
+#Transpose-like operations
+## /!\ those functions can alter the transposition state /!\
+ @numpy_method
+ def moveaxis(self, a, source, destination):
+ """
+ Move axes of an array to new positions.
+ """
+ self.not_implemented_yet('moveaxis')
+ @numpy_method
+ def rollaxis(self, a, axis, start=0):
+ """
+ Roll the specified axis backwards, until it lies in a given position.
+ """
+ self.not_implemented_yet('rollaxis')
+ @numpy_method
+ def swapaxes(self, a, axis1, axis2):
+ """
+ Interchange two axes of an array.
+ """
+ self.not_implemented_yet('swapaxes')
+ @numpy_method
+ def transpose(self, a, axes=None):
+ """
+ Permute the dimensions of an array.
+ """
+ self.not_implemented_yet('transpose')
+
+
+
+#Changing number of dimensions
+ @numpy_method
+ def atleast_1d(self, *arys):
+ """
+ Convert inputs to arrays with at least one dimension.
+ """
+ pass
+ @numpy_method
+ def atleast_2d(self, *arys):
+ """
+ View inputs as arrays with at least two dimensions.
+ """
+ pass
+ @numpy_method
+ def atleast_3d(self, *arys):
+ """
+ View inputs as arrays with at least three dimensions.
+ """
+ pass
+ @numpy_method
+ def broadcast_to(self, array, shape, subok=False):
+ """
+ Broadcast an array to a new shape.
+ """
+ pass
+ @numpy_method
+ def broadcast_arrays(self, *args, **kwargs):
+ """
+ Broadcast any number of arrays against each other.
+ """
+ pass
+ @numpy_method
+ def expand_dims(self, a, axis):
+ """
+ Expand the shape of an array.
+ """
+ pass
+ @numpy_method
+ def squeeze(self, a, axis=None):
+ """
+ Remove single-dimensional entries from the shape of an array.
+ """
+ pass
+
+#Changing kind of array
+ @numpy_method
+ def asfortranarray(self, a, dtype=None):
+ """
+ Return an array laid out in Fortran order in memory.
+ """
+ pass
+ @numpy_method
+ def ascontiguousarray(self, a, dtype=None):
+ """
+ Return a contiguous array in memory (C order).
+ """
+ pass
+ @numpy_method
+ def asarray_chkfinite(self, a, dtype=None, order=default_order):
+ """
+ Convert the input to an array, checking for NaNs or Infs.
+ """
+ pass
+ @numpy_method
+ def asscalar(self, a):
+ """
+ Convert an array of size 1 to its scalar equivalent.
+ """
+ pass
+ @numpy_method
+ def require(self, a, dtype=None, requirements=None):
+ """
+ Return an ndarray of the provided type that satisfies requirements.
+ """
+ pass
+
+#Joining arrays
+ @numpy_method
+ def concatenate(self, a, axis=0):
+ """
+ Join a sequence of arrays along an existing axis.
+ """
+ pass
+ @numpy_method
+ def stack(self, arrays, axis=0):
+ """
+ Join a sequence of arrays along a new axis.
+ """
+ pass
+ @numpy_method
+ def column_stack(self, tup):
+ """
+ Stack 1-D arrays as columns into a 2-D array.
+ """
+ pass
+ @numpy_method
+ def dstack(self, tup):
+ """
+ Stack arrays in sequence depth wise (along third axis).
+ """
+ pass
+ @numpy_method
+ def hstack(self, tup):
+ """
+ Stack arrays in sequence horizontally (column wise).
+ """
+ pass
+ @numpy_method
+ def vstack(self, tup):
+ """
+ Stack arrays in sequence vertically (row wise).
+ """
+ pass
+
+#Splitting arrays
+ @numpy_method
+ def split(self, ary, indices_or_sections, axis=0):
+ """
+ Split an array into multiple sub-arrays.
+ """
+ pass
+ @numpy_method
+ def array_split(self, ary, indices_or_sections, axis=0):
+ """
+ Split an array into multiple sub-arrays.
+ """
+ pass
+ @numpy_method
+ def dsplit(self, ary, indices_or_sections):
+ """
+ Split array into multiple sub-arrays along the 3rd axis (depth).
+ """
+ pass
+ @numpy_method
+ def hsplit(self, ary, indices_or_sections):
+ """
+ Split an array into multiple sub-arrays horizontally (column-wise).
+ """
+ pass
+ @numpy_method
+ def vsplit(self, ary, indices_or_sections):
+ """
+ Split an array into multiple sub-arrays vertically (row-wise).
+ """
+ pass
+
+#Tiling arrays
+ @numpy_method
+ def tile(self, A, reps):
+ """
+ Construct an array by repeating A the number of times given by reps.
+ """
+ pass
+ @numpy_method
+ def repeat(self, a, repeats, axis=None):
+ """
+ Repeat elements of an array.
+ """
+ pass
+
+#Adding and removing elements
+ @numpy_method
+ def delete(self, arr, obj, axis=None):
+ """
+ Return a new array with sub-arrays along an axis deleted.
+ """
+ pass
+ @numpy_method
+ def insert(self, arr, obj, values, axis=None):
+ """
+ Insert values along the given axis before the given indices.
+ """
+ pass
+ @numpy_method
+ def append(self, arr, values, axis=None):
+ """
+ Append values to the end of an array.
+ """
+ pass
+ @numpy_method
+ def resize(self, a, new_shape):
+ """
+ Return a new array with the specified shape.
+ """
+ pass
+ @numpy_method
+ def trim_zeros(self, filt, trim='fb'):
+ """
+ Trim the leading and/or trailing zeros from a 1-D array or sequence.
+ """
+ pass
+ @numpy_method
+ def unique(self, ar, return_index=False, return_inverse=False, return_counts=False):
+ """
+ Find the unique elements of an array.
+ """
+ pass
+
+#Rearranging elements
+ @numpy_method
+ def flip(self, m, axis):
+ """
+ Reverse the order of elements in an array along the given axis.
+ """
+ pass
+ @numpy_method
+ def fliplr(self, m):
+ """
+ Flip array in the left/right direction.
+ """
+ pass
+ @numpy_method
+ def flipud(self, m):
+ """
+ Flip array in the up/down direction.
+ """
+ pass
+ @numpy_method
+ def roll(self, a, shift, axis=None):
+ """
+ Roll array elements along a given axis.
+ """
+ pass
+ @numpy_method
+ def rot90(self, m, k=1, axes=(0,1)):
+ """
+ Rotate an array by 90 degrees in the plane specified by axes.
+ """
+ pass
+
+
+#####################
+# BINARY OPERATIONS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.bitwise.html
+
+# Elementwise bit operations
+ @numpy_method
+ def bitwise_and(self, x1, x2, out=None):
+ """
+ Compute the bit-wise AND of two arrays element-wise.
+ """
+ pass
+ @numpy_method
+ def bitwise_or(self, x1, x2, out=None):
+ """
+ Compute the bit-wise OR of two arrays element-wise.
+ """
+ pass
+ @numpy_method
+ def bitwise_xor(self, x1, x2, out=None):
+ """
+ Compute the bit-wise XOR of two arrays element-wise.
+ """
+ pass
+
+ @numpy_method
+ def invert(self, x, out=None):
+ """
+ Compute bit-wise inversion, or bit-wise NOT, element-wise.
+ """
+ pass
+ @numpy_method
+ def left_shift(self, x1, x2, out=None):
+ """
+ Shift the bits of an integer to the left.
+ """
+ pass
+ @numpy_method
+ def right_shift(self, x1, x2, out=None):
+ """
+ Shift the bits of an integer to the right.
+ """
+ pass
+
+#Bit packing
+ @numpy_method
+ def packbits(self, myarray, axis=None):
+ """
+ Packs the elements of a binary-valued array into bits in a uint8 array.
+ """
+ pass
+ @numpy_method
+ def unpackbits(self, myarray, axis=None):
+ """
+ Unpacks elements of a uint8 array into a binary-valued output array.
+ """
+ pass
+
+#Output formatting
+ @numpy_method
+ def binary_repr(self, num, width=None):
+ """
+ Return the binary representation of the input number as a string.
+ """
+ pass
+
+
+##############################
+# DISCRETE FOURIER TRANSFORM #
+## See https://docs.scipy.org/doc/numpy/reference/routines.fft.html
+
+#Standard FFTs
+ @numpy_method
+ def fft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the one-dimensional discrete Fourier Transform.
+ """
+ pass
+ @numpy_method
+ def ifft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the one-dimensional inverse discrete Fourier Transform.
+ """
+ pass
+ @numpy_method
+ def fft2(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the 2-dimensional discrete Fourier Transform
+ """
+ pass
+ @numpy_method
+ def ifft2(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the 2-dimensional inverse discrete Fourier Transform.
+ """
+ pass
+ @numpy_method
+ def fftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the N-dimensional discrete Fourier Transform.
+ """
+ pass
+ @numpy_method
+ def ifftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the N-dimensional inverse discrete Fourier Transform.
+ """
+ pass
+
+#Real FFTs
+ @numpy_method
+ def rfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the one-dimensional discrete Fourier Transform for real input.
+ """
+ pass
+ @numpy_method
+ def irfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the inverse of the n-point DFT for real input.
+ """
+ pass
+ @numpy_method
+ def rfft2(self, a, s=None, axes=(-2,-1), norm=None):
+ """
+ Compute the 2-dimensional FFT of a real array.
+ """
+ pass
+ @numpy_method
+ def irfft2(self, a, s=None, axes=(-2,-1), norm=None):
+ """
+ Compute the 2-dimensional inverse FFT of a real array.
+ """
+ pass
+ @numpy_method
+ def rfftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the N-dimensional discrete Fourier Transform for real input.
+ """
+ pass
+ @numpy_method
+ def irfftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the inverse of the N-dimensional FFT of real input.
+ """
+ pass
+
+#Hermitian FFTs
+ @numpy_method
+ def hfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the FFT of a signal that has Hermitian symmetry, i.e., a real spectrum.
+ """
+ pass
+ @numpy_method
+ def ihfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the inverse FFT of a signal that has Hermitian symmetry.
+ """
+ pass
+
+#Helper routines
+ @numpy_method
+ def fftfreq(self, n=None, d=1.0):
+ """
+ Return the Discrete Fourier Transform sample frequencies.
+ """
+ pass
+ @numpy_method
+ def rfftfreq(self, n=None, d=1.0):
+ """
+ Return the Discrete Fourier Transform sample frequencies (for usage with rfft, irfft).
+ """
+ pass
+ @numpy_method
+ def fftshift(self, x, axes=None):
+ """
+ Shift the zero-frequency component to the center of the spectrum.
+ """
+ pass
+ @numpy_method
+ def ifftshift(self, x, axes=None):
+ """
+ The inverse of fftshift.
+ """
+ pass
+
+
+##########################
+# FUNCTIONAL PROGRAMMING #
+## See https://docs.scipy.org/doc/numpy/reference/routines.functional.html
+
+ @numpy_method
+ def vectorize(self, pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None):
+ """
+ Generalized function class.
+ """
+ pass
+ @numpy_method
+ def frompyfunc(self, func, nin, nout):
+ """
+ Takes an arbitrary Python function and returns a NumPy ufunc.
+ """
+ pass
+ @numpy_method
+ def piecewise(self, x, condlist, funclist, *args, **kw):
+ """
+ Evaluate a piecewise-defined function.
+ """
+ pass
+
+####################
+# INPUT AND OUTPUT #
+## See https://docs.scipy.org/doc/numpy/reference/routines.io.html
+
+# NumPy binary files (NPY, NPZ)
+ @numpy_method
+ def load(self, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'):
+ """
+ Load arrays or pickled objects from .npy, .npz or pickled files.
+ """
+ pass
+ @numpy_method
+ def save(self, arr, file, allow_pickle=True, fix_imports=True):
+ """
+ Save an array to a binary file in NumPy .npy format.
+ """
+ pass
+ @numpy_method
+ def savez(self, file, *args, **kwds):
+ """
+ Save several arrays into a single file in uncompressed .npz format.
+ """
+ pass
+ @numpy_method
+ def savez_compressed(self, file, *args, **kwds):
+ """
+ Save several arrays into a single file in compressed .npz format.
+ """
+ pass
+
+# Text files
+ @numpy_method
+ def loadtxt(self, dtype=HYSOP_REAL, comments='#', delimiter=None,
+ converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0):
+ """
+ Load data from a text file.
+ """
+ pass
+ @numpy_method
+ def savetxt(self, fname, X, fmt='%.18e', delimiter=' ', newline='\n',
+ header='', footer='', comments='# '):
+ """
+ Save an array to a text file.
+ """
+ pass
+ @numpy_method
+ def genfromtxt(self, fname, dtype=HYSOP_REAL, comments='#', delimiter=None,
+ skip_header=0, skip_footer=0, converters=None, missing_values=None,
+ filling_values=None, usecols=None, names=None, excludelist=None, deletechars=None,
+ replace_space='_', autostrip=False, case_sensitive=True, defaultfmt='f%i',
+ unpack=None, usemask=False, loose=True, invalid_raise=True, max_rows=None):
+ """
+ Load data from a text file, with missing values handled as specified.
+ """
+ pass
+ @numpy_method
+ def fromregex(self, file, regexp, dtype):
+ """
+ Construct an array from a text file, using regular expression parsing.
+ """
+ pass
+ @numpy_method
+ def fromstring(self, string, dtype=HYSOP_REAL, count=-1, sep=''):
+ """
+ A new 1-D array initialized from raw binary or text data in a string.
+ """
+ pass
+
+# String formatting
+ @numpy_method
+ def array2string(self, a, max_line_width=None, precision=None, suppress_small=None,
+ separator=' ', prefix='', style=repr, formatter=None):
+ """
+ Return a string representation of an array.
+ """
+ pass
+ @numpy_method
+ def array_repr(self, arr, max_line_width=None, precision=None, supress_small=None):
+ """
+ Return the string representation of an array.
+ """
+ pass
+ @numpy_method
+ def array_str(self, a, max_line_width=None, precision=None, suppress_small=None):
+ """
+ Return a string representation of the data in an array.
+ """
+ pass
+#Text formatting options
+ @numpy_method
+ def set_printoptions(self, precision=None, threshold=None, edgeitems=None,
+ linewidth=None, suppress=None, nanstr=None,
+ infstr=None, formatter=None):
+ """
+ Set printing options.
+ """
+ pass
+ @numpy_method
+ def get_printoptions(self):
+ """
+ Return the current print options.
+ """
+ pass
+ @numpy_method
+ def set_string_function(self, f, repr=True):
+ """
+ Set a Python function to be used when pretty printing arrays.
+ """
+ pass
+#Base-n representations
+ @numpy_method
+ def binary_repr(self, num, width=None):
+ """
+ Return the binary representation of the input number as a string.
+ """
+ pass
+ @numpy_method
+ def base_repr(self, number, base=2, padding=0):
+ """
+ Return a string representation of a number in the given base system.
+ """
+ pass
+
+
+######################
+### LINEAR ALGEBRA ###
+## See https://docs.scipy.org/doc/numpy/reference/routines.linalg.html
+
+#Matrix and vector products
+ @numpy_method
+ def dot(self, a, b, out=None):
+ """
+ Dot product of two arrays.
+ """
+ pass
+ @numpy_method
+ def vdot(self, a, b):
+ """
+ Return the dot product of two vectors.
+ """
+ pass
+ @numpy_method
+ def inner(self, a, b):
+ """
+ Inner product of two arrays.
+ """
+ pass
+ @numpy_method
+ def outer(self, a, b, out=None):
+ """
+ Compute the outer product of two vectors.
+ """
+ pass
+ @numpy_method
+ def matmul(self, a, b, out=None):
+ """
+ Matrix product of two arrays.
+ """
+ pass
+ @numpy_method
+ def tensordot(self, a, b, axes=2):
+ """
+ Compute tensor dot product along specified axes for arrays >= 1-D.
+ """
+ pass
+ @numpy_method
+ def einsum(self, subscripts, out=None, dtype=None, order=MemoryOrdering.SAME_ORDER,
+ casting='safe', optimize=False, *operands):
+ """
+ Evaluates the Einstein summation convention on the operands.
+ """
+ pass
+ @numpy_method
+ def matrix_power(self, M, n):
+ """
+ Raise a square matrix to the integer power n.
+ """
+ pass
+ @numpy_method
+ def kron(self, a, b):
+ """
+ Kronecker product of two arrays.
+ """
+ pass
+
+#Decompositions
+ @numpy_method
+ def cholesky(self, a):
+ """
+ Cholesky decomposition.
+ """
+ pass
+ @numpy_method
+ def qr(self, a, mode='reduced'):
+ """
+ Compute the qr factorization of a matrix.
+ """
+ pass
+ @numpy_method
+ def svd(self, a, full_matrices=True, compute_uv=True):
+ """
+ Singular Value Decomposition.
+ """
+ pass
+
+#Matrix eigenvalues
+ @numpy_method
+ def eig(self, a):
+ """
+ Compute the eigenvalues and right eigenvectors of a square array.
+ """
+ pass
+ @numpy_method
+ def eigh(self, a, UPLO='L'):
+ """
+ Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix.
+ """
+ pass
+ @numpy_method
+ def eigvals(self, a):
+ """
+ Compute the eigenvalues of a general matrix.
+ """
+ pass
+ @numpy_method
+ def eigvalsh(self, a, UPLO='L'):
+ """
+ Compute the eigenvalues of a Hermitian or real symmetric matrix.
+ """
+ pass
+
+#Norms and other numbers
+ @numpy_method
+ def norm(self, x, ord=None, axis=None, keepdims=False):
+ """
+ Matrix or vector norm.
+ """
+ pass
+ @numpy_method
+ def cond(self, x, p=None):
+ """
+ Compute the condition number of a matrix.
+ """
+ pass
+ @numpy_method
+ def det(self, a):
+ """
+ Compute the determinant of an array.
+ """
+ pass
+ @numpy_method
+ def matrix_rank(self, M, tol=None):
+ """
+ Return matrix rank of array using SVD method
+ """
+ pass
+ @numpy_method
+ def slogdet(self, a):
+ """
+ Compute the sign and natural logarithm of the determinant of an array.
+ """
+ pass
+ @numpy_method
+ def trace(self, a, offset=0, axis1=0, axis2=1, dtype=None, out=None):
+ """
+ Return the sum along diagonals of the array.
+ """
+ pass
+
+#Solving equations and inverting matrices
+ @numpy_method
+ def solve(self, a, b):
+ """
+ Solve a linear matrix equation, or system of linear scalar equations.
+ """
+ pass
+ @numpy_method
+ def tensorsolve(self, a, b, axes=None):
+ """
+ Solve the tensor equation a x = b for x.
+ """
+ pass
+ @numpy_method
+ def lstsq(self, a, b, rcond=-1):
+ """
+ Return the least-squares solution to a linear matrix equation.
+ """
+ pass
+ @numpy_method
+ def inv(self, a):
+ """
+ Compute the (multiplicative) inverse of a matrix.
+ """
+ pass
+ @numpy_method
+ def pinv(self, a, rcond=1e-15):
+ """
+ Compute the (Moore-Penrose) pseudo-inverse of a matrix.
+ """
+ pass
+ @numpy_method
+ def tensorinv(self, a, ind=2):
+ """
+ Compute the 'inverse' of an N-dimensional array.
+ """
+ pass
+
+
+###################
+# LOGIC FUNCTIONS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.logic.html
+
+#Truth value testing
+ @numpy_method
+ def any(self, a, axis=None, out=None):
+ """
+ Test whether any array elements along a given axis evaluate to True.
+ """
+ pass
+ @numpy_method
+ def all(self, a, axis=None, out=None):
+ """
+ Test whether all array elements along a given axis evaluate to True.
+ """
+ pass
+
+#Array contents
+ @numpy_method
+ def isfinite(self, x, out=None):
+ """
+ Test element-wise for finiteness (not infinity or not Not a Number).
+ """
+ pass
+ @numpy_method
+ def isinf(self, x, out=None):
+ """
+ Test element-wise for positive or negative infinity.
+ """
+ pass
+ @numpy_method
+ def isnan(self, x, out=None):
+ """
+ Test element-wise for NaN and return result as a boolean array.
+ """
+ pass
+ @numpy_method
+ def isneginf(self, x, out=None):
+ """
+ Test element-wise for negative infinity, return result as bool array.
+ """
+ pass
+ @numpy_method
+ def isposinf(self, x, out=None):
+ """
+ Test element-wise for positive infinity, return result as bool array.
+ """
+ pass
+
+#Logical operations
+ @numpy_method
+ def logical_and(self, x1, x2, out=None):
+ """
+ Compute the truth value of x1 AND x2 element-wise.
+ """
+ pass
+ @numpy_method
+ def logical_or(self, x1, x2, out=None):
+ """
+ Compute the truth value of x1 OR x2 element-wise.
+ """
+ pass
+ @numpy_method
+ def logical_not(self, x, out=None):
+ """
+ Compute the truth value of NOT x element-wise.
+ """
+ pass
+ @numpy_method
+ def logical_xor(self, x1, x2, out=None):
+ """
+ Compute the truth value of x1 XOR x2, element-wise.
+ """
+ pass
+
+#Comparisson
+ @numpy_method
+ def allclose(self, a, b, rtol=1e-05, atol=1e-08, equal_nan=False):
+ """
+ Returns True if two arrays are element-wise equal within a tolerance.
+ """
+ pass
+ @numpy_method
+ def isclose(self, a, b, rtol=1e-05, atol=1e-08, equal_nan=False):
+ """
+ Returns a boolean array where two arrays are element-wise equal within a tolerance.
+ """
+ pass
+ @numpy_method
+ def array_equal(self, a1, a2):
+ """
+ True if two arrays have the same shape and elements, False otherwise.
+ """
+ pass
+ @numpy_method
+ def array_equiv(self, a1, a2):
+ """
+ returns True if input arrays are shape consistent and all elements equal.
+ """
+ pass
+ @numpy_method
+ def greater(self, x1, x2, out=None):
+ """
+ Return the truth value of (x1 > x2) element-wise.
+ """
+ pass
+ @numpy_method
+ def greater_equal(self, x1, x2, out=None):
+ """
+ Return the truth value of (x1 >= x2) element-wise.
+ """
+ pass
+ @numpy_method
+ def less(self, x1, x2, out=None):
+ """
+ Return the truth value of (x1 < x2) element-wise.
+ """
+ pass
+ @numpy_method
+ def less_equal(self, x1, x2, out=None):
+ """
+ Return the truth value of (x1 =< x2) element-wise.
+ """
+ pass
+ @numpy_method
+ def equal(self, x1, x2, out=None):
+ """
+ Return (x1 == x2) element-wise.
+ """
+ pass
+ @numpy_method
+ def not_equal(self, x1, x2, out=None):
+ """
+ Return (x1 != x2) element-wise.
+ """
+ pass
+
+
+##########################
+# MATHEMATICAL FUNCTIONS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.math.html
+
+# Trigonometric functions
+ @numpy_method
+ def sin(self, x, out=None):
+ """
+ Trigonometric sine, element-wise.
+ """
+ pass
+ @numpy_method
+ def cos(self, x, out=None):
+ """
+ Cosine element-wise.
+ """
+ pass
+ @numpy_method
+ def tan(self, x, out=None):
+ """
+ Compute tangent element-wise.
+ """
+ pass
+
+ @numpy_method
+ def arcsin(self, x, out=None):
+ """
+ Inverse sine, element-wise.
+ """
+ pass
+ @numpy_method
+ def arccos(self, x, out=None):
+ """
+ Trigonometric inverse cosine, element-wise.
+ """
+ pass
+ @numpy_method
+ def arctan(self, x, out=None):
+ """
+ Trigonometric inverse tangent, element-wise.
+ """
+ pass
+ @numpy_method
+ def arctan2(self, x1, x2, out=None):
+ """
+ Element-wise arc tangent of x1/x2 choosing the quadrant correctly.
+ """
+ pass
+
+ @numpy_method
+ def hypot(self, x1, x2, out=None):
+ """
+ Given the legs of a right triangle, return its hypotenuse.
+ """
+ pass
+ @numpy_method
+ def unwrap(self, p, discont=3.141592653589793, axis=-1):
+ """
+ Unwrap by changing deltas between values to 2*pi complement.
+ """
+ pass
+ @numpy_method
+ def deg2rad(self, x, out=None):
+ """
+ Convert angles from degrees to radians.
+ """
+ pass
+ @numpy_method
+ def rad2deg(self, x, out=None):
+ """
+ Convert angles from radians to degrees.
+ """
+ pass
+
+# Hyperbolic functions
+ @numpy_method
+ def sinh(self, x, out=None):
+ """
+ Hyperbolic sine, element-wise.
+ """
+ pass
+ @numpy_method
+ def cosh(self, x, out=None):
+ """
+ Hyperbolic cosine, element-wise.
+ """
+ pass
+ @numpy_method
+ def tanh(self, x, out=None):
+ """
+ Compute hyperbolic tangent element-wise.
+ """
+ pass
+
+ @numpy_method
+ def arcsinh(self, x, out=None):
+ """
+ Inverse hyperbolic sine element-wise.
+ """
+ pass
+ @numpy_method
+ def arccosh(self, x, out=None):
+ """
+ Inverse hyperbolic cosine, element-wise.
+ """
+ pass
+ @numpy_method
+ def arctanh(self, x, out=None):
+ """
+ Inverse hyperbolic tangent element-wise.
+ """
+ pass
+
+# Rounding
+ @numpy_method
+ def around(self, a, decimals=0, out=None):
+ """
+ Evenly round to the given number of decimals.
+ """
+ pass
+
+ @numpy_method
+ def fix(self, x, y=None):
+ """
+ Round to nearest integer towards zero.
+ """
+ pass
+
+ @numpy_method
+ def rint(self, x, out=None):
+ """
+ Round elements of the array to the nearest integer.
+ """
+ pass
+ @numpy_method
+ def floor(self, x, out=None):
+ """
+ Return the floor of the input, element-wise.
+ """
+ pass
+ @numpy_method
+ def ceil(self, x, out=None):
+ """
+ Return the ceiling of the input, element-wise.
+ """
+ pass
+ @numpy_method
+ def trunc(self, x, out=None):
+ """
+ Return the truncated value of the input, element-wise.
+ """
+ pass
+
+
+# Sums, product, differences
+ @numpy_method
+ def prod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the product of array elements over a given axis.
+ """
+ pass
+ @numpy_method
+ def sum(self, a, axis=None, dtype=None, out=None):
+ """
+ Sum of array elements over a given axis.
+ """
+ pass
+ @numpy_method
+ def nanprod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the product of array elements over a given axis treating
+ Not a Numbers (NaNs) as ones.
+ """
+ pass
+ @numpy_method
+ def nansum(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.
+ """
+ pass
+ @numpy_method
+ def cumprod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative product of elements along a given axis.
+ """
+ pass
+ @numpy_method
+ def cumsum(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative sum of the elements along a given axis.
+ """
+ pass
+ @numpy_method
+ def nancumprod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative product of array elements over a given axis treating
+ Not a Numbers (NaNs) as one.
+ """
+ pass
+ @numpy_method
+ def nancumsum(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative sum of array elements over a given axis treating
+ Not a Numbers (NaNs) as zero.
+ """
+ pass
+ @numpy_method
+ def diff(self, a, n=1, axis=-1):
+ """
+ Calculate the n-th discrete difference along given axis.
+ """
+ pass
+ @numpy_method
+ def ediff1d(self, ary, to_end=None, to_begin=None):
+ """
+ The differences between consecutive elements of an array.
+ """
+ pass
+ @numpy_method
+ def gradient(self, f, *varargs, **kwargs):
+ """
+ Return the gradient of an N-dimensional array.
+ """
+ pass
+ @numpy_method
+ def cross(self, a, b, axisa=-1, axisb=-1, axisc=-1, axis=None):
+ """
+ Return the cross product of two (arrays of) vectors.
+ """
+ pass
+ @numpy_method
+ def trapz(self, y, x=None, dx=1.0, axis=-1):
+ """
+ Integrate along the given axis using the composite trapezoidal rule.
+ """
+ pass
+
+#Exponents and logarithms
+ @numpy_method
+ def exp(self, x, out=None):
+ """
+ Calculate the exponential of all elements in the input array.
+ """
+ pass
+ @numpy_method
+ def exp2(self, x, out=None):
+ """
+ Calculate 2**p for all p in the input array.
+ """
+ pass
+ @numpy_method
+ def expm1(self, x, out=None):
+ """
+ Calculate exp(x) - 1 for all elements in the array.
+ """
+ pass
+
+ @numpy_method
+ def log(self, x, out=None):
+ """
+ Natural logarithm, element-wise.
+ """
+ pass
+ @numpy_method
+ def log2(self, x, out=None):
+ """
+ Base-2 logarithm of x.
+ """
+ pass
+ @numpy_method
+ def log10(self, x, out=None):
+ """
+ Return the base 10 logarithm of the input array, element-wise.
+ """
+ pass
+ @numpy_method
+ def log1p(self, x, out=None):
+ """
+ Return the natural logarithm of one plus the input array, element-wise.
+ """
+ pass
+
+ @numpy_method
+ def logaddexp(self, x1, x2, out=None):
+ """
+ Logarithm of the sum of exponentiations of the inputs.
+ """
+ pass
+ @numpy_method
+ def logaddexp2(self, x1, x2, out=None):
+ """
+ Logarithm of the sum of exponentiations of the inputs in base-2.
+ """
+ pass
+
+# Other special functions
+ @numpy_method
+ def i0(self, x):
+ """
+ Modified Bessel function of the first kind, order 0.
+ """
+ pass
+ @numpy_method
+ def sinc(self, x):
+ """
+ Return the sinc function.
+ """
+ pass
+
+# Floating point routines
+ @numpy_method
+ def signbit(self, x, out=None):
+ """
+ Returns element-wise True where signbit is set (less than zero).
+ """
+ pass
+ @numpy_method
+ def copysign(self, x1, x2, out=None):
+ """
+ Change the sign of x1 to that of x2, element-wise.
+ """
+ pass
+ @numpy_method
+ def frexp(self, x, out1=None, out2=None):
+ """
+ Decompose the elements of x into mantissa and twos exponent.
+ """
+ pass
+ @numpy_method
+ def ldexp(self, x1, x2, out=None):
+ """
+ Returns x1 * 2**x2, element-wise.
+ """
+ pass
+
+
+# Arithmetic operations
+ @numpy_method
+ def add(self, x1, x2, out=None):
+ """
+ Add arguments element-wise.
+ """
+ pass
+ @numpy_method
+ def reciprocal(self, x, out=None):
+ """
+ Return the reciprocal of the argument, element-wise.
+ """
+ pass
+ @numpy_method
+ def negative(self, x, out=None):
+ """
+ Numerical negative, element-wise.
+ """
+ pass
+ @numpy_method
+ def multiply(self, x1, x2, out=None):
+ """
+ Multiply arguments element-wise.
+ """
+ pass
+ @numpy_method
+ def divide(self, x1, x2, out=None):
+ """
+ Divide arguments element-wise.
+ """
+ pass
+ @numpy_method
+ def power(self, x1, x2, out=None):
+ """
+ First array elements raised to powers from second array, element-wise.
+ """
+ pass
+ @numpy_method
+ def subtract(self, x1, x2, out=None):
+ """
+ Subtract arguments, element-wise.
+ """
+ pass
+ @numpy_method
+ def true_divide(self, x1, x2, out=None):
+ """
+ Returns a true division of the inputs, element-wise.
+ """
+ pass
+ @numpy_method
+ def floor_divide(self, x1, x2, out=None):
+ """
+ Return the largest integer smaller or equal to the division of the inputs.
+ """
+ pass
+ @numpy_method
+ def fmod(self, x1, x2, out=None):
+ """
+ Return the element-wise remainder of division.
+ """
+ pass
+ @numpy_method
+ def mod(self, x1, x2, out=None):
+ """
+ Return element-wise remainder of division.
+ """
+ pass
+ @numpy_method
+ def modf(self, x, out1=None, out2=None):
+ """
+ Return the fractional and integral parts of an array, element-wise.
+ """
+ pass
+
+# Handling complex numbers
+ @numpy_method
+ def angle(self, z, deg=False):
+ """
+ Return the angle of the complex argument.
+ """
+ pass
+ @numpy_method
+ def real(self, val):
+ """
+ Return the real part of the elements of the array.
+ """
+ pass
+ @numpy_method
+ def imag(self, val):
+ """
+ Return the imaginary part of the elements of the array.
+ """
+ pass
+ @numpy_method
+ def conj(self, x, out=None):
+ """
+ Return the complex conjugate, element-wise.
+ """
+ pass
+
+# Miscellanous
+ @numpy_method
+ def convolve(self, a, v, mode='full'):
+ """
+ Returns the discrete, linear convolution of two one-dimensional sequences.
+ """
+ pass
+ @numpy_method
+ def clip(self, a, a_min, a_max, out=None):
+ """
+ Clip (limit) the values in an array.
+ """
+ pass
+ def clip_components(self, a, a_min, a_max, out=None):
+ """
+ Clip (limit) the values in an array.
+ """
+ assert is_complex(a)
+ out = out or np.empty_like(a)
+ np.clip(a.real, a_min,a_max, out.real)
+ np.clip(a.imag, a_min,a_max, out.imag)
+ return out
+ @numpy_method
+ def sqrt(self, x, out=None):
+ """
+ Return the positive square-root of an array, element-wise.
+ """
+ pass
+ @numpy_method
+ def cbrt(self, x, out=None):
+ """
+ Return the cube-root of an array, element-wise.
+ """
+ pass
+ @numpy_method
+ def square(self, x, out=None):
+ """
+ Return the element-wise square of the input.
+ """
+ pass
+ @numpy_method
+ def nan_to_num(self, x):
+ """
+ Replace nan with zero and inf with finite numbers.
+ """
+ pass
+ @numpy_method
+ def real_if_close(self, a, tol=100):
+ """
+ If complex input returns a real array if complex parts are close to zero.
+ """
+ pass
+ @numpy_method
+ def interp(self, x, xp, fp, left=None, right=None, period=None):
+ """
+ One-dimensional linear interpolation.
+ """
+ pass
+
+ @numpy_method
+ def maximum(self, x1, x2, out=None):
+ """
+ Element-wise maximum of array elements.
+ """
+ pass
+ @numpy_method
+ def minimum(self, x1, x2, out=None):
+ """
+ Element-wise minimum of array elements.
+ """
+ pass
+ @numpy_method
+ def fmin(self, x1, x2, out=None):
+ """
+ Element-wise maximum of array elements, ignore NaNs.
+ """
+ pass
+ @numpy_method
+ def fmax(self, x1, x2, out=None):
+ """
+ Element-wise minimum of array elements, ignore NaNs.
+ """
+ pass
+ @numpy_method
+ def fabs(self, x, out=None):
+ """
+ Calculate the absolute value element-wise, outputs HYSOP_REAL unless out is set.
+ """
+ pass
+ @numpy_method
+ def absolute(self, x, out=None):
+ """
+ Calculate the absolute value element-wise.
+ """
+ pass
+
+ @numpy_method
+ def sign(self, x, out=None):
+ """
+ Returns an element-wise indication of the sign of a number.
+ """
+ pass
+
+
+###################
+# RANDOM SAMPLING #
+## See https://docs.scipy.org/doc/numpy/reference/routines.random.html
+
+# Simple random data
+
+ def rand(self, shape):
+ """
+ Random values in a given shape.
+ """
+ from hysop.backend.host.host_array import HostArray
+ shape=tuple(shape)
+ handle = np.random.rand(*shape)
+ return self.wrap(handle)
+
+ def randn(self, *args):
+ """
+ Return a sample (or samples) from the 'standard normal' distribution.
+ """
+ from hysop.backend.host.host_array import HostArray
+ handle = np.random.randn(*args)
+ return self.wrap(handle)
+ @numpy_method
+ def randint(self, low, high=None, size=None, dtype=HYSOP_INTEGER):
+ """
+ Return random integers from low (inclusive) to high (exclusive).
+ """
+ pass
+ @numpy_method
+ def random_integers(self, low, high=None, size=None):
+ """
+ Random integers of type np.int between low and high, inclusive.
+ """
+ pass
+ @numpy_method
+ def random_sample(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ pass
+ @numpy_method
+ def random(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ pass
+ @numpy_method
+ def ranf(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ pass
+ @numpy_method
+ def sample(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ pass
+ @numpy_method
+ def choice(self, a, size=None, replace=True, p=None):
+ """
+ Generates a random sample from a given 1-D array
+ """
+ pass
+ @numpy_method
+ def bytes(self, length):
+ """
+ Return random bytes.
+ """
+ pass
+
+# Permutations
+ @numpy_method
+ def shuffle(self, x):
+ """
+ Modify a sequence in-place by shuffling its contents.
+ """
+ pass
+ @numpy_method
+ def permutation(self, x):
+ """
+ Randomly permute a sequence, or return a permuted range.
+ """
+ pass
+
+# Distributions
+ @numpy_method
+ def beta(self, a, b, size=None):
+ """
+ Draw samples from a Beta distribution.
+ """
+ pass
+ @numpy_method
+ def binomial(self, n, p, size=None):
+ """
+ Draw samples from a binomial distribution.
+ """
+ pass
+ @numpy_method
+ def chisquare(self, df, size=None):
+ """
+ Draw samples from a chi-square distribution.
+ """
+ pass
+ @numpy_method
+ def dirichlet(self, alpha, size=None):
+ """
+ Draw samples from the Dirichlet distribution.
+ """
+ pass
+ @numpy_method
+ def exponential(self, scale=1.0, size=None):
+ """
+ Draw samples from an exponential distribution.
+ """
+ pass
+ @numpy_method
+ def f(self, dfnum, dfden, size=None):
+ """
+ Draw samples from an F distribution.
+ """
+ pass
+ @numpy_method
+ def gamma(self, shape, scale=1.0, size=None):
+ """
+ Draw samples from a Gamma distribution.
+ """
+ pass
+ @numpy_method
+ def geometric(self, p, size=None):
+ """
+ Draw samples from the geometric distribution.
+ """
+ pass
+ @numpy_method
+ def gumbel(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw samples from a Gumbel distribution.
+ """
+ pass
+ @numpy_method
+ def hypergeometric(self, ngood, nbad, nsample, size=None):
+ """
+ Draw samples from a Hypergeometric distribution.
+ """
+ pass
+ @numpy_method
+ def laplace(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw samples from the Laplace or double exponential distribution with specified location (or mean=0.0) and scale (decay).
+ """
+ pass
+ @numpy_method
+ def logistic(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw samples from a logistic distribution.
+ """
+ pass
+ @numpy_method
+ def lognormal(self, mean=0.0, sigma=1.0, size=None):
+ """
+ Draw samples from a log-normal distribution.
+ """
+ pass
+ @numpy_method
+ def logseries(self, p, size=None):
+ """
+ Draw samples from a logarithmic series distribution.
+ """
+ pass
+ @numpy_method
+ def multinomial(self, n, pvals, size=None):
+ """
+ Draw samples from a multinomial distribution.
+ """
+ pass
+ @numpy_method
+ def multivariate_normal(self, mean, cov, size=None):
+ """
+ Draw random samples from a multivariate normal distribution.
+ """
+ pass
+ @numpy_method
+ def negative_binomial(self, n, p, size=None):
+ """
+ Draw samples from a negative binomial distribution.
+ """
+ pass
+ @numpy_method
+ def noncentral_chisquare(self, df, nonc, size=None):
+ """
+ Draw samples from a noncentral chi-square distribution.
+ """
+ pass
+ @numpy_method
+ def noncentral_f(self, dfnum, dfden, nonc, size=None):
+ """
+ Draw samples from the noncentral F distribution.
+ """
+ pass
+ @numpy_method
+ def normal(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw random samples from a normal (Gaussian) distribution.
+ """
+ pass
+ @numpy_method
+ def pareto(self, a, size=None):
+ """
+ Draw samples from a Pareto II or Lomax distribution with specified shape.
+ """
+ pass
+ @numpy_method
+ def poisson(self, lam, size=None):
+ """
+ Draw samples from a Poisson distribution.
+ """
+ pass
+ @numpy_method
+ def power(self, a, size=None):
+ """
+ Draws samples in 0, 1 from a power distribution with positive exponent a - 1.
+ """
+ pass
+ @numpy_method
+ def rayleigh(self, scale=1.0, size=None):
+ """
+ Draw samples from a Rayleigh distribution.
+ """
+ pass
+ @numpy_method
+ def standard_cauchy(self, size=None):
+ """
+ Draw samples from a standard Cauchy distribution with mode = 0.
+ """
+ pass
+ @numpy_method
+ def standard_exponential(self, size=None):
+ """
+ Draw samples from the standard exponential distribution.
+ """
+ pass
+ @numpy_method
+ def standard_gamma(self, shape, size=None):
+ """
+ Draw samples from a standard Gamma distribution.
+ """
+ pass
+ @numpy_method
+ def standard_normal(self, size=None):
+ """
+ Draw samples from a standard Normal distribution (mean=0.0, stdev=1).
+ """
+ pass
+ @numpy_method
+ def standard_t(self, df, size=None):
+ """
+ Draw samples from a standard Student's t distribution with df degrees of freedom.
+ """
+ pass
+ @numpy_method
+ def triangular(self, left, mode, right, size=None):
+ """
+ Draw samples from the triangular distribution over the interval left, right.
+ """
+ pass
+ @numpy_method
+ def uniform(self, low, high, size=None):
+ """
+ Draw samples from a uniform distribution.
+ """
+ pass
+ @numpy_method
+ def vonmises(self, mu, kappa, size=None):
+ """
+ Draw samples from a von Mises distribution.
+ """
+ pass
+ @numpy_method
+ def wald(self, mean=0.0, scale=1.0, size=None):
+ """
+ Draw samples from a Wald, or inverse Gaussian, distribution.
+ """
+ pass
+ @numpy_method
+ def weibull(self, a, size=None):
+ """
+ Draw samples from a Weibull distribution.
+ """
+ pass
+ @numpy_method
+ def zipf(self, a, size=None):
+ """
+ Draw samples from a Zipf distribution.
+ """
+ pass
+
+# Random generator
+ @numpy_method
+ def seed(self, seed=None):
+ """
+ Seed the generator.
+ """
+ pass
+ @numpy_method
+ def get_state(self):
+ """
+ Return a tuple representing the internal state of the generator.
+ """
+ pass
+ @numpy_method
+ def set_state(self, state):
+ """
+ Set the internal state of the generator from a tuple.
+ """
+ pass
+
+
+################
+# SET ROUTINES #
+## See https://docs.scipy.org/doc/numpy/reference/routines.set.html
+
+# Making proper sets
+ @numpy_method
+ def unique(self, ar, return_index=False, return_inverse=False, return_counts=False):
+ """
+ Find the unique elements of an array.
+ """
+ pass
+
+# Boolean operations
+ @numpy_method
+ def in1d(self, ar1, ar2, assume_unique=False, invert=False):
+ """
+ Test whether each element of a 1-D array is also present in a second array.
+ """
+ pass
+ @numpy_method
+ def intersect1d(self, ar1, ar2, assume_unique=False):
+ """
+ Find the intersection of two arrays.
+ """
+ pass
+ @numpy_method
+ def setdiff1d(self, ar1, ar2, assume_unique=False):
+ """
+ Find the set difference of two arrays.
+ """
+ pass
+ @numpy_method
+ def setxor1d(self, ar1, ar2, assume_unique=False):
+ """
+ Find the set exclusive-or of two arrays.
+ """
+ pass
+ @numpy_method
+ def union1d(self, ar1, ar2):
+ """
+ Find the union of two arrays.
+ """
+ pass
+
+
+###################################
+# SORTING, SEARCHING AND COUNTING #
+## See https://docs.scipy.org/doc/numpy/reference/routines.sort.html
+
+# Sorting
+ @numpy_method
+ def sort(self, a, axis=-1, kind='quicksort', order=None):
+ """
+ Return a sorted copy of an array.
+ """
+ pass
+ @numpy_method
+ def lexsort(self, keys, axis=-1):
+ """
+ Perform an indirect sort using a sequence of keys.
+ """
+ pass
+ @numpy_method
+ def argsort(self, a, axis=-1, kind='quicksort', order=None):
+ """
+ Returns the indices that would sort an array.
+ """
+ pass
+ @numpy_method
+ def msort(self, a):
+ """
+ Return a copy of an array sorted along the first axis.
+ """
+ pass
+ @numpy_method
+ def sort_complex(self, a):
+ """
+ Sort a complex array using the real part first, then the imaginary part.
+ """
+ pass
+ @numpy_method
+ def partition(self, a, kth, axis=-1, kind='quicksort', order=None):
+ """
+ Return a partitioned copy of an array.
+ """
+ pass
+ @numpy_method
+ def argpartition(self, a, kth, axis=-1, kind='quicksort', order=None):
+ """
+ Perform an indirect partition along the given axis using the algorithm specified by the kind keyword.
+ """
+ pass
+
+#Searching
+ @numpy_method
+ def argmax(self, a, axis, out=None):
+ """
+ Returns the indices of the maximum values along an axis.
+ """
+ pass
+ @numpy_method
+ def nanargmax(self, a, axis=None):
+ """
+ Return the indices of the maximum values in the specified axis ignoring NaNs.
+ """
+ pass
+ @numpy_method
+ def argmin(self, a, axis, out=None):
+ """
+ Returns the indices of the minimum values along an axis.
+ """
+ pass
+ @numpy_method
+ def nanargmin(self, a, axis=None):
+ """
+ Return the indices of the minimum values in the specified axis ignoring NaNs.
+ """
+ pass
+ @numpy_method
+ def argwhere(self, a):
+ """
+ Find the indices of array elements that are non-zero, grouped by element.
+ """
+ pass
+ @numpy_method
+ def nonzero(self, a):
+ """
+ Return the indices of the elements that are non-zero.
+ """
+ pass
+ @numpy_method
+ def flatnonzero(self, a):
+ """
+ Return indices that are non-zero in the flattened version of a.
+ """
+ pass
+ @numpy_method
+ def where(self, condition, x, y):
+ """
+ Return elements, either from x or y, depending on condition.
+ """
+ pass
+ @numpy_method
+ def searchsorted(self, a, v, side='left', sorter=None):
+ """
+ Find indices where elements should be inserted to maintain order.
+ """
+ pass
+ @numpy_method
+ def extract(self, condition, arr):
+ """
+ Return the elements of an array that satisfy some condition.
+ """
+ pass
+
+#Counting
+ @numpy_method
+ def count_nonzero(self, a, axis=None):
+ """
+ Counts the number of non-zero values in the array a.
+ """
+ pass
+
+##############
+# STATISTICS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.sort.html
+
+#Order statistics
+ @numpy_method
+ def amin(self, a, axis=None, out=None):
+ """
+ Return the minimum of an array or minimum along an axis.
+ """
+ pass
+ @numpy_method
+ def amax(self, a, axis=None, out=None):
+ """
+ Return the maximum of an array or maximum along an axis.
+ """
+ pass
+ @numpy_method
+ def nanmin(self, a, axis=None, out=None):
+ """
+ Return minimum of an array or minimum along an axis, ignoring any NaNs.
+ """
+ pass
+ @numpy_method
+ def nanmax(self, a, axis=None, out=None):
+ """
+ Return the maximum of an array or maximum along an axis, ignoring any NaNs.
+ """
+ pass
+ @numpy_method
+ def ptp(self, a, axis=None, out=None):
+ """
+ Range of values (maximum - minimum) along an axis.
+ """
+ pass
+ @numpy_method
+ def percentile(self, a, q, axis=None, out=None, overwrite_input=False,
+ interpolation='linear'):
+ """
+ Compute the qth percentile of the data along the specified axis.
+ """
+ pass
+ @numpy_method
+ def nanpercentile(self, a, q, axis=None, out=None, overwrite_input=False,
+ interpolation='linear'):
+ """
+ Compute the qth percentile of the data along the specified axis,
+ while ignoring nan values.
+ """
+ pass
+
+#Averages and variances
+ @numpy_method
+ def median(self, a, axis=None, out=None, overwrite_input=False):
+ """
+ Compute the median along the specified axis.
+ """
+ pass
+ @numpy_method
+ def average(self, a, axis=None, weights=None, returned=False):
+ """
+ Compute the weighted average along the specified axis.
+ """
+ pass
+ @numpy_method
+ def mean(self, a, axis=None, dtype=None, out=None):
+ """
+ Compute the arithmetic mean along the specified axis.
+ """
+ pass
+ @numpy_method
+ def std(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the standard deviation along the specified axis.
+ """
+ pass
+ @numpy_method
+ def var(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the variance along the specified axis.
+ """
+ pass
+ @numpy_method
+ def nanmedian(self, a, axis=None, out=None, overwrite_input=False):
+ """
+ Compute the median along the specified axis, while ignoring NaNs.
+ """
+ pass
+ @numpy_method
+ def nanmean(self, a, axis=None, dtype=None, out=None):
+ """
+ Compute the arithmetic mean along the specified axis, ignoring NaNs.
+ """
+ pass
+ @numpy_method
+ def nanstd(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the standard deviation along the specified axis, while ignoring NaNs.
+ """
+ pass
+ @numpy_method
+ def nanvar(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the variance along the specified axis, while ignoring NaNs.
+ """
+ pass
+
+# Correlating
+ @numpy_method
+ def corrcoef(self, x, y, rowvar=1):
+ """
+ Return Pearson product-moment correlation coefficients.
+ """
+ pass
+ @numpy_method
+ def correlate(self, a, v, mode='valid'):
+ """
+ Cross-correlation of two 1-dimensional sequences.
+ """
+ pass
+ @numpy_method
+ def cov(self, m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, aweights=None):
+ """
+ Estimate a covariance matrix, given data and weights.
+ """
+ pass
+
+# Histograms
+ @numpy_method
+ def histogram(self, a, bins=10, range=None, normed=False, weights=None, density=None):
+ """
+ Compute the histogram of a set of data.
+ """
+ pass
+ @numpy_method
+ def histogram2d(self, x, y, bins, range=None, normed=False, weights=None):
+ """
+ Compute the bi-dimensional histogram of two data samples.
+ """
+ pass
+ @numpy_method
+ def histogramdd(self, sample, bins, range=None, normed=False, weights=None):
+ """
+ Compute the multidimensional histogram of some data.
+ """
+ pass
+ @numpy_method
+ def bincount(self, x, weights=None, minlength=None):
+ """
+ Count number of occurrences of each value in array of non-negative ints.
+ """
+ pass
+ @numpy_method
+ def digitize(self, x, bins, right=False):
+ """
+ Return the indices of the bins to which each value in input array belongs.
+ """
+ pass
+
+ArrayBackend._register_backend(np.ndarray, HostArrayBackend)
+ArrayBackend._register_backend(HostBuffer, HostArrayBackend)
diff --git a/hysop/backend/host/host_buffer.py b/hysop/backend/host/host_buffer.py
new file mode 100644
index 0000000000000000000000000000000000000000..7631c087b0a8b193378dfe79117f7fbafef96c28
--- /dev/null
+++ b/hysop/backend/host/host_buffer.py
@@ -0,0 +1,79 @@
+
+from hysop.deps import np
+from hysop.constants import MemoryOrdering, default_order
+from hysop.tools.types import check_instance
+from hysop.core.memory.buffer import Buffer, PooledBuffer
+
+class HostBuffer(np.ndarray,Buffer):
+ """
+ Host buffer class.
+ """
+ __array_priority__ = +1.0
+
+ def __new__(cls, size,
+ shape=None, dtype=np.uint8, order=None,
+ buffer=None, offset=0, strides=None):
+ from_buffer = False
+ if isinstance(buffer, Buffer):
+ __buffer = buffer
+ buffer = buffer.buf
+ from_buffer = True
+ obj = super(HostBuffer,cls).__new__(cls,
+ shape=shape or (size,), dtype=dtype, order=order,
+ buffer=buffer, offset=offset, strides=strides)
+ if from_buffer:
+ # keep a reference to the buffer (usefull for pooled buffers)
+ # such that buffer.__del__ will only be called when all views
+ # on this HostBuffer have been destroyed.
+ obj.__buffer = __buffer
+ return obj
+
+ def __str__(self):
+ return self.view(np.ndarray).__str__()
+ def __repr__(self):
+ return self.view(np.ndarray).__repr__()
+
+ def get_int_ptr(self):
+ return self.ctypes.data
+ def release(self):
+ pass
+
+ @classmethod
+ def from_int_ptr(cls, int_ptr_value, size):
+ """
+ Given int ptr should never be freed, numpy take ownership.
+ """
+ buf = np.core.multiarray.int_asbuffer(int_ptr_value, size)
+ return cls.from_buffer(buf)
+
+ @classmethod
+ def from_buffer(cls, buf):
+ buf = np.frombuffer(buf, dtype=np.uint8)
+ return cls._wrap(buf)
+
+ def aligned_view(self, alignment, size=None):
+ assert self.ndim == 1
+ assert self.dtype == np.uint8
+ assert alignment>0
+ assert not (alignment & (alignment-1)), 'alignment is not a power of 2.'
+ ptr = self.get_int_ptr()
+ offset = -ptr % alignment
+ if (size is None):
+ size = self.size-offset
+ else:
+ assert self.size >= (offset+size)
+ return self[offset:offset+size]
+
+ @classmethod
+ def _wrap(cls, handle):
+ assert isinstance(handle, np.ndarray)
+ assert handle.ndim == 1
+ assert handle.dtype == np.uint8
+ return handle.view(cls)
+
+ int_ptr = property(get_int_ptr)
+
+class HostPooledBuffer(PooledBuffer):
+ def get_array(self):
+ return self._bufview
+ array = property(get_array)
diff --git a/hysop/backend/host/host_mempool.py b/hysop/backend/host/host_mempool.py
new file mode 100644
index 0000000000000000000000000000000000000000..22aafa8a6212af900c83bf8356b466fb2ff4a385
--- /dev/null
+++ b/hysop/backend/host/host_mempool.py
@@ -0,0 +1,15 @@
+
+from hysop.tools.types import check_instance
+from hysop.backend.host.host_allocator import HostAllocator
+from hysop.backend.host.host_buffer import HostPooledBuffer
+from hysop.core.memory.mempool import MemoryPool
+
+class HostMemoryPool(MemoryPool,HostAllocator):
+
+ def __init__(self, allocator, **kwds):
+ check_instance(allocator, HostAllocator)
+ super(HostMemoryPool,self).__init__(allocator=allocator, **kwds)
+
+ def _wrap_buffer(self, buf, alloc_sz, size, alignment):
+ return HostPooledBuffer(pool=self, buf=buf, alloc_sz=alloc_sz,
+ size=size, alignment=alignment)
diff --git a/hysop/backend/host/python/__init__.py b/hysop/backend/host/python/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/backend/host/python/python_operators.py b/hysop/backend/host/python/python_operators.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/codegen/base/cl_extensions.py b/hysop/codegen/base/cl_extensions.py
deleted file mode 100644
index a6b20c4c3cc521391228a7d721fdbcf2eaf74486..0000000000000000000000000000000000000000
--- a/hysop/codegen/base/cl_extensions.py
+++ /dev/null
@@ -1,35 +0,0 @@
-
-
-_cl_khr_fp64_code = '''
-#if __OPENCL_VERSION__ < 120
- #if cl_khr_fp64
- #pragma OPENCL EXTENSION cl_khr_fp64 : enable
- #elif cl_amd_fp64
- #pragma OPENCL EXTENSION cl_amd_fp64 : enable
- #else
- #error Your OpenCL device is missing double precision extension!
- #endif
-#endif
-'''
-
-_cl_extension_custom_declarations = {
- 'cl_khr_fp64': _cl_khr_fp64_code
-}
-
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.types import OpenClTypeGen
-
-class ClExtCodeGen(OpenClCodeGenerator):
- def __init__(self,ext_name):
- super(ClExtCodeGen,self).__init__(name=ext_name, typegen=OpenClTypeGen(), declare_cl_exts=False)
- self._generate_cl_extension(ext_name)
-
- def _generate_cl_extension(self, ext_name):
- with self._codeblock_('pragma_extensions'):
- if ext_name not in _cl_extension_custom_declarations.keys():
- with self._align_() as al:
- base = '#pragma OPENCL EXTENSION {}$ : enable'
- al.append(base.format(ext_name))
- else:
- self.append(_cl_extension_custom_declarations[ext_name]);
-
diff --git a/hysop/codegen/base/opencl_codegen.py b/hysop/codegen/base/opencl_codegen.py
deleted file mode 100644
index 4ac785b734b4a92af6be0542d26461ad59cd3bb3..0000000000000000000000000000000000000000
--- a/hysop/codegen/base/opencl_codegen.py
+++ /dev/null
@@ -1,161 +0,0 @@
-
-import pyopencl as cl
-from contextlib import contextmanager
-
-from hysop.codegen.base.codegen import CodeGenerator
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import VarDict
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin, CodegenVectorClBuiltinFunc
-
-class OpenClCodeGenerator(CodeGenerator):
- default_keywords = {
- 'global' : '__global',
- 'local' : '__local',
- 'constant' : '__constant',
- 'private' : '__private',
-
- 'read_only' : '__read_only',
- 'write_only' : '__write_only',
- 'read_write' : '__read_write',
-
- 'inline' : 'inline',
- 'kernel' : '__kernel'
- }
- default_escape_seqs = {
- '\t': ' '*4,
- '\n': '\n',
- ' ': ' '
- }
-
- def __init__(self,name,typegen,ext='.cl',
- known_vars=None, declare_cl_exts=True,
- device=None, context=None, **kargs):
- assert isinstance(typegen, OpenClTypeGen)
- super(OpenClCodeGenerator,self).__init__(name=name,typegen=typegen, ext=ext, known_vars=known_vars,
- keywords=self.default_keywords, escape_seqs=self.default_escape_seqs, **kargs)
- self.device = device
- self.context = context
-
- if declare_cl_exts:
- for cl_ext in typegen.cl_requirements():
- if cl_ext is not None:
- self.declare_cl_extension(cl_ext)
-
- def test_compile(self, contexts=None):
- src=self.__str__()
-
- if contexts is None:
- devices = []
- contexts = {}
- for plat in cl.get_platforms():
- devices += plat.get_devices()
- for dev in devices:
- ctx = cl.Context([dev])
- contexts[dev] = ctx
-
- for dev,ctx in contexts.iteritems():
- print 'Test build on device {}: '.format(dev.name),
- #prg = cl.Program(ctx,src)
- #prg.build()
- print 'OK'
-
-
- @staticmethod
- def _mem_flags(_local, _global):
- if _local and _global:
- return 'CLK_LOCAL_MEM_FENCE | CLK_GLOBAL_MEM_FENCE'
- elif _local:
- return 'CLK_LOCAL_MEM_FENCE'
- elif _global:
- return 'CLK_GLOBAL_MEM_FENCE'
- else:
- return None
-
- def barrier(self,_local=False, _global=False):
- if not _local and not _global:
- raise ValueError('Bad barrier configuration!')
- code = 'barrier({});'.format(self._mem_flags(_local,_global))
- self.append(code)
-
- def mem_fence(self,read=False,write=False, _local=False, _global=False):
- if (not read and not write) or (not _local and not _local):
- raise ValueError('Bad memfence configuration!')
-
- #opencl 1.0 has only the barrier function
- self.append('#if __OPENCL_VERSION__ < 110')
- self.indent()
- self.barrier(_local=_local, _global=_global)
- self.dedent()
- self.append('#else')
- self.indent()
- if read and write:
- mem_fun = 'mem_fence'
- elif read:
- mem_fun = 'read_mem_fence'
- else:
- mem_fun = 'write_mem_fence'
- mem_flags = self._mem_flags(_local,_global)
- code = '{}({});'.format(mem_fun,mem_flags)
- self.append(code)
- self.dedent()
- self.append('#endif')
-
-
- def declare_cl_extension(self,extname):
- from hysop.codegen.base.cl_extensions import ClExtCodeGen
- self.require(extname, ClExtCodeGen(extname))
- return self
-
- @contextmanager
- def _kernel_(self,name,args=None,arg_spaces=True,add_impl_const=[],attributes=None):
- if not args:
- args = ['']
- else:
- newargs = []
- i=0
- for ii,arg in enumerate(args):
- newl=(arg[-1] == self.newl())
- arg = arg[:-1] if newl else arg
- newargs.append(arg)
- i+=1
- if newl:
- for j,id in enumerate(add_impl_const):
- if id>=i:
- add_impl_const[j] += 1
- newargs.append(self.newl())
- i+=1
- args = newargs
-
- if arg_spaces:
- comma = ', '
- else:
- comma = ','
-
- kernel_kwd = self.keywords['kernel']
-
- prefix = '{kernel} void {name}('.format(kernel=kernel_kwd,name=name)
- indent_proto = len(prefix)*' '
- if attributes:
- attr = ['{} __attribute__(({}))'.format(len(kernel_kwd)*' ',at) for at in attributes.values()]
- attr[0] = attr[0][len(kernel_kwd)+1:]
- attr = '\n'.join(attr)
- proto_prefix = '{kernel} {attr}\nvoid {name}('.format(kernel=kernel_kwd,attr=attr,name=name)
- indent_proto = len('void {name}('.format(name=name))*' '
- else:
- proto_prefix = prefix
- suffix = '{args})'
- indent = len(self.current_indent() + prefix)*' '
-
- pargs = [arg+comma if arg!=self.newl() else arg+indent_proto for arg in args[:-1]]+[args[-1]]
- prototype = proto_prefix + suffix.format(args=''.join(pargs)) + ';'
-
- for i in add_impl_const:
- args[i] = 'const ' + args[i]
- dargs = [arg+comma if arg!=self.newl() else arg+indent for arg in args[:-1]]+[args[-1]]
- definition = prefix + suffix.format(args=''.join(dargs)) + ' '
-
- self.declare_prototype(prototype, 'kernel')
- with self._codeblock_('kernel_declarations'):
- with self._block_(header_prefix=definition) as b:
- yield b
-
diff --git a/hysop/codegen/base/struct_codegen.py b/hysop/codegen/base/struct_codegen.py
deleted file mode 100644
index c115b8eb60dc247d64dea854612b8401eedd2fa2..0000000000000000000000000000000000000000
--- a/hysop/codegen/base/struct_codegen.py
+++ /dev/null
@@ -1,105 +0,0 @@
-
-import pyopencl as cl
-import pyopencl.tools
-
-import numpy as np
-import re
-
-from hysop.codegen.base.types import np_dtype
-from hysop.codegen.base.codegen import CodeGenerator
-from hysop.codegen.base.variables import VarDict, CodegenVariable, CodegenVector, CodegenStruct, CodegenVectorClBuiltin
-from hysop.codegen.base.variables import register_ctype_dtype
-
-class StructCodeGenerator(CodeGenerator):
- def __init__(self,name,dtype,typegen,device,context,
- comments=None,
- ctype_overrides=None,
- typedef=None,
- custom_types={},
- ext='.tmp',
- initial_indent_level=0,escape_seqs=None,keywords=None):
-
- super(StructCodeGenerator,self).__init__(name=name,typegen=typegen,
- ext=ext,initial_indent_level=initial_indent_level,
- escape_seqs=escape_seqs,keywords=keywords)
-
- self.typedef = typedef
- self.device = device
- self.context = context
- self.dtype = np.dtype(dtype)
- self.ctype = self.typedef if self.typedef else 'struct {}'.format(self.name)
-
- cl.tools.get_or_register_dtype(self.ctype,self.dtype)
- register_ctype_dtype(self.ctype,self.dtype)
-
- for _ctype,_dtype in custom_types.iteritems():
- cl.tools.get_or_register_dtype(_ctype,dtype=_dtype)
-
- self.gencode(comments, ctype_overrides)
-
- def fields(self):
- return self.dtype.fields
-
- def find_cl_device(self):
- device = self.device
- context = self.context
- cls=self.__class__.__name__
- if device is None:
- print 'Warning: no device was specified in {} (name={}).'.format(cls,self.name)
- platforms = cl.get_platforms()
- if not platforms:
- raise RuntimeError('No OpenCl platforms installed, required for C struct code generation!')
- for p in platforms:
- devices = platforms[0].get_devices()
- if devices:
- device = devices[0]
- if not device:
- raise RuntimeError('No OpenCl device present, required for C struct code generation!')
- if context is None:
- print 'Warning: no context was specified in {}(name={}).'.format(cls,self.name)
- context = cl.Context([device])
-
- self.device = device
- self.context = context
-
- def c_decl(self):
- if (self.device is None) or (self.context is None):
- self.find_cl_device()
- dtype,cdecl = cl.tools.match_dtype_to_c_struct(self.device,self.ctype,self.dtype,self.context)
- return cdecl
-
- def gencode(self, comments, ctype_overrides):
- struct_vars = re.compile('\s+((?:struct\s+)?\w+)\s+((?:\s*\**(?:\w+)(?:\[\d+\])*[,;])+)')
- lines = self.c_decl().split('\n')
-
- with self._struct_(name=self.name,typedef=self.typedef):
- with self._var_block_() as vb:
- i=0
- for l in lines:
- match = struct_vars.match(l)
- if match:
- ctype = match.group(1)
- variables = match.group(2).replace(';','').split(',')
- if (ctype_overrides is not None) and (i in ctype_overrides.keys()):
- ctype = ctype_overrides[i]
- if comments is not None:
- vb.decl_var(ctype,','.join(variables), comment=comments[i])
- else:
- vb.decl_var(ctype,','.join(variables))
- i+=1
-
- def build_codegen_variable(self,name,**kargs):
- return CodegenStruct(varname=name, struct=self, **kargs)
-
-if __name__ == '__main__':
-
- dtype = []
- dtype.append( ('f0', np.float32 ) )
- dtype.append( ('d0', np.float64) )
- dtype.append( ('v0', np_dtype('float4')) )
- dtype.append( ('v1', np_dtype('int16')) )
-
- scg = StructCodeGenerator('TestStruct',dtype,typedef='TestStruct_s')
- scg.edit()
-
-
diff --git a/hysop/codegen/base/test.py b/hysop/codegen/base/test.py
deleted file mode 100644
index 51e0bbbc1982b0dba86a9c8873cd451262946df9..0000000000000000000000000000000000000000
--- a/hysop/codegen/base/test.py
+++ /dev/null
@@ -1,48 +0,0 @@
-
-from hysop.constants import np
-from hysop.constants import MeshDir, MeshState
-from hysop.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
-
-def test_mesh_info(typegen,dim,ghosts,resolution,device,context,**kargs):
- ghosts = [ghosts]*dim if np.isscalar(ghosts) else ghosts
- ghosts = np.asarray(ghosts)[:dim]
-
- resolution = [resolution]*dim if np.isscalar(resolution) else resolution
- resolution = np.asarray(resolution)[:dim]
-
- xmin = np.zeros((dim,))
- xmax = np.ones((dim,))
- size = xmax-xmin
- dx = size / (resolution-1)
-
- start = ghosts
- stop = resolution-ghosts
-
- mbs = MeshBaseStruct(typegen, typedef='MeshBase_s',
- device=device, context=context)
- mis = MeshInfoStruct(typegen, typedef='MeshInfo_s', mbs_typedef=mbs.typedef,
- device=device, context=context)
-
- # create a local numpy and a codegen MeshInfoStruct variable
- global_mesh = mbs.create(name='global',
- resolution=resolution, compute_resolution=resolution-2*ghosts,
- xmin=xmin, xmax=xmax,
- size=size,
- **kargs)
- local_mesh = mbs.create(name='local',
- resolution=resolution, compute_resolution=resolution-2*ghosts,
- xmin=xmin, xmax=xmax,
- size=size,
- **kargs)
-
- (np_mis, cg_mis) = mis.create(name='mesh_info',
- dim=dim,
- start=start, stop=stop,
- ghosts=ghosts,
- dx=dx,
- local_mesh=local_mesh, global_mesh=global_mesh,
- mesh_dir=MeshDir.X, mesh_state=MeshState.XYZ,
- device=device, context=context,
- **kargs)
-
- return (np_mis, cg_mis)
diff --git a/hysop/codegen/functions/apply_stencil.py b/hysop/codegen/functions/apply_stencil.py
deleted file mode 100644
index ab601e803d3b2d8b372958635e5212b84f4d746e..0000000000000000000000000000000000000000
--- a/hysop/codegen/functions/apply_stencil.py
+++ /dev/null
@@ -1,81 +0,0 @@
-
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.function_codegen import OpenClFunctionCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import ArgDict
-
-from hysop.codegen.maths.stencil.stencil import Stencil
-
-class ApplyStencilFunction(OpenClFunctionCodeGenerator):
-
- def __init__(self,typegen,stencil,ftype,
- data_storage='__local', itype='int',
- known_args=None):
-
- assert isinstance(stencil, Stencil)
- dim = stencil.dim
-
- args = ArgDict()
- args['data'] = CodegenVariable('data', ftype, typegen, const=True, storage=data_storage, ptr=True)
- args['offset'] = CodegenVariable('offset', 'int', typegen, add_impl_const=True)
- args['stride'] = CodegenVectorClBuiltin('stride', 'int', dim, typegen, add_impl_const=True)
-
- basename = 'apply_stencil_{}d_{}'.format(dim, stencil.hash())
- super(ApplyStencilFunction,self).__init__(basename=basename,
- output=ftype,typegen=typegen,inline=True,
- args=args, known_args=known_args)
- self.dim = dim
- self.ftype = ftype
- self.stencil = stencil
-
- self.gencode()
-
- def gencode(self):
- s = self
- dim = s.dim
- tg = self.typegen
-
- data = s.vars['data']
- offset = s.vars['offset']
- stride = s.vars['stride']
-
- coeffs = self.stencil.iteritems()
-
- res = CodegenVariable('res',self.ftype,tg)
-
- with s._function_():
- s.append(res.declare(init=0))
- with s._block_():
- with s._align_() as al:
- for (off,coeff) in coeffs:
- strided=''
- for i in xrange(dim):
- if off[i]==0:
- continue
- if stride.known() and stride.value[0] == 1:
- strided+='${}'.format(tg.dump(off[i]))
- else:
- strided+='${}*{}'.format(tg.dump(off[i]),stride[i])
- id = '{}+{}'.format(offset(),strided)
- code = '{} += {}$*{};'.format(res(),tg.dump(coeff),data[id])
- al.append(code)
-
- ret = 'return {};'.format(res())
- s.append(ret)
-
-
-if __name__ == '__main__':
-
- stencil = Stencil([2.0,1.0,0.0,-1.0,-2.0], origin=2, order=2)
-
- typegen = OpenClTypeGen('float')
- asf = ApplyStencilFunction(typegen,stencil,ftype=typegen.fbtype)
- print asf
- print
-
- typegen = OpenClTypeGen('double', float_dump_mode='hex')
- asf = ApplyStencilFunction(typegen,stencil,ftype=typegen.fbtype)
- print asf
- print
-
diff --git a/hysop/codegen/functions/cache_load.py b/hysop/codegen/functions/cache_load.py
deleted file mode 100644
index 26ece974b2de4a6fe5a91190e5f5373fde1f0d8b..0000000000000000000000000000000000000000
--- a/hysop/codegen/functions/cache_load.py
+++ /dev/null
@@ -1,152 +0,0 @@
-
-import contextlib
-from contextlib import contextmanager
-
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.function_codegen import OpenClFunctionCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import ArgDict
-
-from hysop.codegen.functions.compute_index import ComputeIndexFunction
-
-class CacheLoadFunction(OpenClFunctionCodeGenerator):
-
- arguments = {
- 'src':'source data',
- 'dst':'destination buffer',
- 'global_id:':'global thread_id',
- 'local_id':'local thread_id',
- 'local_size':'size of a workgroup',
- 'data_size':'size of source data'
- }
-
- def __init__(self, dtype, dim, typegen, boundary=None,
- known_args=None,force_symbolic=True):
-
- assert dim>0
-
- if boundary is None:
- pass
- elif boundary != 'periodic':
- raise NotImplemented('Boundary \'{}\' not implmented yet!'.format(boundary))
-
- tg = typegen
- fs = force_symbolic
- name = 'cache_load_{}d'.format(dim)
- if boundary is not None:
- name+='_{}'.format(boundary)
- output = 'void'
-
- args = ArgDict()
- args['src'] = CodegenVariable('src', dtype, typegen=tg, ptr=True, const=True, storage='__global', nl=True)
- args['dst'] = CodegenVariable('dst', dtype, typegen=tg, ptr=True, const=False, storage='__local' , nl=True)
-
- args['global_id'] = CodegenVectorClBuiltin('gid','int',dim,typegen,add_impl_const=False)
- args['local_id'] = CodegenVectorClBuiltin('lid','int',dim,typegen,add_impl_const=False, nl=True)
-
- args['local_size'] = CodegenVectorClBuiltin('L','int',dim,tg,add_impl_const=True, symbolic_mode=fs)
- args['src_size'] = CodegenVectorClBuiltin('N','int',dim,tg,add_impl_const=True, symbolic_mode=fs, nl=True)
-
- args['lghosts'] = CodegenVectorClBuiltin('lghosts','int',dim,tg,add_impl_const=True, symbolic_mode=fs)
- args['rghosts'] = CodegenVectorClBuiltin('rghosts','int',dim,tg,add_impl_const=True, symbolic_mode=fs)
-
- super(CacheLoadFunction,self).__init__(basename=name, output=output,
- args=args,known_args=known_args,
- typegen=tg,inline=True)
- self.dtype = dtype
- self.dim = dim
- self.boundary = boundary
- self.declare_code()
-
- def declare_code(self):
- s = self
- tg = s.typegen
- dim = s.dim
- boundary=s.boundary
-
- src = s.args['src'];
- dst = s.args['dst'];
-
- global_id = s.args['global_id'];
- local_id = s.args['local_id'];
-
- local_size = s.args['local_size'];
- src_size = s.args['src_size'];
-
- lghosts = s.args['lghosts'];
- rghosts = s.args['rghosts'];
-
- cache_size = CodegenVectorClBuiltin('S' ,'int',dim,tg,const=True)
- local_pos = CodegenVectorClBuiltin('lidx','int',dim,tg)
- global_pos = CodegenVectorClBuiltin('gidx','int',dim,tg)
-
- LID = CodegenVariable('LID','uint', tg)
- GID = CodegenVariable('GID','uint', tg)
-
- compute_index = ComputeIndexFunction(tg,dim,wrap=False)
- s.require('compute_index',compute_index)
-
- with s._function_():
- s.jumpline()
- s.append(cache_size.declare(init='{}+{}+{}'.format(lghosts(),local_size(),rghosts())))
- s.jumpline()
- s.append(global_pos.declare())
- s.append(local_pos.declare())
- s.jumpline()
-
- if boundary == 'periodic':
- s.append('{} += {}-{};'.format(global_id(),src_size(),lghosts()))
-
- @contextmanager
- def _cache_iterate_(i):
- try:
- if (local_size.known() and lghosts.known() and rghosts.known()):
- s.pragma('unroll')
- with s._for_('int k{i}=0; k{i}<({}+{L}-1)/{L}; k{i}++'.format(cache_size[i],i=i,L=local_size[i])) as ctx:
- s.append('{} = ({}+k{i}*{});'.format(local_pos[i],local_id[i],local_size[i],i=i));
- s.append('if ({}>={}) continue;'.format(local_pos[i],cache_size[i]))
- if boundary=='periodic':
- s.append('{} = ({}+k{i}*{})%{};'.format(global_pos[i],global_id[i],local_size[i],src_size[i],i=i));
- else:
- s.append('{} = {}+k{i}*{};'.format(global_pos[i],global_id[i],local_size[i],i=i));
- yield ctx
- except:
- pass
-
- s.mem_fence(read=True,_local=True)
- with s._block_():
- nested_loops = [_cache_iterate_(i) for i in xrange(dim-1,-1,-1)]
- with contextlib.nested(*nested_loops):
- with s._block_():
- s.append(LID.declare(const=True,init=compute_index(idx=local_pos,size=cache_size[:dim])))
- s.append(GID.declare(const=True,init=compute_index(idx=global_pos,size=src_size[:dim])))
- s.append('{} = {};'.format(dst[LID()],src[GID()]))
- s.mem_fence(write=True,_local=True)
-
-
-
-if __name__ == '__main__':
- tg = OpenClTypeGen('float')
- cg = OpenClCodeGenerator(name='base',typegen=tg)
-
- cache_load0 = CacheLoadFunction('float',dim=2,typegen=tg)
-
- known_args = ArgDict(lghosts=(1,2,3),rghosts=(6,4,3))
- cache_load1 = CacheLoadFunction('float4',dim=3,typegen=tg,known_args=known_args)
-
-
- known_args = ArgDict(lghosts=(1,2,3),rghosts=(6,4,3),
- local_size=(16,8,2),src_size=(512,1024,2048))
- cache_load2 = CacheLoadFunction('double16',dim=3,typegen=tg,
- known_args=known_args,force_symbolic=True)
-
- #cg.require('cl0',cache_load0)
- #cg.require('cl1',cache_load1)
- cg.require('cl2',cache_load2)
-
- cg.edit()
- #print cg
- #cg.test_compile()
-
-
diff --git a/hysop/codegen/kernels/directional_stretching.py b/hysop/codegen/kernels/directional_stretching.py
deleted file mode 100644
index 17e628ef8f94404d4a77ec155a4be6c86249eaf1..0000000000000000000000000000000000000000
--- a/hysop/codegen/kernels/directional_stretching.py
+++ /dev/null
@@ -1,458 +0,0 @@
-
-import operator
-
-from hysop.constants import np
-
-from hysop.constants import S_DIR, MeshDir
-
-from hysop.codegen.base.opencl_codegen import OpenClCodeGenerator
-from hysop.codegen.base.kernel_codegen import KernelCodeGenerator
-from hysop.codegen.base.variables import CodegenVariable, CodegenVectorClBuiltin
-from hysop.codegen.base.types import OpenClTypeGen
-from hysop.codegen.base.utils import WriteOnceDict, ArgDict
-
-from hysop.codegen.base.variables import CodegenStruct
-from hysop.codegen.structs.mesh_info import MeshBaseStruct, MeshInfoStruct
-
-from hysop.codegen.functions.compute_index import ComputeIndexFunction
-from hysop.codegen.functions.cache_load import CacheLoadFunction
-from hysop.codegen.functions.apply_stencil import ApplyStencilFunction
-
-from hysop.codegen.maths.stencil.stencil import Stencil1D, Stencil
-
-from hysop.gpu import cl, clCharacterize
-from hysop.gpu.tools import OpenCLEnvironment
-from hysop.gpu.gpu_kernel import KernelLauncher
-from hysop.gpu.kernel_autotuner import KernelAutotuner
-from hysop.gpu.gpu_discrete import GPUDiscreteField
-
-class DirectionalStretchingKernel(KernelCodeGenerator):
-
- @staticmethod
- def codegen_name(ftype,cached,direction):
- cache = 'cached_' if cached else ''
- return 'directional_{}stretching_{}{}'.format(cache,ftype,S_DIR[direction])
-
- def __init__(self, typegen, dim, direction,
- order,
- cached,
- boundary,
- symbolic_mode,
- device,context,
- ftype=None,
- known_vars = None):
-
- assert direction < dim, 'direction error.'
- ftype = ftype if ftype is not None else typegen.fbtype
-
- kernel_reqs = self.build_requirements(typegen,dim, order, cached, device, context)
- kernel_args = self.gen_kernel_arguments(typegen, dim, ftype, kernel_reqs, cached)
-
- name = DirectionalStretchingKernel.codegen_name(ftype,cached,direction)
- super(DirectionalStretchingKernel,self).__init__(
- name=name,
- typegen=typegen,
- work_dim=dim,
- kernel_args=kernel_args,
- known_vars=known_vars,
- device=device, context=context,
- vec_type_hint=ftype,
- symbolic_mode=symbolic_mode)
-
- self.update_requirements(kernel_reqs)
-
- self.order = order
- self.ftype = ftype
- self.cached = cached
- self.direction = direction
- self.dim = dim
- self.boundary = boundary
-
- self.gencode()
-
- def required_workgroup_cache_size(self,order=None,local_size=None):
- if (order is None) ^ (local_size is None):
- msg='order and local_size should be set in the same time.'
- raise ValueError(msg)
-
- if local_size is None:
- local_size = self.vars['local_size']
- if local_size.value is None:
- msg='local_size is not a known variable, you need to specify one.'
- raise ValueError(msg)
- local_size=local_size.value
-
- cache_ghosts = np.zeros_like(local_size)
- if order is None:
- cache_ghosts[0] = self.order//2
- elif order%2!=0:
- raise ValueError('order should be even.')
- else:
- cache_ghosts[0] = self.order//2
-
- static_cache_bytes = 0
- dynamic_cache_bytes = reduce(operator.mul, local_size+2*cache_ghosts, 1)*self.typegen.FLT_BYTES[self.ftype]
- return (static_cache_bytes,dynamic_cache_bytes) # static & dynamic cache
-
-
- @staticmethod
- def autotune(cl_env,
- dim, direction,compute_resolution,
- boundary, order,
- velocity, vorticity, mesh_info, dt,
- nruns, force_renew_cache, build_opts):
-
- if not isinstance(cl_env,OpenCLEnvironment):
- raise ValueError('cl_env is not an OpenCLEnvironment.')
- device = cl_env.device
- context = cl_env.ctx
- platform = cl_env.platform
- queue = cl_env.queue
- typegen = cl_env.typegen
- if context is None:
- raise ValueError('context cannot be None.')
- if device is None:
- raise ValueError('device cannot be None.')
- if platform is None:
- raise ValueError('platform cannot be None.')
- if queue is None:
- raise ValueError('queue cannot be None.')
- if not isinstance(typegen,OpenClTypeGen):
- raise ValueError('typegen is not an OpenClTypeGen.')
-
- if not isinstance(mesh_info,CodegenVariable):
- raise ValueError('mesh_info is not a CodegenVariable.')
- if not isinstance(velocity,GPUDiscreteField):
- raise ValueError('velocity is not a GPUDiscreteField')
- if not isinstance(vorticity,GPUDiscreteField):
- raise ValueError('vorticity is not a GPUDiscreteField')
- if (velocity.nb_components != dim) or (vorticity.nb_components != dim):
- raise ValueError('Vector components mismatch with dim {}.'.format(dim))
- if (not isinstance(mesh_info,CodegenStruct)) or (not mesh_info.known()):
- raise ValueError('mesh_info is not a known MeshInfoStruct codegen variable.')
- if not np.isscalar(dt):
- raise ValueError('dt is not a scalar...')
- if (nruns<1):
- raise ValueError('nruns={} < 1.'.format(nruns))
- if (direction>=dim):
- raise ValueError('direction >= dim.')
- cr = mesh_info['local_mesh']['compute_resolution'].value[:dim]
- if (compute_resolution != cr).any():
- raise ValueError('compute_resolution mismatch in mesh_info.local_mesh, got {} and {}.'.format(compute_resolution,cr))
- if boundary not in [None,'periodic']:
- raise ValueError('unknown boundary type {}.'.format(boundary))
- if order%2 != 0:
- raise ValueError('order must be even.')
- else:
- g0 = mesh_info['ghosts'].value[0]
- if (boundary=='periodic' and g0!=0):
- msg='periodic boundaries implies no ghosts but ghosts.x = {}.'.format(g0)
- raise ValueError(msg)
- elif (boundary is None) and g0<order/2:
- msg='No boundaries implies minimum ghosts numbers to be {} in the first direction '
- msg+='but only {} ghosts are present.'
- msg=msg.format(order/2,g0)
- raise ValueError(msg)
-
-
- # global size is the resolution without ghosts
- global_size = np.ones(3,dtype=np.int32)
- global_size[:dim] = compute_resolution
-
-
- # autotuner parameters
- dump_src=False
- force_verbose=False
- min_load_factor = 32
- max_local_size = (clCharacterize.usable_local_mem_size(device)//cl_env.prec_size,1,1)
-
- ## kernel generator
- def kernel_generator(local_size, kernel_args,
- cached, symbolic_mode, **kargs):
-
- ## Compile time known variables
- # dt is not known because it depends on splitting dir
- # and simulation current time_step
- known_vars = dict(
- mesh_info=mesh_info,
- local_size=local_size[:dim]
- )
-
- ## CodeGenerator
- codegen = DirectionalStretchingKernel(typegen=typegen,
- order=order, dim=dim, direction=direction, boundary=boundary,
- cached=cached, symbolic_mode=symbolic_mode,
- device=device, context=context,
- known_vars=known_vars)
-
- ## allocate cached memory
- if cached:
- cache_bytes = codegen.required_workgroup_cache_size()[1]
- local_mem = cl.LocalMemory(cache_bytes)
- kernel_args[-1] = local_mem
- else:
- cache_bytes = 0
-
- ## generate source code and build kernel
- #codegen.edit()
- #import sys
- #sys.exit(0)
- src = codegen.__str__()
- prg = cl_env.build_raw_src(src, build_opts, force_verbose=force_verbose)
- kernel = prg.all_kernels()[0]
-
- return (kernel, kernel_args, cache_bytes)
-
- def _autotune(_cached,_symbolic_mode):
- ## Kernel Autotuner
- name = DirectionalStretchingKernel.codegen_name(typegen.fbtype, _cached, direction)
- autotuner = KernelAutotuner(name=name,
- work_dim=dim,fbtype=typegen.fbtype,
- nruns=nruns, build_opts=build_opts, force_renew_cache=force_renew_cache)
- autotuner.add_filter('1d_shape_max', autotuner.max_workitems_per_direction)
-
- kernel_args = [cl_env.precision(dt)] + vorticity.gpu_data + velocity.gpu_data
- kernel_args_mapping={
- 'dt':0,
- 'vorticity':slice(1,1+dim,1),
- 'velocity':slice(1+dim,1+2*dim,1)
- }
- if _cached:
- kernel_args.append(None) #will be allocated in kernel_generator
- kernel_args_mapping['cache'] = len(kernel_args_mapping.keys())
-
- (gwi, lwi, stats) = autotuner.bench(device=device, ctx=context, platform=platform,
- global_size=global_size, kernel_args=kernel_args,
- kernel_generator=kernel_generator,
- dump_src=False, verbose=force_verbose,
- min_load_factor=min_load_factor,
- max_local_size=max_local_size,
- cached=_cached, symbolic_mode=_symbolic_mode)
-
- (kernel, kernel_args, cached_bytes) = kernel_generator(local_size=lwi, kernel_args=kernel_args,
- cached=_cached,symbolic_mode=_symbolic_mode)
-
- kernel_launcher = KernelLauncher(kernel, queue, list(gwi), list(lwi))
- return (kernel_launcher, kernel_args, kernel_args_mapping, cached_bytes)
-
- cached = True
- symbolic_mode = False
- return _autotune(cached,symbolic_mode)
-
- def build_requirements(self,typegen,work_dim,order,cached, device, context):
- reqs = WriteOnceDict()
-
- compute_id = ComputeIndexFunction(typegen=typegen, dim=work_dim, itype='int', wrap=False)
- reqs['compute_id'] = compute_id
-
- mesh_base_struct = MeshBaseStruct(typegen=typegen, typedef='MeshBase_s', device=device, context=context)
- reqs['MeshBaseStruct'] = mesh_base_struct
-
- mesh_info_struct = MeshInfoStruct(typegen=typegen, typedef='MeshInfo_s', device=device, context=context)
- reqs['MeshInfoStruct'] = mesh_info_struct
-
- tg=typegen
- assert order%2==0
- h = order//2
- S = Stencil1D().generate(Lx=h,Rx=+h,k=1,order=order)
- stencil = Stencil(S.stencil, origin=S.Lx, order=S.order)
- apply_stencil = ApplyStencilFunction(typegen=tg,stencil=stencil,
- ftype=tg.fbtype,itype='int', data_storage=('__local' if cached else '__global'),
- known_args={'stride':1})
- self.stencil = stencil
- reqs['apply_stencil'] = apply_stencil
-
- return reqs
-
- def min_ghosts(self):
- return int(self.stencil.L)
-
- self.update_requirements(reqs)
- def gen_kernel_arguments(self, typegen, work_dim, ftype, requirements,cached):
- fbtype = typegen.fbtype
- _global = OpenClCodeGenerator.default_keywords['global']
- _local = OpenClCodeGenerator.default_keywords['local']
-
- xyz = ['x','y','z']
- svelocity = 'V'
- svorticity = 'W'
-
- kargs = ArgDict()
- kargs['dt'] = CodegenVariable(ctype=fbtype,name='dt',typegen=typegen,add_impl_const=True,nl=True)
-
- for i in xrange(work_dim):
- name = svorticity+xyz[i]
- kargs[name] = CodegenVariable(storage=_global,name=name,typegen=typegen,
- ctype=ftype,ptr=True)
- for i in xrange(work_dim):
- name = svelocity+xyz[i]
- kargs[name] = CodegenVariable(storage=_global,name=name,ctype=ftype,typegen=typegen,ptr=True,const=True)
-
- kargs['mesh_info'] = requirements['MeshInfoStruct'].build_codegen_variable(const=True,storage='__constant',ptr=True,name='mesh_info')
- if cached:
- kargs['buffer'] = CodegenVariable(storage='__local',ctype=ftype,name='buffer',ptr=True, typegen=typegen, nl=False)
-
- self.svorticity = svorticity
- self.svelocity = svelocity
- self.xyz = xyz
-
- return kargs
-
- def gencode(self):
- s = self
- tg = s.typegen
- direction = s.direction
- cached = s.cached
- work_dim = s.work_dim
- dim = s.dim
- fbtype = tg.fbtype
-
- global_id = s.vars['global_id']
- local_id = s.vars['local_id']
- global_index = s.vars['global_index']
- local_index = s.vars['local_index']
-
- local_size = s.vars['local_size']
- mesh_info = s.vars['mesh_info']
- dt = s.vars['dt']
-
- if cached:
- buf = s.vars['buffer']
-
- grid_size = mesh_info['local_mesh']['resolution'].view('grid_size',slice(None,dim))
- compute_grid_size = mesh_info['local_mesh']['compute_resolution'].view('Nc',slice(None,dim))
- inv_dx = mesh_info['inv_dx'].view('inv_dx',slice(0,1))
-
- ghosts = mesh_info['ghosts'].view('ghosts',slice(0,dim),const=True)
-
- #g0 = mesh_info['ghosts'][0]
- #g = (g0,)+(0,)*(dim-1)
- #init = '({}{})({})'.format(ghosts.btype,'' if dim==1 else dim,','.join(s.__str__() for s in g))
- #if ghosts.known():
- #gv = (ghosts.value[0],)+(0,)*(dim-1)
- #cache_ghosts = CodegenVectorClBuiltin('cache_ghosts',ghosts.btype,dim,tg,init=init,value=gv,const=True)
- #else:
- #cache_ghosts = CodegenVectorClBuiltin('cache_ghosts',ghosts.btype,dim,tg,init=init,const=True)
- cache_ghosts = CodegenVectorClBuiltin('cache_ghosts',ghosts.btype,dim, tg,
- value=(self.min_ghosts(),0,0),const=True)
-
- if cached:
- cache_load = CacheLoadFunction(dtype=tg.fbtype,dim=work_dim,typegen=tg,boundary=self.boundary,
- known_args = {
- 'local_size': local_size,
- 'src_size': grid_size,
- 'lghosts': cache_ghosts,
- 'rghosts': cache_ghosts
- })
- self.require('cache_load',cache_load)
-
-
- W = CodegenVectorClBuiltin('W',fbtype,dim,tg,const=True)
- offset = CodegenVariable('offset','int',tg,const=True)
- K = CodegenVariable('K',tg.fbtype,tg,const=True)
-
- s.update_vars(grid_size=grid_size, inv_dx=inv_dx, W=W)
-
- compute_index = self.reqs['compute_id']
- apply_stencil = self.reqs['apply_stencil']
-
- with s._kernel_():
- s.jumpline()
- with s._align_() as al:
- global_id.declare(al,align=True,const=True)
- local_id.declare(al,align=True,const=True)
- local_size.declare(al,align=True,const=True)
- s.jumpline()
-
- compute_grid_size.declare(s)
- s.check_workitem_bounds(compute_grid_size, compact=False)
- s.jumpline()
-
- with s._align_() as al:
- grid_size.declare(al,align=True)
- ghosts.declare(al,align=True)
- if cached:
- cache_ghosts.declare(al,align=True)
- inv_dx.declare(al,align=True)
-
- with s._block_():
- with s._align_() as al:
- idx = '{}+{}'.format(global_id(),ghosts())
- init = compute_index(idx=idx, size=grid_size)
- global_index.declare(al, const=True, init=init,align=True)
-
- if cached:
- init = '{}+{}'.format(local_id[0],cache_ghosts[0])
- else:
- init = global_index()
- offset.declare(al,align=True,init=init)
-
- if dim>1:
- winit = ''
- for i in xrange(work_dim):
- Wi = self.svorticity+self.xyz[i]
- winit += self.vars[Wi][global_index()] + ','
- winit='({}{})({})'.format(fbtype, work_dim, winit[:-1])
- W.declare(al,init=winit,align=True)
- init = '{}*{}*{}'.format(dt(),inv_dx(),W[direction])
- K.declare(al,align=True,init=init)
- if not cached:
- s.jumpline()
- for i in xrange(work_dim):
- Wi = self.vars[self.svorticity+self.xyz[i]]
- Vi = self.vars[self.svelocity+self.xyz[i]]
- if cached:
- if dim>1:
- s.jumpline()
- load = cache_load(src=Vi, dst=buf, global_id=global_id, local_id=local_id,
- local_size=local_size, src_size=grid_size, lghosts=cache_ghosts, rghosts=cache_ghosts) + ';'
- s.append(load)
- dVi = apply_stencil(data=buf, offset=offset())
- else:
- dVi = apply_stencil(data=Vi, offset=offset())
- if dim==1:
- code = '{} += {}*({}*{})*{};'.format(Wi[global_index()],Wi[global_index()],dt(),inv_dx(),dVi)
- else:
- code = '{} = {} + K*{};'.format(Wi[global_index()],W[i],dVi)
- s.append(code)
- s.jumpline()
-
-
-if __name__ == '__main__':
- from hysop.gpu import cl
- from hysop.codegen.base.test import test_mesh_info
-
- resolution=(1024,512,256)
- local_size = (1024,1,1)
-
- devices = []
- contexts = {}
- for plat in cl.get_platforms():
- devices += plat.get_devices()
- for dev in devices:
- ctx = cl.Context([dev])
- contexts[dev] = ctx
-
- for dev,ctx in contexts.iteritems():
- for fbtype in ['double']:
- tg = OpenClTypeGen(fbtype, 'dec')
- for ghosts in [1,2]:
- order = 2*ghosts
- for dim in [1,2,3]:
- (_,mesh_info) = test_mesh_info(tg,dim,ghosts,resolution,dev,ctx)
- for cached in [False,True]:
- for symbolic_mode in [False,True]:
- for direction in xrange(dim):
- config = '=> fbtype={}, ghosts={}, dim={}, cached={}, symbolic_mode={}, direction={} device={}'.format(
- fbtype,ghosts,dim,cached,symbolic_mode,direction,dev.name)
- print config
- dsk = DirectionalStretchingKernel(typegen=tg,
- order=order, dim=dim, direction=direction,
- cached=cached,
- symbolic_mode=symbolic_mode,
- device=dev, context=ctx,
- known_vars=dict(
- mesh_info=mesh_info,
- dt=0.1,
- local_size=local_size[:dim])
- )
diff --git a/hysop/codegen/maths/stencil/coeffs.py b/hysop/codegen/maths/stencil/coeffs.py
deleted file mode 100644
index d670935400d437de476ce9e2eeefebdccc580437..0000000000000000000000000000000000000000
--- a/hysop/codegen/maths/stencil/coeffs.py
+++ /dev/null
@@ -1,9 +0,0 @@
-
-import numpy as np
-import gmpy2 as gmp
-I = gmp.mpz
-Q = gmp.mpq
-Itype = I(0).__class__
-Qtype = Q(1,2).__class__
-
-Z = I(0)
diff --git a/hysop/codegen/maths/stencil/solver.py b/hysop/codegen/maths/stencil/solver.py
deleted file mode 100644
index 7c61125290d82fed9252f3c86d33653eb773685d..0000000000000000000000000000000000000000
--- a/hysop/codegen/maths/stencil/solver.py
+++ /dev/null
@@ -1,275 +0,0 @@
-
-
-import itertools as it
-import operator, math, sys
-
-import numpy as np
-import sympy as sm
-from sympy.core.singleton import S as singleton
-from sympy.solvers.inequalities import reduce_abs_inequality, solve_poly_inequality, reduce_rational_inequalities, reduce_inequalities
-
-x,y = sm.symbols('x,y')
-f = sm.symbols('f')
-
-dec = ['\u208{}'.format(i).decode('unicode-escape') for i in xrange(10)]
-sign = [u'\u208a',u'\u208b']
-parenthesis = [u'\u208d', u'\u208e']
-
-def subscript(i,with_sign=False):
- decimals = '0123456789'
- snumber = str(i)
- if with_sign:
- s0 = snumber[0]
- if s0 in decimals:
- snumber = '+'+snumber
- out = u''
- for s in snumber:
- if s in decimals:
- out += dec[int(s)]
- elif s=='+':
- out += sign[0]
- elif s=='-':
- out += sign[1]
- else:
- out += s
- return out
-
-def subscripts(ids,sep,with_sign=False,with_parenthesis=False,prefix=''):
- if with_parenthesis:
- return u'{}{}{}{}'.format(prefix,parenthesis[0],sep.join([subscript(i,with_sign) for i in ids]),parenthesis[1])
- else:
- return u'{}{}'.format(prefix,sep.join([subscript(i,with_sign) for i in ids]))
-
-def tensor_symbol(prefix,shape,origin=None,sep=None,with_parenthesis=False,force_sign=False):
- origin = origin if origin is not None else np.asarray([0]*len(shape))
- sep = sep if sep is not None else u','
-
- with_sign = force_sign or ((origin>0).any() and len(shape)>1)
- tensor = np.empty(shape=shape,dtype=object)
- for idx in np.ndindex(*shape):
- ids = idx-origin
- sname = subscripts(ids,sep,with_sign=with_sign,with_parenthesis=with_parenthesis,prefix=prefix)
- tensor[idx] = sm.Symbol(sname.encode('utf-8'), real=True)
- tensor_vars = tensor.ravel().tolist()
- return tensor, tensor_vars
-
-def tensor_xreplace(tensor,vars):
- T = tensor.copy()
- for idx in np.ndindex(*tensor.shape):
- symbol = tensor[idx]
- if (symbol in vars.keys()):
- T[idx] = vars[symbol]
- elif (symbol.name in vars.keys()):
- T[idx] = vars[symbol.name]
- return T
-
-def factor_split(expr,variables,constant_var=None,include_var=False,init=0,_factor=True,_handle_const=True):
- expr = expr.expand()
- factors = {}
- for var in variables:
- factors[var] = init
- for arg in expr.args:
- I = arg.atoms(sm.Symbol).intersection(variables)
- if len(I)==0:
- continue
- elif len(I)==1:
- var = I.pop()
- if not include_var:
- arg = arg.xreplace({var:1})
- factors[var] += arg
- else:
- assert False, 'Expression containing two or more variables!\n{} contains {}.'.format(arg,I)
- #for var in factors:
- #factors[var] = sm.factor(factors[var],var)
- #cterm = expr
- #for var in factors:
- #cterm -= factors[var]
- #if constant_var is None:
- #assert cterm==0, 'No const var provided but there is a constant term \'{}\'!'.format(cterm)
- #else:
- #factors[constant_var] = m
- #if not include_var:
- #for var in factors:
- #factors[var] = sm.subs(factors[var],{var:1})
- return factors
-
-def build_eqs_from_dicts(d0,d1):
- treated = []
- eqs = []
- for k in d0.keys():
- expr0 = d0[k]
- expr1 = d1[k] if k in d1.keys() else 0
- de = expr1-expr0
- if de != 0:
- eqs.append(de)
- treated.append(k)
- for k in d1.keys():
- if k not in treated:
- expr0 = 0
- expr1 = d1[k]
- de = expr1-expr0
- if de != 0:
- eqs.append(de)
- return eqs
-
-def prod(it,init=1):
- return reduce(operator.mul, it, init)
-
-def gen_vec(basename,dim,same=False):
- if same:
- vec = np.array([sm.Symbol(basename, real=True)])
- else:
- vec,_ = tensor_symbol(prefix=basename,shape=(dim,))
- return vec
-
-
-def taylor(df,dx,maxn):
- expr = 0
- for n in xrange(maxn+1):
- expr += taylorn(df,dx,n)
- return expr
-
-def taylorn(df,dx,n):
- dim = dx.size
-
- def preficate(it):
- return sum(it)==n
-
- nn = range(n+1)
- itd = it.product(nn,repeat=dim)
- itd = it.ifilter(preficate,itd)
- expr = 0
- for der in itd:
- expr += taylorn_term(df,dx,der)
- return expr
-
-def taylorn_term(df,dx,der):
- fact = np.asarray([math.factorial(d) for d in der])
- return df[der]*prod((dx**der)/fact)
-
-
-
-dim = 3
-order = 1
-L=np.asarray([-2]*dim)
-R=np.asarray([+2]*dim)
-
-origin=np.abs(L)
-window = R-L+1
-dx = gen_vec('dx',dim,same=True)
-
-df,df_vars = tensor_symbol(prefix='f',shape=[9]*dim)
-S,svars = tensor_symbol(prefix='S',shape=window,origin=origin)
-
-expr = 0
-last = 0
-last2 = 0
-last3 = 0
-for ids in np.ndindex(*window):
- offset = ids-origin
- expr += S[ids]*taylor(df,offset*dx,5)
- last += S[ids]*taylorn(df,offset*dx,6)
- last2 += S[ids]*taylorn(df,offset*dx,7)
- last3 += S[ids]*taylorn(df,offset*dx,8)
-fact = factor_split(expr,df_vars)
-user_eqs = {}
-#user_eqs[df[2,0]] = 1
-#user_eqs[df[0,2]] = 1
-user_eqs[df[2,0,0]] = 1
-user_eqs[df[0,2,0]] = 1
-user_eqs[df[0,0,2]] = 1
-
-eqs = build_eqs_from_dicts(fact,user_eqs)
-
-sol = sm.solve(eqs,svars)
-for s in sol:
- print s,' = ',sol[s]
-
-Ss = tensor_xreplace(S,sol)
-
-#sol2 = {}
-#sol2[S[2,2]] = sm.Integer(0)/2/dx[0]**2
-
-
-print 'MORE MORE SOL'
-new_eqs = []
-nvars = set()
-s = 0
-for k,v in factor_split(last,df_vars).iteritems():
- if v!=0:
- eq = sm.simplify(v.xreplace(sol))
- symbols = eq.atoms(sm.Symbol)
- if eq != 0:
- print k, ' -> ', eq
- s+=eq
- inter = symbols.intersection(svars)
- if inter:
- new_eqs.append(eq)
- nvars = nvars.union(inter)
-sol2 = sm.solve(new_eqs,nvars,ignore=dx.tolist())
-for k,v in factor_split(last2,df_vars).iteritems():
- if v!=0:
- eq = sm.simplify(v.xreplace(sol).xreplace(sol2))
- symbols = eq.atoms(sm.Symbol)
- if eq != 0:
- print k, ' -> ', eq
- s+=eq
- inter = symbols.intersection(svars)
- if inter:
- new_eqs.append(eq)
- nvars = nvars.union(inter)
-sol3 = sm.solve(new_eqs,nvars,ignore=dx.tolist())
-print 'SOL:'
-for k,v in sol3.iteritems():
- print k,'=',v
-print 'MORE MORE MORE SOL'
-new_eqs = []
-nvars = set()
-for k,v in factor_split(last3,df_vars).iteritems():
- if v!=0:
- eq = sm.simplify(v.xreplace(sol).xreplace(sol2).xreplace(sol3))
- symbols = eq.atoms(sm.Symbol)
- if eq != 0:
- print k, ' -> ', eq
- inter = symbols.intersection(svars)
- if inter:
- new_eqs.append(eq)
- nvars = nvars.union(inter)
-sol4 = sm.solve(new_eqs,nvars,ignore=dx.tolist())
-print 'SOL:'
-for k,v in sol4.iteritems():
- print k,'=',v
-for s in [sol2,sol3,sol4]:
- for k,e in sol.iteritems():
- sol[k] = e.xreplace(s)
- sol.update(s)
-print sol
-Ss = tensor_xreplace(S,sol)*dx[0]**2
-print Ss
-
-E = np.zeros_like(S)
-k = gen_vec('k',dim)
-cfl = sm.Symbol('c')
-for ids in np.ndindex(*window):
- offset = ids-origin
- E[ids] = sm.exp(sm.I*np.dot(k,offset))
-stability = (1 + cfl*np.sum(Ss*E))
-stability = stability.rewrite(sm.cos)
-
-cosit = it.product([0,1],repeat=dim)
-cond = True
-econd = []
-for cit in cosit:
- subs = {}
- for i in xrange(dim):
- subs[k[i]] = cit[i]*sm.pi
- stab = stability.xreplace(subs).xreplace({dx[0]:1})
- if cfl in stab.atoms(sm.Symbol):
- try:
- cond &= reduce_abs_inequality(sm.Abs(stab)-1,'<',cfl)
- except:
- econd.append(sm.Abs(stab)<1)
-
-print cond.as_set()
-print econd
-
diff --git a/hysop/codegen/maths/stencil/stencil.py b/hysop/codegen/maths/stencil/stencil.py
deleted file mode 100644
index 8205d2fe81a72ab4516aa2c68e9fa18b13deddd4..0000000000000000000000000000000000000000
--- a/hysop/codegen/maths/stencil/stencil.py
+++ /dev/null
@@ -1,168 +0,0 @@
-import math, hashlib
-import numpy as np
-import scipy as sp
-import sympy as sm
-import itertools as it
-
-import scipy.sparse
-
-import gmpy2 as gmp
-from gmpy2 import mpq
-
-def _mpqize(x):
- return mpq(x.p,x.q)
-mpqize = np.vectorize(_mpqize)
-
-class Stencil(object):
- def __init__(self, stencil_data, origin, order):
- stencil = np.asarray(stencil_data)
- origin = np.asarray(origin)
- order = np.asarray(order)
-
- dim = stencil.ndim
- dtype = stencil.dtype
- shape = stencil.shape
-
- assert (origin>=0).all(), 'origin<0!'
- L = origin
- R = shape-origin-1
-
- self.stencil = stencil
- self.origin = origin
- self.order = order
-
- self.dim = dim
- self.dtype = dtype
- self.shape = shape
-
- self.L = L
- self.R = R
-
- def coo_stencil(self):
- assert self.dim==2
- return sp.sparse.coo_matrix(self.stencil,shape=self.shape,dtype=self.dtype)
-
- def iteritems(self):
- iterator = np.ndindex(self.shape)
- iterator = it.imap(lambda x: (x-self.origin,self.stencil[x]), iterator)
- iterator = it.ifilter(lambda x: x[1]!=0, iterator)
- return iterator
-
- def hash(self):
- stencil = self.stencil
- m = hashlib.sha1()
- m.update(self.origin)
- m.update(self.order)
- for d in stencil:
- m.update(str(d))
- return m.hexdigest()[:8]
-
- def is_centered(self,axe=None):
- if axe==None:
- return (L==R).all()
- else:
- return (L[axe]==R[axe]).all()
-
- def is_cross(self):
- mask = np.ones(self.shape,dtype=bool)
- access = self.origin.tolist()
- for i in xrange(self.dim):
- acc = [x for x in access]
- acc[i] = slice(0,self.shape[i])
- mask[acc] = False
- return not np.any(self.stencil*mask)
-
-
-
-class StencilGenerator(object):
- def __init__(self,derivative,dim,dtype=mpq):
- self.derivative = derivative
- self.dim = dim
- self.dtype = dtype
-
-
- #L = L if np.isscalar(L) else np.asarray(L))
- #if R is None:
- #R = k+order-L-1
- #assert((R>=0).all(), 'R<0...')
- #else:
- #assert((L+R+1 == k+order).all()), 'L+R+1 != k+order, cannot compute coefficients !'
- #R = R if np.isscalar(R) else np.asarray(R))
- #N = L+R+1
-
-class Stencil1D(Stencil):
- def __init__(self):
- self.Lx = 0
- self.Rx = 0
- self.k = 0
- self.order = 0
- self.N = 0
- self.dtype = None
-
- # generate a discrete stencil of the 'k'-th derivative at order 'order' defined over [-Lx,Rx] grid points.
- # Note: generated order can be > specified order if stencil coefficients are 0 at borders.
- def generate(self,Lx,Rx,k,order,dtype=mpq):
- assert(Lx+Rx+1 == k+order), 'Lx+Rx != k+order, cannot compute coefficients !'
- self.Lx = Lx
- self.Rx = Rx
- self.k = k
- self.order = order
- self.dtype = dtype
-
- N = Lx+Rx+1
- A = np.zeros((N,N),dtype=object)
- b = np.zeros(N,dtype=object)
- for i in xrange(N):
- b[i] = dtype(i==k)
- for j in xrange(0,N):
- A[i,j] = dtype(j-Lx)**i
- A = sm.Matrix(N,N,A.flatten())
- b = sm.Matrix(N,1,b.flatten())
-
- S = A.LUsolve(b)
- S *= dtype(math.factorial(k))
- S = mpqize(np.asarray(S.tolist(),dtype=object).ravel())
-
- self.N = N
- self.stencil = S
- return self
-
- def add_zeros(self,L,R):
- S = self.stencil
- Zl = np.zeros(L,dtype=object)
- Zr = np.zeros(R,dtype=object)
- return np.concatenate((Zl,S,Zr))
-
- def __str__(self):
- if(self.N == 0):
- return ''
- else:
- return '['+','.join([s.__str__() for s in self.stencil])+']'
-
-class SymmetricStencil1D(Stencil1D):
- def __init__(self):
- super(self.__class__,self).__init__()
-
- def generate(self,L,k,order,dtype=mpq):
- assert L == k+order, 'L != k+order, cannot compute stencil!'
- Lx = (L-1)//2
- Ly = Lx
- return super(self.__class__,self).generate(Lx,Ly,k,order,dtype)
-
-if __name__ == '__main__':
- print 'first derivative'
- print Stencil1D().generate(Lx=0,Rx=1,k=1,order=1,dtype=mpq)
- print Stencil1D().generate(Lx=1,Rx=0,k=1,order=1,dtype=mpq)
- print Stencil1D().generate(Lx=1,Rx=1,k=1,order=2,dtype=mpq)
- print Stencil1D().generate(Lx=2,Rx=2,k=1,order=4,dtype=mpq)
- print
- print 'second derivative'
- print Stencil1D().generate(Lx=1,Rx=1,k=2,order=1,dtype=mpq)
- print Stencil1D().generate(Lx=1,Rx=2,k=2,order=2,dtype=mpq)
- print Stencil1D().generate(Lx=2,Rx=1,k=2,order=2,dtype=mpq)
- print Stencil1D().generate(Lx=2,Rx=2,k=2,order=3,dtype=mpq)
- print
- print 'using symmetric stencil class'
- for i in xrange(1,5):
- print SymmetricStencil1D().generate(L=2*i+1,k=2,order=2*(i-1)+1)
-
diff --git a/hysop/codegen/maths/sympy_utils.py b/hysop/codegen/maths/sympy_utils.py
deleted file mode 100644
index 8e7cd3604f4b9cfbf0b9c245a3c6308765a83334..0000000000000000000000000000000000000000
--- a/hysop/codegen/maths/sympy_utils.py
+++ /dev/null
@@ -1,45 +0,0 @@
-
-import sympy as sm
-
-def non_eval_xreplace(expr, rule):
- """
- Duplicate of sympy's xreplace but with non-evaluate statement included
- """
- if expr in rule:
- return rule[expr]
- elif rule:
- args = []
- altered = False
- for a in expr.args:
- try:
- new_a = non_eval_xreplace(a, rule)
- except AttributeError:
- new_a = a
- if new_a != a:
- altered = True
- args.append(new_a)
- args = tuple(args)
- if altered:
- return expr.func(*args, evaluate=False)
- return expr
-
-# Convert powers to mult. in polynomial expressions
-# Example: x^3 -> x*x*x
-def remove_pows(expr):
- pows = list(expr.atoms(sm.Pow))
- repl = [sm.Mul(*[b]*e,evaluate=False) for b,e in [i.as_base_exp() for i in pows]]
- e = non_eval_xreplace(expr,dict(zip(pows,repl)))
- print e
- return e
-
-def evalf_str(x,n,literal='',significant=True):
- x = x.evalf(n).__str__()
- if significant:
- i=len(x)
- while i>1 and x[i-1] == '0':
- i-=1
- if i>1:
- x = x[:i+1]
- return x+literal
-
-
diff --git a/hysop/common_f/parameters.f90 b/hysop/common_f/parameters.f90
new file mode 100644
index 0000000000000000000000000000000000000000..ba18998c9b3832f01115bbf5ebad59d2759eb5a6
--- /dev/null
+++ b/hysop/common_f/parameters.f90
@@ -0,0 +1,32 @@
+!> Select float precision for the whole code.
+!! This is a generated file, do not edit.
+!! Usage :
+!! cmake -DDOUBLEPREC=ON ...
+!! with value = simple or value = double
+module parameters
+
+ use, intrinsic :: iso_c_binding
+ use precision
+ implicit none
+
+ !> alias to 1. in wp
+ real(kind=wp), parameter :: ONE = 1.
+ !> alias to 0. in wp
+ real(kind=wp), parameter :: ZERO = 0.
+
+ !> trick to identify coordinates in a more user-friendly way
+ integer, parameter :: c_X=1,c_Y=2,c_Z=3
+
+ !> MPI main communicator
+ integer :: main_comm
+
+ !> Rank of the mpi current process
+ integer :: rank ! current mpi-processus rank
+
+ !> i (sqrt(-1) ...)
+ complex(C_DOUBLE_COMPLEX), parameter :: Icmplx = cmplx(zero, one, kind=wp)
+
+ !> Pi constant
+ real(wp), parameter :: pi = 4.0*atan(one)
+
+end module parameters
diff --git a/hysop/fortran/template.f95 b/hysop/common_f/template.f95
similarity index 77%
rename from hysop/fortran/template.f95
rename to hysop/common_f/template.f95
index 77685fb293e3c9d23968b5f00494b6a35bde7c2b..5a1ade9d83ab0c0360289a3b5ba8a6f668d3960c 100644
--- a/hysop/fortran/template.f95
+++ b/hysop/common_f/template.f95
@@ -13,15 +13,15 @@ contains
!> do something ...
subroutine check_f2py(input, output)
-
+ use precision
!> input array
- real(kind=8), dimension(:,:), intent(in) :: input
+ real(kind=wp), dimension(:,:), intent(in) :: input
!> output array
- real(kind=8), dimension(:,:), intent(inout) :: output
+ real(kind=wp), dimension(:,:), intent(inout) :: output
print *, 'template f2py for tab'
output(:,:) = 2 * input(:,:)
print *, 'aha hah', output(1,1)
end subroutine check_f2py
-
+
end module template_f2py
diff --git a/hysop/common_f/template.pyf b/hysop/common_f/template.pyf
new file mode 100644
index 0000000000000000000000000000000000000000..bf48cb51873bef009fc639ce31700bf7dc90c10e
--- /dev/null
+++ b/hysop/common_f/template.pyf
@@ -0,0 +1,14 @@
+! -*- f90 -*-
+! Note: the context of this file is case sensitive.
+module template_f2py ! in :template_f2py:template.f95
+
+ integer, parameter,optional :: var1=12
+ subroutine check_f2py(input,output) ! in :template_f2py:template.f95:template_f2py
+ use precision
+ real(kind=wp) dimension(:,:),intent(in) :: input
+ real(kind=wp), dimension(size(input,1), size(input,2)), intent(in,out), depend(input,input) :: output
+ end subroutine check_f2py
+end module template_f2py
+
+! This file was auto-generated with f2py (version:2).
+! See http://cens.ioc.ee/projects/f2py2e/
diff --git a/hysop/constants.py b/hysop/constants.py
old mode 100755
new mode 100644
index 5894a663591087c1a71e00828d9ccc7103acc216..0c517fb552817fb091a959bebd2f0629fa8a919b
--- a/hysop/constants.py
+++ b/hysop/constants.py
@@ -1,120 +1,212 @@
-"""
-Constant parameters required for the hysop package.
+"""Default values for constant parameters used
+in hysop package.
+
+Mostly deals with float/int numbers precision and
+some labels for numerical methods and operators.
+
+This file is generated from constants.py.in
+and it's probably a bad idea to modify it.
"""
-from hysop import __VERBOSE__, __DEBUG__, __PROFILE__
-from hysop.mpi import MPI
-from hysop.tools.enum import EnumFactory
-import numpy as np
-import math
+import hysop
+from hysop import __VERBOSE__, __DEBUG__, __PROFILE__,\
+ __KERNEL_DEBUG__, __MPI_ENABLED__
+from hysop.deps import math, np, it, inspect, os
+from hysop.tools.enum import EnumFactory
+
+if __MPI_ENABLED__:
+ from hysop.core.mpi import MPI
+
+HYSOP_ROOT=os.path.dirname(inspect.getfile(hysop))
PI = math.pi
-# Set default type for real and integer numbers
HYSOP_REAL = np.float64
+"""Set default type for real numbers"""
SIZEOF_HYSOP_REAL = int(HYSOP_REAL(1.).nbytes)
+"""Size in memory of hysop real default type"""
+
+assert HYSOP_REAL in [np.float32, np.float64]
+HYSOP_COMPLEX = (np.complex128 if (HYSOP_REAL==np.float64) else np.complex64)
+"""Set default type for complex numbers"""
+SIZEOF_HYSOP_COMPLEX = int(HYSOP_COMPLEX(1.).nbytes)
+"""Size in memory of hysop complex default type"""
-# type for array indices
HYSOP_INDEX = np.uint32
+"""type for array indices"""
SIZEOF_HYSOP_INDEX = int(HYSOP_INDEX(1).nbytes)
+"""Size in memory of hysop index type"""
-# type for integers
HYSOP_INTEGER = np.int32
+"""type for integers"""
SIZEOF_HYSOP_INTEGER = int(HYSOP_INTEGER(1).nbytes)
+"""Size in memory of hysop integer type"""
-# integer used for arrays dimensions
HYSOP_DIM = np.int16
+"""integer used for arrays dimensions"""
SIZEOF_HYSOP_DIM = int(HYSOP_DIM(1).nbytes)
+"""Size in memory of hysop dim type"""
-# float type for MPI messages
-HYSOP_MPI_REAL = MPI.DOUBLE
-# int type for MPI messages
-HYSOP_MPI_INTEGER = MPI.INT
+HYSOP_BOOL = np.uint8
+"""type for booleans"""
+SIZEOF_HYSOP_BOOL = int(HYSOP_BOOL(1).nbytes)
+"""Size in memory of hysop boolean type"""
-## default array layout (fortran or C convention)
-ORDER = 'F'
-## Default array layout for MPI
-ORDERMPI = MPI.ORDER_F
+HYSOP_EPS = np.finfo(HYSOP_REAL).eps
+"""machine epsilon for HYSOP_REAL"""
-if ORDER is 'F':
- CHECK_F_CONT = True
-else:
- CHECK_F_CONT = False
-
-
-## label for x direction
-XDIR = 0
-## label for y direction
-YDIR = 1
-## label for z direction
-ZDIR = 2
-## Directions string
-S_DIR = ['_X', '_Y', '_Z']
-
-MeshDir = EnumFactory.create('MeshDir',
- {'X':XDIR,'Y':YDIR,'Z':ZDIR})
-MeshState = EnumFactory.create('MeshState',
- ['XYZ','YXZ','ZXY','ZYX'])
-
-## Tag for periodic boundary conditions
-PERIODIC = 99
-BoundaryCondition = EnumFactory.create('BoundaryCondition', {'PERIODIC':PERIODIC})
-
-## Stretching formulation ([grad(u)][w]) or conservative (div(w:u))
-GRADUW = 0
-CONSERVATIVE = 1
-StretchingFormulation = EnumFactory.create('StetchingFormulation',
- {'GRADUW':GRADUW, 'CONSERVATIVE':CONSERVATIVE})
-
-
-## Optimisation level for numerics methods
-## default, no optim for numerics methods
-## Optimisation level for time integrators
-## No need to recompute the right-hand side, an initial guess
-## must be given in input arguments.
-WITH_GUESS = 1
-## No need to recompute the right-hand side, an initial guess
-## must be given in input arguments and we ensure that
-## y is different from result arg.
-NOALIAS = 2
-
-## Default value for task id (mpi task)
-DEFAULT_TASK_ID = 999
-
-
-#define debug decorator:
-def debugdecorator(f):
- if __DEBUG__:
- ## function f is being decorated
- def decorator(*args, **kw):
- # Print informations on decorated function
- if f.__name__ is '__new__':
- fullclassname = args[0].__mro__[0].__module__ + '.'
- fullclassname += args[0].__mro__[0].__name__
- print ('Instanciate :', fullclassname,)
- print (' (Inherits from : ',)
- print ([c.__name__ for c in args[0].__mro__[1:]], ')')
- else:
- print ('Call : ', f.__name__, 'in ', f.__code__.co_filename,)
- print (f.__code__.co_firstlineno)
- ## Calling f
- r = f(*args, **kw)
- if f.__name__ is '__new__':
- print (' |-> : ', repr(r))
- return r
- return decorator
+HYSOP_ORDER = 'F'
+"""default array layout (fortran or C convention)"""
+
+if __MPI_ENABLED__:
+ HYSOP_MPI_REAL = MPI.DOUBLE
+ """float type used in MPI"""
+
+ HYSOP_MPI_INTEGER = MPI.INT
+ """integer type used in MPI"""
+
+ HYSOP_MPI_ORDER = MPI.ORDER_F
+ """Default array layout for MPI"""
+
+ HYSOP_DEFAULT_TASK_ID = 999
+ """Default value for task id (mpi task)"""
+
+System = EnumFactory.create('System',
+['WINDOWS', 'DARWIN', 'LINUX'])
+"""
+System type enum.
+"""
+
+Basis = EnumFactory.create('Basis',
+ ['CARTESIAN', 'FOURIER', 'CHEBYSHEV'])
+"""Basis"""
+
+Backend = EnumFactory.create('Backend',
+ ['OPENCL','HOST','CUDA'])
+"""Operator backends"""
+
+Implementation = EnumFactory.create('Implementation',
+ ['OPENCL_STATIC', 'OPENCL_CODEGEN', 'PYTHON', 'FORTRAN', 'CPP'])
+"""Operator implementations"""
+
+def implementation_to_backend(implementation):
+ if implementation in [Implementation.PYTHON, Implementation.FORTRAN, Implementation.CPP]:
+ return Backend.HOST
+ elif implementation in [Implementation.OPENCL_STATIC, Implementation.OPENCL_CODEGEN]:
+ return Backend.OPENCL
else:
- #define empty debug decorator:
- return f
+ msg='Unknown implementation key {}.'.format(implementation)
+ raise ValueError(msg)
+
+
+Precision = EnumFactory.create('Precision',
+ ['DEFAULT', 'SAME', 'QUAD', 'LONG_DOUBLE', 'DOUBLE', 'FLOAT', 'HALF'])
+"""Real number precision configuration (default_precision = HYSOP_REAL)."""
+
+MemoryOrdering = EnumFactory.create('MemoryOrdering',
+ ['C_CONTIGUOUS','FORTRAN_CONTIGUOUS','OUT_OF_ORDER', 'SAME_ORDER'])
+"""Memory ordering enum"""
-debug = debugdecorator
+MemoryType = EnumFactory.create('MemoryType',
+ ['GLOBAL_MEMORY', 'LOCAL_MEMORY','PRIVATE_MEMORY','CONSTANT_MEMORY'])
+"""Memory type enum"""
-# redefine profile decorator
-if __PROFILE__:
- from memory_profiler import profile
- prof = profile
+DeviceType = EnumFactory.create('DeviceType',
+ ['ALL','ACCELERATOR','CPU','CUSTOM','GPU','DEFAULT'])
+"""Device type enum"""
+
+CacheType = EnumFactory.create('CacheType',
+ ['NONE','READ_ONLY_CACHE','READ_WRITE_CACHE'])
+"""Cache type enum"""
+
+FpConfig = EnumFactory.create('FpConfig',
+ ['CORRECTLY_ROUNDED_DIVIDE_SQRT', 'DENORM', 'FMA', 'INF_NAN',
+ 'ROUND_TO_INF', 'ROUND_TO_NEAREST', 'ROUND_TO_ZERO', 'SOFT_FLOAT'])
+"""Floating point flags"""
+
+
+DirectionLabels = 'XYZAB'
+"""Directions labels up to 5d"""
+
+Directions = EnumFactory.create('Directions', DirectionLabels.split())
+"""Directions enum"""
+
+BoundaryCondition = EnumFactory.create('BoundaryCondition',
+ [ 'NONE', # => boundaries are already in ghosts
+ 'PERIODIC', 'NEUMANN', 'DIRICHLET', 'MIXED' ])
+"""Boundary conditions enum"""
+
+FieldProjection = EnumFactory.create('FieldProjection',
+ ['NONE', 'EVERY_STEP'])
+"""Field projection mode for Poisson solver"""
+
+StretchingFormulation = EnumFactory.create('StretchingFormulation',
+ ['GRAD_UW', 'GRAD_UW_T', 'MIXED_GRAD_UW', 'CONSERVATIVE'])
+"""Stretching formulations"""
+
+SpaceDiscretization = EnumFactory.create('SpaceDiscretization',
+ ['FDC2', 'FDC4', 'FDC6', 'FDC8'])
+"""Space discretization for stencil generation"""
+
+
+AutotunerFlags = EnumFactory.create('AutotunerFlags',
+ ['ESTIMATE', 'MEASURE', 'PATIENT', 'EXHAUSTIVE' ])
+"""Configuration flags for kernel autotuner
+ (automatic runtime parameters tuning for cuda and opencl)."""
+DEFAULT_AUTOTUNER_FLAG = AutotunerFlags.MEASURE
+DEFAULT_AUTOTUNER_PRUNE_THRESHOLD = 1.20
+
+TimeIntegratorsOptimisationLevel = EnumFactory.create('TimeIntegratorsOptimisationLevel', \
+ ['WITH_GUESS', 'NOALIAS'])
+"""
+Optimisation level for time integrators.
+
+WITH_GUESS: no need to recompute the right-hand side, an initial guess
+must be given in input arguments.
+
+NOALIAS: no need to recompute the right-hand side, an initial guess
+must be given in input arguments and we ensure that
+y is different from result arg.
+"""
+
+transposition_states = {}
+"""Dictionnary containing transposition states enums up to 5D."""
+
+for i in xrange(1,len(DirectionLabels)):
+ labels = DirectionLabels[:i]
+ entries = it.permutations(labels, i)
+ entries = [''.join(x) for x in entries]
+ cls = EnumFactory.create('TranspositionState{}D'.format(i), entries)
+ default = entries[0]
+ if HYSOP_ORDER == 'F':
+ default = default[::-1]
+ cls.default = cls(default)
+ transposition_states[i] = cls
+del entries
+del cls
+del default
+del labels
+
+TranspositionState1D = transposition_states[1]
+"""1D memory layout (transposition state) enum"""
+
+TranspositionState2D = transposition_states[2]
+"""2D memory layout (transposition state) enum"""
+
+TranspositionState3D = transposition_states[3]
+"""3D memory layout (transposition state) enum"""
+
+default_order = None
+"""
+Default HySoP memory ordering for array allocations.
+"""
+
+if HYSOP_ORDER == 'F':
+ default_order = MemoryOrdering.FORTRAN_CONTIGUOUS
+elif HYSOP_ORDER == 'C':
+ default_order = MemoryOrdering.C_CONTIGUOUS
else:
- def prof(f):
- # Nothing ...
- return f
+ msg='HYSOP_ORDER should be \'F\' or \'C\' (got {}).'
+ raise ValueError(msg.format(HYSOP_ORDER))
+
diff --git a/hysop/constants.py.in b/hysop/constants.py.in
new file mode 100644
index 0000000000000000000000000000000000000000..2d6fdd5a74d4adf2558abbfc0b63e7b0601a3051
--- /dev/null
+++ b/hysop/constants.py.in
@@ -0,0 +1,212 @@
+"""Default values for constant parameters used
+in hysop package.
+
+Mostly deals with float/int numbers precision and
+some labels for numerical methods and operators.
+
+This file is generated from constants.py.in
+and it's probably a bad idea to modify it.
+"""
+
+
+import hysop
+from hysop import __VERBOSE__, __DEBUG__, __PROFILE__,\
+ __KERNEL_DEBUG__, __MPI_ENABLED__
+from hysop.deps import math, np, it, inspect, os
+from hysop.tools.enum import EnumFactory
+
+if __MPI_ENABLED__:
+ from hysop.core.mpi import MPI
+
+HYSOP_ROOT=os.path.dirname(inspect.getfile(hysop))
+
+PI = math.pi
+
+HYSOP_REAL = @PYTHON_PREC@
+"""Set default type for real numbers"""
+SIZEOF_HYSOP_REAL = int(HYSOP_REAL(1.).nbytes)
+"""Size in memory of hysop real default type"""
+
+assert HYSOP_REAL in [np.float32, np.float64]
+HYSOP_COMPLEX = (np.complex128 if (HYSOP_REAL==np.float64) else np.complex64)
+"""Set default type for complex numbers"""
+SIZEOF_HYSOP_COMPLEX = int(HYSOP_COMPLEX(1.).nbytes)
+"""Size in memory of hysop complex default type"""
+
+HYSOP_INDEX = np.uint32
+"""type for array indices"""
+SIZEOF_HYSOP_INDEX = int(HYSOP_INDEX(1).nbytes)
+"""Size in memory of hysop index type"""
+
+HYSOP_INTEGER = np.int32
+"""type for integers"""
+SIZEOF_HYSOP_INTEGER = int(HYSOP_INTEGER(1).nbytes)
+"""Size in memory of hysop integer type"""
+
+HYSOP_DIM = np.int16
+"""integer used for arrays dimensions"""
+SIZEOF_HYSOP_DIM = int(HYSOP_DIM(1).nbytes)
+"""Size in memory of hysop dim type"""
+
+HYSOP_BOOL = np.uint8
+"""type for booleans"""
+SIZEOF_HYSOP_BOOL = int(HYSOP_BOOL(1).nbytes)
+"""Size in memory of hysop boolean type"""
+
+HYSOP_EPS = np.finfo(HYSOP_REAL).eps
+"""machine epsilon for HYSOP_REAL"""
+
+HYSOP_ORDER = @DATA_LAYOUT@
+"""default array layout (fortran or C convention)"""
+
+if __MPI_ENABLED__:
+ HYSOP_MPI_REAL = @MPI_PYTHON_PREC@
+ """float type used in MPI"""
+
+ HYSOP_MPI_INTEGER = MPI.INT
+ """integer type used in MPI"""
+
+ HYSOP_MPI_ORDER = @MPI_DATA_LAYOUT@
+ """Default array layout for MPI"""
+
+ HYSOP_DEFAULT_TASK_ID = 999
+ """Default value for task id (mpi task)"""
+
+System = EnumFactory.create('System',
+['WINDOWS', 'DARWIN', 'LINUX'])
+"""
+System type enum.
+"""
+
+Basis = EnumFactory.create('Basis',
+ ['CARTESIAN', 'FOURIER', 'CHEBYSHEV'])
+"""Basis"""
+
+Backend = EnumFactory.create('Backend',
+ ['OPENCL','HOST','CUDA'])
+"""Operator backends"""
+
+Implementation = EnumFactory.create('Implementation',
+ ['OPENCL_STATIC', 'OPENCL_CODEGEN', 'PYTHON', 'FORTRAN', 'CPP'])
+"""Operator implementations"""
+
+def implementation_to_backend(implementation):
+ if implementation in [Implementation.PYTHON, Implementation.FORTRAN, Implementation.CPP]:
+ return Backend.HOST
+ elif implementation in [Implementation.OPENCL_STATIC, Implementation.OPENCL_CODEGEN]:
+ return Backend.OPENCL
+ else:
+ msg='Unknown implementation key {}.'.format(implementation)
+ raise ValueError(msg)
+
+
+Precision = EnumFactory.create('Precision',
+ ['DEFAULT', 'SAME', 'QUAD', 'LONG_DOUBLE', 'DOUBLE', 'FLOAT', 'HALF'])
+"""Real number precision configuration (default_precision = HYSOP_REAL)."""
+
+MemoryOrdering = EnumFactory.create('MemoryOrdering',
+ ['C_CONTIGUOUS','FORTRAN_CONTIGUOUS','OUT_OF_ORDER', 'SAME_ORDER'])
+"""Memory ordering enum"""
+
+MemoryType = EnumFactory.create('MemoryType',
+ ['GLOBAL_MEMORY', 'LOCAL_MEMORY','PRIVATE_MEMORY','CONSTANT_MEMORY'])
+"""Memory type enum"""
+
+DeviceType = EnumFactory.create('DeviceType',
+ ['ALL','ACCELERATOR','CPU','CUSTOM','GPU','DEFAULT'])
+"""Device type enum"""
+
+CacheType = EnumFactory.create('CacheType',
+ ['NONE','READ_ONLY_CACHE','READ_WRITE_CACHE'])
+"""Cache type enum"""
+
+FpConfig = EnumFactory.create('FpConfig',
+ ['CORRECTLY_ROUNDED_DIVIDE_SQRT', 'DENORM', 'FMA', 'INF_NAN',
+ 'ROUND_TO_INF', 'ROUND_TO_NEAREST', 'ROUND_TO_ZERO', 'SOFT_FLOAT'])
+"""Floating point flags"""
+
+
+DirectionLabels = 'XYZAB'
+"""Directions labels up to 5d"""
+
+Directions = EnumFactory.create('Directions', DirectionLabels.split())
+"""Directions enum"""
+
+BoundaryCondition = EnumFactory.create('BoundaryCondition',
+ [ 'NONE', # => boundaries are already in ghosts
+ 'PERIODIC', 'NEUMANN', 'DIRICHLET', 'MIXED' ])
+"""Boundary conditions enum"""
+
+FieldProjection = EnumFactory.create('FieldProjection',
+ ['NONE', 'EVERY_STEP'])
+"""Field projection mode for Poisson solver"""
+
+StretchingFormulation = EnumFactory.create('StretchingFormulation',
+ ['GRAD_UW', 'GRAD_UW_T', 'MIXED_GRAD_UW', 'CONSERVATIVE'])
+"""Stretching formulations"""
+
+SpaceDiscretization = EnumFactory.create('SpaceDiscretization',
+ ['FDC2', 'FDC4', 'FDC6', 'FDC8'])
+"""Space discretization for stencil generation"""
+
+
+AutotunerFlags = EnumFactory.create('AutotunerFlags',
+ ['ESTIMATE', 'MEASURE', 'PATIENT', 'EXHAUSTIVE' ])
+"""Configuration flags for kernel autotuner
+ (automatic runtime parameters tuning for cuda and opencl)."""
+DEFAULT_AUTOTUNER_FLAG = AutotunerFlags.MEASURE
+DEFAULT_AUTOTUNER_PRUNE_THRESHOLD = 1.20
+
+TimeIntegratorsOptimisationLevel = EnumFactory.create('TimeIntegratorsOptimisationLevel', \
+ ['WITH_GUESS', 'NOALIAS'])
+"""
+Optimisation level for time integrators.
+
+WITH_GUESS: no need to recompute the right-hand side, an initial guess
+must be given in input arguments.
+
+NOALIAS: no need to recompute the right-hand side, an initial guess
+must be given in input arguments and we ensure that
+y is different from result arg.
+"""
+
+transposition_states = {}
+"""Dictionnary containing transposition states enums up to 5D."""
+
+for i in xrange(1,len(DirectionLabels)):
+ labels = DirectionLabels[:i]
+ entries = it.permutations(labels, i)
+ entries = [''.join(x) for x in entries]
+ cls = EnumFactory.create('TranspositionState{}D'.format(i), entries)
+ default = entries[0]
+ if HYSOP_ORDER == 'F':
+ default = default[::-1]
+ cls.default = cls(default)
+ transposition_states[i] = cls
+del entries
+del cls
+del default
+del labels
+
+TranspositionState1D = transposition_states[1]
+"""1D memory layout (transposition state) enum"""
+
+TranspositionState2D = transposition_states[2]
+"""2D memory layout (transposition state) enum"""
+
+TranspositionState3D = transposition_states[3]
+"""3D memory layout (transposition state) enum"""
+
+default_order = None
+"""
+Default HySoP memory ordering for array allocations.
+"""
+
+if HYSOP_ORDER == 'F':
+ default_order = MemoryOrdering.FORTRAN_CONTIGUOUS
+elif HYSOP_ORDER == 'C':
+ default_order = MemoryOrdering.C_CONTIGUOUS
+else:
+ msg='HYSOP_ORDER should be \'F\' or \'C\' (got {}).'
+ raise ValueError(msg.format(HYSOP_ORDER))
+
diff --git a/hysop/core/__init__.py b/hysop/core/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/core/arrays/__init__.py b/hysop/core/arrays/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..63dd10ec025ca291857a09bd51dd5dc3acbe8beb
--- /dev/null
+++ b/hysop/core/arrays/__init__.py
@@ -0,0 +1,6 @@
+
+from hysop.constants import default_order, transposition_states
+from hysop.constants import MemoryOrdering, MemoryType
+
+from hysop.tools.enum import EnumFactory
+QueuePolicy = EnumFactory.create('QueuePolicy', ['NO_QUEUE', 'COPY_QUEUE', 'SAME_AS_TRANSFER'])
diff --git a/hysop/core/arrays/all.py b/hysop/core/arrays/all.py
new file mode 100644
index 0000000000000000000000000000000000000000..589335754727fd3a746f9fb54dcf528a25f286f3
--- /dev/null
+++ b/hysop/core/arrays/all.py
@@ -0,0 +1,12 @@
+
+from hysop.core.arrays.array_backend import ArrayBackend
+from hysop.core.arrays.array import Array
+
+from hysop.backend.host.host_array_backend import HostArrayBackend
+from hysop.backend.host.host_array import HostArray
+
+from hysop.backend.device.opencl.opencl_array_backend import OpenClArrayBackend
+from hysop.backend.device.opencl.opencl_array import OpenClArray
+
+from hysop.backend.host.host_allocator import default_host_mempool
+default_host_array_backend = HostArrayBackend(default_host_mempool)
diff --git a/hysop/core/arrays/array.py b/hysop/core/arrays/array.py
new file mode 100644
index 0000000000000000000000000000000000000000..28dc6dce348b5a64f6854de95bc3553a1af7ab7c
--- /dev/null
+++ b/hysop/core/arrays/array.py
@@ -0,0 +1,813 @@
+from abc import ABCMeta, abstractmethod
+
+import numpy as np
+from hysop.constants import MemoryOrdering
+from hysop.constants import DirectionLabels, transposition_states, default_order
+from hysop.tools.types import check_instance
+from hysop.tools.decorators import required_property, optional_property
+
+class Array(object):
+ """
+ Interface of an abstract array.
+ An array is a numpy.ndarray work-alike that stores its data and performs
+ its computations on various devices, depending on the backend.
+ All exposed functions should work exactly as in numpy.
+ Arithmetic methods in Array, when available, should at least support the
+ broadcasting of scalars.
+ """
+
+ __metaclass__ = ABCMeta
+
+ def __init__(self, handle, backend, **kwds):
+ """
+ Build an Array instance.
+
+ Parameters
+ ----------
+ handle: buffer backend implementation
+ backend: backend used to build this andle
+ kwds: arguments for base classes.
+
+ Notes
+ -----
+ This should never be called directly by the user.
+ Arrays should be constructed using array backend facilities, like zeros or empty.
+ The parameters given here refer to a low-level method for instantiating an array.
+ """
+ from hysop.core.arrays.all import ArrayBackend
+ check_instance(backend, ArrayBackend)
+
+ super(Array,self).__init__(**kwds)
+
+ self._handle=handle
+ self._backend=backend
+
+ if hasattr(handle, '__len__'):
+ setattr(self, '__len__', handle.__len__)
+
+ def get_handle(self):
+ """
+ Return underlying implementation of this buffer.
+ """
+ if not hasattr(self, '_handle'):
+ raise RuntimeError('{} has no _handle defined.', self.__class__)
+ return self._handle
+
+ def get_backend(self):
+ """
+ Return the backend corresponding to this array.
+ """
+ if not hasattr(self, '_backend'):
+ raise RuntimeError('{} has no _backend defined.', self.__class__)
+ return self._backend
+
+ handle = property(get_handle)
+ backend = property(get_backend)
+
+ @classmethod
+ def _not_implemented_yet(cls, funname):
+ msg = '{}::{} has not been implemented yet.'
+ msg=msg.format(cls.__name__, funname)
+ raise NotImplementedError(msg)
+
+ @classmethod
+ def _unsupported_argument(cls, fname, argname, arg, default_value=None):
+ if arg != default_value:
+ msg = '{}::{}() has been implemented but argument \'{}\' is not '
+ msg+= 'supported and should be set to {}.'
+ msg=msg.format(cls.__name__, fname, argname, default_value)
+ raise NotImplementedError(msg)
+
+ def wrap(self, handle):
+ """
+ Wrap handle with the same initialization arguments as this instance.
+ """
+ return self.backend.wrap(handle=handle)
+
+ def _call(self, fname, *args, **kargs):
+ """
+ Calls a handle function.
+ """
+ f = getattr(self.handle, fname)
+ return self.backend._call(f, *args, **kargs)
+
+
+ @abstractmethod
+ @required_property
+ def get_ndim(self):
+ """
+ Number of array dimensions.
+ """
+ pass
+
+ @abstractmethod
+ @required_property
+ def get_shape(self):
+ """
+ The real shape of this buffer.
+ """
+ pass
+
+ @abstractmethod
+ @required_property
+ def get_offset(self):
+ """
+ Offset of array data in buffer.
+ """
+ pass
+
+ @abstractmethod
+ @required_property
+ def get_strides(self):
+ """
+ Tuple of ints that represents the byte step in each dimension when traversing an array.
+ """
+ pass
+
+ @abstractmethod
+ @required_property
+ def get_data(self):
+ """
+ Buffer object pointing to the start of the array's data
+ """
+ pass
+
+ @abstractmethod
+ @required_property
+ def get_base(self):
+ """
+ Base object if memory is from some other object.
+ """
+ pass
+
+ @abstractmethod
+ @required_property
+ def get_dtype(self):
+ """
+ numpy.dtype representing the type stored into this buffer.
+ """
+ pass
+
+ @optional_property
+ def get_flags(self):
+ """
+ Information about the memory layout of the array.
+ """
+ pass
+
+ @optional_property
+ def get_imag(self):
+ """
+ The imaginary part of the array.
+ """
+ pass
+
+ @optional_property
+ def get_real(self):
+ """
+ The real part of the array.
+ """
+ pass
+
+ @optional_property
+ def get_ctypes(self):
+ """
+ An object to simplify the interaction of the array with the ctypes module.
+ """
+ pass
+
+ def get_T(self):
+ """
+ Same as self.transpose(), except that self is returned if self.ndim < 2.
+ """
+ if self.get_ndim()<2:
+ return self
+ else:
+ return self.transpose()
+
+ def get_size(self):
+ """
+ Number of elements in the array.
+ """
+ return np.prod(self.get_shape())
+
+ def get_itemsize(self):
+ """
+ Number of bytes per element.
+ """
+ return self.get_dtype().itemsize
+
+ def get_nbytes(self):
+ """
+ Number of bytes in the whole buffer.
+ """
+ return self.get_itemsize()*self.size
+
+
+ # array properties to be (re)defined
+ ndim = property(get_ndim)
+ shape = property(get_shape)
+ offset = property(get_offset)
+ strides = property(get_strides)
+ data = property(get_data)
+ base = property(get_base)
+ dtype = property(get_dtype)
+
+ # optional array properties
+ flags = property(get_flags)
+ imag = property(get_imag)
+ real = property(get_real)
+ ctypes = property(get_ctypes)
+
+ # deduced array properties, may be redefined
+ size = property(get_size)
+ itemsize = property(get_itemsize)
+ nbytes = property(get_nbytes)
+ T = property(get_T)
+
+ @abstractmethod
+ def get(self, handle=False):
+ """
+ Returns a HostArray, view or copy of this array.
+ Usefull for backends thats do not share physical memory with the host.
+ """
+ pass
+
+ def get_data_base(self):
+ """
+ For a given HostArray, finds the
+ base array that 'owns' the actual data.
+ """
+ base = self
+ while isinstance(base.base, self.__class__):
+ base = base.base
+ return base
+
+ def share_data(self, other):
+ """
+ Returns true if self share the same
+ memory location as other.
+ """
+ return self.get_data_base() is other.get_data_base()
+
+ def ctype(self):
+ """
+ Equivalent C type corresponding to the numpy.dtype.
+ """
+ self.__class__.not_implemented_yet('ctype')
+
+
+ def axes(self):
+ """
+ Axes state (axe 0 is the fastest varying index, last axe is the slowest varying index).
+ ie 3D C-ordering is [2,1,0]
+ 3D fotran-ordering is [0,1,2]
+ """
+ return np.argsort(self.strides, kind='mergesort')
+
+ def transposition_state(self):
+ """
+ Transposition state (from the slowest varying index to the fastest varying index).
+ ie 3D C-ordering is ZYX -> X is the fastest index
+ 3D fotran-ordering is XYZ -> Z is the fastest index
+ """
+ dim = self.ndim
+ axes = self.axes()
+ if dim in transposition_states.keys():
+ state = list(' '*dim)
+ for i,a in enumerate(self.axes()):
+ state[a] = DirectionLabels[i]
+ state=''.join(state)
+ return getattr(transposition_states[dim],state)
+ else:
+ return None
+
+ def get_order(self):
+ """
+ Memory ordering
+ Determine whether the array is written in C-contiguous order
+ (last index varies the fastest), or FORTRAN-contiguous order
+ in memory (first index varies the fastest) or out of order.
+ If dimension is one, default_order is returned.
+ """
+ dim = self.ndim
+ if dim==1:
+ return default_order
+ else:
+ axes = self.axes()
+ fortran = np.arange(dim)
+ if (axes==fortran[::-1]).all():
+ return MemoryOrdering.C_CONTIGUOUS
+ elif (axes==fortran).all():
+ return MemoryOrdering.FORTRAN_CONTIGUOUS
+ else:
+ return MemoryOrdering.OUT_OF_ORDER
+ order = property(get_order)
+
+ def is_fp(self):
+ """
+ Return true if dtype is a floatting point type.
+ """
+ return self.dtype in [np.float16, np.float32, np.float64]
+
+ def is_c_contiguous(self):
+ """
+ Return true if dimension is one or if current order is C_CONTIGUOUS.
+ """
+ return (self.ndim==1) or (self.order == MemoryOrdering.C_CONTIGUOUS)
+
+ def is_fortran_contiguous(self):
+ """
+ Return true if dimension is one or if current order is FORTRAN_CONTIGUOUS.
+ """
+ return (self.ndim==1) or (self.order == MemoryOrdering.FORTRAN_CONTIGUOUS)
+
+ def is_hysop_contiguous(self):
+ """
+ Return true if dimension is one or if current order corresponds to hysop default order.
+ """
+ return self.order == default_order
+
+ def copy_from(self, src, **kargs):
+ """
+ Copy data from buffer src
+ """
+ self.backend.memcpy(self,src, **kargs)
+
+ def copy_to(self, dst, **kargs):
+ """
+ Copy data from buffer to dst
+ """
+ self.backend.memcpy(dst,self, **kargs)
+
+
+ def transpose_to_state(self, state, **kargs):
+ """
+ Transpose buffer to specified transposition state.
+ """
+ origin = str(self.transposition_state())
+ target = str(state)
+ if origin == target:
+ return
+
+ axes = []
+ for axe in target:
+ axes.append(origin.index(axe))
+ return self.transpose(axes=axes)
+
+
+
+ # np.ndarray like methods
+
+ def all(self, axis=None, out=None, **kargs):
+ """
+ Returns True if all elements evaluate to True.
+ """
+ return self.backend.all(a=self, axis=axis, out=out, **kargs)
+
+ def any(self, axis=None, out=None, **kargs):
+ """
+ Returns True if any of the elements of a evaluate to True.
+ """
+ return self.backend.any(a=self, axis=axis, out=out, **kargs)
+
+ def argmax(self, axis=None, out=None, **kargs):
+ """
+ Return indices of the maximum values along the given axis.
+ """
+ return self.backend.argmax(a=self, axis=axis, out=out, **kargs)
+
+ def argmin(self, axis=None, out=None, **kargs):
+ """
+ Return indices of the minimum values along the given axis of a.
+ """
+ return self.backend.argmin(a=self, axis=axis, out=out, **kargs)
+
+ def argpartition(self, kth, axis=-1, kind='quicksort', order=None, **kargs):
+ """
+ Returns the indices that would partition this array.
+ """
+ return self.backend.argpartition(a=self, kth=kth, axis=axis, kind=kind,
+ order=order, **kargs)
+
+ def argsort(self, axis=-1, kind='quicksort', order=None, **kargs):
+ """
+ Returns the indices that would sort this array.
+ """
+ return self.backend.argsort(a=self, axis=axis, kind=kind, order=order, **kargs)
+
+ def astype(self, dtype, order=MemoryOrdering.SAME_ORDER, casting='unsafe', subok=True,
+ copy=True, **kargs):
+ """
+ Copy of the array, cast to a specified type.
+ """
+ return self.backend.astype(a=self, dtype=dtype, order=order, casting=casting,
+ subok=subok, copy=copy, **kargs)
+
+ def byteswap(self, inplace=False, **kargs):
+ """
+ Swap the bytes of the array elements
+ Toggle between low-endian and big-endian data representation by returning
+ a byteswapped array, optionally swapped in-place.
+ """
+ return self.backend.byteswap(a=self, inplace=inplace, **kargs)
+
+ def choose(self, choices, out=None, mode='raise', **kargs):
+ """
+ Use an index array to construct a new array from a set of choices.
+ """
+ return self.backend.choose(choices, out=out, mode='raise', **kargs)
+
+ def clip(self, min=None, max=None, out=None, **kargs):
+ """
+ Return an array whose values are limited to min, max.
+ """
+ return self.backend.clip(a=self, a_min=min, a_max=max, out=out, **kargs)
+
+ def compress(self, condition, axis=None, out=None, **kargs):
+ """
+ Return selected slices of this array along given axis.
+ """
+ return self.backend.compress(a=self, condition=condition, axis=axis, out=out,
+ **kargs)
+
+ def conj(self, out=None, **kargs):
+ """
+ Complex-conjugate of all elements.
+ """
+ return self.backend.conj(x=self, out=out, **kargs)
+
+ def conjugate(self, out=None, **kargs):
+ """
+ Return the complex conjugate, element-wise.
+ """
+ return self.backend.conj(x=self, out=out, **kargs)
+
+ def cumprod(self, axis=None, dtype=None, out=None, **kargs):
+ """
+ Return the cumulative product of the elements along the given axis.
+ """
+ return self.backend.cumprod(a=self, axis=axis, dtype=dtype, out=out, **kargs)
+
+ def cumsum(self, axis=None, dtype=None, out=None, **kargs):
+ """
+ Return the cumulative sum of the elements along the given axis.
+ """
+ return self.backend.cumsum(a=self, axis=axis, dtype=dtype, out=out, **kargs)
+
+ def copy(self, order=MemoryOrdering.SAME_ORDER, **kargs):
+ """
+ Return a copy of the array.
+ """
+ return self.backend.copy(a=self, order=order, **kargs)
+
+ def diagonal(self, offset=0, axis1=0, axis2=1, **kargs):
+ """
+ Return specified diagonals.
+ """
+ return self.backend.diagonal(offset=offset, axis1=axis1, axis2=axis2, **kargs)
+
+ def dot(self, b, out=None, **kargs):
+ """
+ Dot product of two arrays.
+ """
+ return self.backend.dot(a=self, b= b, out=out, **kargs)
+
+ def dump(self, file, **kargs):
+ """
+ Dump a pickle of the array to the specified file.
+ """
+ return self.backend.save(arr=self, file=file, **kargs)
+
+ def dumps(self, **kargs):
+ """
+ Returns the pickle of the array as a string.
+ """
+ return self.backend.array2string(a=self, **kargs)
+
+ def fill(self, value, **kargs):
+ """
+ Fill the array with a scalar value.
+ """
+ return self.backend.fill(a=self, value=value, **kargs)
+
+ def flatten(self, order=MemoryOrdering.SAME_ORDER, **kargs):
+ """
+ Return a copy of the array collapsed into one dimension.
+ """
+ return self.backend.flatten(a=self, order=order, **kargs)
+
+
+ def max(self, axis=None, out=None, **kargs):
+ """
+ Return the maximum along a given axis.
+ """
+ return self.backend.amax(a=self, axis=axis, out=out, **kargs)
+
+ def mean(self, axis=None, dtype=None, out=None, **kargs):
+ """
+ Returns the average of the array elements along given axis.
+ """
+ return self.backend.mean(a=self, axis=axis, dtype=dtype, out=out, **kargs)
+
+ def min(self, axis=None, out=None, **kargs):
+ """
+ Return the minimum along a given axis.
+ """
+ return self.backend.amin(a=self, axis=axis, out=out, **kargs)
+
+ def nonzero(self, **kargs):
+ """
+ Return the indices of the elements that are non-zero.
+ """
+ return self.backend.nonzero(a=self, **kargs)
+
+ def partition(self, kth, axis=-1, kind='quicksort', order=None, **kargs):
+ """
+ Rearranges the elements in the array in such a way that value of the element i
+ in kth position is in the position it would be in a sorted array.
+ """
+ return self.backend.partition(a=self, kth=kth, axis=axis, kind=kind,
+ order=order, **kargs)
+
+ def prod(self, axis=None, dtype=None, out=None, **kargs):
+ """
+ Return the product of the array elements over the given axis
+ """
+ return self.backend.prod(a=self, axis=axis, dtype=dtype, out=out, **kargs)
+
+ def ptp(self, axis=None, out=None, **kargs):
+ """
+ Peak to peak (maximum - minimum) value along a given axis.
+ """
+ return self.backend.ptp(a=self, axis=axis, out=out, **kargs)
+
+ def ravel(self, order=MemoryOrdering.SAME_ORDER, **kargs):
+ """
+ Return a flattened array.
+ """
+ return self.backend.ravel(a=self, order=order, **kargs)
+
+ def repeat(self, repeats, axis=None, **kargs):
+ """
+ Repeat elements of an array.
+ """
+ return self.backend.repeat(a=self, repeats=repeats, axis=axis, **kargs)
+
+ def reshape(self, new_shape, order=default_order, **kargs):
+ """
+ Returns an array containing the same data with a new shape.
+ """
+ return self.backend.reshape(a=self, newshape=new_shape, order=order, **kargs)
+
+ def resize(self, new_shape, refcheck=True, **kargs):
+ """
+ Change shape and size of array in-place.
+ """
+ return self.backend.resize(a=self, new_shape=new_shape, refcheck=refcheck, **kargs)
+
+ def round(self, decimals=0, out=None, **kargs):
+ """
+ Return a with each element rounded to the given number of decimals.
+ """
+ return self.backend.around(a=self, decimals=decimals, out=out, **kargs)
+
+ def searchsorted(self, v, side='left', sorter=None, **kargs):
+ """
+ Find indices where elements of v should be inserted in a to maintain order.
+ """
+ return self.backend.searchsorted(a=self, v=v, side=side, sorter=sorter, **kargs)
+
+ def sort(self, axis=-1, kind='quicksort', order=None, **kargs):
+ """
+ Sort an array, in-place.
+ """
+ return self.backend.sort(a=self, axis=axis, kind=kind, order=order, **kargs)
+
+ def squeeze(self, axis=None, **kargs):
+ """
+ Remove single-dimensional entries from the shape of a.
+ """
+ return self.backend.squeeze(a=self, axis=axis, **kargs)
+
+ def std(self, axis=None, dtype=None, out=None, ddof=0, **kargs):
+ """
+ Returns the standard deviation of the array elements along given axis.
+ """
+ return self.backend.std(a=self, axis=axis, dtype=dtype, out=out,
+ ddof=ddof)
+
+ def sum(self, axis=None, dtype=None, out=None, **kargs):
+ """
+ Return the sum of the array elements over the given axis.
+ """
+ return self.backend.sum(a=self, axis=axis, dtype=dtype, out=out, **kargs)
+
+ def swapaxes(self, axis1, axis2, **kargs):
+ """
+ Return a view of the array with axis1 and axis2 interchanged.
+ """
+ return self.backend.swapaxes(axis1=axis1, axis2=axis2, **kargs)
+
+ def trace(self, offset=0, axis1=0, axis2=1, dtype=None, out=None, **kargs):
+ """
+ Return the sum along diagonals of the array.
+ """
+ return self.backend.trace(a=self, offset=offset,
+ axis1=axis1, axis2=axis2, dtype=dtype, out=out, **kargs)
+
+ def transpose(self, axes=None, **kargs):
+ """
+ Returns a view of the array with axes transposed.
+ """
+ return self.backend.transpose(a=self, axes=axes, **kargs)
+
+ def var(self, axis=None, dtype=None, out=None, ddof=0, **kargs):
+ """
+ Returns the variance of the array elements, along given axis.
+ """
+ return self.backend.var(a=self, axis=axis, dtype=dtype, out=out, ddof=ddof, **kargs)
+
+
+ ## Array restricted methods
+ def setflags(self, write=None, align=None, uic=None):
+ """
+ Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively.
+ """
+ msg='{}::set_flags() should not be called.'
+ msg=msg.format(self.__class__.__name__)
+ raise RuntimeError(msg)
+
+
+ ## Array specific unimplemented methods
+ def tofile(self, fid, sep='', format='%s', **kargs):
+ """
+ Write array to a file as text or binary (default).
+ This is a convenience function for quick storage of array data.
+ Information on endianness and precision is lost.
+ """
+ self.__class__.not_implemented_yet('tofile')
+ def tolist(self, **kargs):
+ """
+ Return the array as a possibly nested list.
+ """
+ self.__class__not_implemented_yet('tolist')
+ def tostring(self, order=MemoryOrdering.SAME_ORDER, **kargs):
+ """
+ Construct Python bytes containing the raw data bytes in the array.
+ """
+ self.__class__not_implemented_yet('tostring')
+
+ def getfield(dtype, offset=0):
+ """
+ Returns a field of the given array as a certain type.
+ """
+ self._not_implemented_yet('get_field')
+ def setfield(val, dtype, offset=0):
+ """
+ Put a value into a specified place in a field defined by a data-type.
+ Place val into a's field defined by dtype and beginning offset bytes into the field.
+ """
+ self._not_implemented_yet('set_field')
+
+ def item(*args):
+ """
+ Copy an element of an array to a standard Python scalar and return it.
+ """
+ self._not_implemented_yet('item')
+ def itemset(*args):
+ """
+ Insert scalar into an array (scalar is cast to array's dtype, if possible)
+ """
+ self._not_implemented_yet('itemset')
+
+ def put(self, indices, values, mode='raise', **kargs):
+ """
+ Set a.flatn = valuesn for all n in indices.
+ """
+ self._not_implemented_yet('put')
+ def take(self, indices, axis=None, out=None, mode='raise', **kargs):
+ """
+ Return an array formed from the elements of a at the given indices.
+ """
+ self._not_implemented_yet('take')
+
+ def view(self, dtype, **kargs):
+ """
+ New view of array with the same data.
+ """
+ self._not_implemented_yet('view')
+ def astype(self, dtype, order=MemoryOrdering.SAME_ORDER,
+ casting='unsafe', subok=True, copy=True, **kargs):
+ """
+ Copy of the array, cast to a specified type.
+ """
+ self._not_implemented_yet('astype')
+
+ def tobytes(self, order=MemoryOrdering.C_CONTIGUOUS):
+ """
+ Construct Python bytes containing the raw data bytes in the array.
+ """
+ self._not_implemented_yet('tobytes')
+
+
+ # logical operators
+ def __eq__(self, other):
+ return self.backend.equal(self, other)
+ def __ne__(self, other):
+ return self.backend.not_equal(self, other)
+ def __le__(self, other):
+ return self.backend.less_equal(self, other)
+ def __ge__(self, other):
+ return self.backend.greater_equal(self, other)
+ def __lt__(self, other):
+ return self.backend.less(self, other)
+ def __gt__(self, other):
+ return self.backend.greater(self, other)
+
+ # arithmetic operators
+ def __neg__(self):
+ return self.backend.negative(self)
+ def __abs__(self):
+ return self.backend.absolute(self)
+ def __invert__(self):
+ return self.backend.invert(self)
+
+ def __add__(self, other):
+ return self.backend.add(self, other)
+ def __sub__(self, other):
+ return self.backend.subtract(self, other)
+ def __mul__(self, other):
+ return self.backend.multiply(self, other)
+ def __pow__(self, other):
+ return self.backend.power(self, other)
+ def __floordiv__(self, other):
+ return self.backend.floor_divide(self, other)
+ def __div__(self, other):
+ return self.backend.divide(self, other)
+ def __mod__(self, other):
+ return self.backend.mod(self, other)
+
+ def __and__ (self, other):
+ return self.backend.bitwise_and(self,other)
+ def __xor__ (self, other):
+ return self.backend.bitwise_xor(self,other)
+ def __or__ (self, other):
+ return self.backend.bitwise_or(self,other)
+ def __lshift__ (self, other):
+ return self.backend.left_shift(self,other)
+ def __rshift__ (self, other):
+ return self.backend.right_shift(self,other)
+
+ def __radd__(self, other):
+ return self.backend.add(other, self)
+ def __rsub__(self, other):
+ return self.backend.subtract(other, self)
+ def __rmul__(self, other):
+ return self.backend.multiply(other, self)
+ def __rpow__(self, other):
+ return self.backend.power(other, self)
+ def __rfloordiv__(self, other):
+ return self.backend.floor_divide(other, self)
+ def __rdiv__(self, other):
+ return self.backend.divide(other, self)
+ def __rmod__(self, other):
+ return self.backend.mod(other, self)
+
+ def __rand__ (other, self):
+ return self.backend.bitwise_and(other, self)
+ def __rxor__ (other, self):
+ return self.backend.bitwise_xor(other, self)
+ def __ror__ (other, self):
+ return self.backend.bitwise_or(other, self)
+ def __rlshift__ (other, self):
+ return self.backend.left_shift(other, self)
+ def __rrshift__ (other, self):
+ return self.backend.right_shift(other, self)
+
+ def __iadd__(self, other):
+ return self.backend.add(self, other, out=self)
+ def __isub__(self, other):
+ return self.backend.subtract(self, other, out=self)
+ def __imul__(self, other):
+ return self.backend.multiply(self, other, out=self)
+ def __ipow__(self, other):
+ return self.backend.power(self, other, out=self)
+ def __ifloordiv__(self, other):
+ return self.backend.floor_divide(self, other, out=self)
+ def __idiv__(self, other):
+ return self.backend.divide(self, other, out=self)
+ def __imod__(self, other):
+ return self.backend.mod(self, other, out=self)
+
+
+ def __str__(self):
+ return self._handle.__str__()
+ def __repr__(self):
+ return self._handle.__repr__()
+
+ def __setitem__(self, slice, value):
+ self._call('__setitem__', slice, value)
+
+ def __getitem__(self, slice):
+ return self._call('__getitem__', slice)
diff --git a/hysop/core/arrays/array_backend.py b/hysop/core/arrays/array_backend.py
new file mode 100644
index 0000000000000000000000000000000000000000..08a9248cd9f7e69b8413408bd2714263153dbd18
--- /dev/null
+++ b/hysop/core/arrays/array_backend.py
@@ -0,0 +1,2942 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.deps import np, sys
+from hysop.constants import default_order, MemoryOrdering
+from hysop.constants import HYSOP_REAL, HYSOP_COMPLEX
+from hysop.constants import HYSOP_INTEGER, HYSOP_INDEX, HYSOP_DIM, HYSOP_BOOL
+from hysop.tools.types import check_instance, to_tuple, to_list
+from hysop.tools.numerics import is_fp, is_complex, match_float_type, \
+ match_complex_type, complex_to_float_dtype
+from hysop.core.memory.allocator import AllocatorBase
+
+class ArrayBackend(object):
+ """
+ Interface of an abstract array backend.
+ An array backend is a numpy work-alike collection of functions that
+ performs its computations on arrays on various devices.
+
+ Most of exposed functions should work exactly as in numpy,
+ some default arguments are changed to match HySoP parameters
+ (default ordering, default floating point type,
+ default integer type, default device, ...)
+ All exposed functions are @classmethods, and this class cannot
+ be instanciated.
+
+ Arithmetic methods, when available, should at least support the
+ broadcasting of scalars.
+
+ See this link for more information about numpy routines:
+ https://docs.scipy.org/doc/numpy/reference/routines.html
+
+ A backend implementation *may* expose subsets of the following
+ routine sections (as listed on previous link):
+ 1) Array creation routines
+ 2) Array manipulation routines
+ 3) Binary operations
+ 4) Discrete Fourier Transform
+ 5) Functional programming
+ 6) Input and Output
+ 7) Linear Algebra
+ 8) Logic functions
+ 9) Mathematical functions
+ 10) Random sampling
+ 11) Set routines
+ 12) Sorting searching and counting
+ 13) Statistics
+
+ Currently unimplemented/unsupported features:
+ 1) String Operations
+ 2) C-Types Foreign Function Interface
+ 3) Datetime Support Functions
+ 4) Data type routines
+ 5) Optionally Scipy-accelerated routines
+ 6) Mathematical functions with automatic domain
+ 7) Floating point error handling
+ 8) NumPy-specific help functions
+ 9) Financial functions
+ 10) Indexing routines
+ 11) Masked Array operations
+ 12) Matrix library
+ 13) Miscellaneous routines
+ 14) Padding arrays
+ 15) Polynomials
+ 16) Test support
+ 17) Window functions
+
+ By default, all exposed methods raise a NotImplementedError with an
+ explicit message through the _not_implemented_yet method.
+ """
+
+ __metaclass__ = ABCMeta
+
+ __registered_backends = {}
+ """
+ Contains all registered backends.
+ keys = array handle type.
+ values = corresponding backend class.
+ Used to wrap array handles in _return().
+ """
+
+ __DEBUG = False
+ """
+ If set to true, prints all wrapped calls and arguments conversion.
+ """
+
+ @staticmethod
+ def get_alignment_and_size(shape, dtype, min_alignment=None):
+ """
+ Returns number of bytes to allocate an array of given
+ shape and given dtype, aligned on given alignment.
+ Returned alignment will be at least dtype.itemsize.
+ Alignment should non zero and a power of two, or None
+ in which case it will be set to 1.
+ """
+ bytes_per_elem = dtype.itemsize
+ min_alignment = min_alignment or 1
+ min_alloc_bytes = np.prod(shape) * bytes_per_elem
+
+ msg0='min_alignment is not a power of two, got {}.'
+ msg1='bytes_per_elem is not a power of two, got {}.'
+ assert min_alloc_bytes>=1, 'min_alloc_bytes <= 0.'
+ assert min_alignment>=1, 'min_alignment <= 0.'
+ assert (min_alignment & (min_alignment-1))==0, msg0.format(min_alignment)
+ assert (bytes_per_elem & (bytes_per_elem-1))==0, msg1.format(bytes_per_elem)
+
+ alignment = max(min_alignment, bytes_per_elem)
+ size = min_alloc_bytes
+ nbytes = min_alloc_bytes + alignment - 1
+
+ return (size,nbytes,alignment)
+
+ @staticmethod
+ def _register_backend(handle, backend_cls):
+ ArrayBackend.__registered_backends[handle] = backend_cls
+
+ @staticmethod
+ def _registered_backends():
+ return ArrayBackend.__registered_backends.copy()
+
+
+ @classmethod
+ def _not_implemented_yet(cls, funname):
+ msg = '{}::{}() has not been implemented yet.'
+ msg=msg.format(cls.__name__, funname)
+ raise NotImplementedError(msg)
+
+ @classmethod
+ def _unsupported_argument(cls, fname, argname, arg, default_value=None):
+ if arg != default_value:
+ msg = '{}::{}() has been implemented but argument \'{}\' is not '
+ msg+= 'supported and should be set to {}.'
+ msg=msg.format(cls.__name__, fname, argname, default_value)
+ raise NotImplementedError(msg)
+
+ @classmethod
+ def _check_argtype(cls, fname, argname, arg, argself):
+ if not isinstance(argself, tuple):
+ argself=(argself,)
+ if not arg.__class__ in argself:
+ msg = '{}::{}(): argument type mismatch, expected a {}'
+ msg+= ' for argument \'{}\' but got a {}.'
+ msg=msg.format(cls.__name__, fname, argself, argname, arg.__class__)
+ raise TypeError(msg)
+
+
+ def __init__(self, allocator, **kwds):
+ """
+ Initialize an ArrayBackend with guven allocator.
+ """
+ check_instance(allocator, AllocatorBase)
+ super(ArrayBackend,self).__init__(**kwds)
+ self._allocator = allocator
+
+
+ def __eq__(self, other):
+ if not other.__class__ == self.__class__:
+ return NotImplemented
+ eq = (self._allocator is other._allocator)
+ return eq
+ def __ne__(self):
+ return not (self == other)
+ def __hash__(self):
+ return id(self._allocator)
+
+ @abstractmethod
+ def get_host_array_backend(self):
+ msg='get_host_array_backend() not implemented in {}.'.format(self.__class__)
+ raise NotImplementedError(msg)
+ host_array_backend=property(get_host_array_backend)
+
+ @abstractmethod
+ def short_description(self):
+ pass
+
+ def identifier(self):
+ return str(hex(hash(self)))[2:6]
+
+ def get_allocator(self):
+ """
+ Get the allocated associated to this backend.
+ """
+ return self._allocator
+
+ allocator = property(get_allocator)
+
+ def _prepare_args(self, *args, **kargs):
+ """
+ Prepare all arguments for a call.
+ """
+ if ArrayBackend.__DEBUG:
+ print '__prepare_args'
+ args = list(args)
+ for i,arg in enumerate(args):
+ args[i] = self._arg(arg)
+ for k,arg in kargs.iteritems():
+ kargs[k] = self._arg(arg)
+ return tuple(args), kargs
+
+ def _return(self, ret, **kargs):
+ """
+ Wrap returned value(s) if they match a backend array.
+ """
+ if isinstance(ret,tuple):
+ if ArrayBackend.__DEBUG:
+ print '__return', [r.__class__.__name__ for r in ret]
+ values = list(ret)
+ for i,val in enumerate(values):
+ if self.can_wrap(val):
+ values[i] = self.wrap(val, **kargs)
+ elif self.host_array_backend.can_wrap(val):
+ values[i] = self.host_array_backend.wrap(val)
+ return tuple(values)
+
+ if ArrayBackend.__DEBUG:
+ print '__return', ret.__class__.__name__
+ if self.can_wrap(ret):
+ ret = self.wrap(ret, **kargs)
+ elif self.host_array_backend.can_wrap(ret):
+ ret = self.host_array_backend.wrap(ret)
+ return ret
+
+ def _call(self, functor, *varargs, **kwargs):
+ """
+ Prepare arguments for a call to functor and calls it.
+ If returned value contains an array handle, it is wrapped into
+ the corresponding hysop.core.arrays.
+ """
+
+ if ArrayBackend.__DEBUG:
+ print '__call {}'.format(functor.__name__)
+
+ args, kargs, _ret, ret = None, None, None, None
+ try:
+ args, kargs = self._prepare_args(*varargs, **kwargs)
+
+ _ret = functor(*args, **kargs)
+
+ ret = self._return(_ret)
+ except Exception as e:
+ _type, _value, _traceback = sys.exc_info()
+ def get_name(val):
+ if hasattr(val, '__class__'):
+ name = val.__class__.__name__
+ elif hasattr(val, '__name__'):
+ name = val.__name__
+ else:
+ name = val
+ if hasattr(val,'__class__') and \
+ val.__class__ in [type,int,long,float,np.dtype,list,tuple,set]:
+ name += ' = {}'.format(val)
+ return name
+
+ def format(val):
+ if val is None:
+ return 'Uninitialized'
+ if isinstance(val,tuple):
+ return ', '.join([get_name(v) for v in val])
+ elif isinstance(val, dict):
+ val = ['{} => {}'.format(k,get_name(val[k]))
+ for k in sorted(val.keys())]
+ return '\n\t'.join(val)
+
+ msg= \
+ '''
+Call of {} ({}) from class self={} failed
+ Before argument processing:
+ args: {}
+ kargs:
+ {}
+ returns: {}
+ After argument processing:
+ args: {}
+ kargs:
+ {}
+ returns: {}
+
+Exception was:
+ {}
+'''.format(functor, functor.__name__, self.__class__.__name__,
+ format(varargs), format(kwargs), format(_ret),
+ format(args), format(kargs), format(ret),
+ e)
+ raise _type, _value, _traceback
+
+ return ret
+
+
+ def _alloc_outputs(self, fname, kargs):
+ if ArrayBackend.__DEBUG:
+ print '__begin allocs'
+ shapes = []
+ orders = []
+ input_dtypes = {}
+ output_arg_names = []
+ for argname, arg in kargs.iteritems():
+ if (argname.find('out')>=0):
+ if (arg is None):
+ output_arg_names.append(argname)
+ elif self.can_wrap(arg):
+ arg = self.wrap(arg)
+ input_dtypes[argname]=arg.dtype
+ shapes.append(arg.shape)
+ orders.append(arg.order)
+
+ if not output_arg_names:
+ return
+
+ if not all(shape==shapes[0] for shape in shapes):
+ msg='Shape mismatch for array operands:\n {}'.format(shapes)
+ raise RuntimeError(msg)
+ else:
+ shape = shapes[0]
+
+ if not all(order==orders[0] for order in orders):
+ order=MemoryOrdering.C_CONTIGUOUS
+ else:
+ order = orders[0]
+
+ if ('axis' in kargs):
+ # this is a reduction, we get rid of reduced axis
+ axis = kargs['axis']
+ if (axis is None):
+ shape = tuple()
+ else:
+ axis = to_tuple(axis)
+ _shape = []
+ for axe,s in enumerate(shape):
+ if axe not in axis:
+ _shape.append(s)
+ shape, _shape = to_tuple(_shape), shape
+ else:
+ axis = None
+ _shape = shape
+
+ if not shape:
+ # scalar output, do not allocate an array
+ return
+
+ output_dtypes = self._find_output_dtypes(fname, input_dtypes, output_arg_names)
+
+ if ArrayBackend.__DEBUG:
+ print '__allocating outputs for function {}'.format(fname)
+ print ' *shape: {} (input shape={}, axis={})'.format(shape, _shape, axis)
+ print ' *order: {}'.format(order)
+ print ' *input dtypes: {}'.format(input_dtypes)
+ print ' *deduced output dtypes: {}'.format(output_dtypes)
+ f = getattr(np, fname)
+ if isinstance(f, np.ufunc):
+ ftypes = f.types
+ ftypes_str = []
+ for ftype in ftypes:
+ type_info = {}
+ fin,fout = ftype.split('->')
+ for typechar in fin+fout:
+ try:
+ type_info[typechar] = np.typename(typechar)
+ except:
+ type_info[typechar] = 'unknown type'
+ ss = '{}->{} ({})'.format(fin,fout, ', '.join('{}={}'.format(k,v)
+ for (k,v) in type_info.iteritems()))
+ ftypes_str.append(ss)
+
+ print ' *ufunc available signatures:\n {}'.format('\n '.join(ftypes_str))
+
+ for argname in output_arg_names:
+ dtype = output_dtypes[argname]
+ kargs[argname] = self.empty(shape=shape, dtype=dtype, order=order).handle
+ if ArrayBackend.__DEBUG:
+ print '__end allocs'
+
+ def _find_output_dtypes(self, fname, input_dtypes, output_arg_names):
+ output_dtypes = {}
+
+ dtypes = input_dtypes.values()
+ dtype = np.find_common_type([], dtypes)
+
+ if fname.find('frexp')==0:
+ output_dtypes['out1'] = match_float_type(dtype)
+ output_dtypes['out2'] = np.int32
+ else:
+ # all outputs share the same dtype
+ if fname in ['rint', 'floor', 'ceil', 'trunc',
+ 'exp', 'exp2', 'expm1',
+ 'log', 'log1p', 'log2', 'log10',
+ 'logaddexp', 'logaddexp2', 'ldexp',
+ 'sqrt', 'cbrt', 'hypot',
+ 'fabs', 'copysign', 'modf',
+ 'sin', 'cos', 'tan', 'arcsin', 'arccos', 'arctan', 'arctan2',
+ 'sinh', 'cosh', 'tanh', 'arcsinh', 'arccosh', 'arctanh',
+ 'rad2deg', 'deg2rad']:
+ if is_complex(dtype):
+ dtype = match_complex_type(dtype)
+ else:
+ dtype = match_float_type(dtype)
+ elif fname in ['absolute']:
+ if is_complex(dtype):
+ dtype = complex_to_float_dtype(dtype)
+ elif fname in ['true_divide']:
+ if (dtypes[0]==dtypes[1]):
+ dtype0 = dtypes[0]
+ if is_fp(dtype0) or is_complex(dtype0):
+ dtype = dtype0
+ else:
+ dtype = np.float64
+ else:
+ dtype = np.float64
+
+ for argname in output_arg_names:
+ output_dtypes[argname] = dtype
+
+ return output_dtypes
+
+############################
+# BACKEND SPECIFIC METHODS #
+
+
+ @abstractmethod
+ def wrap(self, handle, **kargs):
+ """
+ Create a backend specific Array from the corresponding array handle.
+ """
+ pass
+
+ @abstractmethod
+ def can_wrap(self, handle, **kargs):
+ """
+ Should return True if handle is an Array or a array handle corresponding
+ this backend.
+ """
+ pass
+
+ def _arg(self, arg):
+ """
+ Prepare one argument for a call (non backend specific argument conversion).
+ Can be extended for backend specific arguments.
+ """
+ from hysop.core.arrays.array import Array
+ if isinstance(arg, Array):
+ return arg.handle
+ elif isinstance(arg, MemoryOrdering):
+ if arg==MemoryOrdering.C_CONTIGUOUS:
+ return 'C'
+ elif arg==MemoryOrdering.FORTRAN_CONTIGUOUS:
+ return 'F'
+ elif arg==MemoryOrdering.SAME_ORDER:
+ return 'K'
+ elif arg==MemoryOrdering.OUT_OF_ORDER:
+ msg='Unsupported memory ordering {}.'.format(arg)
+ raise RuntimeError(msg)
+ else:
+ msg='Unknown memory ordering {}.'.format(arg)
+ raise RuntimeError(msg)
+ else:
+ return arg
+
+
+ def copyto(self, dst, src, **kargs):
+ """
+ src is an Array
+ dst can be everything
+ """
+ self._not_implemented_yet('copyto')
+
+##############################
+# EXTRA AND MODIFIED METHODS #
+
+
+ def fill(self, a, value):
+ """
+ Fill the array with given value
+ """
+ self._not_implemented_yet('fill')
+
+
+ def memcpy(self, dst, src, **kargs):
+ """
+ Copy memory from src buffer to dst buffer .
+ """
+ from hysop.core.arrays.array import Array
+ from hysop.core.arrays.all import HostArrayBackend
+ if isinstance(src, Array):
+ src.backend.copyto(dst, src, **kargs)
+ elif isinstance(dst, Array):
+ cls = src.__class__
+ if cls in ArrayBackend.__registered_backends:
+ backend_cls = ArrayBackend.__registered_backends[cls]
+ if isinstance(dst.backend, backend_cls):
+ src = dst.backend.wrap(src)
+ dst.backend.copyto(dst, src, **kargs)
+ else:
+ msg='dst does not match registered backend for type {}.'
+ msg=msg.format(cls)
+ raise TypeError(msg)
+ elif cls in [list, tuple, set] and isinstance(dst.backend, HostArrayBackend):
+ src = dst.backend.asarray(src)
+ dst.backend.copyto(dst, src, **kargs)
+ else:
+ print src.__class__, dst.__class__
+ msg='src cannot be converted to type Array.'
+ raise TypeError(msg)
+ else:
+ msg='Neither src nor dst are of type Array.'
+ raise TypeError(msg)
+
+
+
+###########################
+# ARRAY CREATION ROUTINES #
+## See https://docs.scipy.org/doc/numpy/reference/routines.array-creation.html
+
+# Ones and zeros
+
+ def empty(self, shape, dtype=HYSOP_REAL, order=default_order):
+ """
+ Return a new array of given shape and type, without initializing entries.
+ """
+ self._not_implemented_yet('empty')
+
+ def empty_like(self, a, dtype=None, order=MemoryOrdering.SAME_ORDER, subok=True):
+ """
+ Return a new array with the same shape and type as a given array.
+ """
+ self._not_implemented_yet('empty_like')
+
+ def eye(self, N, M, k, dtype=None):
+ """
+ Return a 2-D array with ones on the diagonal and zeros elsewhere.
+ """
+ self._not_implemented_yet('eye')
+
+ def identity(self, n, dtype=None):
+ """
+ Return the identity array.
+ """
+ self._not_implemented_yet('identity')
+
+ def ones(self, shape, dtype=None, order=default_order):
+ """
+ Return a new array of given shape and type, filled with ones.
+ """
+ self._not_implemented_yet('ones')
+
+ def ones_like(self, a, dtype=None, order=MemoryOrdering.SAME_ORDER, subok=True):
+ """
+ Return an array of ones with the same shape and type as a given array.
+ """
+ self._not_implemented_yet('ones_like')
+
+ def zeros(self, shape, dtype=None, order=default_order):
+ """
+ Return a new array of given shape and type, filled with zeros.
+ """
+ self._not_implemented_yet('zeros')
+
+ def zeros_like(self, a, dtype=None, order=MemoryOrdering.SAME_ORDER, subok=True):
+ """
+ Return an array of zeros with the same shape and type as a given array.
+ """
+ self._not_implemented_yet('zeros_like')
+
+ def full(self, shape, fill_value, dtype=None, order=default_order):
+ """
+ Return a new array of given shape and type, filled with fill_value.
+ """
+ self._not_implemented_yet('full')
+
+ def full_like(self, a, fill_value, dtype=None, order=MemoryOrdering.SAME_ORDER, subok=True):
+ """
+ Return a full array with the same shape and type as a given array.
+ """
+ self._not_implemented_yet('full_like')
+
+#From existing data
+
+ def array(self, object, dtype=None, copy=True, order=default_order,
+ subok=False, ndmin=0):
+ """
+ Create an array.
+ """
+ self._not_implemented_yet('array')
+
+ def asarray(self, a, dtype=None, order=default_order, **kargs):
+ """
+ Convert the input to an array.
+ """
+ self._not_implemented_yet('asarray')
+
+ def asanyarray(self, a, dtype=None, order=default_order):
+ """
+ Convert the input to an ndarray, but pass ndarray subclasses through.
+ """
+ self._not_implemented_yet('asanyarray')
+
+ def asmatrix(self, data, dtype=None):
+ """
+ Interpret the input as a matrix.
+ """
+ self._not_implemented_yet('asmatrix')
+
+ def copy(self, a, order=MemoryOrdering.SAME_ORDER):
+ """
+ Return an array copy of the given object.
+ """
+ self._not_implemented_yet('copy')
+
+ def frombuffer(self, afer, dtype=HYSOP_REAL, count=-1, offset=0):
+ """
+ Interpret a afer as a 1-dimensional array.
+ """
+ self._not_implemented_yet('fromafer')
+
+ def fromfile(self, file, dtype=HYSOP_REAL, count=-1, sep=''):
+ """
+ Construct an array from data in a text or binary file.
+ """
+ self._not_implemented_yet('fromfile')
+
+ def fromfunction(self, function, shape, dtype=HYSOP_REAL):
+ """
+ Construct an array by executing a function over each coordinate.
+ """
+ self._not_implemented_yet('fromfunction')
+
+ def fromiter(self, iterable, dtype=HYSOP_REAL, count=-1):
+ """
+ Create a new 1-dimensional array from an iterable object.
+ """
+ self._not_implemented_yet('fromiter')
+
+ def fromstring(self, string, dtype=HYSOP_REAL, count=-1, sep=''):
+ """
+ A new 1-D array initialized from raw binary or text data in a string.
+ """
+ self._not_implemented_yet('fromstring')
+
+ def loadtxt(self, fname, dtype=HYSOP_REAL, comments='#', delimiter=None,
+ converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0):
+ """
+ Load data from a text file.
+ """
+ self._not_implemented_yet('loadtxt')
+
+#Numerical ranges
+
+ def arange(self, dtype=HYSOP_INTEGER, *args, **kargs):
+ """
+ Return evenly spaced values within a given interval.
+ """
+ self._not_implemented_yet('arange')
+
+
+ def linspace(self, start, stop, num=50, endpoint=True, retstep=False, dtype=HYSOP_REAL):
+ """
+ Return evenly spaced numbers over a specified interval.
+ """
+ self._not_implemented_yet('linspace')
+
+ def logspace(self, start, stop, num=50, endpoint=True, base=10.0, dtype=HYSOP_REAL):
+ """
+ Return numbers spaced evenly on a log scale.
+ """
+ self._not_implemented_yet('logspace')
+
+ def geomspace(self, start, stop, num=50, endpoint=True, dtype=HYSOP_REAL):
+ """
+ Return numbers spaced evenly on a log scale (a geometric progression).
+ """
+ self._not_implemented_yet('geomspace')
+
+ def meshgrid(self, *xi, **kwargs):
+ """
+ Return coordinate matrices from coordinate vectors.
+ """
+ self._not_implemented_yet('meshgrid')
+
+#Building matrices
+
+ def diag(self, v, k=0):
+ """
+ Extract a diagonal or construct a diagonal array.
+ """
+ self._not_implemented_yet('diag')
+
+ def diagflat(self, v, k=0):
+ """
+ Create a two-dimensional array with the flattened input as a diagonal.
+ """
+ self._not_implemented_yet('diagflat')
+
+ def tri(self, N, M=None, k=0, dtype=HYSOP_REAL):
+ """
+ An array with ones at and below the given diagonal and zeros elsewhere.
+ """
+ self._not_implemented_yet('tri')
+
+ def tril(self, m, k):
+ """
+ Lower triangle of an array.
+ """
+ self._not_implemented_yet('tril')
+
+ def triu(self, m, k=0):
+ """
+ Upper triangle of an array.
+ """
+ self._not_implemented_yet('triu')
+
+ def vander(self, x, N=None, increasing=False):
+ """
+ Generate a Vandermonde matrix.
+ """
+ self._not_implemented_yet('vander')
+
+
+###############################
+# ARRAY MANIPULATION ROUTINES #
+## See https://docs.scipy.org/doc/numpy/reference/routines.array-manipulation.html
+
+#Changing array shape
+
+ def reshape(self, a, newshape, order=default_order):
+ """
+ Gives a new shape to an array without changing its data.
+ """
+ self._not_implemented_yet('reshape')
+
+ def ravel(self, a, order=MemoryOrdering.SAME_ORDER):
+ """
+ Return a contiguous flattened array.
+ """
+ self._not_implemented_yet('ravel')
+
+#Transpose-like operations
+## /!\ those functions can alter the transposition state /!\
+
+ def moveaxis(self, a, source, destination):
+ """
+ Move axes of an array to new positions.
+ """
+ self._not_implemented_yet('moveaxis')
+
+ def rollaxis(self, a, axis, start=0):
+ """
+ Roll the specified axis backwards, until it lies in a given position.
+ """
+ self._not_implemented_yet('rollaxis')
+
+ def swapaxes(self, a, axis1, axis2):
+ """
+ Interchange two axes of an array.
+ """
+ self._not_implemented_yet('swapaxes')
+
+ def transpose(self, a, axes=None):
+ """
+ Permute the dimensions of an array.
+ """
+ self._not_implemented_yet('transpose')
+
+
+#Changing number of dimensions
+
+ def atleast_1d(self, *arys):
+ """
+ Convert inputs to arrays with at least one dimension.
+ """
+ self._not_implemented_yet('atleast_1d')
+
+ def atleast_2d(self, *arys):
+ """
+ View inputs as arrays with at least two dimensions.
+ """
+ self._not_implemented_yet('atleast_2d')
+
+ def atleast_3d(self, *arys):
+ """
+ View inputs as arrays with at least three dimensions.
+ """
+ self._not_implemented_yet('atleast_3d')
+
+ def broadcast_to(self, array, shape, subok=False):
+ """
+ Broadcast an array to a new shape.
+ """
+ self._not_implemented_yet('broadcast_to')
+
+ def broadcast_arrays(self, *args, **kwargs):
+ """
+ Broadcast any number of arrays against each other.
+ """
+ self._not_implemented_yet('broadcast_arrays')
+
+ def expand_dims(self, a, axis):
+ """
+ Expand the shape of an array.
+ """
+ self._not_implemented_yet('expand_dims')
+
+ def squeeze(self, a, axis=None):
+ """
+ Remove single-dimensional entries from the shape of an array.
+ """
+ self._not_implemented_yet('squeeze')
+
+#Changing kind of array
+
+ def asfortranarray(self, a, dtype=None):
+ """
+ Return an array laid out in Fortran order in memory.
+ """
+ self._not_implemented_yet('asfortranarray')
+
+ def ascontiguousarray(self, a, dtype=None):
+ """
+ Return a contiguous array in memory (C order).
+ """
+ self._not_implemented_yet('ascontiguousarray')
+
+ def asarray_chkfinite(self, a, dtype=None, order=default_order):
+ """
+ Convert the input to an array, checking for NaNs or Infs.
+ """
+ self._not_implemented_yet('asarray_chkfinite')
+
+ def asscalar(self, a):
+ """
+ Convert an array of size 1 to its scalar equivalent.
+ """
+ self._not_implemented_yet('asscalar')
+
+ def require(self, a, dtype=None, requirements=None):
+ """
+ Return an ndarray of the provided type that satisfies requirements.
+ """
+ self._not_implemented_yet('require')
+
+#Joining arrays
+
+ def concatenate(self, a, axis=0):
+ """
+ Join a sequence of arrays along an existing axis.
+ """
+ self._not_implemented_yet('concatenate')
+
+ def stack(self, arrays, axis=0):
+ """
+ Join a sequence of arrays along a new axis.
+ """
+ self._not_implemented_yet('stack')
+
+ def column_stack(self, tup):
+ """
+ Stack 1-D arrays as columns into a 2-D array.
+ """
+ self._not_implemented_yet('column_stack')
+
+ def dstack(self, tup):
+ """
+ Stack arrays in sequence depth wise (along third axis).
+ """
+ self._not_implemented_yet('dstack')
+
+ def hstack(self, tup):
+ """
+ Stack arrays in sequence horizontally (column wise).
+ """
+ self._not_implemented_yet('hstack')
+
+ def vstack(self, tup):
+ """
+ Stack arrays in sequence vertically (row wise).
+ """
+ self._not_implemented_yet('vstack')
+
+#Splitting arrays
+
+ def split(self, ary, indices_or_sections, axis=0):
+ """
+ Split an array into multiple sub-arrays.
+ """
+ self._not_implemented_yet('split')
+
+ def array_split(self, ary, indices_or_sections, axis=0):
+ """
+ Split an array into multiple sub-arrays.
+ """
+ self._not_implemented_yet('array_split')
+
+ def dsplit(self, ary, indices_or_sections):
+ """
+ Split array into multiple sub-arrays along the 3rd axis (depth).
+ """
+ self._not_implemented_yet('dsplit')
+
+ def hsplit(self, ary, indices_or_sections):
+ """
+ Split an array into multiple sub-arrays horizontally (column-wise).
+ """
+ self._not_implemented_yet('hsplit')
+
+ def vsplit(self, ary, indices_or_sections):
+ """
+ Split an array into multiple sub-arrays vertically (row-wise).
+ """
+ self._not_implemented_yet('vsplit')
+
+#Tiling arrays
+
+ def tile(self, A, reps):
+ """
+ Construct an array by repeating A the number of times given by reps.
+ """
+ self._not_implemented_yet('tile')
+
+ def repeat(self, a, repeats, axis=None):
+ """
+ Repeat elements of an array.
+ """
+ self._not_implemented_yet('repeat')
+
+#Adding and removing elements
+
+ def delete(self, arr, obj, axis=None):
+ """
+ Return a new array with sub-arrays along an axis deleted.
+ """
+ self._not_implemented_yet('delete')
+
+ def insert(self, arr, obj, values, axis=None):
+ """
+ Insert values along the given axis before the given indices.
+ """
+ self._not_implemented_yet('insert')
+
+ def append(self, arr, values, axis=None):
+ """
+ Append values to the end of an array.
+ """
+ self._not_implemented_yet('append')
+
+ def resize(self, a, new_shape):
+ """
+ Return a new array with the specified shape.
+ """
+ self._not_implemented_yet('resize')
+
+ def trim_zeros(self, filt, trim='fb'):
+ """
+ Trim the leading and/or trailing zeros from a 1-D array or sequence.
+ """
+ self._not_implemented_yet('trim_zeros')
+
+ def unique(self, ar, return_index=False, return_inverse=False, return_counts=False):
+ """
+ Find the unique elements of an array.
+ """
+ self._not_implemented_yet('unique')
+
+#Rearranging elements
+
+ def flip(self, m, axis):
+ """
+ Reverse the order of elements in an array along the given axis.
+ """
+ self._not_implemented_yet('flip')
+
+ def fliplr(self, m):
+ """
+ Flip array in the left/right direction.
+ """
+ self._not_implemented_yet('fliplr')
+
+ def flipud(self, m):
+ """
+ Flip array in the up/down direction.
+ """
+ self._not_implemented_yet('flipud')
+
+ def roll(self, a, shift, axis=None):
+ """
+ Roll array elements along a given axis.
+ """
+ self._not_implemented_yet('roll')
+
+ def rot90(self, m, k=1, axes=(0,1)):
+ """
+ Rotate an array by 90 degrees in the plane specified by axes.
+ """
+ self._not_implemented_yet('rot90')
+
+
+#####################
+# BINARY OPERATIONS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.bitwise.html
+
+# Elementwise bit operations
+
+ def bitwise_and(self, x1, x2, out=None):
+ """
+ Compute the bit-wise AND of two arrays element-wise.
+ """
+ self._not_implemented_yet('bitwise_and')
+
+ def bitwise_or(self, x1, x2, out=None):
+ """
+ Compute the bit-wise OR of two arrays element-wise.
+ """
+ self._not_implemented_yet('bitwise_or')
+
+ def bitwise_xor(self, x1, x2, out=None):
+ """
+ Compute the bit-wise XOR of two arrays element-wise.
+ """
+ self._not_implemented_yet('bitwise_xor')
+
+
+ def invert(self, x, out=None):
+ """
+ Compute bit-wise inversion, or bit-wise NOT, element-wise.
+ """
+ self._not_implemented_yet('invert')
+
+ def left_shift(self, x1, x2, out=None):
+ """
+ Shift the bits of an integer to the left.
+ """
+ self._not_implemented_yet('left_shift')
+
+ def right_shift(self, x1, x2, out=None):
+ """
+ Shift the bits of an integer to the right.
+ """
+ self._not_implemented_yet('right_shift')
+
+#Bit packing
+
+ def packbits(self, myarray, axis=None):
+ """
+ Packs the elements of a binary-valued array into bits in a uint8 array.
+ """
+ self._not_implemented_yet('packbits')
+
+ def unpackbits(self, myarray, axis=None):
+ """
+ Unpacks elements of a uint8 array into a binary-valued output array.
+ """
+ self._not_implemented_yet('unpackbits')
+
+#Output formatting
+
+ def binary_repr(self, num, width=None):
+ """
+ Return the binary representation of the input number as a string.
+ """
+ self._not_implemented_yet('binary_repr')
+
+
+##############################
+# DISCRETE FOURIER TRANSFORM #
+## See https://docs.scipy.org/doc/numpy/reference/routines.fft.html
+
+#Standard FFTs
+
+ def fft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the one-dimensional discrete Fourier Transform.
+ """
+ self._not_implemented_yet('fft')
+
+ def ifft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the one-dimensional inverse discrete Fourier Transform.
+ """
+ self._not_implemented_yet('ifft')
+
+ def fft2(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the 2-dimensional discrete Fourier Transform
+ """
+ self._not_implemented_yet('fft2')
+
+ def ifft2(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the 2-dimensional inverse discrete Fourier Transform.
+ """
+ self._not_implemented_yet('ifft2')
+
+ def fftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the N-dimensional discrete Fourier Transform.
+ """
+ self._not_implemented_yet('fftn')
+
+ def ifftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the N-dimensional inverse discrete Fourier Transform.
+ """
+ self._not_implemented_yet('ifftn')
+
+#Real FFTs
+
+ def rfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the one-dimensional discrete Fourier Transform for real input.
+ """
+ self._not_implemented_yet('rfft')
+
+ def irfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the inverse of the n-point DFT for real input.
+ """
+ self._not_implemented_yet('irfft')
+
+ def rfft2(self, a, s=None, axes=(-2,-1), norm=None):
+ """
+ Compute the 2-dimensional FFT of a real array.
+ """
+ self._not_implemented_yet('rfft2')
+
+ def irfft2(self, a, s=None, axes=(-2,-1), norm=None):
+ """
+ Compute the 2-dimensional inverse FFT of a real array.
+ """
+ self._not_implemented_yet('irfft2')
+
+ def rfftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the N-dimensional discrete Fourier Transform for real input.
+ """
+ self._not_implemented_yet('rfftn')
+
+ def irfftn(self, a, s=None, axes=None, norm=None):
+ """
+ Compute the inverse of the N-dimensional FFT of real input.
+ """
+ self._not_implemented_yet('irfftn')
+
+#Hermitian FFTs
+
+ def hfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the FFT of a signal that has Hermitian symmetry, i.e., a real spectrum.
+ """
+ self._not_implemented_yet('hfft')
+
+ def ihfft(self, a, n=None, axis=-1, norm=None):
+ """
+ Compute the inverse FFT of a signal that has Hermitian symmetry.
+ """
+ self._not_implemented_yet('ihfft')
+
+#Helper routines
+
+ def fftfreq(self, n=None, d=1.0):
+ """
+ Return the Discrete Fourier Transform sample frequencies.
+ """
+ self._not_implemented_yet('fftfreq')
+
+ def rfftfreq(self, n=None, d=1.0):
+ """
+ Return the Discrete Fourier Transform sample frequencies (for usage with rfft, irfft).
+ """
+ self._not_implemented_yet('rfftfreq')
+
+ def fftshift(self, x, axes=None):
+ """
+ Shift the zero-frequency component to the center of the spectrum.
+ """
+ self._not_implemented_yet('fftshift')
+
+ def ifftshift(self, x, axes=None):
+ """
+ The inverse of fftshift.
+ """
+ self._not_implemented_yet('ifftshift')
+
+
+##########################
+# FUNCTIONAL PROGRAMMING #
+## See https://docs.scipy.org/doc/numpy/reference/routines.functional.html
+
+
+ def apply_along_axis(self, func1d, axis, arr, *args, **kwargs):
+ """
+ Apply a function to 1-D slices along the given axis.
+ """
+ self._not_implemented_yet('apply_along_axis')
+
+ def apply_over_axes(self, func, a, axes):
+ """
+ Apply a function repeatedly over multiple axes.
+ """
+ self._not_implemented_yet('apply_over_axes')
+
+ def vectorize(self, pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None):
+ """
+ Generalized function class.
+ """
+ self._not_implemented_yet('vectorize')
+
+ def frompyfunc(self, func, nin, nout):
+ """
+ Takes an arbitrary Python function and returns a NumPy ufunc.
+ """
+ self._not_implemented_yet('frompyfunc')
+
+ def piecewise(self, x, condlist, funclist, *args, **kw):
+ """
+ Evaluate a piecewise-defined function.
+ """
+ self._not_implemented_yet('piecewise')
+
+
+####################
+# INPUT AND OUTPUT #
+## See https://docs.scipy.org/doc/numpy/reference/routines.io.html
+
+# NumPy binary files (NPY, NPZ)
+
+ def load(self, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'):
+ """
+ Load arrays or pickled objects from .npy, .npz or pickled files.
+ """
+ self._not_implemented_yet('load')
+
+ def save(self, arr, file, allow_pickle=True, fix_imports=True):
+ """
+ Save an array to a binary file in NumPy .npy format.
+ """
+ self._not_implemented_yet('save')
+
+ def savez(self, file, *args, **kwds):
+ """
+ Save several arrays into a single file in uncompressed .npz format.
+ """
+ self._not_implemented_yet('savez')
+
+ def savez_compressed(self, file, *args, **kwds):
+ """
+ Save several arrays into a single file in compressed .npz format.
+ """
+ self._not_implemented_yet('savez_compressed')
+
+# Text files
+
+ def loadtxt(self, dtype=HYSOP_REAL, comments='#', delimiter=None,
+ converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0):
+ """
+ Load data from a text file.
+ """
+ self._not_implemented_yet('loadtxt')
+
+ def savetxt(self, fname, X, fmt='%.18e', delimiter=' ', newline='\n',
+ header='', footer='', comments='# '):
+ """
+ Save an array to a text file.
+ """
+ self._not_implemented_yet('savetxt')
+
+ def genfromtxt(self, fname, dtype=HYSOP_REAL, comments='#', delimiter=None,
+ skip_header=0, skip_footer=0, converters=None, missing_values=None,
+ filling_values=None, usecols=None, names=None, excludelist=None, deletechars=None,
+ replace_space='_', autostrip=False, case_sensitive=True, defaultfmt='f%i',
+ unpack=None, usemask=False, loose=True, invalid_raise=True, max_rows=None):
+ """
+ Load data from a text file, with missing values handled as specified.
+ """
+ self._not_implemented_yet('genfromtxt')
+
+ def fromregex(self, file, regexp, dtype):
+ """
+ Construct an array from a text file, using regular expression parsing.
+ """
+ self._not_implemented_yet('fromregex')
+
+ def fromstring(self, string, dtype=HYSOP_REAL, count=-1, sep=''):
+ """
+ A new 1-D array initialized from raw binary or text data in a string.
+ """
+ self._not_implemented_yet('fromstring')
+
+# String formatting
+
+ def array2string(self, a, max_line_width=None, precision=None, suppress_small=None,
+ separator=' ', prefix='', style=repr, formatter=None):
+ """
+ Return a string representation of an array.
+ """
+ self._not_implemented_yet('array2string')
+
+ def array_repr(self, arr, max_line_width=None, precision=None, supress_small=None):
+ """
+ Return the string representation of an array.
+ """
+ self._not_implemented_yet('array_repr')
+
+ def array_str(self, a, max_line_width=None, precision=None, suppress_small=None):
+ """
+ Return a string representation of the data in an array.
+ """
+ self._not_implemented_yet('array_str')
+#Text formatting options
+
+ def set_printoptions(self, precision=None, threshold=None, edgeitems=None,
+ linewidth=None, suppress=None, nanstr=None,
+ infstr=None, formatter=None):
+ """
+ Set printing options.
+ """
+ self._not_implemented_yet('set_printoptions')
+
+ def get_printoptions(self):
+ """
+ Return the current print options.
+ """
+ self._not_implemented_yet('get_printoptions')
+
+ def set_string_function(self, f, repr=True):
+ """
+ Set a Python function to be used when pretty printing arrays.
+ """
+ self._not_implemented_yet('set_string_function')
+#Base-n representations
+
+ def binary_repr(self, num, width=None):
+ """
+ Return the binary representation of the input number as a string.
+ """
+ self._not_implemented_yet('binary_repr')
+
+ def base_repr(self, number, base=2, padding=0):
+ """
+ Return a string representation of a number in the given base system.
+ """
+ self._not_implemented_yet('base_repr')
+
+
+######################
+### LINEAR ALGEBRA ###
+## See https://docs.scipy.org/doc/numpy/reference/routines.linalg.html
+
+#Matrix and vector products
+
+ def dot(self, a, b, out=None):
+ """
+ Dot product of two arrays.
+ """
+ self._not_implemented_yet('dot')
+
+ def vdot(self, a, b):
+ """
+ Return the dot product of two vectors.
+ """
+ self._not_implemented_yet('vdot')
+
+ def inner(self, a, b):
+ """
+ Inner product of two arrays.
+ """
+ self._not_implemented_yet('inner')
+
+ def outer(self, a, b, out=None):
+ """
+ Compute the outer product of two vectors.
+ """
+ self._not_implemented_yet('outer')
+
+ def matmul(self, a, b, out=None):
+ """
+ Matrix product of two arrays.
+ """
+ self._not_implemented_yet('matmul')
+
+ def tensordot(self, a, b, axes=2):
+ """
+ Compute tensor dot product along specified axes for arrays >= 1-D.
+ """
+ self._not_implemented_yet('tensordot')
+
+ def einsum(self, subscripts, out=None, dtype=None, order=MemoryOrdering.SAME_ORDER,
+ casting='safe', optimize=False, *operands):
+ """
+ Evaluates the Einstein summation convention on the operands.
+ """
+ self._not_implemented_yet('einsum')
+
+ def matrix_power(self, M, n):
+ """
+ Raise a square matrix to the integer power n.
+ """
+ self._not_implemented_yet('matrix_power')
+
+ def kron(self, a, b):
+ """
+ Kronecker product of two arrays.
+ """
+ self._not_implemented_yet('kron')
+
+#Decompositions
+
+ def cholesky(self, a):
+ """
+ Cholesky decomposition.
+ """
+ self._not_implemented_yet('cholesky')
+
+ def qr(self, a, mode='reduced'):
+ """
+ Compute the qr factorization of a matrix.
+ """
+ self._not_implemented_yet('qr')
+
+ def svd(self, a, full_matrices=True, compute_uv=True):
+ """
+ Singular Value Decomposition.
+ """
+ self._not_implemented_yet('svd')
+
+#Matrix eigenvalues
+
+ def eig(self, a):
+ """
+ Compute the eigenvalues and right eigenvectors of a square array.
+ """
+ self._not_implemented_yet('eig')
+
+ def eigh(self, a, UPLO='L'):
+ """
+ Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix.
+ """
+ self._not_implemented_yet('eigh')
+
+ def eigvals(self, a):
+ """
+ Compute the eigenvalues of a general matrix.
+ """
+ self._not_implemented_yet('eigvals')
+
+ def eigvalsh(self, a, UPLO='L'):
+ """
+ Compute the eigenvalues of a Hermitian or real symmetric matrix.
+ """
+ self._not_implemented_yet('eigvalsh')
+
+#Norms and other numbers
+
+ def norm(self, x, ord=None, axis=None, keepdims=False):
+ """
+ Matrix or vector norm.
+ """
+ self._not_implemented_yet('norm')
+
+ def cond(self, x, p=None):
+ """
+ Compute the condition number of a matrix.
+ """
+ self._not_implemented_yet('cond')
+
+ def det(self, a):
+ """
+ Compute the determinant of an array.
+ """
+ self._not_implemented_yet('det')
+
+ def matrix_rank(self, M, tol=None):
+ """
+ Return matrix rank of array using SVD method
+ """
+ self._not_implemented_yet('matrix_rank')
+
+ def slogdet(self, a):
+ """
+ Compute the sign and natural logarithm of the determinant of an array.
+ """
+ self._not_implemented_yet('slogdet')
+
+ def trace(self, a, offset=0, axis1=0, axis2=1, dtype=None, out=None):
+ """
+ Return the sum along diagonals of the array.
+ """
+ self._not_implemented_yet('trace')
+
+#Solving equations and inverting matrices
+
+ def solve(self, a, b):
+ """
+ Solve a linear matrix equation, or system of linear scalar equations.
+ """
+ self._not_implemented_yet('solve')
+
+ def tensorsolve(self, a, b, axes=None):
+ """
+ Solve the tensor equation a x = b for x.
+ """
+ self._not_implemented_yet('tensorsolve')
+
+ def lstsq(self, a, b, rcond=-1):
+ """
+ Return the least-squares solution to a linear matrix equation.
+ """
+ self._not_implemented_yet('lstsq')
+
+ def inv(self, a):
+ """
+ Compute the (multiplicative) inverse of a matrix.
+ """
+ self._not_implemented_yet('inv')
+
+ def pinv(self, a, rcond=1e-15):
+ """
+ Compute the (Moore-Penrose) pseudo-inverse of a matrix.
+ """
+ self._not_implemented_yet('pinv')
+
+ def tensorinv(self, a, ind=2):
+ """
+ Compute the 'inverse' of an N-dimensional array.
+ """
+ self._not_implemented_yet('tensorinv')
+
+
+###################
+# LOGIC FUNCTIONS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.logic.html
+
+#Truth value testing
+
+ def any(self, a, axis=None, out=None):
+ """
+ Test whether any array elements along a given axis evaluate to True.
+ """
+ self._not_implemented_yet('any')
+
+ def all(self, a, axis=None, out=None):
+ """
+ Test whether all array elements along a given axis evaluate to True.
+ """
+ self._not_implemented_yet('all')
+
+#Array contents
+
+ def isfinite(self, x, out=None):
+ """
+ Test element-wise for finiteness (not infinity or not Not a Number).
+ """
+ self._not_implemented_yet('isfinite')
+
+ def isinf(self, x, out=None):
+ """
+ Test element-wise for positive or negative infinity.
+ """
+ self._not_implemented_yet('isinf')
+
+ def isnan(self, x, out=None):
+ """
+ Test element-wise for NaN and return result as a boolean array.
+ """
+ self._not_implemented_yet('isnan')
+
+ def isneginf(self, x, out=None):
+ """
+ Test element-wise for negative infinity, return result as bool array.
+ """
+ self._not_implemented_yet('isneginf')
+
+ def isposinf(self, x, out=None):
+ """
+ Test element-wise for positive infinity, return result as bool array.
+ """
+ self._not_implemented_yet('isposinf')
+
+#Logical operations
+
+ def logical_and(self, x1, x2, out=None):
+ """
+ Compute the truth value of x1 AND x2 element-wise.
+ """
+ self._not_implemented_yet('logical_and')
+
+ def logical_or(self, x1, x2, out=None):
+ """
+ Compute the truth value of x1 OR x2 element-wise.
+ """
+ self._not_implemented_yet('logical_or')
+
+ def logical_not(self, x, out=None):
+ """
+ Compute the truth value of NOT x element-wise.
+ """
+ self._not_implemented_yet('logical_not')
+
+ def logical_xor(self, x1, x2, out=None):
+ """
+ Compute the truth value of x1 XOR x2, element-wise.
+ """
+ self._not_implemented_yet('logical_xor')
+
+#Comparisson
+
+ def allclose(self, a, b, rtol=1e-05, atol=1e-08, equal_nan=False):
+ """
+ Returns True if two arrays are element-wise equal within a tolerance.
+ """
+ self._not_implemented_yet('allclose')
+
+ def isclose(self, a, b, rtol=1e-05, atol=1e-08, equal_nan=False):
+ """
+ Returns a boolean array where two arrays are element-wise equal within a tolerance.
+ """
+ self._not_implemented_yet('isclose')
+
+ def array_equal(self, a1, a2):
+ """
+ True if two arrays have the same shape and elements, False otherwise.
+ """
+ self._not_implemented_yet('array_equal')
+
+ def array_equiv(self, a1, a2):
+ """
+ returns True if input arrays are shape consistent and all elements equal.
+ """
+ self._not_implemented_yet('array_equiv')
+
+ def greater(self, x1, x2, out=None):
+ """
+ Return the truth value of (x1 > x2) element-wise.
+ """
+ self._not_implemented_yet('greater')
+
+ def greater_equal(self, x1, x2, out=None):
+ """
+ Return the truth value of (x1 >= x2) element-wise.
+ """
+ self._not_implemented_yet('greater_equal')
+
+ def less(self, x1, x2, out):
+ """
+ Return the truth value of (x1 < x2) element-wise.
+ """
+ self._not_implemented_yet('less')
+
+ def less_equal(self, x1, x2, out):
+ """
+ Return the truth value of (x1 =< x2) element-wise.
+ """
+ self._not_implemented_yet('less_equal')
+
+ def equal(self, x1, x2, out=None):
+ """
+ Return (x1 == x2) element-wise.
+ """
+ self._not_implemented_yet('equal')
+
+ def not_equal(self, x1, x2, out=None):
+ """
+ Return (x1 != x2) element-wise.
+ """
+ self._not_implemented_yet('not_equal')
+
+
+##########################
+# MATHEMATICAL FUNCTIONS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.math.html
+
+# Trigonometric functions
+
+ def sin(self, x, out=None):
+ """
+ Trigonometric sine, element-wise.
+ """
+ self._not_implemented_yet('sin')
+
+ def cos(self, x, out=None):
+ """
+ Cosine element-wise.
+ """
+ self._not_implemented_yet('cos')
+
+ def tan(self, x, out=None):
+ """
+ Compute tangent element-wise.
+ """
+ self._not_implemented_yet('tan')
+
+
+ def arcsin(self, x, out=None):
+ """
+ Inverse sine, element-wise.
+ """
+ self._not_implemented_yet('arcsin')
+
+ def arccos(self, x, out=None):
+ """
+ Trigonometric inverse cosine, element-wise.
+ """
+ self._not_implemented_yet('arccos')
+
+ def arctan(self, x, out=None):
+ """
+ Trigonometric inverse tangent, element-wise.
+ """
+ self._not_implemented_yet('arctan')
+
+ def arctan2(self, x1, x2, out=None):
+ """
+ Element-wise arc tangent of x1/x2 choosing the quadrant correctly.
+ """
+ self._not_implemented_yet('arctan2')
+
+
+ def hypot(self, x1, x2, out=None):
+ """
+ Given the legs of a right triangle, return its hypotenuse.
+ """
+ self._not_implemented_yet('hypot')
+
+ def unwrap(self, p, discont=3.141592653589793, axis=-1):
+ """
+ Unwrap by changing deltas between values to 2*pi complement.
+ """
+ self._not_implemented_yet('unwrap')
+
+ def deg2rad(self, x, out=None):
+ """
+ Convert angles from degrees to radians.
+ """
+ self._not_implemented_yet('deg2rad')
+
+ def rad2deg(self, x, out=None):
+ """
+ Convert angles from radians to degrees.
+ """
+ self._not_implemented_yet('rad2deg')
+
+# Hyperbolic functions
+
+ def sinh(self, x, out=None):
+ """
+ Hyperbolic sine, element-wise.
+ """
+ self._not_implemented_yet('sinh')
+
+ def cosh(self, x, out=None):
+ """
+ Hyperbolic cosine, element-wise.
+ """
+ self._not_implemented_yet('cosh')
+
+ def tanh(self, x, out=None):
+ """
+ Compute hyperbolic tangent element-wise.
+ """
+ self._not_implemented_yet('tanh')
+
+
+ def arcsinh(self, x, out=None):
+ """
+ Inverse hyperbolic sine element-wise.
+ """
+ self._not_implemented_yet('arcsinh')
+
+ def arccosh(self, x, out=None):
+ """
+ Inverse hyperbolic cosine, element-wise.
+ """
+ self._not_implemented_yet('arccosh')
+
+ def arctanh(self, x, out=None):
+ """
+ Inverse hyperbolic tangent element-wise.
+ """
+ self._not_implemented_yet('arctanh')
+
+# Rounding
+
+ def around(self, a, decimals=0, out=None):
+ """
+ Evenly round to the given number of decimals, returns HYSOP_INTEGER.
+ """
+ self._not_implemented_yet('around')
+
+
+ def fix(self, x, y=None):
+ """
+ Round to nearest integer towards zero.
+ """
+ self._not_implemented_yet('fix')
+
+
+ def rint(self, x, out=None):
+ """
+ Round elements of the array to the nearest integer.
+ """
+ self._not_implemented_yet('rint')
+
+ def floor(self, x, out=None):
+ """
+ Return the floor of the input, element-wise.
+ """
+ self._not_implemented_yet('floor')
+
+ def ceil(self, x, out=None):
+ """
+ Return the ceiling of the input, element-wise.
+ """
+ self._not_implemented_yet('ceil')
+
+ def trunc(self, x, out=None):
+ """
+ Return the truncated value of the input, element-wise.
+ """
+ self._not_implemented_yet('trunc')
+
+
+# Sums, product, differences
+
+ def prod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the product of array elements over a given axis.
+ """
+ self._not_implemented_yet('prod')
+
+ def sum(self, a, axis=None, dtype=None, out=None):
+ """
+ Sum of array elements over a given axis.
+ """
+ self._not_implemented_yet('sum')
+
+ def nanprod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the product of array elements over a given axis treating
+ Not a Numbers (NaNs) as ones.
+ """
+ self._not_implemented_yet('nanprod')
+
+ def nansum(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.
+ """
+ self._not_implemented_yet('nansum')
+
+ def cumprod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative product of elements along a given axis.
+ """
+ self._not_implemented_yet('cumprod')
+
+ def cumsum(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative sum of the elements along a given axis.
+ """
+ self._not_implemented_yet('cumsum')
+
+ def nancumprod(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative product of array elements over a given axis treating
+ Not a Numbers (NaNs) as one.
+ """
+ self._not_implemented_yet('nancumprod')
+
+ def nancumsum(self, a, axis=None, dtype=None, out=None):
+ """
+ Return the cumulative sum of array elements over a given axis treating
+ Not a Numbers (NaNs) as zero.
+ """
+ self._not_implemented_yet('nancumsum')
+
+ def diff(self, a, n=1, axis=-1):
+ """
+ Calculate the n-th discrete difference along given axis.
+ """
+ self._not_implemented_yet('diff')
+
+ def ediff1d(self, ary, to_end=None, to_begin=None):
+ """
+ The differences between consecutive elements of an array.
+ """
+ self._not_implemented_yet('ediff1d')
+
+ def gradient(self, f, *varargs, **kwargs):
+ """
+ Return the gradient of an N-dimensional array.
+ """
+ self._not_implemented_yet('gradient')
+
+ def cross(self, a, b, axisa=-1, axisb=-1, axisc=-1, axis=None):
+ """
+ Return the cross product of two (arrays of) vectors.
+ """
+ self._not_implemented_yet('cross')
+
+ def trapz(self, y, x=None, dx=1.0, axis=-1):
+ """
+ Integrate along the given axis using the composite trapezoidal rule.
+ """
+ self._not_implemented_yet('trapz')
+
+#Exponents and logarithms
+
+ def exp(self, x, out=None):
+ """
+ Calculate the exponential of all elements in the input array.
+ """
+ self._not_implemented_yet('exp')
+
+ def exp2(self, x, out=None):
+ """
+ Calculate 2**p for all p in the input array.
+ """
+ self._not_implemented_yet('exp2')
+
+ def expm1(self, x, out=None):
+ """
+ Calculate exp(x) - 1 for all elements in the array.
+ """
+ self._not_implemented_yet('expm1')
+
+
+ def log(self, x, out=None):
+ """
+ Natural logarithm, element-wise.
+ """
+ self._not_implemented_yet('log')
+
+ def log2(self, x, out=None):
+ """
+ Base-2 logarithm of x.
+ """
+ self._not_implemented_yet('log2')
+
+ def log10(self, x, out=None):
+ """
+ Return the base 10 logarithm of the input array, element-wise.
+ """
+ self._not_implemented_yet('log10')
+
+ def log1p(self, x, out=None):
+ """
+ Return the natural logarithm of one plus the input array, element-wise.
+ """
+ self._not_implemented_yet('log1p')
+
+
+ def logaddexp(self, x1, x2, out=None):
+ """
+ Logarithm of the sum of exponentiations of the inputs.
+ """
+ self._not_implemented_yet('logaddexp')
+
+ def logaddexp2(self, x1, x2, out=None):
+ """
+ Logarithm of the sum of exponentiations of the inputs in base-2.
+ """
+ self._not_implemented_yet('logaddexp2')
+
+# Other special functions
+
+ def i0(self, x):
+ """
+ Modified Bessel function of the first kind, order 0.
+ """
+ self._not_implemented_yet('i0')
+
+ def sinc(self, x):
+ """
+ Return the sinc function.
+ """
+ self._not_implemented_yet('sinc')
+
+# Floating point routines
+
+ def signbit(self, x, out=None):
+ """
+ Returns element-wise True where signbit is set (less than zero).
+ """
+ self._not_implemented_yet('signbit')
+
+ def copysign(self, x1, x2, out=None):
+ """
+ Change the sign of x1 to that of x2, element-wise.
+ """
+ self._not_implemented_yet('copysign')
+
+ def frexp(self, x, out1=None, out2=None):
+ """
+ Decompose the elements of x into mantissa and twos exponent.
+ """
+ self._not_implemented_yet('frexp')
+
+ def ldexp(self, x1, x2, out=None):
+ """
+ Returns x1 * 2**x2, element-wise.
+ """
+ self._not_implemented_yet('ldexp')
+
+
+# Arithmetic operations
+
+ def add(self, x1, x2, out=None):
+ """
+ Add arguments element-wise.
+ """
+ self._not_implemented_yet('add')
+
+ def reciprocal(self, x, out=None):
+ """
+ Return the reciprocal of the argument, element-wise.
+ """
+ self._not_implemented_yet('reciprocal')
+
+ def negative(self, x, out=None):
+ """
+ Numerical negative, element-wise.
+ """
+ self._not_implemented_yet('negative')
+
+ def multiply(self, x1, x2, out=None):
+ """
+ Multiply arguments element-wise.
+ """
+ self._not_implemented_yet('multiply')
+
+ def divide(self, x1, x2, out=None):
+ """
+ Divide arguments element-wise.
+ """
+ self._not_implemented_yet('divide')
+
+ def power(self, x1, x2, out=None):
+ """
+ First array elements raised to powers from second array, element-wise.
+ """
+ self._not_implemented_yet('power')
+
+ def subtract(self, x1, x2, out=None):
+ """
+ Subtract arguments, element-wise.
+ """
+ self._not_implemented_yet('subtract')
+
+ def true_divide(self, x1, x2, out=None):
+ """
+ Returns a true division of the inputs, element-wise.
+ """
+ self._not_implemented_yet('true_divide')
+
+ def floor_divide(self, x1, x2, out=None):
+ """
+ Return the largest integer smaller or equal to the division of the inputs.
+ """
+ self._not_implemented_yet('floor_divide')
+
+ def fmod(self, x1, x2, out=None):
+ """
+ Return the element-wise remainder of division (REM).
+ Remainder has the same sign as the divisor x2.
+ This should not be confused with the Python modulus operator x1 % x2.
+ """
+ self._not_implemented_yet('fmod')
+
+ def mod(self, x1, x2, out=None):
+ """
+ Return element-wise remainder of division (MOD).
+ Remainder has the same sign as the divident x1.
+ It is complementary to the function floor_divide and
+ match Python modfulus operator x1 % x2.
+ """
+ self._not_implemented_yet('mod')
+
+ def modf(self, x, out1=None, out2=None):
+ """
+ Return the fractional and integral parts of an array, element-wise.
+ """
+ self._not_implemented_yet('modf')
+
+# Handling complex numbers
+
+ def angle(self, z, deg=False):
+ """
+ Return the angle of the complex argument.
+ """
+ self._not_implemented_yet('angle')
+
+ def real(self, val):
+ """
+ Return the real part of the elements of the array.
+ """
+ self._not_implemented_yet('real')
+
+ def imag(self, val):
+ """
+ Return the imaginary part of the elements of the array.
+ """
+ self._not_implemented_yet('imag')
+
+ def conj(self, x, out=None):
+ """
+ Return the complex conjugate, element-wise.
+ """
+ self._not_implemented_yet('conj')
+
+# Miscellanous
+
+ def convolve(self, a, v, mode='full'):
+ """
+ Returns the discrete, linear convolution of two one-dimensional sequences.
+ """
+ self._not_implemented_yet('convolve')
+
+ def clip(self, a, a_min, a_max, out=None):
+ """
+ Clip (limit) the values in an array.
+ """
+ self._not_implemented_yet('clip')
+
+ def sqrt(self, x, out=None):
+ """
+ Return the positive square-root of an array, element-wise.
+ """
+ self._not_implemented_yet('sqrt')
+
+ def cbrt(self, x, out=None):
+ """
+ Return the cube-root of an array, element-wise.
+ """
+ self._not_implemented_yet('cbrt')
+
+ def square(self, x, out=None):
+ """
+ Return the element-wise square of the input.
+ """
+ self._not_implemented_yet('square')
+
+ def nan_to_num(self, x):
+ """
+ Replace nan with zero and inf with finite numbers.
+ """
+ self._not_implemented_yet('nan_to_num')
+
+ def real_if_close(self, a, tol=100):
+ """
+ If complex input returns a real array if complex parts are close to zero.
+ """
+ self._not_implemented_yet('real_if_close')
+
+ def interp(self, x, xp, fp, left=None, right=None, period=None):
+ """
+ One-dimensional linear interpolation.
+ """
+ self._not_implemented_yet('interp')
+
+
+ def maximum(self, x1, x2, out=None):
+ """
+ Element-wise maximum of array elements.
+ """
+ self._not_implemented_yet('maximum')
+
+ def minimum(self, x1, x2, out=None):
+ """
+ Element-wise minimum of array elements.
+ """
+ self._not_implemented_yet('minimum')
+
+ def fmin(self, x1, x2, out=None):
+ """
+ Element-wise maximum of array elements, ignore NaNs.
+ """
+ self._not_implemented_yet('fmin')
+
+ def fmax(self, x1, x2, out=None):
+ """
+ Element-wise minimum of array elements, ignore NaNs.
+ """
+ self._not_implemented_yet('fmax')
+
+ def fabs(self, x, out=None):
+ """
+ Calculate the absolute value element-wise, outputs HYSOP_REAL unless out is set.
+ """
+ self._not_implemented_yet('fabs')
+
+
+ def absolute(self, x, out=None):
+ """
+ Calculate the absolute value element-wise.
+ """
+ self._not_implemented_yet('absolute')
+
+
+ def sign(self, x, out=None):
+ """
+ Returns an element-wise indication of the sign of a number.
+ """
+ self._not_implemented_yet('sign')
+
+
+###################
+# RANDOM SAMPLING #
+## See https://docs.scipy.org/doc/numpy/reference/routines.random.html
+
+# Simple random data
+
+ def rand(self, shape):
+ """
+ Random values in a given shape between 0.0 and 1.0.
+ """
+
+ def randn(self, shape):
+ """
+ Return a sample (or samples) from the 'standard normal' distribution.
+ """
+ self._not_implemented_yet('randn')
+
+ def randint(self, low, high=None, size=None, dtype=HYSOP_INTEGER):
+ """
+ Return random integers from low (inclusive) to high (exclusive).
+ """
+ self._not_implemented_yet('randint')
+
+ def random_integers(self, low, high=None, size=None):
+ """
+ Random integers of type np.int between low and high, inclusive.
+ """
+ self._not_implemented_yet('random_integers')
+
+ def random_sample(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ self._not_implemented_yet('random_sample')
+
+ def random(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ self._not_implemented_yet('random')
+
+ def ranf(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ self._not_implemented_yet('ranf')
+
+ def sample(self, size=None):
+ """
+ Return random floats in the half-open interval 0.0, 1.0).
+ """
+ self._not_implemented_yet('sample')
+
+ def choice(self, a, size=None, replace=True, p=None):
+ """
+ Generates a random sample from a given 1-D array
+ """
+ self._not_implemented_yet('choice')
+
+ def bytes(self, length):
+ """
+ Return random bytes.
+ """
+ self._not_implemented_yet('bytes')
+
+# Permutations
+
+ def shuffle(self, x):
+ """
+ Modify a sequence in-place by shuffling its contents.
+ """
+ self._not_implemented_yet('shuffle')
+
+ def permutation(self, x):
+ """
+ Randomly permute a sequence, or return a permuted range.
+ """
+ self._not_implemented_yet('permutation')
+
+# Distributions
+
+ def beta(self, a, b, size=None):
+ """
+ Draw samples from a Beta distribution.
+ """
+ self._not_implemented_yet('beta')
+
+ def binomial(self, n, p, size=None):
+ """
+ Draw samples from a binomial distribution.
+ """
+ self._not_implemented_yet('binomial')
+
+ def chisquare(self, df, size=None):
+ """
+ Draw samples from a chi-square distribution.
+ """
+ self._not_implemented_yet('chisquare')
+
+ def dirichlet(self, alpha, size=None):
+ """
+ Draw samples from the Dirichlet distribution.
+ """
+ self._not_implemented_yet('dirichlet')
+
+ def exponential(self, scale=1.0, size=None):
+ """
+ Draw samples from an exponential distribution.
+ """
+ self._not_implemented_yet('exponential')
+
+ def f(self, dfnum, dfden, size=None):
+ """
+ Draw samples from an F distribution.
+ """
+ self._not_implemented_yet('f')
+
+ def gamma(self, shape, scale=1.0, size=None):
+ """
+ Draw samples from a Gamma distribution.
+ """
+ self._not_implemented_yet('gamma')
+
+ def geometric(self, p, size=None):
+ """
+ Draw samples from the geometric distribution.
+ """
+ self._not_implemented_yet('geometric')
+
+ def gumbel(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw samples from a Gumbel distribution.
+ """
+ self._not_implemented_yet('gumbel')
+
+ def hypergeometric(self, ngood, nbad, nsample, size=None):
+ """
+ Draw samples from a Hypergeometric distribution.
+ """
+ self._not_implemented_yet('hypergeometric')
+
+ def laplace(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw samples from the Laplace or double exponential distribution with specified location (or mean=0.0) and scale (decay).
+ """
+ self._not_implemented_yet('laplace')
+
+ def logistic(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw samples from a logistic distribution.
+ """
+ self._not_implemented_yet('logistic')
+
+ def lognormal(self, mean=0.0, sigma=1.0, size=None):
+ """
+ Draw samples from a log-normal distribution.
+ """
+ self._not_implemented_yet('lognormal')
+
+ def logseries(self, p, size=None):
+ """
+ Draw samples from a logarithmic series distribution.
+ """
+ self._not_implemented_yet('logseries')
+
+ def multinomial(self, n, pvals, size=None):
+ """
+ Draw samples from a multinomial distribution.
+ """
+ self._not_implemented_yet('multinomial')
+
+ def multivariate_normal(self, mean, cov, size=None):
+ """
+ Draw random samples from a multivariate normal distribution.
+ """
+ self._not_implemented_yet('multivariate_normal')
+
+ def negative_binomial(self, n, p, size=None):
+ """
+ Draw samples from a negative binomial distribution.
+ """
+ self._not_implemented_yet('negative_binomial')
+
+ def noncentral_chisquare(self, df, nonc, size=None):
+ """
+ Draw samples from a noncentral chi-square distribution.
+ """
+ self._not_implemented_yet('noncentral_chisquare')
+
+ def noncentral_f(self, dfnum, dfden, nonc, size=None):
+ """
+ Draw samples from the noncentral F distribution.
+ """
+ self._not_implemented_yet('noncentral_f')
+
+ def normal(self, loc=0.0, scale=1.0, size=None):
+ """
+ Draw random samples from a normal (Gaussian) distribution.
+ """
+ self._not_implemented_yet('normal')
+
+ def pareto(self, a, size=None):
+ """
+ Draw samples from a Pareto II or Lomax distribution with specified shape.
+ """
+ self._not_implemented_yet('pareto')
+
+ def poisson(self, lam, size=None):
+ """
+ Draw samples from a Poisson distribution.
+ """
+ self._not_implemented_yet('poisson')
+
+ def power(self, a, size=None):
+ """
+ Draws samples in 0, 1 from a power distribution with positive exponent a - 1.
+ """
+ self._not_implemented_yet('power')
+
+ def rayleigh(self, scale=1.0, size=None):
+ """
+ Draw samples from a Rayleigh distribution.
+ """
+ self._not_implemented_yet('rayleigh')
+
+ def standard_cauchy(self, size=None):
+ """
+ Draw samples from a standard Cauchy distribution with mode = 0.
+ """
+ self._not_implemented_yet('standard_cauchy')
+
+ def standard_exponential(self, size=None):
+ """
+ Draw samples from the standard exponential distribution.
+ """
+ self._not_implemented_yet('standard_exponential')
+
+ def standard_gamma(self, shape, size=None):
+ """
+ Draw samples from a standard Gamma distribution.
+ """
+ self._not_implemented_yet('standard_gamma')
+
+ def standard_normal(self, size=None):
+ """
+ Draw samples from a standard Normal distribution (mean=0.0, stdev=1).
+ """
+ self._not_implemented_yet('standard_normal')
+
+ def standard_t(self, df, size=None):
+ """
+ Draw samples from a standard Student's t distribution with df degrees of freedom.
+ """
+ self._not_implemented_yet('standard_t')
+
+ def triangular(self, left, mode, right, size=None):
+ """
+ Draw samples from the triangular distribution over the interval left, right.
+ """
+ self._not_implemented_yet('triangular')
+
+ def uniform(self, low, high, size=None):
+ """
+ Draw samples from a uniform distribution.
+ """
+ self._not_implemented_yet('uniform')
+
+ def vonmises(self, mu, kappa, size=None):
+ """
+ Draw samples from a von Mises distribution.
+ """
+ self._not_implemented_yet('vonmises')
+
+ def wald(self, mean=0.0, scale=1.0, size=None):
+ """
+ Draw samples from a Wald, or inverse Gaussian, distribution.
+ """
+ self._not_implemented_yet('wald')
+
+ def weibull(self, a, size=None):
+ """
+ Draw samples from a Weibull distribution.
+ """
+ self._not_implemented_yet('weibull')
+
+ def zipf(self, a, size=None):
+ """
+ Draw samples from a Zipf distribution.
+ """
+ self._not_implemented_yet('zipf')
+
+# Random generator
+
+ def seed(self, seed=None):
+ """
+ Seed the generator.
+ """
+ self._not_implemented_yet('seed')
+
+ def get_state(self):
+ """
+ Return a tuple representing the internal state of the generator.
+ """
+ self._not_implemented_yet('get_state')
+
+ def set_state(self, state):
+ """
+ Set the internal state of the generator from a tuple.
+ """
+ self._not_implemented_yet('set_state')
+
+
+################
+# SET ROUTINES #
+## See https://docs.scipy.org/doc/numpy/reference/routines.set.html
+
+# Making proper sets
+
+ def unique(self, ar, return_index=False, return_inverse=False, return_counts=False):
+ """
+ Find the unique elements of an array.
+ """
+ self._not_implemented_yet('unique')
+
+# Boolean operations
+
+ def in1d(self, ar1, ar2, assume_unique=False, invert=False):
+ """
+ Test whether each element of a 1-D array is also present in a second array.
+ """
+ self._not_implemented_yet('in1d')
+
+ def intersect1d(self, ar1, ar2, assume_unique=False):
+ """
+ Find the intersection of two arrays.
+ """
+ self._not_implemented_yet('intersect1d')
+
+ def setdiff1d(self, ar1, ar2, assume_unique=False):
+ """
+ Find the set difference of two arrays.
+ """
+ self._not_implemented_yet('setdiff1d')
+
+ def setxor1d(self, ar1, ar2, assume_unique=False):
+ """
+ Find the set exclusive-or of two arrays.
+ """
+ self._not_implemented_yet('setxor1d')
+
+ def union1d(self, ar1, ar2):
+ """
+ Find the union of two arrays.
+ """
+ self._not_implemented_yet('union1d')
+
+
+###################################
+# SORTING, SEARCHING AND COUNTING #
+## See https://docs.scipy.org/doc/numpy/reference/routines.sort.html
+
+# Sorting
+
+ def sort(self, a, axis=-1, kind='quicksort', order=None):
+ """
+ Return a sorted copy of an array.
+ """
+ self._not_implemented_yet('sort')
+
+ def lexsort(self, keys, axis=-1):
+ """
+ Perform an indirect sort using a sequence of keys.
+ """
+ self._not_implemented_yet('lexsort')
+
+ def argsort(self, a, axis=-1, kind='quicksort', order=None):
+ """
+ Returns the indices that would sort an array.
+ """
+ self._not_implemented_yet('argsort')
+
+ def msort(self, a):
+ """
+ Return a copy of an array sorted along the first axis.
+ """
+ self._not_implemented_yet('msort')
+
+ def sort_complex(self, a):
+ """
+ Sort a complex array using the real part first, then the imaginary part.
+ """
+ self._not_implemented_yet('sort_complex')
+
+ def partition(self, a, kth, axis=-1, kind='quicksort', order=None):
+ """
+ Return a partitioned copy of an array.
+ """
+ self._not_implemented_yet('partition')
+
+ def argpartition(self, a, kth, axis=-1, kind='quicksort', order=None):
+ """
+ Perform an indirect partition along the given axis using the algorithm specified by the kind keyword.
+ """
+ self._not_implemented_yet('argpartition')
+
+#Searching
+
+ def argmax(self, a, axis, out=None):
+ """
+ Returns the indices of the maximum values along an axis.
+ """
+ self._not_implemented_yet('argmax')
+
+ def nanargmax(self, a, axis=None):
+ """
+ Return the indices of the maximum values in the specified axis ignoring NaNs.
+ """
+ self._not_implemented_yet('nanargmax')
+
+ def argmin(self, a, axis, out=None):
+ """
+ Returns the indices of the minimum values along an axis.
+ """
+ self._not_implemented_yet('argmin')
+
+ def nanargmin(self, a, axis=None):
+ """
+ Return the indices of the minimum values in the specified axis ignoring NaNs.
+ """
+ self._not_implemented_yet('nanargmin')
+
+ def argwhere(self, a):
+ """
+ Find the indices of array elements that are non-zero, grouped by element.
+ """
+ self._not_implemented_yet('argwhere')
+
+ def nonzero(self, a):
+ """
+ Return the indices of the elements that are non-zero.
+ """
+ self._not_implemented_yet('nonzero')
+
+ def flatnonzero(self, a):
+ """
+ Return indices that are non-zero in the flattened version of a.
+ """
+ self._not_implemented_yet('flatnonzero')
+
+ def where(self, condition, x, y):
+ """
+ Return elements, either from x or y, depending on condition.
+ """
+ self._not_implemented_yet('where')
+
+ def searchsorted(self, a, v, side='left', sorter=None):
+ """
+ Find indices where elements should be inserted to maintain order.
+ """
+ self._not_implemented_yet('searchsorted')
+
+ def extract(self, condition, arr):
+ """
+ Return the elements of an array that satisfy some condition.
+ """
+ self._not_implemented_yet('extract')
+
+#Counting
+
+ def count_nonzero(self, a, axis=None):
+ """
+ Counts the number of non-zero values in the array a.
+ """
+ self._not_implemented_yet('count_nonzero')
+
+##############
+# STATISTICS #
+## See https://docs.scipy.org/doc/numpy/reference/routines.sort.html
+
+#Order statistics
+
+ def amin(self, a, axis=None, out=None):
+ """
+ Return the minimum of an array or minimum along an axis.
+ """
+ self._not_implemented_yet('amin')
+
+ def amax(self, a, axis=None, out=None):
+ """
+ Return the maximum of an array or maximum along an axis.
+ """
+ self._not_implemented_yet('amax')
+
+ def nanmin(self, a, axis=None, out=None):
+ """
+ Return minimum of an array or minimum along an axis, ignoring any NaNs.
+ """
+ self._not_implemented_yet('nanmin')
+
+ def nanmax(self, a, axis=None, out=None):
+ """
+ Return the maximum of an array or maximum along an axis, ignoring any NaNs.
+ """
+ self._not_implemented_yet('nanmax')
+
+ def ptp(self, a, axis=None, out=None):
+ """
+ Range of values (maximum - minimum) along an axis.
+ """
+ self._not_implemented_yet('ptp')
+
+ def percentile(self, a, q, axis=None, out=None, overwrite_input=False,
+ interpolation='linear'):
+ """
+ Compute the qth percentile of the data along the specified axis.
+ """
+ self._not_implemented_yet('percentile')
+
+ def nanpercentile(self, a, q, axis=None, out=None, overwrite_input=False,
+ interpolation='linear'):
+ """
+ Compute the qth percentile of the data along the specified axis,
+ while ignoring nan values.
+ """
+ self._not_implemented_yet('nanpercentile')
+
+#Averages and variances
+
+ def median(self, a, axis=None, out=None, overwrite_input=False):
+ """
+ Compute the median along the specified axis.
+ """
+ self._not_implemented_yet('median')
+
+ def average(self, a, axis=None, weights=None, returned=False):
+ """
+ Compute the weighted average along the specified axis.
+ """
+ self._not_implemented_yet('average')
+
+ def mean(self, a, axis=None, dtype=None, out=None):
+ """
+ Compute the arithmetic mean along the specified axis.
+ """
+ self._not_implemented_yet('mean')
+
+ def std(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the standard deviation along the specified axis.
+ """
+ self._not_implemented_yet('std')
+
+ def var(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the variance along the specified axis.
+ """
+ self._not_implemented_yet('var')
+
+ def nanmedian(self, a, axis=None, out=None, overwrite_input=False):
+ """
+ Compute the median along the specified axis, while ignoring NaNs.
+ """
+ self._not_implemented_yet('nanmedian')
+
+ def nanmean(self, a, axis=None, dtype=None, out=None):
+ """
+ Compute the arithmetic mean along the specified axis, ignoring NaNs.
+ """
+ self._not_implemented_yet('nanmean')
+
+ def nanstd(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the standard deviation along the specified axis, while ignoring NaNs.
+ """
+ self._not_implemented_yet('nanstd')
+
+ def nanvar(self, a, axis=None, dtype=None, out=None, ddof=0):
+ """
+ Compute the variance along the specified axis, while ignoring NaNs.
+ """
+ self._not_implemented_yet('nanvar')
+
+# Correlating
+ def corrcoef(self, x, y, rowvar=1):
+ """
+ Return Pearson product-moment correlation coefficients.
+ """
+ self._not_implemented_yet('corrcoef')
+
+ def correlate(self, a, v, mode='valid'):
+ """
+ Cross-correlation of two 1-dimensional sequences.
+ """
+ self._not_implemented_yet('correlate')
+
+ def cov(self, m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, aweights=None):
+ """
+ Estimate a covariance matrix, given data and weights.
+ """
+ self._not_implemented_yet('cov')
+
+# Histograms
+
+ def histogram(self, a, bins=10, range=None, normed=False, weights=None, density=None):
+ """
+ Compute the histogram of a set of data.
+ """
+ self._not_implemented_yet('histogram')
+
+ def histogram2d(self, x, y, bins, range=None, normed=False, weights=None):
+ """
+ Compute the bi-dimensional histogram of two data samples.
+ """
+ self._not_implemented_yet('histogram2d')
+
+ def histogramdd(self, sample, bins, range=None, normed=False, weights=None):
+ """
+ Compute the multidimensional histogram of some data.
+ """
+ self._not_implemented_yet('histogramdd')
+
+ def bincount(self, x, weights=None, minlength=None):
+ """
+ Count number of occurrences of each value in array of non-negative ints.
+ """
+ self._not_implemented_yet('bincount')
+
+ def digitize(self, x, bins, right=False):
+ """
+ Return the indices of the bins to which each value in input array belongs.
+ """
+ self._not_implemented_yet('digitize')
+
+###############
+### ALIASES ###
+ def degrees(self, x, out=None, **kargs):
+ """
+ Convert angles from radians to degrees.
+ """
+ return self.rad2deg(x=x,out=out, **kargs)
+
+ def radians(self, x, out=None, **kargs):
+ """
+ Convert angles from degrees to radians.
+ """
+ return self.deg2rad(x=x,out=out, **kargs)
+
+
+ def remainder(self, x1, x2, out=None,**kargs):
+ """
+ Return element-wise remainder of division (MOD).
+ Remainder has the same sign as the divisor x2.
+ match Python modfulus operator x1 % x2.
+ Returns x - y*floor(x/y)
+ """
+ return self.mod(x1=x1, x2=x2, out=out, **kargs)
+
+
+##########################
+### EXTRA HYSOP METHODS ##
+
+def __generate_hysop_type_functions():
+
+ functions = {
+
+ 'as{type}array':
+'''
+def __hysop_array_generated_method(self, a, order=default_order, **kargs):
+ """
+ Convert the input to an array of dtype HYSOP_{TYPE}.
+ """
+ dtype = HYSOP_{TYPE}
+ return self.asarray(a=a, dtype=dtype, order=order, **kargs)
+''',
+ '{type}_prod':
+'''
+def __hysop_array_generated_method(self, a, axis=None, out=None, **kargs):
+ """
+ Sum of array elements over a given axis.
+ """
+ dtype = HYSOP_{TYPE}
+ return self.prod(a=a,axis=axis,out=out,dtype=dtype,**kargs)
+''',
+ '{type}_sum':
+'''
+def __hysop_array_generated_method(self, a, axis=None, out=None, **kargs):
+ """
+ Sum of array elements over a given axis.
+ """
+ dtype = HYSOP_{TYPE}
+ return self.sum(a=a,axis=axis,out=out,dtype=dtype,**kargs)
+''',
+
+ '{type}_empty':
+'''
+def __hysop_array_generated_method(self, shape, order=default_order, **kargs):
+ """
+ Return a new array of given shape and type, without initializing entries.
+ """
+ dtype = HYSOP_{TYPE}
+ return self.empty(shape=shape, dtype=dtype, order=order, **kargs)
+''',
+
+ '{type}_ones':
+'''
+def __hysop_array_generated_method(self, shape, order=default_order, **kargs):
+ """
+ Return a new array of given shape filled with ones of type HYSOP_{TYPE}.
+ """
+ dtype = HYSOP_{TYPE}
+ return self.ones(shape=shape, order=order, dtype=dtype, **kargs)
+''',
+
+ '{type}_zeros':
+'''
+def __hysop_array_generated_method(self, shape, order=default_order, **kargs):
+ """
+ Return a new array of given shape, filled with zeros of type HYSOP_{TYPE}.
+ """
+ dtype = HYSOP_{TYPE}
+ return self.zeros(shape=shape, order=order, dtype=dtype, **kargs)
+''',
+
+ '{type}_full':
+'''
+def __hysop_array_generated_method(self, shape, fill_value, order=default_order, **kargs):
+ """
+ Return a new array of given shape, filled with fill_value of type HYSOP_{TYPE}.
+ """
+ dtype = HYSOP_{TYPE}
+ return self.full(shape=shape, fill_value=filling_value, order=order, dtype=dtype, **kargs)
+'''
+}
+
+ hysop_types = ['real', 'complex', 'integer', 'index', 'dim', 'bool']
+
+ for ht in hysop_types:
+ for fname, fdefinition in functions.iteritems():
+ fname = fname.format(type=ht, TYPE=ht.upper())
+ fdef = fdefinition.format(type=ht, TYPE=ht.upper())
+ exec(fdef)
+ setattr(ArrayBackend, fname, __hysop_array_generated_method)
+
+__generate_hysop_type_functions()
+
diff --git a/hysop/core/arrays/tests/test_array.py b/hysop/core/arrays/tests/test_array.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f33e4c806fd04190acf04eb7a9e0dc9b3254348
--- /dev/null
+++ b/hysop/core/arrays/tests/test_array.py
@@ -0,0 +1,722 @@
+import numpy as np
+import warnings
+from contextlib import contextmanager
+from hysop.testsenv import opencl_failed, iter_clenv, \
+ __HAS_OPENCL_BACKEND__, __ENABLE_LONG_TESTS__
+from hysop.tools.contexts import printoptions
+from hysop.tools.numerics import match_float_type, is_unsigned, is_integer, is_complex
+from hysop.tools.types import to_list
+from hysop.constants import HYSOP_BOOL, HYSOP_REAL, HYSOP_INTEGER
+from hysop.constants import MemoryOrdering, transposition_states, default_order
+from hysop.core.arrays.all import HostArray, OpenClArray, Array
+from hysop.core.arrays.all import HostArrayBackend, OpenClArrayBackend, ArrayBackend
+from hysop.backend.host.host_allocator import HostAllocator
+from hysop.core.memory.mempool import MemoryPool
+
+class TestArray(object):
+
+ @classmethod
+ def setup_class(cls):
+ pass
+
+ @classmethod
+ def teardown_class(cls):
+ pass
+
+ def setup_method(self, method):
+ pass
+
+ def teardown_method(self, method):
+ pass
+
+ def _test_array_creation_routines(self, backend):
+ a = backend.empty(shape=10, dtype=np.int16)
+ a.fill(-1)
+ b = backend.zeros_like(a)
+ c = backend.ones_like(b)
+ d = backend.full_like(c, fill_value=2)
+ e = backend.empty_like(d)
+ e.fill(3)
+ for buf,val in zip([a,b,c,d,e],[-1,0,1,2,3]):
+ assert buf.ndim == 1
+ assert buf.size == 10
+ assert buf.shape == (10,)
+ assert buf.itemsize == 2
+ assert buf.nbytes == 20
+ assert buf.dtype == np.int16
+ assert buf.sum().get()==val*10
+ assert buf.prod()==val**10
+ assert buf.is_c_contiguous()
+ assert buf.is_fortran_contiguous()
+ assert buf.is_hysop_contiguous()
+
+ a = backend.empty(shape=(10,10,), dtype=np.float64,
+ order=MemoryOrdering.C_CONTIGUOUS)
+ a.fill(15)
+ b = backend.zeros_like(a)
+ c = backend.ones_like(b)
+ d = backend.full_like(c, fill_value=2)
+ for buf,val in zip([a,b,c,d],[15,0,1,2]):
+ assert buf.ndim == 2
+ assert buf.size == 100
+ assert buf.shape == (10,10,)
+ assert buf.itemsize == 8
+ assert buf.nbytes == 800
+ assert buf.dtype == np.float64
+ assert np.allclose(buf.sum().get(),val*100.0)
+ assert buf.is_c_contiguous()
+
+ a = backend.empty(shape=(10,10,), dtype=np.float32,
+ order=MemoryOrdering.FORTRAN_CONTIGUOUS)
+ a.fill(15)
+ b = backend.zeros_like(a)
+ c = backend.ones_like(b)
+ d = backend.full_like(c, fill_value=2)
+ for buf,val in zip([a,b,c,d],[15,0,1,2]):
+ assert buf.ndim == 2
+ assert buf.size == 100
+ assert buf.shape == (10,10,)
+ assert buf.itemsize == 4
+ assert buf.nbytes == 400
+ assert buf.dtype == np.float32
+ assert buf.sum().get()==val*100
+ assert buf.is_fortran_contiguous()
+
+ a.fill(5)
+ b.copy_from(a)
+ c.copy_from(b.handle)
+ d = c.copy()
+ for buf in [a,b,c,d]:
+ assert buf.ndim == 2
+ assert buf.size == 100
+ assert buf.shape == (10,10,)
+ assert buf.itemsize == 4
+ assert buf.nbytes == 400
+ assert buf.dtype == np.float32
+ assert buf.sum().get()==5*100
+ assert buf.is_fortran_contiguous()
+
+
+ def _test_array_manipulation_routines(self, backend):
+ t3d = transposition_states[3]
+
+ a = backend.empty(shape=(8,4,2), dtype=np.int8,
+ order=MemoryOrdering.C_CONTIGUOUS)
+ b = backend.empty(shape=(2,4,8), dtype=np.int8,
+ order=MemoryOrdering.FORTRAN_CONTIGUOUS)
+ a.copy_from(backend.arange(0,a.size,dtype=a.dtype))
+ b.copy_from(backend.arange(0,b.size,dtype=b.dtype))
+
+ assert a.transposition_state()==t3d.ZYX
+ assert b.transposition_state()==t3d.XYZ
+ assert (a.ravel()==b.ravel(order=MemoryOrdering.C_CONTIGUOUS)).all()
+
+ a = a.transpose_to_state(t3d.XZY)
+ b = b.transpose_to_state(t3d.XZY)
+ assert a.order == MemoryOrdering.OUT_OF_ORDER
+ assert b.order == MemoryOrdering.OUT_OF_ORDER
+ assert a.transposition_state()==t3d.XZY
+ assert b.transposition_state()==t3d.XZY
+
+ a = a.transpose([2,0,1])
+ b = b.transpose([1,2,0])
+ assert a.transposition_state()==t3d.YXZ
+ assert b.transposition_state()==t3d.ZYX
+
+ a = a.transpose_to_state(t3d.ZYX)
+ b = b.transpose_to_state(t3d.XYZ)
+ assert (a.ravel()==b.ravel(order=MemoryOrdering.C_CONTIGUOUS)).all()
+
+ a = a.reshape(8*4*2)
+ b = a.reshape(8*4*2)
+ assert a.order == default_order
+ assert b.order == default_order
+ assert (a==b).all()
+
+ a = a.reshape((8,4,2), order=MemoryOrdering.C_CONTIGUOUS)
+ b = b.reshape((8,4,2), order=MemoryOrdering.FORTRAN_CONTIGUOUS)
+ assert a.order == MemoryOrdering.C_CONTIGUOUS
+ assert b.order == MemoryOrdering.FORTRAN_CONTIGUOUS
+
+ assert a.transposition_state() == t3d.ZYX
+ a = backend.moveaxis(a, 0, 1)
+ assert a.transposition_state() == t3d.YZX
+ a = backend.swapaxes(a, 1, 2)
+ assert a.transposition_state() == t3d.YXZ
+ a = backend.rollaxis(a, 2)
+ assert a.transposition_state() == t3d.ZYX
+ a = backend.rollaxis(a, 2, 1)
+ assert a.transposition_state() == t3d.ZXY
+
+ a0 = backend.asfortranarray(a)
+ a1 = backend.ascontiguousarray(a)
+ a2 = backend.asarray_chkfinite(a)
+
+ assert a0.order == MemoryOrdering.FORTRAN_CONTIGUOUS
+ assert a1.order == MemoryOrdering.C_CONTIGUOUS
+ assert a2.order == default_order
+
+ assert a0.transposition_state() == t3d.XYZ
+ assert a1.transposition_state() == t3d.ZYX
+
+ assert (a0==a).all()
+ assert (a1==a).all()
+ assert (a2==a).all()
+
+ def _test_binary_operations(self, backend):
+ a = backend.rand((10,10))
+ b = backend.rint(a)
+ a = backend.rint(backend.rand((10,10))).astype(np.uint8)
+ b = backend.rint(backend.rand((10,10))).astype(np.uint8)
+ c = backend.rint(backend.rand((10,10))).astype(np.uint8)
+ d = backend.rint(backend.rand((10,10))).astype(np.uint8)
+
+ assert ((~(~a)) == a).all()
+ assert (((a<<2<<3)>>5) == a).all()
+ assert ((a>>1)==0).all()
+ assert ((a|b|c|d)==(d|c|b|a)).all()
+ assert ((a&b&c&d)==(d&c&b&a)).all()
+ assert ((a^b)==(b^a)).all()
+ assert ((~(a|b))==((~a)&(~b))).all()
+
+ a = backend.rint(10000*backend.rand((10,10))).astype(np.uint64)
+ b = backend.rint(10000*backend.rand((10,10))).astype(np.uint64)
+ c = backend.rint(10000*backend.rand((10,10))).astype(np.uint64)
+ d = backend.rint(10000*backend.rand((10,10))).astype(np.uint64)
+
+ assert ((~(~a)) == a).all()
+ assert (((a<<2<<3)>>5) == a).all()
+ assert ((a|b|c|d)==(d|c|b|a)).all()
+ assert ((a&b&c&d)==(d&c&b&a)).all()
+ assert ((a^b)==(b^a)).all()
+ assert ((~(a|b))==((~a)&(~b))).all()
+
+ def _test_arithmetic_operations(self, backend):
+ a = backend.rand((10,10)).astype(np.float64).clip(0.1, 0.9)
+ a = (a-0.5)*10
+
+ b = 10*backend.rand((10,10)).astype(np.float64).clip(0.1, 0.9)
+ c = 10*backend.rand((10,10)).astype(np.float64).clip(0.1, 0.9)
+ d = 10*backend.rand((10,10)).astype(np.float64).clip(0.1, 0.9)
+
+
+ assert backend.allclose( 4.0+a, a+4.0 )
+ assert backend.allclose( 4.0-a, -(a-4.0) )
+ assert backend.allclose( 4.0*a, a*4.0 )
+ assert backend.allclose( 4.0/a, 1.0/(a/4.0) )
+
+ f,i = backend.modf(a)
+ assert backend.allclose( backend.trunc(a), i )
+ f,i = backend.modf(b)
+ assert backend.allclose( backend.fmod(b,1), f )
+
+ assert backend.allclose( b//1, i )
+ assert backend.allclose( b%1, f )
+
+ assert backend.allclose( a-b, -(b-a) )
+ assert backend.allclose( a+b-c-d, -c-d+b+a )
+ assert backend.allclose( a*b*c*d, d*c*a*b )
+ #assert backend.allclose( (a/b)*(c/d), (a*c)/(b*d) )
+ a = a%b
+ a = a//b
+
+ a = c.copy()
+ assert backend.allclose(c, a)
+ a+=1
+ assert backend.allclose(c+1,a)
+ a-=3
+ assert backend.allclose(c+1-3,a)
+ a*=2
+ assert backend.allclose(2*(c+1-3),a)
+ a/=3
+ assert backend.allclose(2*(c+1-3)/3,a)
+ a//=4
+ assert backend.allclose((2*(c+1-3)/3)//4,a)
+ a%=2
+ assert backend.allclose(((2*(c+1-3)/3)//4)%2,a)
+
+ def _test_backend_versus_numpy_operations(self, backend):
+ npb = backend
+
+ atol = [None]
+
+ # pollute array with +inf, -inf and NaNs values
+ def pollute(arr):
+ mask = lambda p: (np.random.rand(*arr.shape)<p)
+ arr[mask(0.20)] = -np.inf
+ arr[mask(0.20)] = +np.inf
+ arr[mask(0.20)] = np.nan
+
+ def allclose(np_array, backend_array, equal_nan=True, atol=atol,
+ relaxed_precision=False, ignore_mask=None):
+ atol = atol[0] # 1*epsilon
+ if relaxed_precision:
+ atol=1e-2
+ if (backend_array is None):
+ msg='Backend returned nothing (got None).'
+ raise ValueError(msg)
+ if not np.isscalar(np_array) and not isinstance(np_array, np.ndarray):
+ msg='first arg is not a np.ndarray (got {})'
+ msg=msg.format(np_array)
+ raise ValueError(msg)
+ if isinstance(backend_array, Array):
+ backend_array = backend_array.get().handle
+ if (ignore_mask is not None):
+ np_array = np_array[~ignore_mask]
+ backend_array = backend_array[~ignore_mask]
+ return np.allclose(np_array, backend_array, equal_nan=equal_nan, atol=atol)
+
+ # FIXME tan(x) returns -tan(x) with amd mesa drivers...
+ unary_ops = [
+ 'reciprocal', 'negative', 'absolute', 'fabs',
+ 'sin', 'cos', 'arcsin', 'arccos', 'arctan', #'tan',
+ 'degrees', 'radians', 'deg2rad', 'rad2deg',
+ 'sinh', 'cosh', 'tanh', 'arcsinh', 'arccosh', 'arctanh',
+ 'around', 'rint', 'fix', 'floor', 'ceil', 'trunc',
+ 'exp', 'expm1', 'exp2',
+ 'log', 'log10', 'log2', 'log1p',
+ 'signbit', 'reciprocal', 'negative',
+ 'sqrt', 'cbrt', 'square', 'sign',
+ 'nan_to_num',
+ 'prod', 'sum', 'nanprod', 'nansum',
+ 'cumprod', 'cumsum', 'nancumprod', 'nancumsum',
+ 'isfinite', 'isinf', 'isnan', 'isneginf', 'isposinf',
+ 'real', 'imag', 'angle', 'conj', 'real_if_close'
+ ]
+
+ binary_ops = [
+ 'minimum', 'maximum', 'fmin', 'fmax',
+ 'add', 'subtract', 'multiply', 'power',
+ 'divide', 'floor_divide', 'true_divide',
+ 'equal', 'not_equal', 'less_equal', 'greater_equal', 'less', 'greater',
+ 'mod', 'fmod', 'remainder',
+ 'hypot', 'arctan2',
+ 'logaddexp', 'logaddexp2',
+ 'copysign'
+ ]
+
+ array_unary_ops = ['__neg__', '__abs__']
+
+ array_binary_ops = [
+ '__eq__', '__ne__', '__le__', '__ge__', '__lt__', '__gt__',
+ '__add__', '__sub__', '__mul__', '__pow__',
+ '__floordiv__', '__div__', '__mod__',
+ '__radd__', '__rsub__', '__rmul__', '__rpow__',
+ '__rfloordiv__', '__rdiv__', '__rmod__'
+ ]
+
+ # real_skip_list = ['angle', 'real', 'imag', 'conj', 'real_if_close']
+ complex_skip_list = ['fabs', 'floor', 'ceil', 'trunc', 'fix',
+ 'degrees', 'radians', 'deg2rad', 'rad2deg',
+ 'signbit', 'cbrt', 'isneginf', 'isposinf',
+ 'remainder', 'mod', 'fmod', 'modf', 'hypot', 'arctan2',
+ 'logaddexp', 'logaddexp2', 'copysign', 'frexp',
+ '__mod__', '__rmod__']
+
+ splitting_ops = [ 'frexp', 'modf' ]
+
+ def ignore_infty(ref_out,backend_out,**kargs):
+ mask = np.isinf(ref_out)
+ mask |= np.isinf(backend_out)
+ return mask
+
+ def positive_int_rhs(variables):
+ assert 'b' in variables # b is rhs
+ rhs = variables['b']
+ dtype = rhs[0].dtype
+ if is_integer(dtype):
+ for i,v in enumerate(rhs):
+ rhs[i] = abs(v)
+
+ def clamp(_amin,_amax):
+ def _filter(variables):
+ for k,_vars in variables.iteritems():
+ for i,var in enumerate(_vars):
+ if is_complex(var):
+ if isinstance(var,np.ndarray):
+ np.clip(var.real, _amin,_amax, variables[k][i].real)
+ np.clip(var.imag, _amin,_amax, variables[k][i].imag)
+ else:
+ amin = _amin + 1j*_amin
+ amax = _amax + 1j*_amax
+ var.backend.clip_components(var,amin,amax,variables[k][i])
+ else:
+ if isinstance(var,np.ndarray):
+ np.clip(var.real,_amin,_amax,variables[k][i])
+ else:
+ var.backend.clip(var,_amin,_amax,variables[k][i])
+ return _filter
+
+
+ pow_constraints = [positive_int_rhs]
+ pow_constraints.append( clamp(+0,+3) )
+
+ ## Extra contraints on inputs
+ # should be a list of functions taking variables as inputsq
+ input_constraints = {
+ 'power': pow_constraints,
+ '__pow__': pow_constraints,
+ '__rpow__': pow_constraints,
+ 'cumprod': clamp(0.1,1.1),
+ 'nancumprod': clamp(0.1,1.1)
+ }
+
+ ## Extra contraints on outputs
+ # Generate a mask of values thats should not
+ # be compared to numpy solution in allclose check)
+ # all keys are operator names
+ # all values are function of dtype and backend,
+ output_constraints = {
+ 'cumprod': [ignore_infty],
+ 'nancumprod': [ignore_infty]
+ }
+
+ class TestContext(object):
+ def __init__(self, opname, input_constraints, variables):
+
+ self.opname = opname
+
+
+ # if there is a specific constrain we copy everything
+ dtypes = {}
+ if opname in input_constraints:
+ for vname,vargs in variables.iteritems():
+ for i,var in enumerate(vargs):
+ variables[vname][i] = variables[vname][i].copy()
+ filters = to_list(input_constraints[opname])
+ for f in filters:
+ f(variables)
+ self.dtypes = dtypes
+
+ for vname,vargs in variables.iteritems():
+ dtypes[vname] = variables[vname][0].dtype
+ for i,var in enumerate(vargs):
+ varname='{}{}'.format(vname,i)
+ setattr(self, varname, var)
+ setattr(self, vname, vargs)
+
+ def __enter__(self):
+ return self
+
+ def __exit__(self, exception, e, traceback):
+ if (e is not None):
+ msg='\nTESTING: Test failed in at {}::{}() with dtypes {}\n'
+ msg=msg.format(backend.__class__.__name__,self.opname,self.dtypes)
+ print msg
+ raise exception, e, traceback
+
+
+ def check_inputs(name, _in):
+ isclose = np.isclose(_in[0],_in[1].get(handle=True), equal_nan=True)
+ if not isclose.all():
+ print '{} inputs mismatch...'.format(name)
+ print '{} NUMPY INPUT:'.format(name.upper())
+ print _in[0][~isclose]
+ print '{} BACKEND INPUT:'.format(name.upper())
+ print _in[1].get()[~isclose]
+ raise RuntimeError('Inputs did not match... Fix your input filters.')
+
+ def check_close(lhs, rhs, r0, r1, opname):
+ if (r0 is None) and (r1 is None):
+ return
+ elif (r0 is None):
+ msg='numpy::{} returned None.'.format(opname)
+ raise TypeError(msg)
+ elif (r1 is None):
+ msg='{}::{} returned None.'.format(backend.__class__.__name__,opname)
+ raise TypeError(msg)
+ else:
+ if isinstance(r1, Array):
+ r1 = r1.get(handle=True)
+ if isinstance(backend,OpenClArrayBackend):
+ # FIXME OpenCl support for float16
+ if r0.dtype==np.float16:
+ r1 = r1.astype(np.float16)
+ if r0.dtype==np.bool:
+ r1 = r1.astype(np.bool)
+
+ l2 = np.sqrt(np.nansum((r0-r1)*np.conj(r0-r1)) / r0.size)
+ linf = np.nanmax(np.abs(r0-r1))
+ msg1='(l2={}, linf={}).'
+ msg1=msg1.format(l2, linf)
+
+ if (r0.dtype == r1.dtype):
+ mask=None
+ if opname in output_constraints:
+ mask_generators = to_list(output_constraints[opname])
+ mask = mask_generators[0](ref_out=r0,backend_out=r1)
+ for mask_gen in mask_generators[1:]:
+ mask |= mask_gen(ref_out=r0,backend_out=r1)
+
+ close = allclose(r0,r1,ignore_mask=mask)
+ tol = atol[0]
+ if not close:
+ close = allclose(r0,r1,relaxed_precision=True,ignore_mask=mask)
+ tol = 1e-2
+ if close:
+ msg='WARNING: test passed with relaxed precision for {}::{}.'
+ msg=msg.format(backend.__class__.__name__, opname)
+ print msg
+ if not close:
+ msg = '\n{}::{} returned dtypes did match (got {}) '
+ msg+= 'but failed to match numpy output,\n absolute tolerance was set to {}.'
+ msg=msg.format(backend.__class__.__name__,opname,r1.dtype,tol)
+ print msg
+ if isinstance(r0, np.ndarray) and isinstance(r1, np.ndarray):
+ failed=(~np.isclose(r0,r1,equal_nan=True,atol=atol[0]))
+ if (lhs is not None):
+ check_inputs('lhs',lhs)
+ print 'LHS_INPUT'
+ print lhs[0][failed]
+ if (rhs is not None):
+ check_inputs('rhs',rhs)
+ print 'RHS INPUT'
+ print rhs[0][failed]
+ print 'EXPECTED'
+ print r0[failed]
+ print 'GOT'
+ print r1[failed]
+ else:
+ print 'r0 => {}'.format(r0.__class__)
+ print 'r1 => {}'.format(r1.__class__)
+ msg0='Method {}::{} failed to match numpy output'
+ msg0=msg0.format(backend.__class__.__name__, opname)
+ msg=msg0+msg1
+ print
+ print msg
+ raise ValueError(msg)
+ else:
+ msg0='{}::{} matched numpy output '
+ msg0=msg0.format(backend.__class__.__name__, opname)
+ msg=msg0+msg1
+ print msg
+ else:
+ msg = '\n{}::{} returned dtypes didn\'t match (expected {} but got {}).'
+ msg = msg.format(backend.__class__.__name__, opname, r0.dtype, r1.dtype)
+ print msg
+
+ msg='{}::{} returned dtypes did not match, '\
+ 'got {} but numpy returned {}.'
+ msg=msg.format(backend.__class__.__name__, opname, r1.dtype, r0.dtype)
+ raise ValueError(msg)
+
+ def test_operators(a,b,A,B,skip=[]):
+ with warnings.catch_warnings():
+ warnings.simplefilter('ignore')
+
+ for opname in unary_ops:
+ if opname in skip:
+ continue
+ f0 = getattr(np, opname)
+ f1 = getattr(npb, opname)
+ with TestContext(opname, input_constraints,
+ variables={'a':[a,A]}) as ctx:
+ r0 = f0(ctx.a0)
+ r1 = f1(ctx.a1)
+ check_close(ctx.a,None,r0,r1,opname)
+
+ for opname in binary_ops:
+ if opname in skip:
+ continue
+ f0 = getattr(np, opname)
+ f1 = getattr(npb, opname)
+ with TestContext(opname, input_constraints,
+ variables={'a':[a,A],'b':[b,B]}) as ctx:
+ r0 = f0(ctx.a0,ctx.b0)
+ r1 = f1(ctx.a1,ctx.b1)
+ check_close(ctx.a,ctx.b,r0,r1,opname)
+
+ for opname in splitting_ops:
+ if opname in skip:
+ continue
+ with TestContext(opname, input_constraints,
+ variables={'a':[a,A],'b':[b,B]}) as ctx:
+ f0 = getattr(np, opname)
+ f1 = getattr(npb, opname)
+ r00, r01 = f0(ctx.a0)
+ r10, r11 = f1(ctx.a1)
+ check_close(ctx.a,None,r00,r10,opname)
+ check_close(ctx.a,None,r01,r11,opname)
+
+ for opname in array_unary_ops:
+ if opname in skip:
+ continue
+ with TestContext(opname, input_constraints,
+ variables={'a':[a,A]}) as ctx:
+ f0 = getattr(ctx.a0, opname)
+ f1 = getattr(ctx.a1, opname)
+ r0 = f0()
+ r1 = f1()
+ check_close(ctx.a,None,r0,r1,opname)
+
+ for opname in array_binary_ops:
+ if opname in skip:
+ continue
+ with TestContext(opname, input_constraints,
+ variables={'a':[a,A],'b':[b,B]}) as ctx:
+ if opname.find('__r')==0:
+ f0 = getattr(ctx.b0, opname)
+ f1 = getattr(ctx.b1, opname)
+ r0 = f0(ctx.a0)
+ r1 = f1(ctx.a1)
+ else:
+ f0 = getattr(ctx.a0, opname)
+ f1 = getattr(ctx.a1, opname)
+ r0 = f0(ctx.b0)
+ r1 = f1(ctx.b1)
+ check_close(ctx.a,ctx.b,r0,r1,opname)
+
+
+ def make_arrays(dtype):
+ ftype = match_float_type(dtype)
+ atol[0] = np.finfo(ftype).eps
+ print '::atol switched to {} epsilon: {}.'.format(ftype, atol)
+
+ a = (np.random.rand(8192)-0.5)*100
+ b = (np.random.rand(8192)-0.5)*100
+ if is_unsigned(dtype):
+ a = abs(a)
+ b = abs(b)
+ a = a.astype(dtype) # <= negative number to unsigned dtype conversion wraps
+ b = b.astype(dtype)
+ if is_complex(dtype):
+ a+= (np.random.rand(8192)-0.5)*100j
+ b+= (np.random.rand(8192)-0.5)*100j
+
+ A, B = npb.asarray(a), npb.asarray(b)
+ assert allclose( a, A )
+ assert allclose( b, B )
+ assert npb.allclose( npb.asarray(a), A, equal_nan=True )
+ assert npb.allclose( npb.asarray(b), B, equal_nan=True )
+
+ return a,b,A,B
+
+ #FIXME numpy quad float support (gcc __float128)
+ if __ENABLE_LONG_TESTS__:
+ signed_types = (np.int8, np.int16, np.int32, np.int64,)
+ unsigned_types = (np.uint8, np.uint16, np.uint32, np.uint64,)
+ float_types = (np.float16,np.float32,np.float64, np.longdouble)
+ complex_types = (np.complex64, np.complex128, np.clongdouble)
+ else:
+ signed_types = (np.int32,)
+ unsigned_types = (np.uint32,)
+ float_types = (np.float32,)
+ complex_types = (np.complex64,)
+
+ for dtype in signed_types:
+ print '\n== SIGNED INTEGER OPS {} =='.format(dtype)
+ a,b,A,B = make_arrays(dtype)
+ test_operators(a,b,A,B)
+
+ for dtype in unsigned_types:
+ print '\n== UNSIGNED INTEGER OPS {} =='.format(dtype)
+ a,b,A,B = make_arrays(dtype)
+ test_operators(a,b,A,B)
+
+ # FIXME OpenCl backend half float, long double support
+ for dtype in float_types:
+ print '\n== FLOAT OPS {} =='.format(dtype)
+ if isinstance(backend,OpenClArrayBackend) and (dtype in [np.float16,np.longdouble]):
+ print ' -- NO SUPPORT PROVIDED BY BACKEND --'
+ continue
+
+ a,b,A,B = make_arrays(dtype)
+ test_operators(a,b,A,B)
+
+ print '\n== POLLUTED FLOAT OPS {} =='.format(dtype)
+ pollute(a)
+ pollute(b)
+
+ A, B = npb.asarray(a), npb.asarray(b)
+ test_operators(a,b,A,B)
+
+ #FIXME OpenCL complex functions: arcsin, arccos, floordix, pow, ...
+ for dtype in complex_types:
+ print '\n== COMPLEX OPS {} =='.format(dtype)
+ if isinstance(backend,OpenClArrayBackend):
+ if dtype in [np.clongdouble]:
+ print ' -- NO SUPPORT PROVIDED BY BACKEND --'
+ continue
+
+ skip_list = [x for x in complex_skip_list]
+ skip_list += ['arcsin', 'arccos', 'arctan',
+ 'arcsinh', 'arccosh', 'arctanh',
+ 'exp2', 'expm1',
+ 'log2', 'log10', 'log1p',
+ 'floor_divide', '__floordiv__', '__rfloordiv__']
+ else:
+ skip_list = complex_skip_list
+
+ a,b,A,B = make_arrays(dtype)
+ test_operators(a,b,A,B, skip=skip_list)
+
+ print '\n== POLLUTED COMPLEX OPS {} =='.format(dtype)
+ pollute(a)
+ pollute(b)
+
+ if isinstance(backend,OpenClArrayBackend):
+ skip_list+=['power', '__rpow__', '__pow__']
+
+ A, B = npb.asarray(a), npb.asarray(b)
+ test_operators(a,b,A,B, skip=skip_list)
+
+ def _test_backend_versus_numpy(self, backend):
+ self._test_backend_versus_numpy_operations(backend)
+
+
+ def _test_backend(self, backend):
+ with printoptions(linewidth=240, edgeitems=4, threshold=20):
+ self._test_array_creation_routines(backend)
+ self._test_binary_operations(backend)
+ self._test_arithmetic_operations(backend)
+ self._test_backend_versus_numpy(backend)
+ #self._test_array_manipulation_routines(backend)
+
+ def test_host_array_backend_allocator(self):
+ allocator = HostAllocator()
+ backend = HostArrayBackend(allocator=allocator)
+ self._test_backend(backend)
+
+ def test_host_array_backend_mempool(self):
+ allocator = HostAllocator()
+ pool = allocator.memory_pool(name='host')
+ backend = HostArrayBackend(allocator=pool)
+
+ self._test_backend(backend)
+
+ backend.allocator.print_allocation_report()
+ assert backend.allocator.active_blocks == 0
+ backend.allocator.stop_holding()
+ assert backend.allocator.held_blocks == 0
+ backend.allocator.print_allocation_report()
+
+ @opencl_failed
+ def test_opencl_array_backend_allocator(self):
+ from hysop.backend.device.opencl.opencl_allocator import OpenClImmediateAllocator
+ for cl_env in iter_clenv():
+ allocator = OpenClImmediateAllocator(cl_env.default_queue)
+ backend = OpenClArrayBackend(cl_env=cl_env, allocator=allocator)
+ self._test_backend(backend)
+
+ @opencl_failed
+ def test_opencl_array_backend_pool(self):
+ from hysop.backend.device.opencl.opencl_allocator import OpenClImmediateAllocator
+ for cl_env in iter_clenv():
+ allocator = OpenClImmediateAllocator(cl_env.default_queue).memory_pool(name=cl_env.device.name)
+ backend = OpenClArrayBackend(cl_env=cl_env, allocator=allocator)
+
+ self._test_backend(backend)
+
+ backend.allocator.print_allocation_report()
+ assert backend.allocator.active_blocks == 0
+ backend.allocator.stop_holding()
+ assert backend.allocator.held_blocks == 0
+ backend.allocator.print_allocation_report()
+
+if __name__ == '__main__':
+ test = TestArray()
+ test.test_host_array_backend_allocator()
+ test.test_host_array_backend_mempool()
+ if __HAS_OPENCL_BACKEND__:
+ test.test_opencl_array_backend_allocator()
+ test.test_opencl_array_backend_pool()
diff --git a/hysop/core/graph/__init__.py b/hysop/core/graph/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/core/graph/all.py b/hysop/core/graph/all.py
new file mode 100644
index 0000000000000000000000000000000000000000..63e4fbc40ba6b81f54fd7189b34d4842fc05148f
--- /dev/null
+++ b/hysop/core/graph/all.py
@@ -0,0 +1,4 @@
+from hysop.core.graph.computational_graph import ComputationalGraph
+from hysop.core.graph.computational_node import ComputationalGraphNode
+from hysop.core.graph.computational_operator import ComputationalGraphOperator
+from hysop.core.graph.node_generator import ComputationalGraphNodeGenerator
diff --git a/hysop/core/graph/allocator.py b/hysop/core/graph/allocator.py
new file mode 100644
index 0000000000000000000000000000000000000000..bf80ce7962c76d8b2fd864e71ecd814ee22c98df
--- /dev/null
+++ b/hysop/core/graph/allocator.py
@@ -0,0 +1,118 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.deps import np
+from hysop.tools.types import check_instance
+
+from hysop.core.arrays.all import ArrayBackend, HostArrayBackend, OpenClArrayBackend
+
+
+class MemoryRequestsAllocator(object):
+ __metaclass__ = ABCMeta
+
+ @classmethod
+ @not_implemented
+ def handle_requests(cls, requests):
+ pass
+
+class StandardArrayAllocator(MemoryAllocator):
+
+ def __init__(self, array_backend):
+ check_instance(self, ArrayBackend)
+ self.array_backend = array_backend
+
+ def allocate(self, nbytes):
+ npb = self.array_backend
+ dtype = np.dtype(np.uint8)
+ assert dtype.itemsize == 1
+ return npb.empty(shape=(nbytes,), dtype=dtype)
+
+ def handle_requests(self, requests):
+ from hysop.core.graph.mem_request import MultipleOperatorMemoryRequests
+ if not isinstance(requests, MultipleOperatorMemoryRequests):
+ msg = 'requests is not an instance of MultipleOperatorMemoryRequests (got a {}).'
+ raise ValueError(msg.format(requests.__class__))
+
+ cls = self.__class__
+
+ total_bytes = requests.min_bytes_to_allocate(self)
+ if total_bytes == 0:
+ return
+ array = self.allocate(total_bytes)
+
+ op_requests = requests._all_requests_per_allocator[self]
+ views = requests._allocated_buffers
+ self.build_array_views(array, op_requests, views)
+
+ def build_array_views(self, array, op_requests, views):
+ from hysop.core.graph.mem_request import OperatorMemoryRequests
+ check_instance(op_requests, dict)
+ ptr = array.ctypes.data
+ for (op,requests) in op_requests.iteritems():
+ check_instance(requests, dict, values=OperatorMemoryRequests)
+ start_idx = 0
+ for (req_id, req) in requests.iteritems():
+ align_offset = (-ptr % req.alignment)
+ start_idx += align_offset
+ end_idx = start_idx + req.data_bytes()
+
+ view = data[start_idx:end_idx].view(req.dtype).reshape(req.shape)
+ if op not in views:
+ views[op] = {}
+ views[op][req_id] = view
+
+ start_idx = end_idx
+ ptr += align_offset + req.data_bytes()
+ assert end_idx <= total_bytes
+
+NumpyMemoryRequestAllocator = StandardArrayAllocator(array_backend=HostArray)
+
+def OpenClMemoryRequestAllocator(cl_env):
+ return StandardArrayAllocator(array_backend=cl_env.array_backend())
+
+if __name__ == '__main__':
+ m0 = NumpyMemRequest(count=1, dtype=np.int32)
+ m1 = NumpyMemRequest(shape=(2,), dtype=np.int32)
+ m2 = NumpyMemRequest(shape=(2,2), dtype=np.int32)
+ m3 = NumpyMemRequest(shape=(2,2,2,), dtype=np.int32, alignment=64)
+
+ m4 = NumpyMemRequest(count=3, dtype=np.int32)
+ m5 = NumpyMemRequest(shape=(4,), dtype=np.int32)
+ m6 = NumpyMemRequest(shape=(8,), dtype=np.int32)
+
+ opm0 = OperatorMemoryRequests('opA')
+ opm0.add_mem_request('reqA0', m0)
+ opm0.add_mem_request('reqA1', m1)
+ opm0.add_mem_request('reqA2', m2)
+ opm0.add_mem_request('reqA3', m3)
+
+ opm1 = OperatorMemoryRequests('opB')
+ opm1.add_mem_request('reqB0', m4)
+ opm1.add_mem_request('reqB1', m5)
+ opm1.add_mem_request('reqB2', m6)
+
+ all_reqs = MultipleOperatorMemoryRequests()
+ all_reqs.add_mem_requests(opm0)
+ all_reqs.add_mem_requests(opm1)
+
+ all_reqs.allocate()
+
+ m0.data[...] = 1
+ m1.data[...] = 2
+ m2.data[...] = 3
+ m3.data[...] = 4
+
+ print m0.data
+ print m1.data
+ print m2.data
+ print m3.data
+ print
+ print m4.data
+ print m5.data
+ print m6.data
+ print
+ print all_reqs.buffers[NumpyMemoryAllocator][0].dtype
+ print all_reqs.buffers[NumpyMemoryAllocator][0].shape
+ print all_reqs.buffers[NumpyMemoryAllocator][0].view(dtype=np.int32)
+
+ assert m3.data.ctypes.data % 64 == 0
+
diff --git a/hysop/core/graph/computational_graph.py b/hysop/core/graph/computational_graph.py
new file mode 100644
index 0000000000000000000000000000000000000000..271a7b68927cebe3593c46eb7938c3b519ca39d1
--- /dev/null
+++ b/hysop/core/graph/computational_graph.py
@@ -0,0 +1,616 @@
+import numpy as np
+from hysop import __DEBUG__, __VERBOSE__, vprint
+from hysop.tools.decorators import debug
+from hysop.tools.types import to_list, to_set
+from hysop.operator.redistribute import Redistribute
+from hysop.core.graph.graph import not_implemented, initialized, discretized, \
+ ready, graph_built, not_initialized
+from hysop.core.graph.graph import Graph, ComputationalGraphNodeData, gt, graph_draw
+from hysop.core.graph.computational_node import ComputationalGraphNode
+from hysop.core.graph.computational_operator import ComputationalGraphOperator
+from hysop.core.graph.node_generator import ComputationalGraphNodeGenerator
+from hysop.core.memory.memory_request import MultipleOperatorMemoryRequests
+from hysop.fields.field_requirements import MultiFieldRequirements
+
+from abc import ABCMeta, abstractmethod
+
+class ComputationalGraph(ComputationalGraphNode):
+ """
+ Interface of an abstract graph of continuous operators (ie. a computational graph).
+ """
+
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, **kargs):
+ """
+ Parameters
+ ----------
+ kwds: arguments for base classes.
+
+ Notes
+ -----
+ The following base class variables cannot be specified during graph construction:
+ variables, input_variables, output_variables
+ Order of operation is: add_node, initialize, discretize,
+ get_work_properties, setup, apply, finalize.
+ Node can also be added during pre_init
+ Graph building is done at the end of the initialization step, after all internal
+ nodes have been initialized.
+ """
+
+ if ('input_vars' in kargs.keys()) or ('output_vars' in kargs.keys()):
+ msg='input_vars or output_vars parameters should not be used in {}, they are \
+ deduced during graph construction (building step).'.format(cls)
+ raise ValueError(msg)
+
+ super(ComputationalGraph,self).__init__(input_vars=None, output_vars=None,
+ **kargs)
+
+ self.nodes = []
+ self.graph = None
+ self.graph_built = False
+
+ def field_requirements_report(self, requirements):
+
+ inputs = {}
+ sinputs = ''
+ for field, mreqs in requirements.input_field_requirements.iteritems():
+ for td, reqs in mreqs.requirements.iteritems():
+ for req in reqs:
+ if __DEBUG__ or (__VERBOSE__ and not req.is_default()):
+ inputs.setdefault(td, {}).setdefault(field, []).append(req)
+ for td, td_reqs in inputs.iteritems():
+ sinputs += '\n {}'.format(td)
+ for field, reqs in td_reqs.iteritems():
+ for req in reqs:
+ sinputs += '\n *{}'.format(req)
+
+ outputs = {}
+ soutputs = ''
+ for field, mreqs in requirements.output_field_requirements.iteritems():
+ for td, reqs in mreqs.requirements.iteritems():
+ for req in reqs:
+ if __DEBUG__ or (__VERBOSE__ and not req.is_default()):
+ outputs.setdefault(td, {}).setdefault(field, []).append(req)
+ for td, td_reqs in outputs.iteritems():
+ soutputs += '\n {}'.format(td)
+ for field, reqs in td_reqs.iteritems():
+ for req in reqs:
+ soutputs += '\n *{}'.format(req)
+
+ ss = '== ComputationalGraph {} field requirements report =='.format(self.name)
+ if sinputs:
+ ss+= '\n>INPUTS:{}'.format(sinputs)
+ else:
+ ss+= '\n>INPUTS: None'
+ if soutputs:
+ ss+= '\n>OUTPUTS:{}'.format(soutputs)
+ else:
+ ss+= '\n>OUTPUTS: None'
+ ss += '\n'+len('== ComputationalGraph {} field requirements report =='.format(self.name))*'='+'\n'
+ return ss
+
+ def topology_report(self):
+
+ ss = '== ComputationalGraph {} topology report =='.format(self.name)
+ for (backend,topologies) in self.get_topologies().iteritems():
+ ss += '\n {}:'.format(backend.short_description())
+ ss += '\n *'+'\n *'.join( [t.short_description()
+ for t in sorted(topologies,key=lambda x: x.get_id())] )
+ ss += '\n{}\n'.format(len('== ComputationalGraph {} topology report =='.format(self.name))*'=')
+ return ss
+
+
+ @graph_built
+ def get_topologies(self):
+ topologies = {}
+ for node in self.nodes:
+ node_topologies = node.get_topologies()
+ for (backend, topos) in node_topologies.iteritems():
+ topos = to_set(topos)
+ if backend not in topologies:
+ topologies[backend] = set()
+ topologies[backend].update(topos)
+ return topologies
+
+ @debug
+ @not_initialized
+ def push_nodes(self, *args):
+ for node in args:
+ if isinstance(node, ComputationalGraphNode):
+ self.nodes.append(node)
+ elif isinstance(node, ComputationalGraphNodeGenerator):
+ node.generate()
+ for gnode in node.nodes:
+ self.nodes.append(gnode)
+ else:
+ msg = 'Given node is not an instance of ComputationalGraphNode (got a {}).'
+ raise ValueError(msg.format(node.__class__))
+
+ def available_methods(self):
+ avail_methods = {}
+ for node in self.nodes:
+ for k,v in node.available_methods().iteritems():
+ if k in avail_methods:
+ avail_methods[k].add(v)
+ else:
+ avail_methods[k] = to_set(v)
+ return avail_methods
+
+ @debug
+ def initialize(self,
+ is_root=True,
+ topgraph_method=None,
+ outputs_are_inputs=False,
+ **kwds):
+ if self.initialized:
+ return
+
+ self.is_root = is_root
+
+ self.pre_initialize(**kwds)
+ assert len(self.nodes) > 0, msg
+
+ method = self._setup_method(topgraph_method)
+ self.handle_method(method)
+
+ for node in self.nodes:
+ if __DEBUG__:
+ print
+ print '{} INITIALIZE'.format(node.name)
+ node.initialize(is_root=False,
+ outputs_are_inputs=False,
+ topgraph_method=method,
+ **kwds)
+ if __DEBUG__:
+ print '=========================='
+ print
+
+ if is_root:
+ field_requirements = self.get_field_requirements()
+ field_requirements.build_topologies()
+ self.handle_topologies()
+ self._build_graph(outputs_are_inputs=outputs_are_inputs, current_level=0)
+
+ self.initialized=True
+
+ self.post_initialize(**kwds)
+
+ if is_root:
+ self.check()
+
+ @debug
+ def get_field_requirements(self):
+ requirements = super(ComputationalGraph, self).get_field_requirements()
+ for node in self.nodes:
+ node_requirements = node.get_field_requirements()
+ requirements.update(node_requirements)
+ if (self.is_root and __VERBOSE__) or __DEBUG__:
+ print self.field_requirements_report(requirements)
+ return requirements
+
+ @debug
+ def handle_topologies(self):
+ super(ComputationalGraph, self).handle_topologies()
+ for node in self.nodes:
+ node.handle_topologies()
+
+
+ @staticmethod
+ def _op_info(op, jmp=False):
+ ifields = op.input_vars
+ ofields = op.output_vars
+ ss = 'Operator {} => \n inputs:{}\n outputs:{}\n {}'.format(op.name,
+ [(f.name,topo.get_id()) for (f,topo) in ifields.iteritems()],
+ [(f.name,topo.get_id()) for (f,topo) in ofields.iteritems()],
+ op.__class__)
+ if jmp:
+ return ss
+ else:
+ return ss.replace('\n',' ')
+
+ @debug
+ def _build_graph(self, current_level, outputs_are_inputs=False, **kwds):
+ if self.graph_built:
+ return
+
+ graph = Graph(directed=True)
+
+ vertex_properties = {}
+ vertex_properties['op_names'] = graph.new_vertex_property('string')
+ vertex_properties['op_info'] = graph.new_vertex_property('string')
+ vertex_properties['op_data'] = graph.new_vertex_property('python::object')
+ vertex_properties['operators'] = graph.new_vertex_property('python::object')
+
+ edge_properties = {}
+ edge_properties['var_names'] = graph.new_edge_property('string')
+ edge_properties['variables'] = graph.new_edge_property('python::object')
+
+ # get all inputs and outputs variables
+ continuous_inputs = set()
+ continuous_outputs = set()
+ for node in self.nodes:
+ if isinstance(node, ComputationalGraphNode):
+ pass
+ else:
+ msg = 'Uknown node type {}.'.format(node.__class__)
+ raise TypeError(msg)
+ cin = set(node.input_vars.keys())
+ cout = set(node.output_vars.keys())
+ continuous_inputs = continuous_inputs.union(cin)
+ continuous_outputs = continuous_outputs.union(cout)
+
+ continuous_variables = continuous_inputs.union(continuous_outputs)
+
+ input_vars = {}
+ output_vars = {}
+
+ # dictionnary topology -> node that wrote this topology
+ field_write_nodes = {}
+ # dictionnary topology -> list of nodes that reads field:topo
+ field_read_nodes = {}
+
+ for node_id,node in enumerate(self.nodes):
+ node_ops = []
+ node_vertices = []
+
+ from_subgraph = False
+ extra_node_props = []
+
+ if isinstance(node, ComputationalGraph):
+ node._build_graph(current_level=current_level+1, **kwds)
+ node_ordering = node.sorted_nodes
+ subgraph = node.reduced_graph
+ subgraph_ops = subgraph.vertex_properties['operators']
+ node_properties = None
+ for nid in node_ordering:
+ _node = subgraph.vertex(nid)
+ op = subgraph_ops[_node]
+ node_vertices.append(_node)
+ node_ops.append(op)
+ for prop_name,vp in subgraph.vertex_properties.iteritems():
+ if prop_name not in vertex_properties:
+ vertex_properties[prop_name] = \
+ graph.new_vertex_property(vp.value_type())
+ extra_node_props.append(prop_name)
+ from_subgraph = True
+ elif isinstance(node, ComputationalGraphOperator):
+ node_ops.append(node)
+ node_vertices.append(None)
+ else:
+ msg = 'Unknown node type {}.'
+ raise NotImplementedError(msg.format(node.__class__.__name__))
+
+ for (oldvertex, op) in zip(node_vertices,node_ops):
+ opname = op.name
+ ifields = op.input_vars
+ ofields = op.output_vars
+ if __DEBUG__:
+ print self._op_info(op)
+
+ opnode = graph.add_vertex()
+ vertex_properties['op_names'][opnode] = opname
+ vertex_properties['operators'][opnode] = op
+
+ if from_subgraph:
+ level = node.level + 1
+ for enp in extra_node_props:
+ vertex_properties[enp][opnode] = subgraph.vp[enp][oldvertex]
+ else:
+ level = current_level
+ vertex_properties['op_data'][opnode] = ComputationalGraphNodeData(level,
+ node_id)
+ vertex_properties['op_info'][opnode] = self._op_info(op)
+
+ for (ifield,itopo) in ifields.iteritems():
+ uptodate_topologies = field_write_nodes.setdefault(ifield, {})
+ if not uptodate_topologies:
+ input_vars[ifield] = itopo
+
+ if not uptodate_topologies:
+ last_write_node = None
+ elif itopo in uptodate_topologies:
+ last_write_node = uptodate_topologies[itopo]
+ else:
+ redistribute_op = Redistribute(
+ variables=ifield,
+ source_topos=uptodate_topologies.keys(),
+ target_topo=itopo)
+ redistribute_op.generate()
+ assert len(redistribute_op.nodes)==1
+ redistribute_op = redistribute_op.nodes[0]
+ redistribute_op.name = 'Redis_{}'.format(ifield.name)
+ redistribute_op.initialize()
+ src_topo = redistribute_op.source_topo
+ src_op = uptodate_topologies[src_topo]
+
+ redis = graph.add_vertex()
+ edge = graph.add_edge(src_op,redis)
+ vertex_properties['operators'][redis] = redistribute_op
+ vertex_properties['op_names'][redis] = redistribute_op.name
+ vertex_properties['op_info'][redis] = self._op_info(redistribute_op)
+ edge_properties['var_names'][edge] = \
+ '{}_t{}'.format(ifield.name, src_topo.get_id())
+ if src_topo in field_read_nodes[ifield]:
+ field_read_nodes[ifield][src_topo].append(redis)
+ else:
+ field_read_nodes[ifield][src_topo] = [redis]
+ field_write_nodes[ifield][itopo] = redis
+ last_write_node = redis
+
+ if (last_write_node is not None):
+ edge = graph.add_edge(last_write_node,opnode)
+ edge_properties['var_names'][edge] = \
+ '{}_t{}'.format(ifield.name,itopo.get_id())
+
+ field_read_nodes.setdefault(ifield, {})\
+ .setdefault(itopo, [])\
+ .append(opnode)
+
+ for (ofield,otopo) in ofields.iteritems():
+ uptodate_topologies = field_write_nodes[ofield]
+ if otopo in uptodate_topologies:
+ last_write_node = uptodate_topologies[otopo]
+ edge = graph.add_edge(last_write_node, opnode)
+ edge_properties['var_names'][edge] = \
+ '{}_t{}'.format(ofield.name,otopo.get_id())
+
+ for (ro_topo,ro_nodes) in field_read_nodes[ofield].iteritems():
+ for ro_node in ro_nodes:
+ if ro_node != opnode:
+ edge = graph.add_edge(ro_node, opnode)
+ edge_properties['var_names'][edge] = \
+ '{}_t{}'.format(ofield.name,otopo.get_id())
+ field_read_nodes[ofield].clear()
+ field_write_nodes[ofield].clear()
+
+ field_write_nodes[ofield][otopo] = opnode
+ output_vars[ofield] = otopo
+
+ # if requested redistribute outputs to inputs
+ if current_level==0 and outputs_are_inputs:
+ redistribute_variables = set(input_vars.keys()).intersection(output_vars.keys())
+ redistribute_variables = set([var for var in redistribute_variables if
+ input_vars[var] not in field_write_nodes[var]])
+ for var in redistribute_variables:
+ src_topos = field_write_nodes[var].keys()
+ dst_topo = input_vars[var]
+ redistribute_op = Redistribute(
+ variables=var,
+ source_topos=src_topos,
+ target_topo=dst_topo)
+ redistribute_op.generate()
+ assert len(redistribute_op.nodes)==1
+ redistribute_op = redistribute_op.nodes[0]
+ redistribute_op.name = 'Redis_{}'.format(var.name)
+ redistribute_op.initialize()
+ src_topo = redistribute_op.source_topo
+ src_op = field_write_nodes[var][src_topo]
+
+ redis = graph.add_vertex()
+ edge = graph.add_edge(src_op,redis)
+ vertex_properties['operators'][redis] = redistribute_op
+ vertex_properties['op_names'][redis] = redistribute_op.name
+ vertex_properties['op_info'][redis] = self._op_info(redistribute_op)
+ edge_properties['var_names'][edge] = \
+ '{}_t{}'.format(var.name, src_topo.get_id())
+
+
+ if not gt.topology.is_DAG(graph):
+ msg='\nGenerated operator graph is not acyclic.'
+ print msg
+
+ #display for debug purposes
+ gt.stats.remove_parallel_edges(graph)
+ for prop_name,edge_property in edge_properties.iteritems():
+ graph.edge_properties[prop_name] = edge_property
+ for prop_name,vertex_property in vertex_properties.iteritems():
+ graph.vertex_properties[prop_name] = vertex_property
+ self.graph_built=True
+ self.reduced_graph = graph
+ self.display()
+
+ # and finally raise error
+ raise RuntimeError(msg)
+
+ # Transitive reduction
+ transitive_reduction = gt.stats.label_parallel_edges(graph, mark_only=True,
+ eprop = graph.new_edge_property('bool',val=False))
+ for vertex in graph.vertices():
+ for neighbor_vertex in vertex.out_neighbours():
+ accessible_vertices = \
+ [v for v in gt.search.dfs_iterator(graph, neighbor_vertex)]
+ for edge in accessible_vertices:
+ edge = graph.edge(vertex, edge.target())
+ if edge is not None:
+ transitive_reduction[edge] = True
+ transitive_reduction.a = [ not val for val in transitive_reduction.get_array()]
+ reduced_graph = gt.GraphView(graph, efilt = transitive_reduction)
+
+ # Topological sort
+ sorted_nodes = gt.topology.topological_sort(reduced_graph)
+ vertex_properties['op_ordering'] = reduced_graph.new_vertex_property('int')
+ for i,node_id in enumerate(sorted_nodes):
+ vertex = reduced_graph.vertex(node_id)
+ vertex_properties['op_ordering'][vertex] = i
+ vertex_properties['op_names'][vertex] += ' ('+str(i)+')'
+
+ # Command queues (each color represents a command queue)
+ color = 0
+ queues = {}
+ vertex_properties['command_queues'] = graph.new_vertex_property('int',val=-1)
+ for vertex_id in sorted_nodes:
+ vertex = reduced_graph.vertex(vertex_id)
+ if (vertex_properties['command_queues'][vertex] >= 0):
+ continue
+
+ vertices = [vertex]
+ uncolored_childs = [ v for v in vertex.out_neighbours() \
+ if (vertex_properties['command_queues'][v] == -1) ]
+ while len(uncolored_childs)>0:
+ vid = np.argmin( [vertex_properties['op_ordering'][v]
+ for v in uncolored_childs] )
+ vertex = uncolored_childs[vid]
+ vertices.append(vertex)
+ uncolored_childs = [ v for v in vertex.out_neighbours() \
+ if (vertex_properties['command_queues'][v] == -1) ]
+
+ idx_range = (vertex_properties['op_ordering'][vertices[0]],
+ vertex_properties['op_ordering'][vertices[-1]])
+
+ if queues:
+ color = queues.keys()[-1]+1
+
+ for k in queues.keys()[::-1]:
+ paths = queues[k]
+ if (paths[-1][1] < idx_range[0]):
+ src = reduced_graph.vertex(sorted_nodes[paths[-1][1]])
+ dst = reduced_graph.vertex(sorted_nodes[idx_range[0]])
+ all_paths = gt.topology.all_paths(reduced_graph,src,dst)
+ all_paths = [p for p in all_paths]
+ if len(all_paths)>0:
+ color = k
+ break
+
+ if color not in queues:
+ queues[color] = []
+ queues[color].append(idx_range)
+
+ for vertex in vertices:
+ vertex_properties['command_queues'][vertex] = color
+
+ # bind all properties to reduced graph
+ for prop_name,edge_property in edge_properties.iteritems():
+ reduced_graph.edge_properties[prop_name] = edge_property
+ for prop_name,vertex_property in vertex_properties.iteritems():
+ reduced_graph.vertex_properties[prop_name] = vertex_property
+
+ # keep variables
+ super(ComputationalGraph,self).__init__(name=self.name,
+ input_vars=input_vars, output_vars=output_vars)
+
+ self.graph = graph
+ self.reduced_graph = reduced_graph
+ self.sorted_nodes = sorted_nodes
+
+ self.level = current_level
+
+ self.initialized = True
+ self.graph_built = True
+
+ self.input_vars = input_vars
+ self.output_vars = output_vars
+
+ self._init_base(**self._kwds)
+
+ if (self.is_root and __VERBOSE__) or __DEBUG__:
+ print self.topology_report()
+
+ @debug
+ @graph_built
+ def display(self, vertex_font_size=10, edge_font_size=16):
+ """
+ Display the reduced computational graph.
+ """
+ graph = self.reduced_graph
+ edge_text = graph.edge_properties['var_names']
+ vertex_text = graph.vertex_properties['op_names']
+ vertex_info = graph.vertex_properties['op_info']
+ command_queues = graph.vertex_properties['command_queues']
+
+ graph_draw(graph,
+ vertex_text = vertex_text,
+ edge_text = edge_text,
+ vertex_font_size = vertex_font_size,
+ edge_font_size = edge_font_size,
+ vertex_fill_color=command_queues,
+ display_props=vertex_info,
+ display_props_size=14)
+
+ @debug
+ @graph_built
+ def discretize(self):
+ reduced_graph = self.reduced_graph
+ operators = reduced_graph.vertex_properties['operators']
+ for vid in self.sorted_nodes:
+ vertex = reduced_graph.vertex(vid)
+ op = operators[vertex]
+ if not op.discretized:
+ op.discretize()
+ self.discretized = True
+
+ @debug
+ @discretized
+ def get_work_properties(self):
+ requests = MultipleOperatorMemoryRequests()
+
+ reduced_graph = self.reduced_graph
+ operators = reduced_graph.vertex_properties['operators']
+ for vid in self.sorted_nodes:
+ vertex = reduced_graph.vertex(vid)
+ op = operators[vertex]
+ if op not in requests.operators():
+ wp = op.get_work_properties()
+ requests += op.get_work_properties()
+ if __DEBUG__ or (__VERBOSE__ and self.level==0):
+ srequests = str(requests)
+ print '\n== ComputationalGraph {} work properties report =='.format(self.name)
+ print srequests if (srequests != '') else ' *no extra work requested*'
+ print '='*len('== ComputationalGraph {} work properties report =='.format(self.name))
+ print
+ return requests
+
+ @debug
+ @discretized
+ def setup(self, work=None):
+ if (work is None):
+ work = self.get_work_properties()
+ work.allocate()
+ reduced_graph = self.reduced_graph
+ operators = reduced_graph.vertex_properties['operators']
+ for vid in self.sorted_nodes:
+ vertex = reduced_graph.vertex(vid)
+ op = operators[vertex]
+ if not op.ready:
+ op.setup(work=work)
+ self.ready = True
+
+ @debug
+ @ready
+ def apply(self, **kargs):
+ reduced_graph = self.reduced_graph
+ operators = reduced_graph.vertex_properties['operators']
+ op_datas = reduced_graph.vertex_properties['op_data']
+ for vid in self.sorted_nodes:
+ vertex = reduced_graph.vertex(vid)
+ op = operators[vertex]
+ op_kargs = kargs.copy()
+ if vertex in op_datas:
+ op_data = op_datas[vertex]
+ for kwds in op_data.apply_kargs:
+ op_kargs.update(kwds)
+ op.apply(**op_kargs)
+ self.discretized = True
+
+ @debug
+ @ready
+ def finalize(self):
+ reduced_graph = self.reduced_graph
+ operators = reduced_graph.vertex_properties['operators']
+ for vid in self.sorted_nodes:
+ vertex = reduced_graph.vertex(vid)
+ op = operators[vertex]
+ if op.ready:
+ op.finalize()
+ self.ready = False
+
+ @classmethod
+ def supports_multiple_field_topologies(cls):
+ return True
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return True
+ @classmethod
+ def supports_mpi(cls):
+ return True
diff --git a/hysop/core/graph/computational_node.py b/hysop/core/graph/computational_node.py
new file mode 100644
index 0000000000000000000000000000000000000000..a933f8213a23a413260ed46a42038e6578b75d02
--- /dev/null
+++ b/hysop/core/graph/computational_node.py
@@ -0,0 +1,543 @@
+"""
+@file graph_operator.py
+Base for directionally splitted advection solvers (pure-python and GPU version).
+"""
+
+from abc import ABCMeta, abstractmethod
+
+from hysop.deps import copy
+from hysop.tools.types import InstanceOf, to_set, check_instance
+from hysop.fields.continuous import Field
+from hysop.core.graph.graph import not_implemented, wraps,\
+ not_initialized, initialized, discretized, ready
+from hysop.core.graph.continuous import OperatorBase
+from hysop.core.mpi.topology import Topology
+from hysop.tools.decorators import debug
+
+def base_initialized(f):
+ assert callable(f)
+ @wraps(f)
+ def _check(*args,**kargs):
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if not self._base_initialized:
+ reason='this self._init_base() has not been called yet.'
+ raise RuntimeError(msg.format(reason))
+ return f(*args,**kargs)
+ return _check
+
+def topology_handled(f):
+ assert callable(f)
+ @wraps(f)
+ def _check(*args,**kargs):
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if not self.topology_handled:
+ reason='this self.handle_topologies() has not been called yet.'
+ raise RuntimeError(msg.format(reason))
+ return f(*args,**kargs)
+ return _check
+
+class ComputationalGraphNode(OperatorBase):
+ """
+ Interface of an abstract computational graph node.
+ """
+
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, input_vars, output_vars, name=None, method=None, **kwds):
+ """
+ Initialize a ComputationalGraphNode.
+
+ Parameters
+ ----------
+ input_vars: dict
+ input variables as a dictionnary (see Notes).
+ output_vars: dict
+ output variables as a dictionnary (see Notes).
+ name: str
+ name of this node (string), optional, defaults to top class name.
+ method: dict
+ user method specification for this graph node, optional, defaults to None.
+ kwds:
+ arguments for base classes (mpi_params and io_params).
+
+ Attributes
+ ----------
+ name: str
+ name of this node (used for printing and display purpose).
+ input_vars: dict
+ input variables as a dictionnary (see Notes).
+ output_vars: dict
+ output variables as a dictionnary (see Notes).
+ base_method: dict
+ base method specification for this graph node.
+ initialized: bool
+ flag set after initialize() has been called.
+ discretized: bool
+ flag set after discretize() has been called.
+ ready: bool
+ flag set after setup() has been called.
+
+ method : dict(MethodKey, MethodValue)
+ method, set after initialize() has been called.
+ input_field_requirements : dict(Field, DiscreteFieldRequirements)
+ input constraints, set after initialize() has been called.
+ output_field_requirements = {}
+ output constraints, set after initialize() has been called.
+
+ Notes
+ -----
+ For the input and output variables, the keys of the dicts have to be of
+ type :class:`hysop.fields.continuous.Field`.
+ and the values should consist of :class:`hysop.core.mpi.topology.Topology` instances.
+
+ Giving the following keywords as inputs (in **kwds) will throw a ValueError:
+ variables, iwork, rwork, work, backend
+
+ About the method parameter:
+ One can not directly use the method parameter after this call.
+ User method is put into attribute base_method awaiting the initialization step.
+ See ComputationalGraphNode.handle_method() to see how method is handled.
+ """
+
+ # Check extra args
+ if 'variables' in kwds.keys():
+ msg='variables parameter should not be used in {}, use input_vars and \
+ output_vars instead.'.format(cls)
+ raise ValueError(msg)
+ if ('iwork' in kwds) or ('rwork' in kwds) or ('work' in kwds):
+ msg='work, rwork or iwork parameters can not be used before the full description \
+ of the graph in class {}.'.format(cls)
+ raise ValueError(msg)
+ if ('backend' in kwds):
+ msg='{} is not a ComputationalGraphNodeFrontend thus no backend can be specified.'
+ msg=msg.format(cls)
+ raise ValueError(msg)
+
+ # Check input values
+ input_vars = input_vars or dict()
+ output_vars = output_vars or dict()
+ method = method or dict()
+ name = name or self.__class__.__name__
+
+ if not isinstance(name, str):
+ msg='name is not a string but a {}.'
+ raise ValueError(msg.format(name.__class__))
+ if not isinstance(input_vars, dict):
+ msg='input_vars is not a dict but a {}.'
+ raise ValueError(msg.format(input_vars.__class__))
+ if not isinstance(output_vars, dict):
+ msg='output_vars is not a dict but a {}.'
+ raise ValueError(msg.format(output_vars.__class__))
+
+ self.name = name
+ self.input_vars = input_vars
+ self.output_vars = output_vars
+ self.base_method = method
+
+ self.initialized = False
+ self.topology_handled = False
+ self.discretized = False
+ self.ready = False
+
+ self._base_initialized = False
+ if (input_vars or output_vars):
+ self._init_base(**kwds)
+ else:
+ # if we are a graph we still don't know input and output variables
+ # => defer initialization of base class until full initialization.
+ from hysop.core.graph.computational_graph import ComputationalGraph
+ check_instance(self, ComputationalGraph)
+ self._kwds = kwds
+
+ @debug
+ def _setup_method(self, topgraph_method):
+ """
+ Get method values from top graph method in computational graph,
+ and combines it to user method to build final method dictionnary.
+ """
+ cls = self.__class__
+ if topgraph_method:
+ base_method = self.base_method
+ avail_methods = self.available_methods()
+ extra_keys = set(topgraph_method.keys())\
+ .intersection(avail_methods.keys())\
+ .difference(self.base_method.keys())
+
+ method = self.base_method.copy()
+ for k in extra_keys:
+ method[k] = topgraph_method[k]
+ else:
+ method = self.base_method
+ method = self._check_method(method)
+
+ return method
+
+ @debug
+ def _init_base(self, **kwds):
+ """
+ Initialize base class and check everything.
+ """
+ ifields = set(self.input_vars.keys())
+ ofields = set(self.output_vars.keys())
+ fields = list(ifields.union(ofields))
+ super(ComputationalGraphNode, self).__init__(fields=fields, **kwds)
+ self._base_initialized = True
+
+ @debug
+ def _check_method(self, user_method):
+ """
+ Update user method with default method and check
+ againt available methods.
+ """
+ method = self.default_method().copy()
+ if (user_method is not None):
+ method.update(user_method)
+
+ available_methods = self.available_methods()
+ for (k,v) in method.iteritems():
+ if k not in available_methods.keys():
+ msg='{} is not an available method key.'
+ raise ValueError(msg.format(k))
+
+ available = to_set(available_methods[k])
+ instances = set(x for x in available if isinstance(x,InstanceOf))
+ available = available.difference(instances)
+
+ good=False
+ for instance in instances:
+ if instance.match_instance(v):
+ good=True
+ break
+ good = good or (v in available)
+
+ if (not good):
+ msg='{} is not an available method value for key {},'.format(k,v)
+ msg+='\n possible values are {}.'.format(available_methods[k])
+ raise ValueError(msg)
+ return method
+
+ @debug
+ @base_initialized
+ def check(self):
+ """
+ Check if node was correctly initialized.
+ By default this checks variables, topologies and support.
+ """
+ self._check_variables()
+ self._check_topologies()
+ self._check_support()
+
+ @debug
+ @base_initialized
+ def _check_variables(self):
+ """
+ Check input and output variables.
+ Called automatically in ComputationalGraphNode.check()
+ """
+ for variables in [self.input_vars, self.output_vars]:
+ for (k,v) in variables.iteritems():
+ if not isinstance(k,Field):
+ msg = 'Given key is not a continuous Field (got a {}).'
+ raise TypeError(msg.format(k.__class__))
+ if not isinstance(v, Topology):
+ msg='Expected a Topology instance but got a {}.'.format(topo.__class__)
+ msg+='\nAll topologies are expected to be set after '
+ msg+='ComputationalGraph.get_field_requirements() has been called.'
+ raise TypeError(msg)
+
+ @debug
+ @base_initialized
+ def _check_topologies(self):
+ """
+ Sets topologies flags.
+ _is_distributed
+ _has_multiple_topologies
+ _has_multiple_field_topologies
+ Sets the following attributes:
+ _multi_topo_fields (list of field that have at least two different topologies)
+ Called automatically in ComputationalGraphNode.check()
+ """
+ is_distributed = self.mpi_params.size > 1
+ has_multiple_topologies = False
+ has_multiple_field_topologies = False
+ multi_topo_fields = set()
+
+ topo_ref = (self.input_vars.values()+self.output_vars.values())[0]
+ for variables in [self.input_vars, self.output_vars]:
+ for field, topo in variables.iteritems():
+ if topo != topo_ref:
+ has_multiple_topologies = True
+
+ for ifield in self.input_vars:
+ if ifield in self.output_vars and \
+ self.input_vars[ifield] != self.output_vars[ifield]:
+ multi_topo_fields.add(ifield)
+ has_multiple_field_topologies = True
+
+ self._is_distributed = is_distributed
+ self._has_multiple_topologies = has_multiple_topologies
+ self._has_multiple_field_topologies = has_multiple_field_topologies
+ self._multi_topo_fields = multi_topo_fields
+
+ @debug
+ @base_initialized
+ def _check_support(self):
+ """
+ Check input and output variables topologies against the supported topologies of this node.
+ See ComputationalGraphNode.supports_multiple_topologies()
+ ComputationalGraphNode.supports_multiple_field_topologies()
+ ComputationalGraphNode.supports_mpi()
+ Called automatically in ComputationalGraphNode.check()
+ """
+ cls = self.__class__
+ if (self._has_multiple_field_topologies) and \
+ (not cls.supports_multiple_field_topologies()):
+ msg='Graph operator \'{}\' does not support multiple topologies yet.'
+ msg+= '\nTopology mismatch for continuous variable(s) {} between '
+ msg+= 'input and output variables.'
+ msg=msg.format(self.name, [f.name for f in self._multi_topo_fields])
+ raise NotImplementedError(msg)
+ if (self._has_multiple_topologies) and \
+ (not cls.supports_multiple_topologies()):
+ msg='Graph operator \'{}\' does not support multiple field topologies yet.'
+ msg=msg.format(self.name)
+ raise NotImplementedError(msg)
+ if (self._is_distributed) and (not cls.supports_mpi()):
+ msg='MPI multi-process has not been implemented in graph operator \'{}\' yet!'
+ msg=msg.format(self.name)
+ raise NotImplementedError(msg)
+
+
+## ComputationalGraphNode interface
+ @base_initialized
+ def get_topologies(self):
+ """
+ Returns all the topologies used in this operator.
+ Topologies are organized by backend in a dictionnary.
+ """
+ topologies = {}
+ for topo in set(self.input_vars.values()+self.output_vars.values()):
+ backend = topo.backend
+ if backend not in topologies:
+ topologies[backend] = set()
+ topologies[backend].add(topo)
+ return topologies
+
+ @base_initialized
+ def get_backends(self):
+ """
+ Returns all the backends used in this operator as a set.
+ """
+ return self.get_topologies().keys()
+
+ def available_methods(self):
+ """
+ Returns the available methods of this node.
+ This should return a dictionary of method as keys
+ and possible values as a scalar or an iterable.
+ See hysop.types.InstanceOf to support specific
+ class types. This is used to check user method input.
+ """
+ return dict()
+
+ def default_method(self):
+ """
+ Returns the default method of this node.
+ Default methods should be compatible with available_methods.
+ If the user provided method dictionnaty misses some method keys,
+ a default value for this key will be extracted from the default one.
+ """
+ return dict()
+
+ @debug
+ def handle_method(self, method):
+ """
+ Method automatically called during initialization.
+ This allow to extract method values after method preprocessing.
+ Method preprocessing means:
+ 1) complete user input with compatible top graph user inputs
+ 2) complete the resulting dictionnary with the node default_method
+ 3) check method against available_methods.
+ The result of this process is fed as argument of this function.
+ """
+ self.method = copy.deepcopy(method)
+
+ @debug
+ def handle_topologies(self):
+ """
+ Called after all topologies have been set up.
+ Topologies are available as values of self.input_vars
+ and self.output_vars and are mapped by continuous Field.
+ """
+ self.topology_handled = True
+
+ @abstractmethod
+ def get_field_requirements(self):
+ """
+ Called just after handle_method(), ie self.method has been set.
+ Topology requirements are:
+ 1) min and max ghosts for each input and output variables
+ 2) allowed splitting directions for cartesian topologies
+ 3) required local and global transposition state, if any.
+ and more
+ They are stored in self.input_field_requirements and
+ self.output_field_requirements.
+
+ Keys are continuous fields and values are of type
+ hysop.fields.field_requirement.DiscreteFieldRequirements
+ """
+ from hysop.fields.field_requirements import OperatorFieldRequirements
+ return OperatorFieldRequirements()
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ """
+ Should return True if this node supports multiple topologies.
+ """
+ return False
+
+ @classmethod
+ def supports_multiple_field_topologies(cls):
+ """
+ Should return True if an input field that is also an output field
+ can have an input topology different from its output topology.
+ This is usefull in Redistribute like operators.
+ If this returns True this implies supports_multiple_topologies().
+ It also implies that self.variables[field] may return a set of topologies.
+ In this case one can recover input and output topologies by using
+ self.input_vars[field] and self.output_vars[field].
+ In addition one can find such fields by using the list self.multi_topo_fields
+ which is set after ComputationalGraphNode.initialize() has been called.
+ """
+ return False
+
+ @classmethod
+ def supports_mpi(cls):
+ """
+ Return True if this operator was implemented to support multiple mpi processes.
+ """
+ return False
+
+ @debug
+ def pre_initialize(self, **kwds):
+ """
+ Function called before initialization,
+ can be used to alter variables set in __init__ like
+ input_vars or output_vars.
+ By default this does nothing.
+ """
+ pass
+
+ @debug
+ def post_initialize(self, **kwds):
+ """
+ Function called after initialization,
+ can be used to execute routines after handle_method has been called.
+ By default this does nothing.
+ """
+ pass
+
+ @debug
+ def initialize(self, topgraph_method=None, **kwds):
+ """
+ Initialize this node.
+
+ Initialization step sets the following variables:
+ *self.method,
+ *self.input_field_requirements
+ *self.output_field_requirements
+ *self.initialized
+ It returns self.method.
+
+ Order of execution is:
+ self.pre_initialize()
+ self._setup_method()
+ self.handle_method()
+ self.get_field_requirements()
+ self._initialized = True
+ self.post_initialize()
+
+ See ComputationalGraphNode.handle_method() to see how user method is handled.
+ See ComputationalGraphNode.get_field_requirements() to see how topology requirements
+ are handled.
+
+ After this method has been handled by all operators, initialization collects min and max
+ ghosts required by each operators which will be usefull in the discretiezation step
+ to automatically build topologies or check against user supplied topologies.
+
+ This function also sets the self.initialized flag to True (just before post
+ initialization).
+ Once this flag is set one may call ComputationalGraphNode.discretize().
+ """
+ if self.initialized:
+ return
+
+ self.pre_initialize(**kwds)
+
+ method = self._setup_method(topgraph_method)
+ self.handle_method(method)
+ self.initialized=True
+
+ self.post_initialize(**kwds)
+
+ return method
+
+ @debug
+ @topology_handled
+ def discretize(self):
+ """
+ Discretize this operator.
+ By default this just sets the self.discretized flag to True.
+ Once this flag is set one may call ComputationalGraphNode.get_work_properties() and
+ ComputationalGraphNode.setup().
+ """
+ self.discretized = True
+
+ @debug
+ @discretized
+ def get_work_properties(self):
+ """
+ Returns extra memory requirements of this node.
+ This allows operators to request for temporary buffers
+ that will be shared between operators in a graph to reduce
+ the memory footprint and the number of allocations.
+ By default this returns None, meanning that this node requires
+ no extra buffers.
+ """
+ return None
+
+ @debug
+ @discretized
+ def setup(self, work):
+ """
+ Setup temporary buffer that have been requested in get_work_properties().
+ This function may be used to execute post allocation routines.
+ This sets self.ready flag to True.
+ Once this flag is set one may call ComputationalGraphNode.apply() and
+ ComputationalGraphNode.finalize().
+ """
+ self.ready = True
+
+ @abstractmethod
+ @debug
+ @ready
+ def apply(self, simulation=None, **kargs):
+ """
+ Abstract method that should be implemented.
+ Applies this node (operator, computational graph operator...).
+ """
+ pass
+
+ @debug
+ @ready
+ def finalize(self, **kargs):
+ """
+ Cleanup this node (free memory from external solvers, ...)
+ By default, this does nothing
+ """
+ self.ready = False
diff --git a/hysop/core/graph/computational_node_frontend.py b/hysop/core/graph/computational_node_frontend.py
new file mode 100644
index 0000000000000000000000000000000000000000..2fb588d5bacca95dc4d9179e08d94ac42134bb50
--- /dev/null
+++ b/hysop/core/graph/computational_node_frontend.py
@@ -0,0 +1,120 @@
+
+from hysop.constants import Implementation, Backend, implementation_to_backend
+from hysop.tools.decorators import debug
+from hysop.core.graph.node_generator import ComputationalGraphNodeGenerator
+from hysop.tools.types import check_instance
+from hysop.core.graph.graph import not_implemented
+
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology import Topology
+
+class ComputationalGraphNodeFrontend(ComputationalGraphNodeGenerator):
+
+ @debug
+ def __init__(self, implementation=None, base_kwds=None, **impl_kwds):
+ """
+ Initialize a ComputationalGraphNodeFrontend
+
+ Parameters
+ ----------
+ implementation: Implementation, optional, defaults to None
+ target implementation, should be contained in available_implementations().
+ If None, implementation will be set to default_implementation().
+ base_kwds: dict, optional, defaults to None
+ Base class keywords arguments.
+ If None, an empty dict will be passed.
+ impl_kwds:
+ Keywords arguments that will be passed towards implementation implemention
+ __init__.
+
+ Attributes
+ ----------
+ implementation: Implementation
+ the implementation key
+ backend: Backend
+ the backend corresponding to implementation
+ impl: ComputationalGraphNodeGenerator or ComputationalGraphNode
+ the implementation class
+ impl_kwds:
+ Keywords arguments that will be passed towards implementation implemention
+ impl.__init__ during a call to _generate.
+ """
+
+ base_kwds = base_kwds or dict()
+ super(ComputationalGraphNodeFrontend,self).__init__(**base_kwds)
+
+ check_instance(implementation, Implementation, allow_none=True)
+
+ default_implementation = self.__class__.default_implementation()
+ available_implementations = self.__class__.available_implementations()
+
+ if not isinstance(default_implementation, Implementation):
+ raise TypeError('default_implementation is not a instance of hysop.backend.Implementation.')
+ for b in available_implementations:
+ if not isinstance(b, Implementation):
+ msg='{} is not a instance of hysop.backend.Implementation.'
+ msg=msg.format(b)
+ raise TypeError(msg)
+
+ if default_implementation not in available_implementations:
+ raise ValueError('default_implementation is not contained in available_implementations.')
+
+ if implementation is None:
+ implementation = default_implementation
+ elif implementation not in available_implementations:
+ simplementations=[]
+ simplementations.append('-{} (default)'.format(default_implementation))
+ for b in available_implementations:
+ if b!=default_implementation:
+ simplementations.append('-{}'.format(b))
+
+ msg = 'Specified implementation \'{}\' is not an available implementation, '
+ msg+= 'available implementations are:\n {}'
+ msg=msg.format(implementation, '\n '.join(implementations))
+ raise ValueError(msg)
+
+ self.implementation = implementation
+ self.backend = implementation_to_backend(implementation)
+ self.impl = self.implementations()[implementation]
+ self.impl_kwds = impl_kwds
+
+ def _generate(self):
+ try:
+ op = self.impl(**self.impl_kwds)
+ except:
+ sargs = ['*{} = {}'.format(k,v.__class__)
+ for (k,v) in self.impl_kwds.iteritems()]
+ msg = 'FATAL ERROR during {}.generate():\n'
+ msg += ' => failed to call {}.__init__()\n with the following keywords:'
+ msg += '\n '+'\n '.join(sargs)
+ msg = msg.format(self.__class__, self.impl)
+ print '\n{}\n'.format(msg)
+ raise
+
+ return [op]
+
+ @classmethod
+ @not_implemented
+ def implementations(cls):
+ """
+ Should return all implementations as a dictionnary.
+ Keys are Implementation instances and values are either ComputationalGraphNode
+ or ComputationalGraphNodeGenerator.
+ """
+ pass
+
+ @classmethod
+ @not_implemented
+ def default_implementation(cls):
+ """
+ Return the default Implementation, should be compatible with available_implementations.
+ """
+ pass
+
+ @classmethod
+ def available_implementations(cls):
+ """
+ Return all available implementations.
+ """
+ return cls.implementations().keys()
+
diff --git a/hysop/core/graph/computational_operator.py b/hysop/core/graph/computational_operator.py
new file mode 100644
index 0000000000000000000000000000000000000000..e0df05d3569fc04acc9241d2df7e548359127047
--- /dev/null
+++ b/hysop/core/graph/computational_operator.py
@@ -0,0 +1,267 @@
+
+from hysop.constants import Backend
+from hysop.tools.decorators import debug
+from hysop.core.graph.computational_node import ComputationalGraphNode
+from hysop.core.graph.graph import initialized, discretized
+from hysop.core.memory.memory_request import OperatorMemoryRequests
+from hysop.core.mpi.topology_descriptor import TopologyDescriptor
+from hysop.fields.field_requirements import DiscreteFieldRequirements
+from abc import ABCMeta
+
+class ComputationalGraphOperator(ComputationalGraphNode):
+ """
+ Interface of an abstract computational graph operator.
+ An operator is a single graph node with its own inputs and outputs.
+
+ For more complex operators that combines multiple operators, see
+ hysop.core.graph.computational_graph.ComputationalGraph
+
+ For operators that offers different implementation backend, see
+ hysop.core.graph.computational_node_frontend.ComputationalGraphNodeFrontend
+
+ About inputs and outputs variables (continuous fields):
+ *An operator may be working on multiple topologies exposed by different
+ fields. In this case supports_multiple_topologies() should return True.
+
+ *An input continuous field may have different topologies as input
+ and output. In this case supports_multiple_field_topologies()
+ should return True.
+
+ *An operator may support distribution along mpi processes.
+ In this case supports_mpi() should return True.
+ Distribution constraints along process can be specified
+ by redefining get_field_requirements() for inputs and outputs.
+
+ *Min and max ghosts and input/output state (base or transposition state for exemple)
+ can be specified on a per variable basis in get_field_requirements()
+
+ An operator may thus *override* the following class methods:
+ supports_multiple_topologies()
+ supports_multiple_field_topologies()
+ supports_mpi()
+ By default all those methods return False,
+ meaning that it can only have input and output variables
+ defined on one unique topology that is not distributed
+ along multiple processes.
+
+ To support the 'method' keyword, *override* the following methods:
+ available_methods()
+ default_method()
+ handle method()
+
+ To add contraints on variables and their topologies, *override* the following method:
+ get_field_requirements()
+
+ An operator has to *extend* the following abstract method:
+ apply(simulation, **kwds)
+
+ An operator may *extend* the definition the following methods:
+ pre_initialize()
+ initialize()
+ post_initialize()
+ get_work_properties()
+ setup()
+ finalize()
+
+ When extending methods pay attention to *always* call base class methods.
+ Not calling base methods may lead to unexpected behaviours in present/future
+ releases.
+ When overriding methods, you can just redefine it.
+
+ See hysop.core.computational_node.ComputationalGraphNode for more information
+ about those methods.
+
+ Order of operation of an operator:
+ __init__()
+ self.initialized is False
+ self.discretized is False
+ self.ready is False
+ -> topologies and support are checked
+ initialize()
+ pre_initialize()
+ handle method() -> self.method is set
+ get_field_requirements() -> self.input_field_requirements it set
+ self._initialized is set
+ post_intialize()
+ check() (requires self.initialized to be set)
+ discretize() (requires self.initialized to be set)
+ self.discretized is set
+ get_work_properties() (requires self.discretized to be set)
+ returns required work (extra temporary buffers required for the computations)
+ setup() (requires self.discretized to be set)
+ self.ready is set
+ apply() (requires self.ready to be set)
+ abtract method to be implemented
+ finalize() (requires self.ready to be set)
+ sets self.ready to False
+
+ Nothing besides __init__ should be called explicitely by the user as a
+ ComputationalGraphOperator should always be embedded in a hysop.problem.Problem,
+ or at least, a child class of hysop.core.graph.computational_graph.ComputationalGraph.
+ """
+
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, **kwds):
+ """
+ Parameters
+ ----------
+ kwds: arguments for base classes.
+ required: input_vars, output_vars
+ optional: name, method, mpi_params, io_params
+
+ Attributes
+ ----------
+ input_discrete_fields: dict
+ Dictionary containing continuous input fields as keys and discrete
+ variables as values.
+ output_discrete_fields: dict
+ Dictionary containing continuous output fields as keys and discrete
+ variables as values.
+
+ Notes
+ -----
+ The following base class variables cannot be specified in kwds
+ variables, rwork, iwork, work, backend
+
+ Nothing besides __init__ should be called manually by the user as it
+ should be embedded into a hysop.problem.Problem, or at least in a
+ ComputationalGraph.
+ """
+
+ super(ComputationalGraphOperator,self).__init__(**kwds)
+ self.input_discrete_fields = {}
+ self.output_discrete_fields = {}
+
+ @debug
+ def get_field_requirements(self):
+ """
+ Called just after handle_method(), ie self.method has been set.
+ Topology requirements are:
+ 1) min and max ghosts for each input and output variables
+ 2) allowed splitting directions for cartesian topologies
+ 3) required local and global transposition state, if any.
+ 4) required space (fourier, physical, ...)
+ and more
+
+ Default is Backend.HOST, no min or max ghosts, Basis.CARTESIAN and no specific
+ transposition state for each input and output variables.
+ """
+
+ # by default we create HOST (cpu) TopologyDescriptors
+ for field,topo_descriptor in self.input_vars.iteritems():
+ topo_descriptor = TopologyDescriptor.build_descriptor(
+ backend=Backend.HOST,
+ operator=self,
+ field=field,
+ handle=topo_descriptor)
+ self.input_vars[field] = topo_descriptor
+
+ for field,topo_descriptor in self.output_vars.iteritems():
+ topo_descriptor = TopologyDescriptor.build_descriptor(
+ backend=Backend.HOST,
+ operator=self,
+ field=field,
+ handle=topo_descriptor)
+ self.output_vars[field] = topo_descriptor
+
+ # and we use default DiscreteFieldRequirements (ie. no min ghosts, no max ghosts,
+ # can_split set to True in all directions, Basis.CARTESIAN, TranspositionState.XYZ).
+ input_field_requirements = {}
+ for field, topo_descriptor in self.input_vars.iteritems():
+ req = DiscreteFieldRequirements(self, self.input_vars, field)
+ input_field_requirements[field] = req
+
+ output_field_requirements = {}
+ for field, topo_descriptor in self.output_vars.iteritems():
+ req = DiscreteFieldRequirements(self, self.output_vars, field)
+ output_field_requirements[field] = req
+
+ requirements = super(ComputationalGraphOperator, self).get_field_requirements()
+ requirements.update_inputs(input_field_requirements)
+ requirements.update_outputs(output_field_requirements)
+ return requirements
+
+
+ @debug
+ @initialized
+ def discretize(self):
+ """
+ By default, an operator discretize all its variables.
+ For each inout field, input topology may be different
+ from the output topology.
+
+ After this call, one can access self.input_discrete_fields
+ and self.output_discrete_fields, which contains input and output
+ dicretised fields.
+ """
+ if not self.topology_handled:
+ import warnings
+ msg= '\nTopologies in operator {} has not been handled yet.'
+ msg+='\nThis may be the case if this operator was not embedded into '
+ msg+='a ComputationalGraph.'
+ msg=msg.format(self.name)
+ print
+ warnings.warn(msg)
+ print
+
+ requirements = self.get_field_requirements()
+ requirements.build_topologies()
+ self.handle_topologies()
+
+ super(ComputationalGraphOperator,self).discretize()
+ for field,topology in self.input_vars.iteritems():
+ self.input_discrete_fields[field] = field.discretize(topology)
+ for field,topology in self.output_vars.iteritems():
+ self.output_discrete_fields[field] = field.discretize(topology)
+
+ @debug
+ @discretized
+ def get_work_properties(self):
+ """
+ Returns extra memory requirements of this node.
+ This allows operators to request for temporary buffers
+ that will be shared between operators in a graph to reduce
+ the memory footprint and the number of allocations.
+
+ By default this returns no requests, meanning that this node requires
+ no extra buffers.
+ """
+ return OperatorMemoryRequests(self)
+
+ def supported_backends(self):
+ """
+ Return the backends that this operator's topologies can support as a set.
+ By default all operators support only Backend.HOST.
+ """
+ return set([Backend.HOST])
+
+ @debug
+ @initialized
+ def check(self):
+ """
+ Check if node was correctly initialized.
+ This calls ComputationalGraphNode.check() and then checks backend
+ by comparing all variables topology backend to set.supported_backends().
+ """
+ super(ComputationalGraphOperator, self).check()
+ self._check_backend()
+
+ def _check_backend(self):
+ """
+ Checks backend support and topologies.
+ """
+ topologies_per_backend = self.get_topologies()
+ supported_backends = self.supported_backends()
+ for (backend, topologies) in topologies_per_backend.iteritems():
+ if backend.kind not in supported_backends:
+ msg='\n\nOperator {} topology backend mismatch:'.format(self.name)
+ msg+='\n -> got topologies defined on backend {}.'.format(backend)
+ msg+='\n *bad topology ids were {}'.format([t.get_id() for t in topologies])
+ msg+='\n -> this operator only supports the following backends:'
+ msg+='\n *'+'\n *'.join([str(b) for b in supported_backends])
+ for t in topologies:
+ print '\n',t
+ raise RuntimeError(msg)
+
diff --git a/hysop/core/graph/continuous.py b/hysop/core/graph/continuous.py
new file mode 100755
index 0000000000000000000000000000000000000000..4422f5d7201bab68a4d70f75abbc8434610346b9
--- /dev/null
+++ b/hysop/core/graph/continuous.py
@@ -0,0 +1,111 @@
+"""Common interface for all continuous operators.
+
+"""
+from abc import ABCMeta, abstractmethod
+
+from hysop.tools.io_utils import IOParams, IO
+from hysop.tools.parameters import MPIParams
+from hysop.tools.decorators import debug
+from hysop.tools.types import check_instance
+from hysop.fields.continuous import Field
+
+import hysop.tools.io_utils as io
+
+class OperatorBase(object):
+ """Abstract interface to continuous operators.
+ """
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, fields,
+ mpi_params=None,
+ io_params=None,
+ **kwds):
+ """
+ Parameters
+ ----------
+ field: list of Field
+ fields on which this operator operates
+ mpi_params : :class:`hysop.tools.parameters.MPIParams`
+ mpi config for the operator (comm, task ...)
+ io_params : :class:`hysop.tools.io_utils.IOParams`
+ file i/o config (filename, format ...)
+
+ Attributes
+ ----------
+ fields: list of Field
+ io_params: IOParams
+ mpi_params: MPIParams
+ """
+ super(OperatorBase,self).__init__(**kwds)
+
+ check_instance(fields, list, values=Field)
+ check_instance(io_params, IOParams, allow_none=True)
+ check_instance(mpi_params, MPIParams, allow_none=True)
+
+ self.fields = fields
+ self.io_params = io_params
+ self.mpi_params = mpi_params
+
+ self._set_domain_and_tasks()
+
+ def _set_io(self, filename, buffshape):
+ """
+ Parameters
+ -----------
+ filename : string
+ name of the output file used by this operator
+ buffshape : tuple
+ shape of the numpy buffer used to save data to
+ be printed out into filename. Must be 2D.
+ Example : shape (2,4)
+
+ Notes
+ -----
+ This function is private and must not be called by
+ external object. It is usually called by operator
+ during construction (__init__).
+
+ """
+ iopar = self.io_params
+ # if iopar is not None (i.e. set in operator init)
+ # and True or set as an IOParams , then build a writer
+ if iopar:
+ if isinstance(iopar, bool):
+ if iopar:
+ self.io_params = IOParams(filename, fileformat=IO.ASCII)
+ else:
+ msg = 'Error, wrong file format for operator output.'
+ assert self.io_params.fileformat is IO.ASCII, msg
+ self._writer = io.Writer(io_params=self.io_params,
+ mpi_params=self.mpi_params,
+ buffshape=buffshape)
+
+ def _set_domain_and_tasks(self):
+ """
+ Initialize the mpi context, depending on local fields, domain
+ and so on.
+
+ Notes
+ -----
+ This function is private and must not be called by
+ external object. It is usually called by operator
+ during construction (__init__).
+ """
+ # When this function is called, the operator must at least
+ # have one field.
+ assert len(self.fields) > 0
+ self.domain = self.fields[0].domain
+
+ # Check if all fields have the same domain
+ for field in self.fields:
+ assert field.domain is self.domain, 'All fields of the operator\
+ must be defined on the same domain.'
+
+ # Set/check mpi context
+ if self.mpi_params is None:
+ self.mpi_params = MPIParams(comm=self.domain.comm_task,
+ task_id=self.domain.current_task())
+
+ # Set profiler
+ #self.profiler = Profiler(self, self.domain.comm_task)
diff --git a/hysop/core/graph/graph.py b/hysop/core/graph/graph.py
new file mode 100644
index 0000000000000000000000000000000000000000..afda85f1ff9be0946cad64739e379ab890f6b8dc
--- /dev/null
+++ b/hysop/core/graph/graph.py
@@ -0,0 +1,99 @@
+
+import graph_tool as gt
+from graph_tool import Graph, GraphView
+from graph_tool import topology, stats, search
+from hysop.tools.decorators import not_implemented, debug, wraps
+try:
+ from graph_tool.all import graph_draw as graph_draw
+except:
+ graph_draw = None
+
+class ComputationalGraphNodeData(object):
+ """
+ Simple class to hold some node data.
+ """
+ def __init__(self, current_level, node_id):
+ self.current_level = current_level
+ self.node_id = node_id
+ self.apply_kargs = [] #list of dictionnary, last one has priority
+ def __str__(self):
+ return '(lvl={},id={})'.format(self.current_level, self.node_id)
+
+
+def not_initialized(f):
+ assert callable(f)
+ @wraps(f)
+ def check(*args,**kargs):
+ return f(*args,**kargs)
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if self.initialized:
+ reason='this node has already been initialized.'
+ raise RuntimeError(msg.format(reason))
+ return check
+
+def initialized(f):
+ assert callable(f)
+ @wraps(f)
+ def check(*args,**kargs):
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if not self.initialized:
+ reason='this node has not been initialized yet.'
+ raise RuntimeError(msg.format(reason))
+ return f(*args,**kargs)
+ return check
+
+def discretized(f):
+ assert callable(f)
+ @wraps(f)
+ def check(*args,**kargs):
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if not self.discretized:
+ reason='this node has not been discretized yet.'
+ raise RuntimeError(msg.format(reason))
+ return f(*args,**kargs)
+ return check
+
+def ready(f):
+ assert callable(f)
+ @wraps(f)
+ def check(*args,**kargs):
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if not self.ready:
+ reason='this node has not been set up.'
+ raise RuntimeError(msg.format(reason))
+ return f(*args,**kargs)
+ return check
+
+def graph_built(f):
+ assert callable(f)
+ @wraps(f)
+ def check(*args,**kargs):
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if not self.graph_built:
+ reason = 'the graph has not been built yet.'
+ raise RuntimeError(msg.format(reason))
+ return f(*args,**kargs)
+ return check
+
+def generated(f):
+ assert callable(f)
+ @wraps(f)
+ def check(*args,**kargs):
+ self = args[0]
+ msg = 'Cannot call {}.{}() on node \'{}\' because {}'\
+ .format(self.__class__.__name__,f.__name__,self.name,'{}')
+ if not self.generated:
+ reason='this node has not been generated yet.'
+ raise RuntimeError(msg.format(reason))
+ return f(*args,**kargs)
+ return check
diff --git a/hysop/core/graph/node_generator.py b/hysop/core/graph/node_generator.py
new file mode 100644
index 0000000000000000000000000000000000000000..85f1644f8c6adf432e1ec780f51b84ce5e58bd51
--- /dev/null
+++ b/hysop/core/graph/node_generator.py
@@ -0,0 +1,67 @@
+from abc import ABCMeta, abstractmethod
+from hysop.tools.decorators import debug
+from hysop.core.graph.computational_node import ComputationalGraphNode
+
+class ComputationalGraphNodeGenerator(object):
+ """
+ A class that can generate multiple hysop.core.graph.ComputationalGraphNode.
+ """
+
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, name=None, **kwds):
+ super(ComputationalGraphNodeGenerator, self).__init__(**kwds)
+ self.name = name or self.__class__.__name__
+ self.nodes = []
+ self.generated = False
+
+ @abstractmethod
+ def _generate(self, **kargs):
+ """
+ Method that should return a list of generated nodes.
+ """
+ pass
+
+ def _pre_generate(self, **kargs):
+ """
+ Optional method called before _generate.
+ """
+ pass
+
+ def _post_generate(self, **kargs):
+ """
+ Optional method called after _generate.
+ """
+ pass
+
+ @debug
+ def generate(self, **kargs):
+ """
+ Recursively generate nodes.
+ Do not override.
+ """
+ if not self.generated:
+ self._pre_generate(**kargs)
+
+ assert len(self.nodes)==0
+ try:
+ for op in self._generate(**kargs):
+ if isinstance(op,ComputationalGraphNode):
+ self.nodes.append(op)
+ elif isinstance(op,ComputationalGraphNodeGenerator):
+ op.generate(**kargs)
+ self.nodes += op.nodes
+ else:
+ msg='Unknown node type {}.'.format(op.__class__)
+ raise TypeError(msg)
+ except:
+ msg='\nFailed to call generate() in class {}.\n'.format(self.__class__)
+ print msg
+ raise
+ assert len(self.nodes)>=1
+
+ self._post_generate(**kargs)
+ self.generated = True
+ return self.nodes
+
diff --git a/hysop/core/graph/tests/test_graph.py b/hysop/core/graph/tests/test_graph.py
new file mode 100644
index 0000000000000000000000000000000000000000..6a14be8c3423b36d9f39e42e98b4753a2857bca3
--- /dev/null
+++ b/hysop/core/graph/tests/test_graph.py
@@ -0,0 +1,104 @@
+
+from hysop.domain.box import Box
+from hysop.core.mpi.topology import Cartesian
+from hysop.tools.parameters import Discretization
+from hysop.fields.continuous import Field
+from hysop.core.graph.all import ComputationalGraphOperator, ComputationalGraph
+
+class _ComputationalGraph(ComputationalGraph):
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return True
+
+class _ComputationalGraphOperator(ComputationalGraphOperator):
+ def initialize(self, methpd):
+ pass
+ def discretize(self):
+ pass
+ def get_work_properties(self):
+ return None
+ def setup(self,work):
+ pass
+ def apply(self):
+ pass
+
+ def available_methods(self):
+ return {}
+ def default_method(self):
+ return {}
+ def handle_method(self, method):
+ pass
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return True
+
+def test_graph_build(display=False):
+ box = Box(length=[1.0]*3, origin=[0.0]*3)
+ Vg = Field(domain=box, name='Vg', is_vector=True)
+ Vp = Field(domain=box, name='Vp', is_vector=True)
+ Wg = Field(domain=box, name='Wg', is_vector=True)
+ Wp = Field(domain=box, name='Wp', is_vector=True)
+ rho0g = Field(domain=box, name='rho0g')
+ rho0p = Field(domain=box, name='rho0p')
+ rho1g = Field(domain=box, name='rho1g')
+ rho1p = Field(domain=box, name='rho1p')
+
+ d3d0 = Discretization(resolution=(64,64,64), ghosts=None)
+ d3d1 = Discretization(resolution=(128,128,128), ghosts=None)
+ t0 = Cartesian(box,d3d0,3)
+ t1 = Cartesian(box,d3d1,3)
+
+ ops = [
+ ('copyW', [Wg], [Wp]),
+ ('copyS0', [rho0g], [rho0p]),
+ ('copyS1', [rho1g], [rho1p]),
+ ('copyV', [Vg], [Vg]),
+ ]
+ g0 = _ComputationalGraph(name='g0')
+ for (opname,_in,_out) in ops:
+ invars = {}
+ outvars = {}
+ for var in _in:
+ invars[var] = t0 if (var.name.find('rho')) else t1
+ for var in _out:
+ outvars[var] = t0 if (var.name.find('rho')) else t1
+ g0.push_nodes(_ComputationalGraphOperator(name=opname,
+ input_vars=invars,output_vars=outvars))
+
+ ops = [
+ ('advecWx', [Vg, Wp], [Wg]),
+ ('stretchWx', [Vg, Wg], [Wg]),
+ ('diffWx', [Wg], [Wg]),
+ ('advecS0x', [Vg,rho0p], [rho0g]),
+ ('advecS1x', [Vg,rho1p], [rho1g]),
+ ('diffS0x', [rho0g], [rho0g]),
+ ('diffS1x', [rho1g], [rho1g]),
+ ('forceWx', [rho0g,rho1g,Wg], [Wg]),
+ ]
+ g1 = _ComputationalGraph(name='g1')
+ for (opname,_in,_out) in ops:
+ invars = {}
+ outvars = {}
+ for var in _in:
+ invars[var] = t0 if (var.name.find('rho')) else t1
+ for var in _out:
+ outvars[var] = t0 if (var.name.find('rho')) else t1
+ g1.push_nodes(_ComputationalGraphOperator(name=opname,
+ input_vars=invars,output_vars=outvars))
+
+ g = _ComputationalGraph(name='exec')
+ g.push_nodes(g0)
+ g.push_nodes(g1)
+
+ g.initialize()
+ g.discretize()
+ g.setup(None)
+ g.apply()
+
+ if display:
+ g.display()
+
+
+if __name__ == '__main__':
+ test_graph_build(display=True)
diff --git a/hysop/core/memory/__init__.py b/hysop/core/memory/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/core/memory/allocator.py b/hysop/core/memory/allocator.py
new file mode 100644
index 0000000000000000000000000000000000000000..5534a5c36198989eea8be54998b3d0482649dd2b
--- /dev/null
+++ b/hysop/core/memory/allocator.py
@@ -0,0 +1,79 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.tools.types import check_instance
+
+class AllocatorBase(object):
+ """
+ Base class for allocators.
+ """
+
+ __metaclass__=ABCMeta
+
+ is_deferred=False
+
+ def __init__(self, **kwds):
+ super(AllocatorBase,self).__init__(**kwds)
+
+ def __call__(self, size, alignment=None):
+ """
+ Allocate nbytes aligned on min_alignment.
+ If the first allocation fails, call the garbage collector and try again.
+ It this fails a second time, raise a MemoryError.
+ """
+
+ try_count = 0
+ while try_count < 2:
+ try:
+ if (alignment > 1):
+ buf = self.allocate_aligned(size=size, alignment=alignment)
+ else:
+ buf = self.allocate(nbytes=size)
+ if (buf is None):
+ msg='{}.allocate(): returned allocation is None.'.format(self.__class__)
+ raise ValueError(msg)
+ return buf
+ except MemoryError:
+ try_count += 1
+ if try_count == 2:
+ raise
+
+ self.try_release_blocks()
+
+ @abstractmethod
+ def is_on_host(self):
+ """
+ Return true if buffers are allocated in host memory.
+ """
+ pass
+
+ @abstractmethod
+ def allocate(self, nbytes):
+ """
+ Allocate nbytes bytes of memory.
+ No minimal memory alignment is guaranteed.
+ If allocation fails, this method has to raise a MemoryError.
+ """
+ pass
+
+ def allocate_aligned(self, size, alignment):
+ """
+ Allocate size bytes aligned on alignment.
+ """
+ assert alignment>0
+ assert (alignment & (alignment-1))==0, 'alignment is not a power of 2.'
+ nbytes = size + alignment - 1
+ return self.allocate(nbytes).aligned_view(alignment=alignment, size=size)
+
+ def try_release_blocks(self):
+ """
+ Try to release memory blocks by calling the garbage collector.
+ """
+ import gc
+ gc.collect()
+
+ def free(self, buf):
+ """
+ Release the allocated buffer.
+ """
+ buf.release()
+
diff --git a/hysop/core/memory/buffer.py b/hysop/core/memory/buffer.py
new file mode 100644
index 0000000000000000000000000000000000000000..77b37f43c3e0eda7c5da3eefd945f8358915f9e9
--- /dev/null
+++ b/hysop/core/memory/buffer.py
@@ -0,0 +1,139 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.deps import np
+from hysop.tools.types import check_instance
+
+class Buffer(object):
+ """
+ Base class for releasable buffers.
+ A buffer should just offer a release method to be compatible with allocators.
+
+ Host buffers are numpy buffers.
+ Cuda and OpenCl buffers are the one provided by pycuda and pyopencl.
+
+ Buffers should be obtained through allocators or memory pools.
+ """
+
+ #/!\ ptr, size and int_ptr properties should be redefined in child classes.
+ __metaclass__ = ABCMeta
+
+ def __init__(self, size, **kwds):
+ obj = super(Buffer, self).__init__(**kwds)
+ self._size = size
+ return obj
+
+ @abstractmethod
+ def release(self):
+ """
+ Release this buffer (decrease internal implementation defined reference counter).
+ """
+ msg='Buffer.release() is not implemented and should never have been called.'
+ raise RuntimeError(msg)
+
+ @classmethod
+ def from_int_ptr(cls, int_ptr_value, **kargs):
+ """
+ Constructs a pyopencl handle from a C-level pointer (given as the integer int_ptr_value).
+ If the previous owner of the object owns the handle and will not release it,
+ on can set retain to False, to effectively transfer ownership.
+ Setting retain to True should increase an implementation specific reference counter.
+ The buffer will be freed when buffer reference counter is 0.
+ """
+ msg='Buffer.from_int_ptr() is not implemented and should never have been called.'
+ raise RuntimeError(msg)
+
+ @abstractmethod
+ def aligned_view(self, alignment, size=None):
+ """
+ Return a view of this buffer with an offset such that
+ the returned buffer is now aligned on min_alignment
+ and has now given size.
+ """
+ pass
+
+ @abstractmethod
+ def get_int_ptr(self):
+ """
+ Return buffer pointer as an int.
+ Should be accessible trough property 'int_ptr' as well.
+ """
+ raise NotImplementedError('int_ptr property has not been implemented.')
+
+ def get_buffer(self):
+ return self
+ def get_size(self):
+ return self._size
+
+ int_ptr = property(get_int_ptr)
+ buf = property(get_buffer)
+ size = property(get_size)
+
+
+class PooledBuffer(Buffer):
+ """
+ Memory pool allocated buffer wrapper.
+ """
+ __metaclass__ = ABCMeta
+
+ __DEBUG=False
+ """
+ Extra flag for debugging PooledBuffers.
+ """
+
+ def __init__(self, pool, buf, alloc_sz, size, alignment, **kwds):
+ """
+ Create a memory pool wrapped buffer.
+ Input buffer buf was allocated by given pool with real size alloc_sz.
+ Buffer is resized and aligned to given size and alignment.
+ On destruction, buffer will be given back to the pool.
+ """
+ from hysop.core.memory.mempool import MemoryPool
+ super(PooledBuffer,self).__init__(size=size, **kwds)
+ if PooledBuffer.__DEBUG:
+ print 'pooled buffer size={}, alignment={}, real_size={}'.format(size,alignment,alloc_sz)
+ assert alloc_sz >= size + alignment - 1
+ check_instance(pool, MemoryPool)
+ check_instance(buf, Buffer)
+ self._alloc_size = alloc_sz
+ self._pool = pool
+ self._buf = buf
+ self._bufview = buf.aligned_view(size=size, alignment=alignment)
+
+ def get_buf(self):
+ """
+ Get wrapped buffer handle.
+ """
+ return self._bufview
+ def get_pool(self):
+ """
+ Get pool that allocated this buffer.
+ """
+ return self._pool
+ def get_int_ptr(self):
+ """
+ Get wrapped buffer handle pointer as an int.
+ """
+ return self._bufview.get_int_ptr()
+ def aligned_view(self, alignment, size=None):
+ return self._bufview.aligned_view(alignment=alignment, size=size)
+
+ def release(self):
+ """
+ Tells the memory pool that this buffer has no longer to be held.
+ """
+ if PooledBuffer.__DEBUG:
+ print 'pooled buffer release()'
+ self._pool.free(self._buf, self._size)
+ self._buf = None
+ self._bufview = None
+
+ def __del__(self):
+ if PooledBuffer.__DEBUG:
+ print 'pooled buffer __del__()'
+ if (self._buf is not None):
+ self.release()
+
+ buf = property(get_buf)
+ pool = property(get_pool)
+ int_ptr = property(get_int_ptr)
+
diff --git a/hysop/core/memory/mem_utils.py b/hysop/core/memory/mem_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..4fcea5592b3bdfbd1020838278933991730f75a7
--- /dev/null
+++ b/hysop/core/memory/mem_utils.py
@@ -0,0 +1,31 @@
+
+import resource, psutil
+from psutil import virtual_memory
+
+def disable_vmem():
+ physical_memory = psutil.virtual_memory().total
+ _, vmem_hard = resource.getrlimit(resource.RLIMIT_AS)
+ vmem_soft = max(0.95*physical_memory, physical_memory-512*1024*1024)
+ if vmem_hard != resource.RLIM_INFINITY:
+ vmem_soft = min(vmem_soft, vmem_hard)
+ vmem_hard = vmem_soft
+ resource.setrlimit(resource.RLIMIT_AS, (vmem_soft, vmem_hard))
+ return (vmem_soft, vmem_hard)
+
+def memory_repport():
+ from hysop.tools.units import bytes2str
+ vmem = psutil.virtual_memory()
+ ss='== Memory Repport =='
+ ss+='\n Virtual memory mapping:'
+ for attr in ['total', 'available', 'used', 'free', 'active', 'inactive', 'buffers', 'cached', 'shared']:
+ val=getattr(vmem,attr)
+ ss+='\n *{:<10} {}'.format(attr, bytes2str(val))
+ ss+='\n'
+ ss+='\n Memory resource limits (soft/hard):'
+ for attr in ['RLIMIT_AS','RLIMIT_DATA','RLIMIT_MEMLOCK','RLIMIT_RSS','RLIMIT_STACK']:
+ soft,hard = resource.getrlimit(getattr(resource,attr))
+ soft = 'INFTY' if soft==resource.RLIM_INFINITY else bytes2str(soft)
+ hard = 'INFTY' if hard==resource.RLIM_INFINITY else bytes2str(hard)
+ ss+='\n *{:<15} {:<8} / {:<8}'.format(attr,soft,hard)
+ ss+='\n===================='
+ return ss
diff --git a/hysop/core/memory/memory_request.py b/hysop/core/memory/memory_request.py
new file mode 100644
index 0000000000000000000000000000000000000000..e6bcec75bceb4cb23c1ea8b3315094b5a793c64f
--- /dev/null
+++ b/hysop/core/memory/memory_request.py
@@ -0,0 +1,354 @@
+
+from abc import ABCMeta, abstractmethod
+
+from hysop.deps import np, copy
+from hysop.tools.types import check_instance
+from hysop.tools.units import bytes2str
+from hysop.tools.numerics import get_dtype
+from hysop.core.arrays.array_backend import ArrayBackend
+from hysop.constants import HYSOP_BOOL, Backend
+
+class MemoryRequest(object):
+ """Memory request that can be requested in get_work_properties()"""
+
+ def __init__(self, backend,
+ count=None, shape=None,
+ dtype=None, alignment=None,
+ ncomponents=1):
+ """
+ Creates a memory request to be served from given backend.
+
+ When dtype is not specified, count represents the number of bytes
+ else the number of elements of given data type.
+
+ Count can be specified directly by a n-dimensional shape parameter.
+ In this case, depending on the chosen backend, the output buffer
+ may be altered to accomodate this shape (like numpy n-dimensional arrays).
+
+ Every np.bool request is converted to HYSOP_BOOL dtype.
+ """
+ if dtype == np.bool:
+ dtype = HYSOP_BOOL
+
+ check_instance(backend, ArrayBackend)
+ check_instance(count, (int,long,np.integer), allow_none=True)
+ check_instance(alignment, (int,long,np.integer), allow_none=True)
+ check_instance(ncomponents, (int,long,np.integer), allow_none=True)
+ check_instance(shape, (tuple,list,np.ndarray), allow_none=True)
+
+ if (dtype is None):
+ dtype = np.dtype(np.uint8)
+ assert dtype.itemsize == 1
+ else:
+ dtype = get_dtype(dtype)
+ assert (dtype is not None)
+ dtype = np.dtype(dtype)
+
+ if (count is not None) and (shape is not None):
+ pass
+ if (count is not None):
+ if count<1:
+ raise ValueError('count < 1.')
+ shape = (count,)
+ elif (shape is not None):
+ count = 1
+ for s in shape:
+ if s<1:
+ raise ValueError('shape {} < 1'.format(shape))
+ count *= s
+ else:
+ raise ValueError('count and shape have not been specified.')
+
+ dtype_alignment = self.min_alignment(dtype)
+ if (dtype is not None) and (alignment is not None):
+ min_alignment = min(dtype_alignment, alignment)
+ max_alignment = max(dtype_alignment, alignment)
+ if max_alignment % min_alignment != 0:
+ msg = 'Incompatible aligmenents, specified an alignment of {} '
+ msg += 'but given dtype should be aligned on {} bytes.'
+ msg = msg.format(alignment, dtype_alignment)
+ raise ValueError(msg)
+ alignment = max_alignment
+ elif (dtype is not None):
+ alignment = dtype_alignment
+ elif (alignment is not None):
+ pass
+ else:
+ msg = 'Cannot determine required memory alignment.'
+ msg += '\nSpecify one either explicitely or through a numpy.dtype.'
+ raise ValueError(msg)
+
+ if np.prod(shape) != count:
+ msg='Shape does not match count (count={}, prod(shape)={}).'
+ msg.format(count, np.prod(shape))
+ raise ValueError(msg)
+ if alignment <= 0:
+ msg = 'Alignment should be positive (got {}).'.format(alignment)
+ raise ValueError(alignment)
+ if (alignment&(alignment-1)!=0):
+ msg = 'Alignment is not a power of two (got {}).'.format(alignment)
+ raise ValueError(alignment)
+
+ self.backend = backend
+ self.alignment = alignment
+ self.dtype = dtype
+ self.count = count
+ self.shape = tuple(shape)
+ self.ncomponents = ncomponents
+
+ def data_bytes_per_component(self):
+ """
+ Bytes to be allocated per components.
+ """
+ return self.count * self.bytes_per_element(self.dtype)
+ def min_bytes(self):
+ """
+ Minimum number bytes that may be allocated for all components.
+ """
+ return self.ncomponents*(self.data_bytes_per_component())
+ def max_bytes(self):
+ """
+ Real number bytes that will be allocated for all components.
+ """
+ return self.ncomponents*(self.data_bytes_per_component() + self.alignment - 1)
+ def min_alignment(self,dtype):
+ """
+ Returns the minimum alignement of the allocated buffer (in bytes).
+ """
+ return self.bytes_per_element(dtype)
+ def bytes_per_element(self,dtype):
+ """
+ Returns the size in bytes of the allocated data type.
+ """
+ return dtype.itemsize
+
+ @classmethod
+ def dfield_like(cls, a, backend=None, alignment=None,
+ dtype=None, ncomponents=None,
+ ghosts=None):
+
+ from hysop.fields.discrete import DiscreteField
+ from hysop.tools.parameters import Discretization
+ from hysop.domain.mesh import Mesh
+ check_instance(a, DiscreteField)
+
+ backend = backend or a.backend
+ dtype = dtype or a[0].dtype
+ ncomponents = ncomponents or a.nb_components
+ ghosts = ghosts or a.ghosts
+
+ if np.isscalar(ghosts):
+ ghosts=(ghosts,)*a.dimension
+ elif isinstance(ghosts, bool):
+ ghosts = a.ghosts if ghosts else (0,)*a.dimension
+ assert len(ghosts)==a.dimension
+ ghosts = np.asarray(ghosts)
+
+ shape = a.compute_resolution + 2*ghosts
+
+ base_mesh = a.topology.mesh
+ discretization = Discretization(base_mesh.discretization.resolution, ghosts)
+ mesh = Mesh(base_mesh.domain, discretization=discretization,
+ resolution=base_mesh.resolution, global_start=base_mesh.start() )
+
+ request = MemoryRequest(backend=backend, alignment=alignment,
+ dtype=dtype, shape=shape,
+ ncomponents=ncomponents)
+
+ return request, mesh
+
+ def __str__(self):
+ if not hasattr(self,'identifier'):
+ identifier='None'
+ else:
+ identifier = self.identifier
+ return 'request of size {:<9} (ncomponents={}, shape={:<12}, dtype={:<8}, alignment={:<2}, id={})'.format(
+ bytes2str(self.min_bytes(), decimal=False), self.ncomponents, self.shape,
+ self.dtype, self.alignment, identifier)
+
+ @classmethod
+ def empty_like(cls, a, backend=None, alignment=None,
+ dtype=None, count=None, shape=None, ncomponents=None):
+
+ if hasattr(a, 'backend'):
+ backend = backend or a.backend
+ if hasattr(a, 'alignment'):
+ alignment = alignment or a.alignment
+ if hasattr(a, 'dtype'):
+ dtype = dtype or a.dtype
+ if hasattr(a, 'count'):
+ count = count or a.count
+ if hasattr(a, 'shape'):
+ shape = shape or a.shape
+ if hasattr(a, 'ncomponents'):
+ ncomponents = ncomponents or a.ncomponents
+
+ return MemoryRequest(backend=backend, alignment=alignment,
+ dtype=dtype, count=count, shape=shape,
+ ncomponents=ncomponents)
+
+
+class OperatorMemoryRequests(object):
+ """
+ Set of memory requests originating from one operator, sorted by backend.
+ """
+ def __init__(self, operator):
+ self._operator = operator
+ self._requests_per_backend = {}
+ self._requests_per_identifier = {}
+
+ def push_mem_request(self, request_identifier, mem_request):
+ if request_identifier in self._requests_per_identifier:
+ raise ValueError('Identifier {} was already requested.'.format(request_identifier))
+ if not isinstance(mem_request, MemoryRequest):
+ cls = mem_request.__class__.__name__
+ raise ValueError('Input is not a MemoryRequest (got a {}).'.format(cls))
+ backend = mem_request.backend
+ mem_request.id = request_identifier
+ if backend not in self._requests_per_backend:
+ self._requests_per_backend[backend] = []
+ self._requests_per_backend[backend].append(mem_request)
+ self._requests_per_identifier[request_identifier] = mem_request
+ mem_request.identifier = request_identifier
+
+ def min_bytes_to_allocate(self, backend):
+ return sum( [req.max_bytes() for req in self._requests_per_backend[backend]] )
+
+
+class MultipleOperatorMemoryRequests(object):
+ """
+ Set of memory requests originating from one or more operators.
+ """
+ def __init__(self):
+ self._allocated_buffers = {}
+ self._all_requests_per_backend = {}
+ self._allocated = False
+
+ def push_mem_requests(self, *requests):
+ for mem_requests in requests:
+ if isinstance(mem_requests, MultipleOperatorMemoryRequests):
+ for backend, op_requests in \
+ mem_requests._all_requests_per_backend.iteritems():
+ for requests in op_requests:
+ self.add_mem_request(requests)
+
+ elif isinstance(mem_requests, OperatorMemoryRequests):
+ operator = mem_requests._operator
+ for (backend, requests) in mem_requests._requests_per_backend.iteritems():
+ if backend not in self._all_requests_per_backend.keys():
+ self._all_requests_per_backend[backend] = {}
+ if operator in self._all_requests_per_backend[backend].keys():
+ msg='Operator {} has already requested memory.'.format(operator)
+ raise ValueError(msg)
+ self._all_requests_per_backend[backend][operator] = requests
+ else:
+ cls = op_mem_requests.__class__
+ msg='Input is not an OperatorMemoryRequests (got a {}).'.format(cls)
+ raise ValueError(msg)
+ return self
+
+ def operators(self):
+ ops = []
+ for requests in self._all_requests_per_backend.values():
+ ops += requests.keys()
+ return ops
+
+ def __iadd__(self, other):
+ if (other is None):
+ return self
+ return self.push_mem_requests(other)
+
+ def min_bytes_to_allocate(self, backend):
+ max_bytes = 0
+ for mem_requests in self._all_requests_per_backend[backend].values():
+ req_bytes = sum( [req.max_bytes() for req in mem_requests] )
+ max_bytes = max(req_bytes,max_bytes)
+ return max_bytes
+
+ def allocate(self):
+ """
+ Handle memory request issued by operators.
+ """
+ if self._allocated:
+ return
+ assert not self._allocated, 'Memory requests were already allocated.'
+ for backend in self._all_requests_per_backend.keys():
+ self._allocate_on_backend(backend)
+ self._allocated = True
+
+ def _allocate_on_backend(self, backend):
+ views = self._allocated_buffers
+ op_requests = self._all_requests_per_backend[backend]
+ check_instance(views, dict)
+ check_instance(op_requests, dict)
+
+ total_bytes = self.min_bytes_to_allocate(backend)
+ if total_bytes == 0:
+ return
+
+ data = backend.empty(shape=(total_bytes,), dtype=np.uint8)
+ ptr = data.data.int_ptr
+
+ for op,requests in op_requests.iteritems():
+ check_instance(requests, list, values=MemoryRequest)
+ start_idx = 0
+ for req in requests:
+ req_views = []
+ size = req.data_bytes_per_component()
+ for i in xrange(req.ncomponents):
+ align_offset = (-ptr % req.alignment)
+ start_idx += align_offset
+ end_idx = start_idx + size
+
+ view = data[start_idx:end_idx].view(dtype=req.dtype).reshape(req.shape)
+ req_views.append(view)
+
+ start_idx = end_idx
+ ptr += align_offset + size
+ if op not in views:
+ views[op] = {}
+ if req.ncomponents>1:
+ views[op][req.id] = tuple(req_views)
+ else:
+ views[op][req.id] = req_views[0]
+ assert end_idx <= total_bytes
+
+ def get_buffer(self, operator, request_identifier):
+ if not self._allocated:
+ msg='Memory request have not been allocated yet.'
+ raise RuntimeError(msg)
+ if operator not in self._allocated_buffers:
+ msg='Operator {} did not request any extra memory.'
+ msg=msg.format(operator)
+ raise RuntimeError(msg)
+ op_buffers = self._allocated_buffers[operator]
+ if request_identifier not in op_buffers:
+ msg='Unknown request identifier {} for operator {}.'
+ msg=msg.format(request_identifier, operator)
+ raise ValueError(msg)
+ return op_buffers[request_identifier]
+
+ def __str__(self):
+ s=''
+ for backend, backend_requests in self._all_requests_per_backend.iteritems():
+ kind = backend.kind
+ if kind == Backend.OPENCL:
+ precision = ' on device {}'.format(backend.device.name)
+ else:
+ precision = ''
+ s+= ' Backend {}{}:'.format(kind, precision)
+ total=0
+ for op,op_requests in backend_requests.iteritems():
+ s+= '\n Operator {} ({})'.format(op.name, op.__class__.__name__)
+ local_total=0
+ for req in op_requests:
+ s+= '\n *{}'.format(req)
+ local_total+=req.max_bytes()
+ if local_total>total:
+ total=local_total
+ s +='\n Total work requested: {} ({})'.format(
+ bytes2str(total,decimal=False),
+ bytes2str(total,decimal=True))
+ s +='\n'
+ return s[:-1]
+
diff --git a/hysop/core/memory/mempool.py b/hysop/core/memory/mempool.py
new file mode 100644
index 0000000000000000000000000000000000000000..836d9bfb3e2c504703f255d6a361754628a11da5
--- /dev/null
+++ b/hysop/core/memory/mempool.py
@@ -0,0 +1,546 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.deps import math, six
+from hysop.constants import __VERBOSE__
+from hysop.backend import __HAS_OPENCL_BACKEND__, __HAS_CUDA_BACKEND__
+from hysop.tools.units import bytes2str, time2str
+from hysop.tools.types import check_instance
+from hysop.tools.contexts import Timer
+from hysop.core.memory.mem_utils import memory_repport, virtual_memory
+from hysop.core.memory.buffer import Buffer, PooledBuffer
+from hysop.core.memory.allocator import AllocatorBase
+
+if __HAS_OPENCL_BACKEND__:
+ from pyopencl.tools import bitlog2
+elif __HAS_CUDA_BACKEND__:
+ from pycuda.tools import bitlog2
+else:
+ def bitlog2(x):
+ assert x>0
+ p=0
+ while(x):
+ p+=1
+ x>>=1
+ return p-1
+
+
+class MemoryPool(object):
+ """
+ pyopencl/pycuda like memory pool extended to be compatible for all backends.
+ """
+
+ __metaclass__ = ABCMeta
+
+ def __init__(self, name, allocator, max_alloc_bytes=None,
+ mantissa_bits=4, verbose=None, **kwds):
+ """
+ Builds a MemoryPool from an allocator.
+ Provides an allocator like interface.
+
+ Parameters
+ ----------
+ name: str
+ the name of this allocator for logging purposes
+ allocator: hysop.core.memory.AllocatorBase
+ allocator used by this memory pool, must be an immediate allocator.
+ verbose: bool
+ turn on or off allocator messages (defaults to hysop verbosity configuration)
+ max_alloc_bytes: int
+ maximum number of bytes this pool will try to allocate before raising a MemoryError.
+ default value is:
+ -80% of physical host memory if allocator is a HostAllocator.
+ -None (no limit) if allocator is a DeviceAllocator
+ mantissa_bits: int
+ subdivisions bits of power of two allocations.
+ higher values means more bins (less memory waste) but less buffer reuse.
+
+ Notes
+ -----
+ An allocator that fails to allocate memory should raise a MemoryError
+ to expect the pool to work correctly.
+
+ Some allocators may fail to raise a MemoryError when there is no more memory
+ left and will just trigger a SIGKILL from operating system or deadlock instead.
+ To avoid such situations, put an artificial software allocation imit trough the
+ max_alloc_bytes parameter. Exceeding this allocation limit will throw a proper
+ MemoryError.
+
+ Examples:
+ *Host allocation on ubuntu 16.04 => SIGKILL
+ *OpenCl AMD mesa open source driver on ubuntu 16.04 => deadlock
+ *OpenCl Nvidia 375.20 driver on ubuntu 16.04 => work as expected
+ """
+ super(MemoryPool, self).__init__(**kwds)
+
+ check_instance(allocator, AllocatorBase)
+ default_limit = int(0.80*virtual_memory().total) if allocator.is_on_host() else None
+
+ max_alloc_bytes = max_alloc_bytes or default_limit
+ verbose = verbose if isinstance(verbose,bool) else __VERBOSE__
+
+ check_instance(name, str)
+ check_instance(mantissa_bits, int)
+ check_instance(max_alloc_bytes,(int,long), allow_none=True)
+ check_instance(verbose, bool)
+
+ self.name = name
+ self.allocator = allocator
+ self.verbose = verbose
+
+ self.bin_nr_to_bin = {}
+ self.alloc_statistics = {}
+
+ self.mantissa_bits = mantissa_bits
+ self.mantissa_mask = (1 << mantissa_bits) - 1
+
+ self.allocated_bytes = 0
+ self.max_alloc_bytes = max_alloc_bytes
+
+ if self.allocator.is_deferred:
+ msg = ("Memory pools expect non-deferred "
+ "semantics from their allocators. You passed a deferred "
+ "allocator, i.e. an allocator whose allocations can turn out to "
+ "be unavailable long after allocation.")
+ raise RuntimeError(msg)
+
+ self.active_blocks = 0
+ self.stop_holding_flag = False
+
+ @abstractmethod
+ def _wrap_buffer(self, buf, alloc_sz, size, alignment):
+ """
+ Wrap allocated buffer into a PooledBuffer.
+ """
+ pass
+
+ def may_alloc(self, size):
+ """
+ Return true if this pool may allocate a buffer of given size (in bytes).
+ Only logical bound is checked (max_alloc_bytes).
+ """
+ alloc_sz = alloc_size(bin_number(size))
+ return self._may_alloc(alloc_sz)
+
+ def _may_alloc(self, alloc_sz):
+ if (self.max_alloc_bytes is None):
+ return True
+ else:
+ return (self.allocated_bytes + alloc_sz <= self.max_alloc_bytes)
+
+ def bin_number(self, size):
+ """
+ Returns the bin number in witch a buffer of given size would be put.
+ """
+ l = bitlog2(size)
+
+ mantissa_bits = self.mantissa_bits
+ if l >= mantissa_bits:
+ shifted = size >> (l - mantissa_bits)
+ else:
+ shifted = size << (mantissa_bits - l)
+
+ assert not (size and (shifted & (1 << mantissa_bits)) == 0)
+
+ chopped = shifted & self.mantissa_mask
+
+ return l << mantissa_bits | chopped
+
+ def alloc_size(self, bin_nr):
+ """
+ Compute real allocation size given an bin number.
+ Note that alloc_size(bin_number(x)) is always >= x.
+ """
+ mantissa_bits = self.mantissa_bits
+
+ exponent = bin_nr >> mantissa_bits
+ mantissa = bin_nr & self.mantissa_mask
+
+ exp_minus_mbits = exponent-mantissa_bits
+ if exp_minus_mbits >= 0:
+ ones = (1 << exp_minus_mbits) - 1
+ head = ((1 << mantissa_bits) | mantissa) << exp_minus_mbits
+ else:
+ ones = 0
+ head = ((1 << mantissa_bits) | mantissa) >> -exp_minus_mbits
+
+ assert not (ones & head)
+ return head | ones
+
+ def stop_holding(self):
+ """
+ Tells the pool to stop holding back freed buffer
+ and direclty free all unused buffers.
+ """
+ self.stop_holding_flag = True
+ self.free_held()
+
+ def free_held(self):
+ """
+ Free all unused held buffers but does not set
+ the stop_holding_flag flag.
+ """
+ for _ in self._try_to_free_memory():
+ pass
+
+ @property
+ def held_blocks(self):
+ """
+ Returns the number of held blocks.
+ """
+ return sum(len(bin_list)
+ for bin_list in six.itervalues(self.bin_nr_to_bin))
+
+ def header(self):
+ """
+ Return the header of this pool for logging purposes.
+ """
+ return '[{}]'.format(self.name)
+
+ def allocate_aligned(self, size, alignment):
+ """
+ Same as allocate for a memory pool.
+ """
+ return self.allocate(nbytes=size, alignment=alignment)
+
+ def allocate(self, nbytes, alignment=None):
+ """
+ Allocate a buffer of size nbytes and given alignment.
+ The real size of the allocated buffer may be greater and wasted memory mostly
+ depend on configured mantissa_bits (default is 2).
+ The returned buffer is an instance of hysop.core.memory.buffer.PooledBuffer.
+ While a reference to the returned object is kept, it won't return to the pool.
+ """
+
+ alignment = alignment or 1
+ assert alignment>0
+ assert not (alignment & alignment-1), 'alignment is not a power of 2.'
+
+ # we may need more memory to align returned ptr
+ min_alloc_size = nbytes + alignment - 1
+
+ # maybe bin allocation size will be sufficient
+ bin_nr = self.bin_number(nbytes)
+ alloc_sz = self.alloc_size(bin_nr)
+
+ # else we choose a bin that can provide min_alloc_size bytes
+ if (alloc_sz < min_alloc_size):
+ bin_nr = self.bin_number(min_alloc_size)
+ alloc_sz = self.alloc_size(bin_nr)
+
+ bin_list = self.bin_nr_to_bin.setdefault(bin_nr, [])
+ assert self.bin_number(alloc_sz) == bin_nr
+
+ size = nbytes
+ stat_nr = bitlog2(size)
+ statistic = self.alloc_statistics.setdefault(stat_nr, PoolAllocationStatistics())
+
+ verbose = self.verbose
+ if bin_list:
+ if verbose:
+ msg='{} allocation request of size {} served from bin {}.'
+ # which contained {} entries.'
+ msg=msg.format(self.header(),
+ bytes2str(size,decimal=False),
+ bin_nr)
+ #len(bin_list))
+ print msg
+ self.active_blocks += 1
+ statistic.push_reuse(alloc_sz)
+ return self._wrap_buffer(bin_list.pop(), alloc_sz, size, alignment)
+
+ if self._may_alloc(alloc_sz):
+ try:
+ with Timer() as t:
+ result = self.allocator(alloc_sz)
+ self.active_blocks += 1
+ self.allocated_bytes += alloc_sz
+ statistic.push_alloc(alloc_sz, t.interval)
+ if verbose:
+ msg='{} allocated new block of size {} to serve a {} request.'
+ msg=msg.format(self.header(),
+ bytes2str(alloc_sz, decimal=False),
+ bytes2str(size, decimal=False))
+ print msg
+
+ return self._wrap_buffer(result, alloc_sz, size, alignment)
+ except MemoryError as e:
+ if verbose:
+ msg='{} allocation of size {} failed, freeing unused blocks.'
+ msg=msg.format(self.header(), bytes2str(alloc_sz, decimal=False))
+ print msg
+ else:
+ prefix = ' '*len(self.header())
+ allocated_bytes = self.allocated_bytes
+ max_alloc_bytes = self.max_alloc_bytes
+ available = max_alloc_bytes - allocated_bytes
+ msg='{} allocating {} would exceed pool max allocation limits:'
+ msg+='\n{p} *current {}'
+ msg+='\n{p} *max {}'
+ msg+='\n{p} *available {}'
+ msg+='\n{p} => trying to free unused blocks before allocation.'
+ msg=msg.format(self.header(),
+ bytes2str(alloc_sz, decimal=False),
+ bytes2str(allocated_bytes, decimal=False),
+ bytes2str(max_alloc_bytes, decimal=False),
+ bytes2str(available, decimal=False),
+ p=prefix)
+ print msg
+
+ freed_bytes = 0
+ try_last_alloc = False
+ for fb in self._try_to_free_memory():
+ may_alloc = self._may_alloc(alloc_sz)
+ if (fb is None):
+ #all unused block were freed, last chance to allocate
+ if may_alloc:
+ try_last_alloc = True
+ else:
+ prefix = ' '*len(self.header())
+ allocated_bytes = self.allocated_bytes
+ max_alloc_bytes = self.max_alloc_bytes
+ available = max_alloc_bytes - allocated_bytes
+ msg='{} all unused blocks freed but allocation would '
+ msg+='still exceed pool limits:'
+ msg+='\n{p} *current {}'
+ msg+='\n{p} *max {}'
+ msg+='\n{p} *available {}'
+ msg=msg.format(self.header(),
+ bytes2str(allocated_bytes, decimal=False),
+ bytes2str(max_alloc_bytes, decimal=False),
+ bytes2str(available, decimal=False),
+ p=prefix)
+ print msg
+ else:
+ freed_bytes += fb
+
+ if ((freed_bytes>=alloc_sz) and may_alloc) or try_last_alloc:
+ try:
+ with Timer() as t:
+ result = self.allocator(alloc_sz)
+ self.active_blocks += 1
+ self.allocated_bytes += alloc_sz
+ statistic.push_alloc(alloc_sz, t.interval)
+ if verbose:
+ msg='{} allocation succeded after block destruction.'
+ msg=msg.format(self.header())
+ print msg
+ return (self, result, alloc_sz, size, alignment)
+ except MemoryError:
+ pass
+
+ msg='{} no more free blocks left, allocation failed.'
+ msg=msg.format(self.header())
+
+ print msg
+ print
+ print memory_repport()
+
+ if statistic.nallocs==0:
+ self.alloc_statistics.pop(stat_nr)
+ self.print_allocation_report()
+
+ raise MemoryError(msg)
+
+ __call__ = allocate
+
+ def free(self, buf, size):
+ bin_nr = self.bin_number(size)
+ stat_nr = bitlog2(size)
+ statistics = self.alloc_statistics[stat_nr]
+ self.active_blocks -= 1
+
+ if not self.stop_holding_flag:
+ self.bin_nr_to_bin.setdefault(bin_nr, []).append(buf)
+
+ if self.verbose:
+ msg = '{} block of size {} returned to bin {}.'# wich now contains {} entries.'
+ msg = msg.format(self.header(), bytes2str(size,decimal=False), bin_nr)
+ #len(self.bin_nr_to_bin[bin_nr]))
+ print msg
+ statistics.push_return(size)
+ else:
+ if self.verbose:
+ msg = '{} freeing block of size {} in bin {}.'
+ msg = msg.format(self.header(), bytes2str(size), bin_nr)
+ print msg
+ with Timer() as t:
+ self.allocator.free(buf)
+ self.allocated_bytes -= size
+ statistics.push_free(size, t.interval)
+
+ def _try_to_free_memory(self):
+ for bin_nr, bin_list in six.iteritems(self.bin_nr_to_bin):
+ if not bin_list:
+ continue
+ size = bin_list[0].size
+ stat_nr = bitlog2(size)
+ statistics = self.alloc_statistics[stat_nr]
+ while bin_list:
+ block = bin_list.pop()
+ if self.verbose:
+ msg = '{} freeing block of size {}.'
+ msg=msg.format(self.header(), bytes2str(size,decimal=False))
+ print msg
+ with Timer() as t:
+ self.allocator.free(block)
+ self.allocated_bytes -= size
+ statistics.push_free(size, t.interval)
+ yield size
+ yield None
+
+
+ def allocation_report(self):
+ """
+ Returns various statistics of this pool as a string.
+ """
+
+ stats = self.alloc_statistics.values()
+
+ nrequests = sum(v.nrequests for v in stats)
+ nallocs = sum(v.nallocs for v in stats)
+ nreuses = sum(v.nreuses for v in stats)
+ nreturns = sum(v.nreturns for v in stats)
+ nfrees = sum(v.nfrees for v in stats)
+
+ ballocs = sum(v.ballocs for v in stats)
+ breuses = sum(v.breuses for v in stats)
+ bfrees = sum(v.bfrees for v in stats)
+ breturns = sum(v.breturns for v in stats)
+
+ active_blocks = self.active_blocks
+ held_blocks = self.held_blocks
+ allocated_bytes = self.allocated_bytes
+
+ assert active_blocks+held_blocks == nallocs-nfrees
+ assert allocated_bytes == ballocs - bfrees
+ assert active_blocks == nallocs+nreuses-nreturns
+ assert held_blocks == nreturns-nreuses-nfrees
+ assert nrequests == nallocs + nreuses
+
+ width=0
+ for n in [active_blocks,held_blocks,nrequests,nallocs,nreuses,nfrees]:
+ if n==0:
+ continue
+ width=max(width,int(math.ceil(math.log10(n))))
+ ss = '== Memory pool {} allocation report =='.format(self.name)
+ ss += '\n Global pool statistics:'
+ ss += '\n {:>{width}} blocks active {} ({})'.format(active_blocks,
+ bytes2str(ballocs+breuses-breturns, decimal=False),
+ bytes2str(ballocs+breuses-breturns), width=width)
+ ss += '\n {:>{width}} blocks held {} ({})'.format(held_blocks,
+ bytes2str(breturns-breuses-bfrees, decimal=False),
+ bytes2str(breturns-breuses-bfrees), width=width)
+ ss += '\n'
+ ss += '\n {:>{width}} blocks requested {} ({})'.format(nrequests,
+ bytes2str(ballocs+breuses, decimal=False),
+ bytes2str(ballocs+breuses), width=width)
+ ss += '\n {:>{width}} blocks reused {} ({})'.format(nreuses,
+ bytes2str(breuses, decimal=False),
+ bytes2str(breuses), width=width)
+ ss += '\n {:>{width}} blocks allocated {} ({})'.format(nallocs,
+ bytes2str(ballocs, decimal=False),
+ bytes2str(ballocs), width=width)
+ ss += '\n {:>{width}} blocks freed {} ({})'.format(nfrees,
+ bytes2str(bfrees, decimal=False),
+ bytes2str(bfrees), width=width)
+ ss += '\n'
+ ss += '\n Detailed pool statistics:'
+ has_stats=False
+ for stat_nr, stat in self.alloc_statistics.iteritems():
+ has_stats=True
+ ss += '\n {:>10} <{} x <= {:<10} => {}'.format(
+ bytes2str(2**(stat_nr), decimal=False),
+ '=' if stat_nr==0 else ' ',
+ bytes2str(2**(stat_nr+1), decimal=False),
+ stat)
+ if not has_stats:
+ ss += '\n *no allocated blocks*'
+ ss += '\n\n Held blocks:'
+ has_block = False
+ for bin_nr in sorted(self.bin_nr_to_bin.keys()):
+ blocks = self.bin_nr_to_bin[bin_nr]
+ nblocks = len(blocks)
+ if nblocks == 0:
+ continue
+ has_block = True
+ mean_bytes = sum([b.size for b in blocks]) / nblocks
+ ss += '\n *bin {}: nblocks={} mean_block_size={}'.format(bin_nr, nblocks,
+ bytes2str(mean_bytes))
+ if not has_block:
+ ss += '\n *no held blocks, all blocks are in use*'
+ ss += '\n=========================================='
+ return ss
+
+ def print_allocation_report(self):
+ """
+ Print various statistics of this pool.
+ """
+ print
+ print self.allocation_report()
+ print
+
+class PoolAllocationStatistics(object):
+ def __init__(self):
+ #counters
+ self.nrequests = 0
+ self.nallocs = 0
+ self.nfrees = 0
+ self.nreturns = 0
+ self.nreuses = 0
+
+ # bytes
+ self.ballocs = 0
+ self.bfrees = 0
+ self.breuses = 0
+ self.breturns = 0
+
+ # profiling
+ self.tallocs = 0
+ self.tfrees = 0
+
+ def push_alloc(self, size, t):
+ self.nrequests += 1
+ self.nallocs += 1
+ self.ballocs += size
+ self.tallocs += t
+ def push_reuse(self, size):
+ assert self.nallocs>0
+ self.nrequests += 1
+ self.nreuses += 1
+ self.breuses += size
+ def push_return(self, size):
+ assert self.nallocs>0
+ self.nreturns += 1
+ self.breturns += size
+ def push_free(self, size, t):
+ assert self.nallocs>0
+ self.nfrees += 1
+ self.bfrees += size
+ self.tfrees += t
+
+ def reuse_factor(self):
+ if self.nallocs>0:
+ return float(self.nreuses) / self.nrequests
+ else:
+ return 0
+
+ def mean_alloc_time(self):
+ if self.nallocs>0:
+ return self.tallocs / self.nallocs
+ else:
+ return 0
+ def mean_free_time(self):
+ if self.nfrees>0:
+ return self.tfrees / self.nfrees
+ else:
+ return 0
+
+ def __str__(self):
+ ss = '{:>4} requests | {:>4} reuse | {} allocs | {} frees'.format(
+ self.nrequests,
+ '{}%'.format(int(self.reuse_factor()*1000)/10.0) if self.nreuses else ' no',
+ time2str(self.mean_alloc_time(), on_zero=' no'),
+ time2str(self.mean_free_time(), on_zero=' no'))
+ return ss
+
+
diff --git a/hysop/core/memory/tests/test_allocator.py b/hysop/core/memory/tests/test_allocator.py
new file mode 100644
index 0000000000000000000000000000000000000000..919e65bc553e904bd082587053ae42408308ce63
--- /dev/null
+++ b/hysop/core/memory/tests/test_allocator.py
@@ -0,0 +1,49 @@
+
+from hysop.backend import __HAS_OPENCL_BACKEND__, __HAS_CUDA_BACKEND__
+from hysop.backend.host.host_allocator import HostAllocator
+
+sizes = (1,89,7919,32*1024*1024)
+alignments = (1,2,4,8,16,32,64,128,256,512,1024)
+
+def test_host_allocator():
+ allocator = HostAllocator()
+
+ for nbytes in sizes:
+ for alignment in alignments:
+ buf = allocator.allocate(nbytes)
+ assert buf.size == nbytes
+ buf = allocator(nbytes)
+ assert buf.size == nbytes
+ buf = allocator.allocate_aligned(nbytes, alignment)
+ assert buf.size == nbytes
+ assert buf.int_ptr % alignment == 0
+ buf = allocator(nbytes, alignment)
+ assert buf.size == nbytes
+ assert buf.int_ptr % alignment == 0
+
+if __HAS_OPENCL_BACKEND__:
+ from hysop.backend.device.opencl import cl
+ from hysop.backend.device.opencl.opencl_allocator import OpenClImmediateAllocator, \
+ OpenClDeferredAllocator
+ from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+
+ cl_env = get_or_create_opencl_env()
+
+ def test_opencl_immediate_allocator():
+ allocator = OpenClImmediateAllocator(cl_env.default_queue)
+ for nbytes in sizes:
+ buf = allocator.allocate(nbytes)
+ assert buf.size == nbytes
+
+ def test_opencl_deferred_allocator():
+ allocator = OpenClDeferredAllocator(cl_env.default_queue)
+ for nbytes in sizes:
+ buf = allocator.allocate(nbytes)
+ cl.enqueue_barrier(cl_env.default_queue)
+ assert buf.size == nbytes
+
+if __name__ == '__main__':
+ test_host_allocator()
+ if __HAS_OPENCL_BACKEND__:
+ test_opencl_immediate_allocator()
+ test_opencl_deferred_allocator()
diff --git a/hysop/core/memory/tests/test_buffer.py b/hysop/core/memory/tests/test_buffer.py
new file mode 100644
index 0000000000000000000000000000000000000000..e7bcd97182a99643aaef5887f7a5668dbbbc27b1
--- /dev/null
+++ b/hysop/core/memory/tests/test_buffer.py
@@ -0,0 +1,144 @@
+
+from hysop.deps import np
+from hysop.backend.host.host_buffer import HostBuffer
+from hysop.backend import __HAS_OPENCL_BACKEND__, __HAS_CUDA_BACKEND__
+
+size = 32*1024*1024 # 32Mo
+
+def test_host_buffer():
+ buf1 = HostBuffer(size=size)
+ assert buf1.get_int_ptr() == buf1.int_ptr
+ assert buf1.get_size() == buf1.size
+ assert buf1.get_buffer() is buf1.buf
+
+ buf2 = HostBuffer(size=size)
+ assert buf1.int_ptr != buf2.int_ptr
+ assert buf1.size == size
+ assert buf1.size == buf2.size
+
+ arr1 = np.frombuffer(buf1, dtype=np.uint8)
+ arr2 = np.frombuffer(buf2, dtype=np.uint8)
+ arr1.fill(0)
+ arr2.fill(1)
+ assert (arr1==0).all()
+ assert (arr2==1).all()
+
+ buf2 = HostBuffer.from_buffer(buf1)
+ assert buf1.int_ptr == buf2.int_ptr
+ assert buf1.size == buf2.size
+
+ buf3 = HostBuffer.from_int_ptr(buf2.int_ptr, buf2.size)
+ assert buf1.int_ptr == buf3.int_ptr
+ assert buf1.size == buf3.size
+
+ arr1 = np.frombuffer(buf1, dtype=np.uint8)
+ arr2 = np.frombuffer(buf2, dtype=np.uint8)
+ arr3 = np.frombuffer(buf3, dtype=np.uint8)
+ arr1.fill(0)
+ assert (arr1==0).all()
+ assert (arr2==0).all()
+ assert (arr3==0).all()
+ arr2.fill(1)
+ assert (arr1==1).all()
+ assert (arr2==1).all()
+ assert (arr3==1).all()
+ arr3.fill(2)
+ assert (arr1==2).all()
+ assert (arr2==2).all()
+ assert (arr3==2).all()
+ buf1.release()
+ arr1.fill(0)
+ assert (arr1==0).all()
+ assert (arr2==0).all()
+ assert (arr3==0).all()
+ buf2.release()
+ arr2.fill(1)
+ assert (arr1==1).all()
+ assert (arr2==1).all()
+ assert (arr3==1).all()
+ buf3.release()
+ arr3.fill(2)
+ assert (arr1==2).all()
+ assert (arr2==2).all()
+ assert (arr3==2).all()
+ del arr1
+ arr3.fill(12)
+ assert (arr2==12).all()
+ assert (arr3==12).all()
+ del arr3
+ arr2.fill(42)
+ assert(arr2==42).all()
+ del arr2
+
+if __HAS_OPENCL_BACKEND__:
+ from hysop.backend.device.opencl import cl
+ from hysop.backend.device.opencl.opencl_buffer import OpenClBuffer
+ from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+
+ cl_env = get_or_create_opencl_env()
+
+ def test_opencl_buffer():
+ mf = cl.mem_flags
+
+ buf = cl.Buffer(cl_env.context, size=size, flags=mf.READ_ONLY)
+
+ buf1 = OpenClBuffer(cl_env.context, size=size, mem_flags=mf.READ_WRITE)
+ assert buf1.int_ptr == buf1.get_int_ptr()
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf1,
+ byte_count=size).wait()
+
+ assert buf1.ref_count() == 1
+ buf1.release()
+
+ buf1 = OpenClBuffer(cl_env.context, size=size, mem_flags=mf.READ_WRITE)
+ assert buf1.ref_count() == 1
+ buf2 = OpenClBuffer.from_cl_buffer(buf1)
+ assert buf1.ref_count() == 2
+ assert buf2.ref_count() == 2
+ assert buf1.int_ptr == buf2.int_ptr
+ buf3 = OpenClBuffer.from_int_ptr(buf1.int_ptr, retain=True)
+ assert buf1.ref_count() == 3
+ assert buf2.ref_count() == 3
+ assert buf3.ref_count() == 3
+ assert buf1.int_ptr == buf2.int_ptr
+ assert buf1.int_ptr == buf3.int_ptr
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf1,
+ byte_count=size).wait()
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
+ byte_count=size).wait()
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf3,
+ byte_count=size).wait()
+ buf1.release()
+ assert buf2.ref_count() == 2
+ assert buf3.ref_count() == 2
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
+ byte_count=size).wait()
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf3,
+ byte_count=size).wait()
+ buf3.release()
+ assert buf2.ref_count() == 1
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
+ byte_count=size).wait()
+ buf2.release()
+
+
+ def test_opencl_host_device_buffer():
+ mf = cl.mem_flags
+
+ # try to alloc pinned memory
+ buf = OpenClBuffer(cl_env.context, size=size, mem_flags=mf.ALLOC_HOST_PTR, hostbuf=None)
+
+ # try to use unified memory (or something like zero copy memory)
+ hbuf = np.ndarray(shape=size, dtype=np.float32)
+ buf = OpenClBuffer(cl_env.context, mem_flags=mf.USE_HOST_PTR, hostbuf=hbuf)
+
+ # copy host buf at creation
+ hbuf = np.ndarray(shape=(1024,1024,), dtype=np.int64)
+ buf = OpenClBuffer(cl_env.context, mem_flags=mf.COPY_HOST_PTR, hostbuf=hbuf)
+
+
+if __name__ == '__main__':
+ test_host_buffer()
+ if __HAS_OPENCL_BACKEND__:
+ test_opencl_buffer()
+ test_opencl_host_device_buffer()
diff --git a/hysop/core/memory/tests/test_mempool.py b/hysop/core/memory/tests/test_mempool.py
new file mode 100644
index 0000000000000000000000000000000000000000..64e1f07fae9dbe11fa05420571ff164a54fabddd
--- /dev/null
+++ b/hysop/core/memory/tests/test_mempool.py
@@ -0,0 +1,40 @@
+
+from hysop.deps import np
+from hysop.testsenv import opencl_failed, iter_clenv, \
+ __HAS_OPENCL_BACKEND__, __ENABLE_LONG_TESTS__
+from hysop.core.memory.mempool import MemoryPool
+
+import random
+max_bytes_per_alloc = 1024*1024*128 # 128MB
+free = lambda: bool(random.random()>0.1) # 80% probability of free
+nbytes = lambda: int(2.0**(np.log2(max_bytes_per_alloc)*random.random()))
+
+def test_mempool_python_allocator():
+ from hysop.backend.host.host_allocator import HostAllocator
+ allocator = HostAllocator()
+ _test_mempool_allocator('python', allocator)
+
+@opencl_failed
+def test_mempool_opencl_immediate_allocator():
+ from hysop.backend.device.opencl.opencl_allocator import OpenClImmediateAllocator
+
+ for cl_env in iter_clenv():
+ allocator = OpenClImmediateAllocator(cl_env.default_queue)
+ _test_mempool_allocator(cl_env.platform.name, allocator)
+
+def _test_mempool_allocator(name, allocator):
+ pool = allocator.memory_pool(name=name, verbose=True)
+ buffers = []
+ try:
+ while True:
+ size = nbytes()
+ buf = pool.allocate(size)
+ if not free():
+ buffers.append(buf)
+ except MemoryError:
+ pass
+
+if __name__ == '__main__':
+ test_mempool_python_allocator()
+ if __HAS_OPENCL_BACKEND__:
+ test_mempool_opencl_immediate_allocator()
diff --git a/hysop/core/mpi/__init__.py b/hysop/core/mpi/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..f931e70aea6eb7558f3b36d064dbadac8a95a584
--- /dev/null
+++ b/hysop/core/mpi/__init__.py
@@ -0,0 +1,96 @@
+"""Hysop interface to the mpi implementation.
+
+It contains :
+
+* mpi basic variables (main communicator, rank, size ...)
+* :class:`hysop.core.mpi.topology.Cartesian` : mpi process distribution + local mesh
+
+
+This package is used to hide the underlying mpi interface
+in order to make any change of this interface, if required, easiest.
+
+At this time we use mpi4py : http://mpi4py.scipy.org
+
+"""
+
+# Everything concerning the chosen mpi implementation is hidden from hysop
+# main interface.
+# Why? --> to avoid that things like mpi4py. ... spread everywhere in the
+# soft so to ease a change of this implementation (if needed).
+import hashlib
+from mpi4py import MPI as MPI
+"""MPI interface"""
+
+processor_name = MPI.Get_processor_name()
+"""MPI processor name"""
+processor_hash = int(hashlib.sha1(processor_name).hexdigest(), 16) % (1<<31)
+"""MPI hashed processor name as integer (fits into a 32bit signed integer)"""
+
+main_comm = MPI.COMM_WORLD.Dup()
+"""Main communicator"""
+main_rank = main_comm.Get_rank()
+"""Rank of the current process in main communicator"""
+main_size = main_comm.Get_size()
+"""Number of mpi process in main communicator"""
+
+shm_comm = main_comm.Split_type(MPI.COMM_TYPE_SHARED, main_rank)
+"""Shared memory communicator"""
+shm_rank = shm_comm.Get_rank()
+"""Shared memory process id in shm_comm (ie. NUMA node id)"""
+shm_size = shm_comm.Get_size()
+"""Shared memory process count in shm_comm (ie. NUMA nodes count)"""
+
+intershm_comm = main_comm.Split(color=int(shm_rank==0), key=main_rank)
+"""Communicator between shared memory local master ranks"""
+
+if shm_rank!=0:
+ intershm_comm.Free()
+ intershm_comm = None
+ intershm_rank = None
+ intershm_size = None
+ is_multishm = False
+else:
+ intershm_rank = intershm_comm.Get_rank()
+ """Communicator rank between shm masters"""
+ intershm_size = intershm_comm.Get_size()
+ """Communicator size between shm masters"""
+ is_multishm = (intershm_size>1)
+ """True if shm_rank=0 and the programm runs on different shared memory communicators"""
+
+host_comm = main_comm.Split(color=processor_hash, key=main_rank)
+"""Intrahost communicator"""
+host_rank = host_comm.Get_rank()
+"""Intrahost rank"""
+host_size = host_comm.Get_size()
+"""Intrahost size"""
+
+interhost_comm = main_comm.Split(color=int(host_rank==0), key=main_rank)
+"""Interhost communicator (between each host local master rank)"""
+
+if host_rank!=0:
+ interhost_comm.Free()
+ interhost_comm = None
+ interhost_rank = None
+ interhost_size = None
+ is_multihost = False
+else:
+ interhost_rank = interhost_comm.Get_rank()
+ """Communicator rank between hosts"""
+ interhost_size = interhost_comm.Get_size()
+ """Communicator size between hosts"""
+ is_multihost = (interhost_size>1)
+ """True if host_rank=0 and the programm runs on different hosts"""
+
+Wtime = MPI.Wtime
+"""Function to return elapsed time since some time in the past.
+Usage:
+tref = Wtime()
+# proceed with some computations ...
+elapsed = Wtime() - tref
+# -> elapsed == time for 'some computations' on the current mpi process
+"""
+
+if main_rank==0:
+ assert shm_rank==0
+ assert host_rank==0
+ assert interhost_rank==0
diff --git a/hysop/mpi/bridge.py b/hysop/core/mpi/bridge.py
similarity index 95%
rename from hysop/mpi/bridge.py
rename to hysop/core/mpi/bridge.py
index e5d799771bb2ab7da7c5cb878bab97e4a9281d9f..91f1dd576ea196cf7ffa2b96bedbe7b38c34c259 100644
--- a/hysop/mpi/bridge.py
+++ b/hysop/core/mpi/bridge.py
@@ -1,6 +1,6 @@
"""Tools to compute the intersection between two topologies.
-`.. currentmodule : hysop.mpi.bridge
+`.. currentmodule : hysop.core.mpi.bridge
* :class:`~Bridge` for topologies/operators defined
inside the same mpi communicator
@@ -10,15 +10,15 @@
with a different number of processes
"""
-from hysop.mpi.topology import Cartesian, TopoTools
+from hysop.core.mpi.topology import Cartesian, TopoTools
from hysop.tools.misc import Utils
-from hysop.mpi import MPI
-import hysop.tools.numpywrappers as npw
+from hysop.core.mpi import MPI
+from hysop.tools.numpywrappers import npw
class Bridge(object):
"""
- todo
+ Intersection between two topologies.
"""
def __init__(self, source, target):
@@ -27,14 +27,14 @@ class Bridge(object):
Parameters
----------
- source, target : :class:`~hysop.mpi.topology.Cartesian`
+ source, target : :class:`~hysop.core.mpi.topology.Cartesian`
topologies that own the source mesh and targeted mesh
"""
- # -- All dictionnaries belows used rank number (in parent comm)
+ # -- All dictionnaries below use rank number (in parent comm)
# as keys. --
# Dictionnary of indices of grid points to be received on target.
self._recv_indices = {}
- # Dictionnary of indices of grid points to be sent from sourceId
+ # Dictionnary of indices of grid points to be sent from current rank
self._send_indices = {}
# Dictionnary of MPI derived types used for MPI receive
self._recv_types = None
@@ -57,7 +57,6 @@ class Bridge(object):
def _check_topologies(self):
"""Check if source/target topologies exists and are complient"""
- msg = 'Bridge error, one or both topologies are None.'
msg = 'Bridge error, input source/target must be topologies.'
assert isinstance(self._source, Cartesian), msg
assert isinstance(self._target, Cartesian), msg
@@ -172,7 +171,7 @@ class BridgeInter(object):
Parameters
----------
- current : :class:`~hysop.mpi.topology.Cartesian`
+ current : :class:`~hysop.core.mpi.topology.Cartesian`
parent : MPI.COMM
mpi communicator that must owns all the
processes involved in source and target.
@@ -264,20 +263,20 @@ class BridgeInter(object):
if current_task is self.source_id:
# Local 0 broadcast current_indices to remote comm
if rank == 0:
- self.comm.bcast(current_indices, root=MPI.ROOT)
+ self.comm.bcast(current_indices.handle(), root=MPI.ROOT)
else:
- self.comm.bcast(current_indices, root=MPI.PROC_NULL)
+ self.comm.bcast(current_indices.handle(), root=MPI.PROC_NULL)
# Get remote indices from remote comm
remote_indices = self.comm.bcast(remote_indices, root=0)
elif current_task is self.target_id:
# Get remote indices from remote comm
- remote_indices = self.comm.bcast(remote_indices, root=0)
+ remote_indices = self.comm.bcast(remote_indices.handle(), root=0)
# Local 0 broadcast current_indices to remote comm
if rank == 0:
- self.comm.bcast(current_indices, root=MPI.ROOT)
+ self.comm.bcast(current_indices.handle(), root=MPI.ROOT)
else:
- self.comm.bcast(current_indices, root=MPI.PROC_NULL)
+ self.comm.bcast(current_indices.handle(), root=MPI.PROC_NULL)
# Convert numpy arrays to dict of slices ...
current_indices = Utils.array_to_dict(current_indices)
diff --git a/hysop/core/mpi/redistribute.py b/hysop/core/mpi/redistribute.py
new file mode 100644
index 0000000000000000000000000000000000000000..20c2985a65c3b47f99b2c9c267e71098f7e66a52
--- /dev/null
+++ b/hysop/core/mpi/redistribute.py
@@ -0,0 +1,349 @@
+"""Implementation for data transfer/redistribution between topologies
+
+`.. currentmodule : hysop.core.mpi.redistribute
+
+See hysop.operator.redistribute.Redistribute for automatic
+redistribute deployment.
+
+* :class:`~RedistributeOperator` abstract base class
+* :class:`~RedistributeIntra` for topologies/operators defined
+ inside the same mpi communicator
+* :class:`~RedistributeInter` for topologies/operators defined
+ on two different mpi communicator
+* :class:`~RedistributeOverlap` for topologies defined
+ inside the same mpi parent communicator and
+ with a different number of processes
+"""
+
+from abc import ABCMeta, abstractmethod
+from hysop.constants import Backend, DirectionLabels
+from hysop.tools.types import check_instance, to_set
+from hysop.tools.decorators import debug, not_implemented
+from hysop.tools.numpywrappers import npw
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology import Topology, Cartesian, TopoTools
+from hysop.core.graph.computational_operator import ComputationalGraphOperator
+from hysop.core.mpi.bridge import Bridge, BridgeOverlap, BridgeInter
+
+ # print '{}::{} source indices: {}'.format(skind, src.dtype, source_indices)
+ # print 'sshape = {}'.format(src.shape)
+ # print 'sstart = {}'.format(sstart)
+ # print 'sstop = {}'.format(sstop)
+ # print 'sstep = {}'.format(sstep)
+ # print 'sregion = {}'.format(sregion)
+ # print 'sstrides = {}'.format(sstrides)
+ # print 'spitches = {}'.format(sstep*sstrides)
+ # print 'sorigin = {}'.format((sstart-sstep+1)/sstep)
+ # print
+ # print '{}::{} target indices: {}'.format(tkind, dst.dtype, target_indices)
+ # print 'tshape = {}'.format(dst.shape)
+ # print 'tstart = {}'.format(tstart)
+ # print 'tstop = {}'.format(tstop)
+ # print 'tstep = {}'.format(tstep)
+ # print 'tregion = {}'.format(tregion)
+ # print 'tstrides = {}'.format(tstrides)
+ # print 'tpitches = {}'.format(tstep*tstrides)
+ # print 'torigin = {}'.format((tstart-tstep+1)/tstep)
+
+def decompose_slices(array, indices):
+ kind = array.backend.kind
+ shape = array.shape
+ dtype = array.dtype
+ strides = array.strides
+
+ start = npw.asindexarray(
+ [x.start if (x.start is not None) else 0 for x in indices])
+ stop = npw.asindexarray(
+ [x.stop if (x.stop is not None) else shape[i] for (i,x) in enumerate(indices)])
+ step = npw.asindexarray(
+ [x.step if (x.step is not None) else 1 for x in indices ])
+
+ region = (stop-start-step+1)/step
+
+ return (kind, start, stop, step, region, strides)
+
+def _memcpy(dst, src, target_indices, source_indices):
+
+ def _runtime_error():
+ msg='Copy from {} to {} are not handled yet.'
+ msg=msg.format(src.__class__, dst.__class__)
+ raise RuntimeError(msg)
+
+ skind, sstart, sstop, sstep, sregion, sstrides = decompose_slices(src, source_indices)
+ tkind, tstart, tstop, tstep, tregion, tstrides = decompose_slices(dst, target_indices)
+
+ if skind == tkind:
+ dst[target_indices] = src[source_indices]
+ elif skind==Backend.HOST:
+ if tkind==Backend.OPENCL:
+ from hysop.backend.device.opencl import cl
+ assert (sregion==tregion).all()
+ assert src.dtype == dst.dtype
+ assert sstep[0]==1
+ assert tstep[0]==1
+
+ scale_width = npw.ones_like(sstart)
+ scale_width[0] = src.dtype.itemsize
+ region = sregion*scale_width
+
+ host_origin = (sstart-sstep+1)/tstep * scale_width
+ host_pitches = (sstep*sstrides)[1:]
+ buffer_origin = (tstart-tstep+1)/tstep * scale_width
+ buffer_pitches = (tstep*tstrides)[1:]
+
+ cl.enqueue_copy(queue=dst.default_queue,
+ dest=dst.data, src=src.data, region=region,
+ buffer_origin=buffer_origin, buffer_pitches=buffer_pitches,
+ host_origin=buffer_origin, host_pitches=host_pitches)
+ else:
+ _runtime_error()
+ elif skind==Backend.OPENCL:
+ if tkind==Backend.HOST:
+ from hysop.backend.device.opencl import cl
+ assert (sregion==tregion).all()
+ assert src.dtype == dst.dtype
+ assert sstep[0]==1
+ assert tstep[0]==1
+
+ scale_width = npw.ones_like(sstart)
+ scale_width[0] = src.dtype.itemsize
+ region = sregion*scale_width
+
+ buffer_origin = (sstart-sstep+1)/tstep * scale_width
+ buffer_pitches = (sstep*sstrides)[1:]
+ host_origin = (tstart-tstep+1)/tstep * scale_width
+ host_pitches = (tstep*tstrides)[1:]
+
+ cl.enqueue_copy(queue=src.default_queue,
+ dest=dst.data, src=src.data, region=region,
+ buffer_origin=buffer_origin, buffer_pitches=buffer_pitches,
+ host_origin=buffer_origin, host_pitches=host_pitches)
+ else:
+ _runtime_error()
+ else:
+ _runtime_error()
+
+class RedistributeOperator(ComputationalGraphOperator):
+ """Abstract interface to redistribute operators
+ """
+
+ __metaclass__ = ABCMeta
+
+ @classmethod
+ @not_implemented
+ def can_redistribute(cls, source_topo, target_topo):
+ """
+ Return true if this RedistributeOperator can be applied
+ to redistribute a variable from source_topo to target_topo,
+ else return False.
+ """
+ pass
+
+ def supported_backends(self):
+ """
+ return the backends that this operator's topologies can support.
+ """
+ return Backend.all
+
+ def __init__(self, variable, source_topo, target_topo, components=None, **kwds):
+ """
+ Parameters
+ ----------
+ variable: :class:`~hysop.field.continuous.Field`
+ the variable to be distributed
+ source_topo: :class:`~hysop.core.mpi.topology.Topology`
+ source mesh topology
+ target_topo: :class:`~hysop.core.mpi.topology.Topology`
+ target mesh topology
+ components: int or list of ints
+ which component of the field must be distributed (default = all)
+ """
+ check_instance(variable, Field)
+ check_instance(source_topo, Topology)
+ check_instance(target_topo, Topology)
+
+ components = to_set(components) if (components is not None) else \
+ set(xrange(variable.nb_components))
+ check_instance(components, set, values=int)
+
+ input_vars = {variable: source_topo}
+ output_vars = {variable: target_topo}
+ super(RedistributeOperator, self).__init__(input_vars=input_vars,
+ output_vars=output_vars, **kwds)
+
+ self.variable = variable
+ self.source_topo = source_topo
+ self.target_topo = target_topo
+ self.components = components
+
+ # Set domain and mpi params
+ self._set_domain_and_tasks()
+
+
+
+ @debug
+ def initialize(self, topgraph_method=None, **kwds):
+ super(RedistributeOperator,self).initialize(topgraph_method)
+ @debug
+ def discretize(self):
+ self.handle_topologies()
+ super(RedistributeOperator,self).discretize()
+ # Dictionnary of discrete fields to be sent and received
+ v = self.variable
+ self._vsource = {v: v.discretize(self.source_topo)}
+ self._vtarget = {v: v.discretize(self.target_topo)}
+
+ @debug
+ def get_work_properties(self):
+ return None
+ @debug
+ def setup(self, work=None):
+ super(RedistributeOperator,self).setup(work=work)
+
+ @classmethod
+ def supports_multiple_field_topologies(cls):
+ return True
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return True
+ @classmethod
+ def supports_mpi(cls):
+ return True
+
+ def available_methods(self):
+ return {}
+ def default_method(self):
+ return {}
+ def handle_method(self, method):
+ super(RedistributeOperator,self).handle_method(method)
+
+
+
+class RedistributeIntra(RedistributeOperator):
+ """Data transfer between two operators/topologies.
+ Source and target must:
+ * be Cartesian topologies with the same global resolution
+ * be defined on the same communicator
+ * work on the same number of mpi processes
+ """
+
+ @classmethod
+ def can_redistribute(cls, source_topo, target_topo):
+ tin = source_topo
+ tout = target_topo
+
+ # source and target must be Cartesian topology defined on HostArrayBackend
+ if not isinstance(source_topo, Cartesian):
+ return False
+ if not isinstance(target_topo, Cartesian):
+ return False
+
+ # source and target must have the same global resolution
+ source_res = tin.mesh.discretization.resolution
+ target_res = tout.mesh.discretization.resolution
+ if not (source_res==target_res).all():
+ return False
+
+ # defined on the same communicator
+ # and work on the same number of mpi process
+ if not TopoTools.compare_comm(tin.parent(), tout.parent()):
+ return False
+
+ return True
+
+
+ def __init__(self, **kwds):
+ """Data transfer between two operators/topologies defined on the
+ same communicator
+
+ Source and target must:
+ * be defined on the same communicator
+ * work on the same number of mpi process
+ * work with the same global resolution
+ """
+
+ # Base class initialisation
+ super(RedistributeIntra, self).__init__(**kwds)
+
+ # Warning : comm from io_params will be used as
+ # reference for all mpi communication of this operator.
+ # --> rank computed in refcomm
+ # --> source and target must work inside refcomm
+ # If io_params is None, refcomm will COMM_WORLD.
+
+
+ def discretize(self):
+ super(RedistributeIntra,self).discretize()
+
+ # We can create the bridge
+ self.bridge = Bridge(self.source_topo, self.target_topo)
+ self._rank = self.bridge._rank
+
+ # dictionnary which maps rank with mpi derived type
+ # for send operations
+ self._send = self.bridge.send_types()
+
+ # dictionnay which maps rank with mpi derived type
+ # for send operations
+ self._receive = self.bridge.recv_types()
+
+ def apply(self, simulation=None):
+ # Try different way to send vars?
+ # - Buffered : copy all data into a buffer and send/recv
+ # - Standard : one send/recv per component
+
+ # --- Standard send/recv ---
+ br = self.bridge
+
+ # dictionnary which map rank/field name with a receive request
+ self._r_request = {}
+ # dictionnary which map rank/field name with a send request
+ self._s_request = {}
+
+ basetag = self.mpi_params.rank + 1
+
+ # Comm used for send/receive operations
+ # It must contains all proc. of source topo and
+ # target topo.
+ refcomm = self.bridge.comm
+
+ # Loop over all required components of each variable
+ v = self.variable
+ for d in self.components:
+ v_name = v.name + DirectionLabels[d]
+
+ # Deal with local copies of data
+ if br.has_local_inter():
+ dst = self._vtarget[v].data[d]
+ src = self._vsource[v].data[d]
+ source_indices = br.local_source_ind()
+ target_indices = br.local_target_ind()
+ _memcpy(dst, src, target_indices, source_indices)
+
+ # Transfers to other mpi processes
+ for rk in self._receive:
+ if rk == self._rank:
+ continue
+ recvtag = basetag * 989 + (rk + 1) * 99 + (d + 1) * 88
+ mpi_type = self._receive[rk]
+ dst = self._vtarget[v].data[d]
+ self._r_request[v_name + str(rk)] = \
+ refcomm.Irecv([dst.handle, 1, mpi_type], source=rk, tag=recvtag)
+ self._has_requests = True
+ for rk in self._send:
+ if rk == self._rank:
+ continue
+ sendtag = (rk + 1) * 989 + basetag * 99 + (d + 1) * 88
+ mpi_type = self._send[rk]
+ src = self._vsource[v].data[d]
+ self._s_request[v_name + str(rk)] = \
+ refcomm.Issend([src.handle, 1, mpi_type], dest=rk, tag=sendtag)
+ self._has_requests = True
+
+ def wait(self):
+ if self._has_requests:
+ for rk in self._r_request:
+ self._r_request[rk].Wait()
+ for rk in self._s_request:
+ self._s_request[rk].Wait()
+ self._has_requests = False
diff --git a/hysop/core/mpi/tests/__init__.py b/hysop/core/mpi/tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/mpi/tests/test_bridge.py b/hysop/core/mpi/tests/test_bridge.py
similarity index 95%
rename from hysop/mpi/tests/test_bridge.py
rename to hysop/core/mpi/tests/test_bridge.py
index 936fb00c18889171f64f4d6eb0078829916772ff..a83af7d447aafb36131de30102f3b457ae32a9f6 100755
--- a/hysop/mpi/tests/test_bridge.py
+++ b/hysop/core/mpi/tests/test_bridge.py
@@ -1,8 +1,8 @@
from hysop.domain.box import Box
from hysop.tools.parameters import Discretization
-from hysop.mpi.bridge import Bridge, BridgeInter, BridgeOverlap
-from hysop.mpi import main_size, main_comm
-from hysop.mpi.tests.utils import create_subtopos, create_inter_topos
+from hysop.core.mpi.bridge import Bridge, BridgeInter, BridgeOverlap
+from hysop.core.mpi import main_size, main_comm
+from hysop.core.mpi.tests.utils import create_subtopos, create_inter_topos
import math
diff --git a/hysop/mpi/tests/test_topology.py b/hysop/core/mpi/tests/test_topology.py
similarity index 92%
rename from hysop/mpi/tests/test_topology.py
rename to hysop/core/mpi/tests/test_topology.py
index 2b22daa48d909d40f3b286063d198637ffdd6677..8bc50bc323eb7a14b08a6843a985f0077ca0ad93 100755
--- a/hysop/mpi/tests/test_topology.py
+++ b/hysop/core/mpi/tests/test_topology.py
@@ -1,10 +1,9 @@
-import hysop as pp
from hysop.domain.box import Box
-from hysop.constants import DEFAULT_TASK_ID
+from hysop.constants import HYSOP_DEFAULT_TASK_ID
from hysop.tools.parameters import Discretization
-from hysop.mpi import main_size
+from hysop.core.mpi import main_size
import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
N = 33
@@ -13,7 +12,7 @@ r2D = Discretization([N, 17]) # No ghosts
r3D = Discretization([N, N, 17]) # No ghosts
r3DGh = Discretization([N, N, 17], [2, 2, 2]) # Ghosts
-CPU = DEFAULT_TASK_ID
+CPU = HYSOP_DEFAULT_TASK_ID
GPU = 29
proc_tasks = [CPU] * main_size
if main_size > 2:
@@ -35,14 +34,14 @@ refmesh2d = toporef2d.mesh
def check2D(topo):
assert topo.size == main_size
- assert topo.task_id() == DEFAULT_TASK_ID
+ assert topo.task_id() == HYSOP_DEFAULT_TASK_ID
assert np.allclose(topo.mesh.discretization.resolution,
r2D.resolution)
def check3D(topo):
assert topo.size == main_size
- assert topo.task_id() == DEFAULT_TASK_ID
+ assert topo.task_id() == HYSOP_DEFAULT_TASK_ID
assert np.allclose(topo.mesh.discretization.resolution,
r3D.resolution)
@@ -85,7 +84,7 @@ def test_create_topologyFromShape_2d():
topo = dom.create_topology(r2D, shape=topoShape)
assert topo.domain == dom
assert topo.dimension == 2
- assert topo.size == pp.mpi.main_size
+ assert topo.size == main_size
assert (topo.shape == topoShape).all()
assert (topo.mesh.resolution == [16, 4]).all()
@@ -104,7 +103,7 @@ def test_create_topologyFromCutdir_2d():
topo = dom.create_topology(r2D, cutdir=[False, True])
assert topo.domain == dom
assert topo.dimension == 1
- assert topo.size == pp.mpi.main_size
+ assert topo.size == main_size
assert (topo.shape == [1, main_size]).all()
topo2 = dom.create_topology(r2D, cutdir=[True, False])
@@ -124,7 +123,7 @@ def test_create_planetopology_2d():
)
assert topo.domain == dom
assert topo.dimension == 1
- assert topo.size == pp.mpi.main_size
+ assert topo.size == main_size
assert (topo.shape == [1, main_size]).all()
assert topo.mesh == refmesh2d
topo2 = dom.create_plane_topology_from_mesh(discretization=r2D,
@@ -132,7 +131,7 @@ def test_create_planetopology_2d():
localres=lres, cdir=0)
assert topo2.domain == dom
assert topo2.dimension == 1
- assert topo2.size == pp.mpi.main_size
+ assert topo2.size == main_size
assert (topo2.shape == [main_size, 1]).all()
@@ -176,7 +175,7 @@ def test_create_topologyFromShape():
topo = dom.create_topology(r3D, shape=topoShape)
assert topo.domain == dom
assert topo.dimension == 3
- assert topo.size == pp.mpi.main_size
+ assert topo.size == main_size
assert (topo.shape == topoShape).all()
assert (topo.mesh.resolution == [16, 16, 8]).all()
@@ -195,7 +194,7 @@ def test_create_topologyFromCutdir():
topo = dom.create_topology(r3D, cutdir=[False, True, True])
assert topo.domain == dom
assert topo.dimension == 2
- assert topo.size == pp.mpi.main_size
+ assert topo.size == main_size
assert (topo.shape == [1, 2, 4]).all()
topo2 = dom.create_topology(r3D, cutdir=[False, True, False])
@@ -214,7 +213,7 @@ def test_create_planetopology():
localres=lres)
assert topo.domain == dom
assert topo.dimension == 1
- assert topo.size == pp.mpi.main_size
+ assert topo.size == main_size
assert (topo.shape == [1, 1, main_size]).all()
assert topo.mesh == refmesh
topo2 = dom.create_plane_topology_from_mesh(discretization=r3DGh,
@@ -222,7 +221,7 @@ def test_create_planetopology():
localres=lres, cdir=1)
assert topo2.domain == dom
assert topo2.dimension == 1
- assert topo2.size == pp.mpi.main_size
+ assert topo2.size == main_size
assert (topo2.shape == [1, main_size, 1]).all()
diff --git a/hysop/mpi/tests/utils.py b/hysop/core/mpi/tests/utils.py
similarity index 94%
rename from hysop/mpi/tests/utils.py
rename to hysop/core/mpi/tests/utils.py
index 6de9749e4764a3bead8ff60dd0e74a1b4b440b64..8347988f98248448622ddc8280e437a84bd86c4e 100644
--- a/hysop/mpi/tests/utils.py
+++ b/hysop/core/mpi/tests/utils.py
@@ -1,7 +1,7 @@
"""Functions used in mpi-related tests.
"""
-from hysop.mpi import main_comm, main_rank, main_size
+from hysop.core.mpi import main_comm, main_rank, main_size
from hysop.tools.parameters import MPIParams
import hysop as pp
GPU = 4
@@ -23,7 +23,7 @@ def create_multitask_context(dim, discr):
-------
dom : :class:`~hysop.domain.box.Box`
a domain (box-shaped) defined on three differents tasks
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
topology associated to the domain
Notes
@@ -61,7 +61,7 @@ def create_subtopos(domain, discr_source, discr_target):
Returns
-------
- source_topo, target_topo: class:`~hysop.mpi.topology.Cartesian`
+ source_topo, target_topo: class:`~hysop.core.mpi.topology.Cartesian`
topologies associated with rank 0 and last rank for 'target'
and other ranks for 'source'.
"""
@@ -104,7 +104,7 @@ def create_nonoverlap_topos(domain, discr_source, discr_target):
Returns
-------
- source_topo, target_topo: class:`~hysop.mpi.topology.Cartesian`
+ source_topo, target_topo: class:`~hysop.core.mpi.topology.Cartesian`
topologies associated with even ranks for 'source'
and odd ranks for 'target'.
"""
@@ -145,7 +145,7 @@ def create_inter_topos(dim, discr1, discr2):
-------
dom : :class:`~hysop.domain.box.Box`
a domain (box-shaped) defined on three differents tasks
- topo1, topo2 : :class:`~hysop.mpi.topology.Cartesian`
+ topo1, topo2 : :class:`~hysop.core.mpi.topology.Cartesian`
topologies associated to the domain
Notes
diff --git a/hysop/mpi/topology.py b/hysop/core/mpi/topology.py
similarity index 70%
rename from hysop/mpi/topology.py
rename to hysop/core/mpi/topology.py
index f21282fdc01a093488eb3a74595010d0ce72a1a8..afe862db5b26974ed78097d6247ca54b956e1228 100644
--- a/hysop/mpi/topology.py
+++ b/hysop/core/mpi/topology.py
@@ -1,22 +1,126 @@
"""Tools and definitions for HySoP topologies
+if topology.discretization != self.discretization():
(MPI Processes layout + space discretization)
-* :class:`~hysop.mpi.topology.Cartesian`
-* :class:`~hysop.mpi.topology.TopoTools`
+* :class:`~hysop.core.mpi.topology.Cartesian`
+* :class:`~hysop.core.mpi.topology.TopoTools`
"""
-
-from hysop.constants import debug, ORDER, PERIODIC
-from hysop.domain.mesh import Mesh
from itertools import count
-from hysop.mpi import MPI
+from abc import ABCMeta, abstractmethod
+from hysop.constants import np, math, Backend
+from hysop.constants import HYSOP_ORDER, BoundaryCondition
+from hysop.constants import HYSOP_MPI_REAL, HYSOP_MPI_ORDER
+from hysop.domain.mesh import Mesh
+from hysop.core.mpi import MPI
+from hysop.tools.types import check_instance, to_tuple
from hysop.tools.parameters import Discretization, MPIParams
-import numpy as np
-import hysop.tools.numpywrappers as npw
from hysop.tools.misc import Utils
+from hysop.tools.decorators import debug
+from hysop.tools.numpywrappers import npw
+from hysop.tools.string_utils import prepend
+
+class Topology(object):
+ __metaclass__ = ABCMeta
+
+ # Counter of topology.Topology instances to set a unique id for each topology.
+ __ids = count(0)
+ __registered_topologies = {}
+
+ @debug
+ def __new__(cls, **kwds):
+ def fmt(x):
+ if isinstance(x, (list,np.ndarray)):
+ return to_tuple(x)
+ else:
+ return x
+ key = tuple( fmt(kwds[k]) for k in sorted(kwds.keys()) )
+
+ registered_topologies = cls.__registered_topologies
+ if key in registered_topologies:
+ obj = registered_topologies[key]
+ assert obj._initialized
+ return obj
+ else:
+ obj = super(Topology,cls).__new__(cls, **kwds)
+ obj.__id = cls.__ids.next()
+ obj._initialized = False
+ registered_topologies[key] = obj
+ return obj
+
+ def __eq__(self, other):
+ if self.__class__ != other.__class__:
+ return NotImplemented
+ return id(self) == id(other)
+
+ def __neq__(self, other):
+ if self.__class__ != other.__class__:
+ return NotImplemented
+ return id(self) != id(other)
+
+ def __hash(self):
+ return id(self)
+
+ def __init__(self, mpi_params, domain, backend=Backend.HOST ,
+ cl_env=None, allocator=None, queue=None, **kwds):
+
+ if self._initialized:
+ return
+ self._initialized = True
+
+ super(Topology,self).__init__(**kwds)
+
+ # MPI parameters and domain
+ if mpi_params is None:
+ mpi_params = MPIParams(comm=domain.comm_task,
+ task_id=domain.current_task())
+ assert mpi_params.task_id is not None
+
+ self.mpi_params = mpi_params
+ self.domain = domain
+
+ # Backend
+ check_instance(backend, Backend)
+ if backend == Backend.HOST:
+ from hysop.core.arrays.all import HostArrayBackend
+ from hysop.backend.host.host_allocator import default_host_mempool
+ allocator = allocator or default_host_mempool
+ backend = HostArrayBackend(allocator)
+ elif backend == Backend.OPENCL:
+ from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+ from hysop.core.arrays.all import OpenClArrayBackend
+ cl_env = cl_env or get_or_create_opencl_env(mpi_params.comm)
+ self.cl_env = cl_env
+ assert cl_env.comm == mpi_params.comm
+
+ backend = OpenClArrayBackend(cl_env=cl_env,queue=queue,allocator=allocator)
+ else:
+ msg = 'Unsupported backend {}.'.format(backend)
+ raise ValueError(msg)
+ self._backend = backend
+ if kwds:
+ msg='Unused arguments: {}.'.format(kargs)
+ raise RuntimeError(msg)
+
+ @abstractmethod
+ def short_description(topo):
+ pass
-class Cartesian(object):
+ def get_backend(self):
+ return self._backend
+
+ def get_id(self):
+ """
+ return the id of the present topology.
+ This id is unique among all defined topologies.
+ """
+ return self.__id
+
+ backend = property(get_backend)
+ id = property(get_id)
+
+class Cartesian(Topology):
"""
In hysop, a topology is defined as the association of
a mpi process distribution (mpi topology) and of a set of local meshes
@@ -26,7 +130,7 @@ class Cartesian(object):
Example :
\code
- >>> from hysop.mpi.topology import Cartesian
+ >>> from hysop.core.mpi.topology import Cartesian
>>> from hysop.tools.parameters import Discretization
>>> from hysop.domain.box import Box
>>> dom = Box()
@@ -40,18 +144,10 @@ class Cartesian(object):
"""
- @debug
- def __new__(cls, *args, **kw):
- return object.__new__(cls, *args, **kw)
- #
- # Counter of topology.Cartesian instances to set a unique id for each
- # Cartesian topology instance.
- __ids = count(0)
-
@debug
def __init__(self, domain, discretization, dim=None, mpi_params=None,
isperiodic=None, cutdir=None, shape=None, mesh=None,
- cartesian_topology=None):
+ cartesian_topology=None, backend=Backend.HOST, **kwds):
"""
Parameters
@@ -65,7 +161,7 @@ class Cartesian(object):
mpi topology dimension.
mpi_params : :class:`~hysop.tools.parameters.MPIParams`, optional
mpi setup (comm, task ...).
- If None, comm = main_comm, task = DEFAULT_TASK_ID.
+ If None, comm = main_comm, task = HYSOP_DEFAULT_TASK_ID.
isperiodic : tuple, list or array of bool, optional
mpi grid periodicity
cutdir : list or array of bool
@@ -88,26 +184,16 @@ class Cartesian(object):
* when cartesian_topology is given, dim, shape and cutdir parameters,
if set, are not used to build the mpi topology, but compared with
cartesian_topology parameters. If they do not fit, error may occur.
- * See hysop.mpi.topology.Cartesian.plane_precomputed
+ * See hysop.core.mpi.topology.Cartesian.plane_precomputed
details to build a plane topology from a given local discretization
(e.g. from fftw or scales precomputation).
"""
- # ===== 1 - Required parameters : domain and mpi (comm, task) ====
- # An id for the topology
- self.__id = self.__ids.next()
- # Associated domain
- self.domain = domain
- # - MPI topo params :
- if mpi_params is None:
- mpi_params = MPIParams(comm=domain.comm_task,
- task_id=domain.current_task())
+ if self._initialized:
+ return
- # mpi parameters : Communicator used to build the topology
- # and task_id
- self._mpis = mpi_params
- # Each topo must be associated to one and only one topology
- assert self._mpis.task_id is not None
+ super(Cartesian,self).__init__(domain=domain, mpi_params=mpi_params,
+ backend=backend, **kwds)
# ===== 2 - Prepare MPI processes layout ====
# 3 methods :
@@ -127,7 +213,10 @@ class Cartesian(object):
self.cutdir = None
# mpi communicator (cartesian topo)
self.comm = None
-
+
+ # discretization used to build this topology
+ self.discretization = discretization
+
if cartesian_topology is None:
self._build_mpi_topo(shape, cutdir, dim, isperiodic)
else:
@@ -135,10 +224,13 @@ class Cartesian(object):
cutdir, dim, isperiodic)
# ===== 3 - Get features of the mpi processes grid =====
+
# Size of the topology (i.e. total number of mpi processes)
self.size = self.comm.Get_size()
+
# Rank of the current process in the topology
self.rank = self.comm.Get_rank()
+
# Coordinates of the current process
reduced_coords = npw.asdimarray(self.comm.Get_coords(self.rank))
@@ -154,9 +246,17 @@ class Cartesian(object):
# previous (resp. next) neighbour in direction i
# (warning : direction in the grid of process).
self.neighbours = npw.dim_zeros((2, self.dimension))
+ self.neighbours_tmp = []
+ for direction in range(self.domain.dimension):
+ self.neighbours_tmp.append(self.comm.Shift(direction, 1))
+ self.distributed_dirs = tuple([d for d in xrange(self.domain.dimension)
+ if self.neighbours_tmp[d][0]
+ is not self.rank])
+ self.bc_dirs = tuple([d for d in xrange(self.domain.dimension)
+ if d not in self.distributed_dirs])
+
for direction in range(self.dimension):
self.neighbours[:, direction] = self.comm.Shift(direction, 1)
-
# ===== 4 - Computation of the local meshes =====
# Local mesh on the current mpi process.
@@ -169,21 +269,20 @@ class Cartesian(object):
# ===== 5 - Final setup ====
- # The topology is register into domain list.
- # If it already exists (in the sense of the comparison operator
- # of the present class) then isNew is turned to false
- # and the present instance will be destroyed.
- self.isNew = True
- self.__id = self.domain.register(self)
- # If a similar topology (in the sense of operator
- # equal defined below) exists, we link
- # its arg with those of the current topo.
- # It seems to be impossible to delete the present
- # object in its __init__ function.
- if not self.isNew:
- topo = self.domain.topologies[self.__id]
- self.mesh = topo.mesh
- self.comm = topo.comm
+ # The topology is registered into domain list.
+ self.domain.register(self)
+
+ # sub-communicators of the current topo
+ # sub_comm[d] = 1 or 2D comm, with direction d undistributed
+ self.sub_comms = None
+
+ # list of neighbours in sub_comm,
+ # sub_neighbours[i, d] = mpi process
+ # at distance i in direction d, in sub_comm[d].
+ self.sub_neighbours = None
+ # The two variables above are mainly use with the fortran interface.
+ # They are build only when build_subcomms method is called.
+
def _build_mpi_topo(self, shape=None, cutdir=None,
dim=None, isperiodic=None):
@@ -200,7 +299,7 @@ class Cartesian(object):
# Then, we can create the mpi topology.
#self.comm = \
self._isperiodic = tuple([True, ] * self.domain.dimension)
- self.comm = self._mpis.comm.Create_cart(self.shape,
+ self.comm = self.mpi_params.comm.Create_cart(self.shape,
periods=self._isperiodic,
reorder=True)
@@ -232,7 +331,7 @@ class Cartesian(object):
# - self._isperiodic
"""
# number of process in parent comm
- origin_size = self._mpis.comm.Get_size()
+ origin_size = self.mpi_params.comm.Get_size()
if shape is not None:
# method (a)
msg = ' parameter is useless when shape is provided.'
@@ -302,29 +401,54 @@ class Cartesian(object):
self.dimension = 1
self.cutdir[-1] = True
+ def build_subcomms(self):
+ """Split the cartesian topology and init neighbours, ranks ...
+ """
+ if self.sub_neighbours is not None and self.sub_comms is not None:
+ return
+ dimension = self.domain.dimension
+ remain_dims = np.asarray([False, ] * dimension)
+ # Compute sub-communicators
+ sub_comm = [None, ] * dimension
+ for d in xrange(dimension):
+ remain_dims[d] = True
+ sub_comm[d] = self.comm.Sub(remain_dims)
+ remain_dims[...] = False
+ # Compute neighbours in the subtopologies.
+ sub_rank = [sub_comm[d].Get_rank() for d in xrange(dimension)]
+ self.sub_neighbours = npw.integer_zeros((9, dimension))
+ for direction in xrange(dimension):
+ self.sub_neighbours[4, direction] = sub_rank[direction]
+ for step in xrange(1, 5):
+ neigh = sub_comm[direction].Shift(direction, step)
+ self.sub_neighbours[4 - step, direction] = neigh[0]
+ self.sub_neighbours[4 + step, direction] = neigh[1]
+ self.sub_comms = [sub_comm[d].py2f() for d in xrange(dimension)]
+
@staticmethod
def _optimizeshape(shape):
"""Reorder 'shape' according to the chosen
data layout to optimize data distribution.
"""
shape.sort()
- if ORDER == 'C':
+ if HYSOP_ORDER == 'C':
shape[:] = shape[::-1]
def parent(self):
"""returns the communicator used to build this topology
"""
- return self._mpis.comm
+ return self.mpi_params.comm
- def ghosts(self):
+ def get_ghosts(self):
"""returns ghost layer width.
"""
return self.mesh.discretization.ghosts
+ ghosts = property(get_ghosts)
def task_id(self):
"""returns id of the task that owns this topology
"""
- return self._mpis.task_id
+ return self.mpi_params.task_id
@classmethod
def plane_precomputed(cls, localres, global_start, cdir=None, **kwds):
@@ -345,8 +469,8 @@ class Cartesian(object):
"""
msg = 'parameter is not required for plane_precomputed'
msg += ' topology construction.'
- assert 'dim' not in kwds, 'dim ' + msg
- assert 'shape ' not in kwds, 'shape ' + msg
+ assert 'dim' not in kwds, 'dim ' + msg
+ assert 'shape ' not in kwds, 'shape ' + msg
assert 'cutdir ' not in kwds, 'cutdir ' + msg
# Local mesh :
global_start = npw.asdimarray(global_start)
@@ -355,12 +479,12 @@ class Cartesian(object):
localres, global_start)
# MPI layout
domain = kwds['domain']
- cutdir = npw.zeros(domain.dimension, dtype=npw.bool)
+ cutdir = npw.bool_zeros(domain.dimension)
if cdir is not None:
cutdir[cdir] = True
else:
- if ORDER == 'C':
+ if HYSOP_ORDER == 'C':
cutdir[0] = True
else:
cutdir[-1] = True
@@ -377,13 +501,15 @@ class Cartesian(object):
# Warning FP : we should test boundary conditions type here
# If periodic, resol_calc = (global_resolution - 1)
# else, resol_calc = (global_resolution - 2)
-
- is_periodic = len(np.where(self.domain.boundaries == PERIODIC)[0])\
- == self.domain.dimension
+
+ periodic = BoundaryCondition.PERIODIC
+ is_periodic = (self.domain.boundaries[0]==periodic).all() \
+ and (self.domain.boundaries[1]==periodic).all()
if is_periodic:
computational_grid_resolution = discretization.resolution - 1
else:
- raise AttributeError('Unknwon boundary conditions.')
+ msg='Unknown boundary conditions {}.'
+ raise AttributeError(msg)
pts_noghost[:] = computational_grid_resolution // self.shape
@@ -409,39 +535,26 @@ class Cartesian(object):
self.mesh = Mesh(self.domain, discretization,
local_resolution, global_start)
- def __eq__(self, other):
- """Comparison of two topologies.
-
- Two topos are equal if they have the same mesh, shape and domain.
- """
- if self.__class__ != other.__class__:
- return False
- return self.mesh == other.mesh and \
- npw.equal(self.shape, other.shape).all() and \
- self.domain == other.domain
-
- def __ne__(self, other):
- """Not equal operator.
-
- Seems to be required in addition to __eq__ to
- avoid 'corner-case' behaviors.
- """
- result = self.__eq__(other)
- if result is NotImplemented:
- return result
- return not result
+ def short_description(topo):
+ return 'topology_id={}, task_id={}, shape={}, ghosts={}, is_periodic={}'.format(
+ topo.get_id(), topo.task_id(), topo.shape, topo.ghosts,
+ '[{}]'.format(','.join('T' if per else 'F' for per in topo._isperiodic)))
def __str__(self):
s = '======== Topology id : ' + str(self.__id) + ' ========\n'
- s += ' - on task : ' + str(self.task_id()) + '\n'
- s += ' - shape :' + str(self.shape) + '\n'
- s += ' - process of coordinates ' + str(self.proc_coords[:])
+ s += ' *on task: ' + str(self.task_id()) + '\n'
+ s += ' *backend: ' + str(self.backend) + '\n'
+ s += ' *shape: ' + str(self.shape) + '\n'
+ s += ' *process of coordinates ' + str(self.proc_coords[:])
s += ' and of ranks (topo/origin) ' + str(self.rank) + '/'
- s += str(self._mpis.rank) + '.\n'
- s += '- neighbours coordinates : \n'
- s += str(self.neighbours) + '\n'
- s += str(self.mesh)
- s += '\n=================================\n'
+ s += str(self.mpi_params.rank) + '.\n'
+ s += ' *neighbours coordinates:\n'
+ s += prepend(str(self.neighbours), ' '*4) + '\n'
+ s += ' *full neighbours coordinates:\n'
+ s += prepend(str(self.neighbours_tmp), ' '*4) + '\n'
+ s += prepend('*'+str(self.domain), ' '*2)
+ s += prepend('*'+str(self.mesh),' '*2)
+ s += '=================================\n'
return s
def has_ghosts(self):
@@ -450,13 +563,6 @@ class Cartesian(object):
"""
return not np.all(self.mesh.discretization.ghosts == 0)
- def get_id(self):
- """
- return the id of the present topology.
- This id is unique among all defined topologies.
- """
- return self.__id
-
def is_consistent_with(self, target):
"""True if target and current object are equal and
have the same parent. Equal means same mesh, same shape and
@@ -509,7 +615,7 @@ class TopoTools(object):
Parameters
----------
- topo : :class:`~ hysop.mpi.topology.Cartesian`
+ topo : :class:`~ hysop.core.mpi.topology.Cartesian`
topology on which indices are collected.
toslice : boolean, optional
true to return the result a dict of slices, else
@@ -540,8 +646,8 @@ class TopoTools(object):
# communicator that owns the topology
rank = comm.Get_rank()
dimension = topo.domain.dimension
- iglob = npw.int_zeros((dimension * 2, size))
- iglob_res = npw.int_zeros((dimension * 2, size))
+ iglob = npw.integer_zeros((dimension * 2, size))
+ iglob_res = npw.integer_zeros((dimension * 2, size))
iglob[0::2, rank] = start
iglob[1::2, rank] = end
# iglob is saved as a numpy array and then transform into
@@ -579,7 +685,7 @@ class TopoTools(object):
Parameters
----------
- topo : :class:`~ hysop.mpi.topology.Cartesian`, optional
+ topo : :class:`~ hysop.core.mpi.topology.Cartesian`, optional
topology on which indices are collected.
toslice : boolean, optional
true to return the result a dict of slices, else
@@ -609,8 +715,8 @@ class TopoTools(object):
size = comm.Get_size()
rank = comm.Get_rank()
dimension = dom.dimension
- iglob = npw.int_zeros((dimension * 2, size))
- iglob_res = npw.int_zeros((dimension * 2, size))
+ iglob = npw.integer_zeros((dimension * 2, size))
+ iglob_res = npw.integer_zeros((dimension * 2, size))
iglob[1::2, rank] = -1
if root is None:
comm.Allgather([iglob[:, rank], MPI.INT], [iglob_res, MPI.INT])
@@ -716,7 +822,6 @@ class TopoTools(object):
:Returns : dictionnary of MPI derived types.
Keys = ranks in parent communicator.
"""
- from hysop.constants import HYSOP_MPI_REAL, ORDERMPI
subtypes = {}
dim = len(data_shape)
for rk in sl_dict.keys():
@@ -725,7 +830,66 @@ class TopoTools(object):
substart = tuple((sl_dict[rk][i].start for i in xrange(dim)))
subtypes[rk] = \
HYSOP_MPI_REAL.Create_subarray(data_shape, subvshape,
- substart, order=ORDERMPI)
+ substart, order=HYSOP_MPI_ORDER)
subtypes[rk].Commit()
return subtypes
+
+ @staticmethod
+ def set_group_size(topo):
+ """Set default size for groups of lines of particles,
+ depending on the local resolution
+
+ Parameters
+ ----------
+ topo: :class:`~hysop.core.mpi.topology.Cartesian`
+
+ Notes
+ -----
+ group_size shape == (problem dim - 1, problem dim)
+ group_size[i, d] = size of groups in direction i when
+ advection is performed in direction d.
+
+ """
+ resolution = topo.mesh.resolution - topo.ghosts()
+ size_ref = [8, 5, 4, 2, 1]
+ group_size = npw.int_ones((topo.domain.dimension - 1,
+ topo.domain.dimension))
+ # Default --> same size in each dir.
+ # Note that a more complex mechanism is provided in scales
+ # to compute group size.
+ for i in size_ref:
+ if (resolution % i == 0).all():
+ group_size[...] = i
+ return group_size
+
+ @staticmethod
+ def initialize_tag_parameters(topo, group_size):
+ """Initialize tag_rank and tag_size, some
+ parameters used to compute unique tag/ids for MPI messages.
+
+ Parameters
+ ----------
+ topo: :class:`~hysop.core.mpi.topology.Cartesian`
+ group_size : numpy array
+ size of groups of lines of particles in other directions
+ than the current advection dir.
+
+ Notes
+ -----
+ group_size shape == (problem dim - 1, problem dim)
+ group_size[i, d] = size of groups in direction i when
+ advection is performed in direction d.
+ """
+ # tag_size = smallest power of ten to ensure tag_size > max ind_group
+ reduced_res = np.asarray(topo.mesh.resolution - topo.ghosts())
+ n_group = npw.zeros_like(group_size)
+ dimension = topo.domain.dimension
+ for i in xrange(dimension):
+ ind = [j for j in xrange(len(reduced_res)) if j != i]
+ n_group[:, i] = reduced_res[ind] / group_size[:, i]
+
+ tag_size = npw.asintegerarray(np.ceil(np.log10(n_group)))
+ tag_rank = max(2, math.ceil(math.log10(3 * max(topo.shape))))
+
+ return tag_size, tag_rank
diff --git a/hysop/core/mpi/topology_descriptor.py b/hysop/core/mpi/topology_descriptor.py
new file mode 100644
index 0000000000000000000000000000000000000000..9425bf2be290bf1ab31f4222d34a5ea54c3c4b62
--- /dev/null
+++ b/hysop/core/mpi/topology_descriptor.py
@@ -0,0 +1,225 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.deps import np, hashlib, copy
+from hysop.tools.types import check_instance
+from hysop.tools.numpywrappers import npw
+from hysop.constants import Backend, BoundaryCondition
+from hysop.tools.parameters import Discretization
+from hysop.core.mpi.topology import Topology, Cartesian
+from hysop.fields.continuous import Field
+from hysop.domain.mesh import Mesh
+
+class TopologyDescriptor(object):
+ """
+ Describes how a topology should be built.
+ kwds allows for backend specific variables.
+
+ TopologyDescriptor is immutable.
+ """
+ __metaclass__ = ABCMeta
+
+ def __init__(self, mpi_params, domain, backend, **kwds):
+ super(TopologyDescriptor, self).__init__()
+ self._mpi_params = mpi_params
+ self._domain = domain
+ self._backend=backend
+ self._extra_kwds = frozenset(kwds.items())
+
+ def get_mpi_params(self):
+ return self._mpi_params
+ def get_domain(self):
+ return self._domain
+ def get_backend(self):
+ return self._backend
+ def get_extra_kwds(self):
+ return dict(self._extra_kwds)
+
+ mpi_params = property(get_mpi_params)
+ domain = property(get_domain)
+ backend = property(get_backend)
+ extra_kwds = property(get_extra_kwds)
+
+ def __eq__(self, other):
+ if not isinstance(other, TopologyDescriptor):
+ return NotImplemented
+ eq = (self.mpi_params == other.mpi_params)
+ eq &= (self.domain == other.domain)
+ eq &= (self.backend == other.backend)
+ eq &= (self.extra_kwds == other.extra_kwds)
+ return eq
+
+ def __ne__(self, other):
+ return not self.__eq__(other)
+
+ def __hash__(self):
+ return hash((self._mpi_params, self._domain, self._backend, self._extra_kwds))
+
+ @staticmethod
+ def build_descriptor(backend, operator, field, handle, **kwds):
+ if isinstance(handle, Topology):
+ # handle is already a Topology, so we return it.
+ return handle
+ elif isinstance(handle, TopologyDescriptor):
+ # handle is already a TopologyDescriptor, so we return it.
+ return handle
+ elif isinstance(handle, CartesianDescriptors):
+ return CartesianDescriptor.build_descriptor(backend, operator,
+ field, handle, **kwds)
+ else:
+ msg='Unknown handle of class {} to build a TopologyDescriptor.'
+ msg=msg.format(handle.__class__)
+ raise TypeError(msg)
+
+ def choose_or_create_topology(self, known_topologies, **kwds):
+ """
+ Returns a topology that is either taken from known_topologies, a set
+ of user specified topologies which are ensured to be compatible
+ with the current TopologyDescriptor, or created from the descriptor
+ if choose_topology() returns None.
+ """
+ check_instance(known_topologies, list, values=Topology)
+ topo = self.choose_topology(known_topologies, **kwds) or \
+ self.create_topology(**kwds)
+ return topo
+
+ @abstractmethod
+ def choose_topology(self, known_topologies, **kwds):
+ return known_topologies[0]
+
+ @abstractmethod
+ def create_topology(self, **kwds):
+ pass
+
+ def dim(self):
+ return self.domain.dimension
+
+ def is_periodic(self):
+ is_lperiodic = [lboundary==BoundaryCondition.PERIODIC
+ for lboundary in self.domain.boundaries[0]]
+ is_rperiodic = [rboundary==BoundaryCondition.PERIODIC
+ for rboundary in self.domain.boundaries[1]]
+ assert len(is_lperiodic)==self.dim()
+ assert len(is_rperiodic)==self.dim()
+ assert is_lperiodic == is_rperiodic
+ return npw.asintegerarray(is_lperiodic)
+
+
+class CartesianDescriptor(TopologyDescriptor):
+ """
+ Describes how a Cartesian topology should be built.
+ kwds allows for backend specific variables.
+
+ CartesianDescriptor is immutable.
+ """
+ def __init__(self, mpi_params, domain, backend, discretization, **kwds):
+ super(CartesianDescriptor, self).__init__(mpi_params=mpi_params,
+ domain=domain, backend=backend, **kwds)
+ # boundaries are stored in domain
+ discretization = copy.copy(discretization)
+ discretization.resolution.flags.writeable = False
+ discretization.ghosts.flags.writeable = False
+
+ self._discretization = discretization
+ self._mesh = self._global_mesh(domain, discretization)
+
+ def get_discretization(self):
+ return self._discretization
+ def get_mesh(self):
+ return self._mesh
+
+ discretization = property(get_discretization)
+ mesh = property(get_mesh)
+
+ def __eq__(self, other):
+ if not isinstance(other, CartesianDescriptor):
+ return NotImplemented
+ eq = super(CartesianDescriptor, self).__eq__(other)
+ eq &= (self.discretization == other.discretization)
+ return eq
+
+ def __hash__(self):
+ # hash(super(...)) does not work as expected so be call __hash__ directly
+ return super(CartesianDescriptor,self).__hash__() ^ hash(self._discretization)
+
+ def __str__(self):
+ return ':CartesianDescriptor: backend={}, resolution={}, domain={}'.format(
+ self.backend, self.discretization.resolution,
+ self.domain.short_description())
+
+ @staticmethod
+ def build_descriptor(backend, operator, field, handle, **kwds):
+ from hysop.core.graph.computational_operator import ComputationalGraphOperator
+ check_instance(backend, Backend)
+ check_instance(operator, ComputationalGraphOperator)
+ check_instance(field, Field)
+ check_instance(handle, CartesianDescriptors)
+ msg='A Cartesian topology descriptor should not contain any ghosts, '
+ msg+='they will be determined during the get_field_requirements() in the '
+ msg+=' operator initialization step to minimize the number of topologies created.'
+ msg+='\nIf you want to impose a specific topology, you can directly pass a '
+ msg+='Cartesian instance into operator\'s input or output variables dictionnary instead.'
+ if isinstance(handle, Discretization):
+ if handle.ghosts.sum() > 0:
+ raise ValueError(msg)
+ if not hasattr(operator, 'mpi_params'):
+ msg='mpi_params has not been set in operator {}.'.format(operator.name)
+ raise RuntimeError(msg)
+ return CartesianDescriptor(
+ backend=backend,
+ domain=field.domain,
+ mpi_params=operator.mpi_params,
+ discretization=handle,
+ **kwds)
+ elif isinstance(handle, CartesianDescriptor):
+ if handle.discretization.ghosts.sum() > 0:
+ raise ValueError(msg)
+ return handle
+ else:
+ # handle is a Cartesian instance, ghosts can be imposed freely by user here
+ return handle
+
+ def _global_mesh(self, domain, discretization):
+ assert discretization.resolution.size == domain.dimension
+ assert domain.dimension == discretization.resolution.size, \
+ 'The resolution size differs from the domain dimension.'
+
+ periodic = BoundaryCondition.PERIODIC
+ is_lperiodic = (domain.boundaries[0]==periodic)
+ is_rperiodic = (domain.boundaries[1]==periodic)
+ assert (is_lperiodic == is_rperiodic).all()
+
+ global_start = npw.dim_zeros(shape=(domain.dimension))
+ local_resolution = discretization.resolution - is_lperiodic
+
+ mesh = Mesh(domain, discretization,
+ local_resolution, global_start)
+
+ return mesh
+
+ def choose_topology(self, known_topologies, **kwds):
+ """
+ Find optimal topology parameters from known_topologies.
+ If None is returned, create_topology will be called instead.
+ """
+ pass
+
+ def create_topology(self, cutdir, ghosts):
+ """
+ Build a topology with the current TopologyDescriptor.
+ Free parameters are cutdir and ghosts which are imposed
+ by operators on variables and solved during operator's
+ method get_field_requirements().
+ """
+ is_periodic = self.is_periodic()
+ discretization = Discretization(self.discretization.resolution, ghosts)
+ return Cartesian(domain=self.domain, discretization=discretization,
+ mpi_params=self.mpi_params, isperiodic=is_periodic,
+ cutdir=cutdir, backend=self.backend, **self.extra_kwds)
+
+
+CartesianDescriptors = (Cartesian, CartesianDescriptor, Discretization)
+"""
+Instance of those types can be used to create a CartesianDescriptor.
+Thus they can be passed in the variables of each operator supporting
+Cartesian topologies.
+"""
diff --git a/hysop/default_methods.py b/hysop/default_methods.py
deleted file mode 100644
index 6edf5868d957f7178f83aa4f018095d5918df151..0000000000000000000000000000000000000000
--- a/hysop/default_methods.py
+++ /dev/null
@@ -1,60 +0,0 @@
-"""Default parameters values for numerical methods in operators.
-"""
-from hysop.methods_keys import TimeIntegrator, Interpolation, GhostUpdate,\
- Remesh, Support, Splitting, MultiScale, Formulation, SpaceDiscretisation, \
- Precision
-from hysop.constants import HYSOP_REAL
-from hysop.numerics.odesolvers import RK2, RK3
-from hysop.numerics.interpolation import Linear
-from hysop.numerics.remeshing import L2_1, Linear as Rmsh_Linear
-from hysop.numerics.finite_differences import FDC4, FDC2
-#from hysop.operator.discrete.stretching import Conservative
-
-
-# ADVECTION = {TimeIntegrator: RK2, Interpolation: Linear,
- # Remesh: L2_1, Support: '', Splitting: 'o2', MultiScale: L2_1,
- # Precision: HYSOP_REAL}
-ADVECTION = {Support:'python'}
-"""Advection operators default setup
- other default parameters are Support dependant.
-"""
-
-DIFFERENTIAL = {SpaceDiscretisation: FDC4, GhostUpdate: True}
-"""Differential operators (finite differencies based) default setup
-"""
-
-ADAPT_TIME_STEP = {TimeIntegrator: RK3, SpaceDiscretisation: FDC4}
-"""Adaptative time step default setup
-"""
-
-BAROCLINIC = {SpaceDiscretisation: FDC4}
-"""Baroclinic operators default setup
-"""
-
-MULTIPHASEBAROCLINIC = {SpaceDiscretisation: FDC4}
-
-MULTIPHASEGRADP = {SpaceDiscretisation: FDC4}
-
-DIFFUSION = {SpaceDiscretisation: 'fftw', GhostUpdate: True}
-"""Differential operators (finite differencies based) default setup
-"""
-
-POISSON = {SpaceDiscretisation: 'fftw', GhostUpdate: True,
- Formulation: 'velocity'}
-"""Poisson operators default setup
-"""
-
-STRETCHING = {TimeIntegrator: RK3, Formulation: 'Conservative',
- SpaceDiscretisation: FDC4}
-GPU_STRETCHING = {TimeIntegrator: RK3, Formulation: 'GradUW',
- SpaceDiscretisation: FDC4, Support: 'GPU' }
-"""Stretching operators default setup
-"""
-
-FORCES = {SpaceDiscretisation: FDC2}
-"""Drag/lift computation operators default setup
-"""
-
-MULTIRESOLUTION_FILTER = {Remesh: Rmsh_Linear, }
-"""filters operators default setup
-"""
diff --git a/hysop/deps.py b/hysop/deps.py
new file mode 100644
index 0000000000000000000000000000000000000000..7abbe217de97a4fb1cff9b4ed447a2ef96f0181a
--- /dev/null
+++ b/hysop/deps.py
@@ -0,0 +1,39 @@
+
+from __future__ import absolute_import
+from __future__ import print_function
+
+try:
+ import __builtin__
+except:
+ import builtins as __builtin__
+
+try:
+ import cPickle as pickle
+except:
+ import pickle
+
+try:
+ import h5py
+except ImportError as e:
+ h5py = None
+ msg = 'Warning: h5py not found, you may not be able to'
+ msg += ' use hdf5 I/O functionnalities.'
+ print(msg)
+
+import sys, os, subprocess, platform
+import resource, psutil, tempfile, cpuinfo
+import inspect, functools, operator
+import hashlib, gzip, copy, types, string
+import math, re, contextlib
+import six, itertools
+
+import itertools as it
+import numpy as np
+
+import sympy as sm
+import sympy.abc, sympy.polys, sympy.solvers, sympy.functions
+
+import scipy as sp
+import scipy.linalg, scipy.interpolate
+
+import gmpy2 as gmp
diff --git a/hysop/domain/box.py b/hysop/domain/box.py
index 7a45d2e8142165a21bc9071ac7869d4f89efddb1..b6260152dc6ac9ceb556306e37b0ef0913674831 100644
--- a/hysop/domain/box.py
+++ b/hysop/domain/box.py
@@ -1,8 +1,9 @@
"""Box-shaped domains definition.
"""
+from hysop.constants import BoundaryCondition
from hysop.domain.domain import Domain
-from hysop.constants import PERIODIC, debug
-import hysop.tools.numpywrappers as npw
+from hysop.tools.decorators import debug
+from hysop.tools.numpywrappers import npw
class Box(Domain):
@@ -45,30 +46,44 @@ class Box(Domain):
length = [1.0] * self.dimension
if origin is None:
origin = [0.] * self.dimension
- self.length = npw.const_realarray(length)
+ self.length = npw.asrealarray(length)
# Box origin
- self.origin = npw.const_realarray(origin)
+ self.origin = npw.asrealarray(origin)
# Maximum Box position. max = origin + length
self.end = self.origin + self.length
# set periodic boundary conditions
+ bc = BoundaryCondition.PERIODIC
if self.boundaries is None:
- self.boundaries = npw.asdimarray([PERIODIC] * self.dimension)
+ self.boundaries = (npw.asarray((bc,) * self.dimension),
+ npw.asarray((bc,) * self.dimension))
else:
msg = 'Boundary conditions must be periodic.'
- assert list(self.boundaries).count(PERIODIC) == self.dimension, msg
+ assert (self.boundaries[0]==BoundaryCondition.PERIODIC).all() \
+ and (self.boundaries[1]==BoundaryCondition.PERIODIC).all(), msg
def __str__(self):
- s = str(self.dimension) + \
- "D box (parallelepipedic or rectangular) domain : \n"
-
- s += " origin : " + str(self.origin) + ", maxPosition :" \
- + str(self.end) + ", lengths :" + str(self.length) + "."
+ s = 'domain:'
+ s+= '\n *{}D rectangular box'.format(self.dimension)
+ s+= '\n *origin: {}'.format(self.origin)
+ s+= '\n *max_pos: {}'.format(self.end)
+ s+= '\n *length: {}'.format(self.length)
+ s+= '\n *boundary conditions: {}'.format(self.boundaries)
+ s+= '\n'
return s
+ def short_description(self):
+ return 'Box(O=[{}], L=[{}], BC=[{}], task={})'.format(
+ ','.join(('{:1.1f}'.format(val) for val in self.origin)),
+ ','.join(('{:1.1f}'.format(val) for val in self.length)),
+ ','.join(('{}/{}'.format(str(lb)[:3],str(rb)[:3]) for (lb,rb) in zip(*self.boundaries))),
+ self.current_task())
+
+
def __eq__(self, other):
c1 = (self.length == other.length).all()
c2 = (self.origin == other.origin).all()
- c3 = (self.boundaries == other.boundaries).all()
+ c3 = (self.boundaries[0] == other.boundaries[0]).all()
+ c3 = (self.boundaries[1] == other.boundaries[1]).all()
c4 = self.current_task() == other.current_task()
return c1 and c2 and c3 and c4
diff --git a/hysop/domain/control_box.py b/hysop/domain/control_box.py
index 2664e4f6c423facd1ba69e344ada9afb4a0b4bc4..868496bf9e6959312c4fab217c12d15a404e558c 100644
--- a/hysop/domain/control_box.py
+++ b/hysop/domain/control_box.py
@@ -1,7 +1,7 @@
"""Define a volume of control inside a domain (volume + all faces)"""
from hysop.domain.subsets import SubBox
import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
class ControlBox(SubBox):
@@ -66,7 +66,7 @@ class ControlBox(SubBox):
----------
field : :class:`~hysop.fields.continuous.Field`
a field to be integrated on the box
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
list_dir : list of int
indices of faces on which integration is required
@@ -100,7 +100,7 @@ class ControlBox(SubBox):
----------
field : :class:`~hysop.fields.continuous.Field`
a field to be integrated on the box
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
list_dir : list of int
indices of faces on which integration is required
@@ -123,7 +123,7 @@ class ControlBox(SubBox):
for i in xrange(nbc):
res[i] += surf.integrate_field_on_proc(field, topo, i)
if root is None:
- topo.comm.Allreduce(res, gres)
+ topo.comm.Allreduce(res.handle(), gres.handle())
else:
- topo.comm.Reduce(res, gres, root=root)
+ topo.comm.Reduce(res.handle(), gres.handle(), root=root)
return gres
diff --git a/hysop/domain/domain.py b/hysop/domain/domain.py
index 7ba343ab6a0518ea79d2b831c551159c92061c9c..a5c5674444345489cc5b4180a76f3476029f5ad7 100644
--- a/hysop/domain/domain.py
+++ b/hysop/domain/domain.py
@@ -2,10 +2,11 @@
"""
from abc import ABCMeta, abstractmethod
-from hysop.constants import debug, DEFAULT_TASK_ID, PERIODIC
-from hysop.mpi.topology import Cartesian
-from hysop.mpi import main_rank, main_size, main_comm
+from hysop.constants import HYSOP_DEFAULT_TASK_ID, BoundaryCondition
+from hysop.core.mpi.topology import Cartesian
+from hysop.core.mpi import main_rank, main_size, main_comm
from hysop.tools.parameters import MPIParams
+from hysop.tools.decorators import debug
import numpy as np
@@ -13,14 +14,26 @@ class Domain(object):
"""Abstract base class for description of physical domain. """
__metaclass__ = ABCMeta
+
+ __registered_domains = {}
@debug
- def __new__(cls, *args, **kw):
- return object.__new__(cls, *args, **kw)
+ def __new__(cls, **kwds):
+ key = tuple(kwds[k] for k in sorted(kwds.keys()))
+ __registered_domains = cls.__registered_domains
+ if key in __registered_domains:
+ obj = __registered_domains[key]
+ assert obj._initialized
+ else:
+ obj = super(Domain, cls).__new__(cls, **kwds)
+ obj._initialized = False
+ __registered_domains[key] = obj
+ return obj
@debug
@abstractmethod
- def __init__(self, dimension=3, proc_tasks=None, bc=None):
+ def __init__(self, dimension=3, proc_tasks=None,
+ lbc=None, rbc=None):
"""
Parameters
@@ -28,37 +41,44 @@ class Domain(object):
dimension : integer, optional
proc_tasks : list or array of int, optional
connectivity between mpi process id and task number.
- See notes below. Default : all procs on task DEFAULT_TASK_ID.
- bc : list or array of int, optional
- type of boundary condtions. See notes below.
+ See notes below. Default : all procs on task HYSOP_DEFAULT_TASK_ID.
+ lbc : list or array of BoundaryCondition
+ left boundary conditions
+ rbc : list or array of BoundaryCondition
+ right boundary conditions
Attributes
----------
dimension : int
- topologies : dictionnary of :class:`~hysop.mpi.topology.Cartesian`
+ topologies : dictionnary of :class:`~hysop.core.mpi.topology.Cartesian`
all topologies already built for this domain.
comm_task : mpi communicator
corresponds to the task that owns the current process.
- boundaries : list or array of int
+ boundaries : list or array of BoundaryCondition
boundary conditions type.
Notes
-----
* About boundary conditions:
- At the time, only periodic boundary conditions are implemented.
+ At this time, only periodic boundary conditions are implemented.
Do not use this parameter (i.e. let default values)
*About MPI Tasks
proc_tasks[n] = 12 means that task 12 owns proc n.
"""
+
+ if self._initialized:
+ return
+ self._initialized = True
+
# Domain dimension.
self.dimension = dimension
# A list of all the topologies defined on this domain.
# Each topology is unique in the sense defined by
- # the comparison operator in the class hysop.mpi.topology.Cartesian.
+ # the comparison operator in the class hysop.core.mpi.topology.Cartesian.
self.topologies = {}
# Connectivity between mpi tasks and proc numbers :
@@ -69,7 +89,7 @@ class Domain(object):
# Maybe we should change this and allow proc_tasks in subcomm
# but at the time it's not necessary.
if proc_tasks is None:
- self._tasks_on_proc = [DEFAULT_TASK_ID, ] * main_size
+ self._tasks_on_proc = [HYSOP_DEFAULT_TASK_ID, ] * main_size
comm_s = main_comm
else:
assert len(proc_tasks) == main_size
@@ -83,12 +103,14 @@ class Domain(object):
self.comm_task = comm_s
# Boundary conditions type.
# At the moment, only periodic conditions are allowed.
- self.boundaries = bc
+ lbc = lbc or (BoundaryCondition.PERIODIC,)*dimension
+ rbc = rbc or (BoundaryCondition.PERIODIC,)*dimension
+ self.boundaries = (np.asarray(lbc), np.asarray(rbc))
def is_on_task(self, params):
"""Test if the current process corresponds to param task.
- :param params: :class:`~hysop.mpi.MPIParams` or int
+ :param params: :class:`~hysop.core.mpi.MPIParams` or int
description of the mpi setup or task number.
or an int (task number)
:return bool:
@@ -134,7 +156,7 @@ class Domain(object):
def create_topology(self, discretization, dim=None, mpi_params=None,
shape=None, cutdir=None, isperiodic=None,
cartesian_topology=None):
- """Create or return an existing :class:`~hysop.mpi.topology.Cartesian`.
+ """Create or return an existing :class:`~hysop.core.mpi.topology.Cartesian`.
Parameters
-----------
@@ -145,7 +167,7 @@ class Domain(object):
mpi topology dimension.
mpi_params : :class:`~hysop.tools.parameters.MPIParams`, optional
mpi setup (comm, task ...).
- If None, comm = main_comm, task = DEFAULT_TASK_ID.
+ If None, comm = main_comm, task = HYSOP_DEFAULT_TASK_ID.
shape : list or array of int
mpi grid layout
cutdir : list or array of bool
@@ -160,10 +182,10 @@ class Domain(object):
Returns
-------
- :class:`~hysop.mpi.topology.Cartesian`
+ :class:`~hysop.core.mpi.topology.Cartesian`
Either it gets the topology corresponding to the input arguments
if it exists (in the sense of the comparison operator defined in
- :class:`~hysop.mpi.topology.Cartesian`)
+ :class:`~hysop.core.mpi.topology.Cartesian`)
or it creates a new topology and register it in the topology dict.
Notes:
@@ -212,7 +234,7 @@ class Domain(object):
direction where data must be distributed in priority.
Default = last if fortran order, first if C order.
**kwds : other args
- used in :class:`~hysop.mpi.topology.Cartesian` build.
+ used in :class:`~hysop.core.mpi.topology.Cartesian` build.
"""
tid = self.current_task()
@@ -295,9 +317,13 @@ class Domain(object):
return result
return not result
+ @abstractmethod
+ def short_description(self):
+ pass
+
def i_periodic_boundaries(self):
"""
Returns the list of directions where
boundaries are periodic
"""
- return np.where(self.boundaries == PERIODIC)[0]
+ return np.where(self.boundaries == BoundaryCondition.PERIODIC)[0]
diff --git a/hysop/domain/mesh.py b/hysop/domain/mesh.py
index 01ea25d8677820689dbbc0a7d40c8ab176c4f171..8420a20f813e11ff0d9b2abe00a8908abb8c0b72 100644
--- a/hysop/domain/mesh.py
+++ b/hysop/domain/mesh.py
@@ -3,15 +3,16 @@
See also
--------
-* :class:`~hysop.mpi.topology.Cartesian`
+* :class:`~hysop.core.mpi.topology.Cartesian`
* :ref:`topologies` in HySoP user guide.
"""
-from hysop.constants import debug
-import hysop.tools.numpywrappers as npw
+from hysop.constants import np, BoundaryCondition
from hysop.tools.parameters import Discretization
-import numpy as np
from hysop.tools.misc import Utils
+from hysop.tools.decorators import debug
+from hysop.tools.numpywrappers import npw
+from hysop.tools.string_utils import prepend
class Mesh(object):
@@ -124,7 +125,7 @@ class Mesh(object):
# ---
# Local resolution of this mesh, INCLUDING ghost points
- self.resolution = npw.const_dimarray(resolution)
+ self.resolution = npw.asdimarray(resolution)
# Position of the local mesh in the global grid
self.position = []
@@ -134,7 +135,7 @@ class Mesh(object):
# last computational point, global index
ghosts = self.discretization.ghosts
# resolution of the computational grid (i.e. grid without ghosts)
- self.compute_resolution = tuple(npw.const_dimarray(resolution) -
+ self.compute_resolution = tuple(npw.asdimarray(resolution) -
2 * ghosts)
# shift between local and global index,
@@ -171,13 +172,30 @@ class Mesh(object):
gend = self.discretization.resolution - 1
# Is this mesh on the last process in some direction in the
# mpi grid of process?
+ is_first = np.asarray([self.position[d].start == 0
+ for d in xrange(self._dim)])
is_last = np.asarray([gend[d] < self.position[d].stop
for d in xrange(self._dim)])
+ self.is_first = is_first
+ self.is_last = is_last
+
# indices of points that must be used to compute integrals on this mesh
self.ind4integ = self.compute_integ_point(is_last, self.compute_index)
self.coords4int = self.reduce_coords(self.coords, self.ind4integ)
# True if the current mesh is locally defined on the current mpi proc.
self.on_proc = True
+
+ # global boundaries
+ (lboundaries, rboundaries) = self.domain.boundaries
+ self.global_boundaries = (lboundaries, rboundaries)
+
+ # local boundaries
+ lboundaries = np.asarray( [bc if is_first[i] else BoundaryCondition.NONE
+ for (i,bc) in enumerate(lboundaries)] )
+ rboundaries = np.asarray( [bc if is_last[i] else BoundaryCondition.NONE
+ for (i,bc) in enumerate(rboundaries)] )
+
+ self.boundaries = (lboundaries, rboundaries)
@staticmethod
def compute_integ_point(is_last, ic, n_dir=None):
@@ -268,11 +286,11 @@ class Mesh(object):
"""
mesh display
"""
- s = 'Local mesh: \n'
- s += ' - resolution : ' + str(self.resolution) + '\n'
- s += ' - position in global mesh: ' + str(self.position) + '\n'
- s += ' - global discretization : ' + str(self.discretization) + '\n'
- s += ' - computation points :' + str(self.compute_index) + '\n'
+ s = 'local mesh:\n'
+ s += ' *resolution: ' + str(self.resolution) + '\n'
+ s += ' *position in global mesh: ' + str(self.position) + '\n'
+ s += prepend('*global '+str(self.discretization),' '*2) + '\n'
+ s += ' *computation points: ' + str(self.compute_index)+'\n'
return s
def convert2local(self, sl):
diff --git a/hysop/domain/porous.py b/hysop/domain/porous.py
index fcbeb09bfd3839121b14733133d13e26758cfc1f..854b67cf0d7b5b6e27420e7286fe7238113d980c 100644
--- a/hysop/domain/porous.py
+++ b/hysop/domain/porous.py
@@ -16,8 +16,8 @@ See also
"""
from hysop.domain.subsets import Subset, Sphere, HemiSphere
from hysop.domain.subsets import Cylinder, HemiCylinder, SubBox
-import hysop.tools.numpywrappers as npw
-from hysop.mpi.topology import Cartesian
+from hysop.tools.numpywrappers import npw
+from hysop.core.mpi.topology import Cartesian
import numpy as np
diff --git a/hysop/domain/submesh.py b/hysop/domain/submesh.py
index 412f5fb63175e4ab7e23f872405f90c23215ea3c..dda8c068c81162afba5b30a66478fc39e773ddbc 100644
--- a/hysop/domain/submesh.py
+++ b/hysop/domain/submesh.py
@@ -2,7 +2,7 @@
(like a subset for a domain)
"""
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.tools.parameters import Discretization
import numpy as np
from hysop.tools.misc import Utils
diff --git a/hysop/domain/subsets.py b/hysop/domain/subsets.py
index 5dbdd9b245907ebe8768901806919a9c88d6aa02..6260cf43f1e46b0b29218f581bd5d25dcd018e4c 100644
--- a/hysop/domain/subsets.py
+++ b/hysop/domain/subsets.py
@@ -16,13 +16,13 @@ See also
"""
from hysop.domain.domain import Domain
import numpy as np
-from hysop.mpi.topology import Cartesian
+from hysop.core.mpi.topology import Cartesian
from hysop.fields.discrete import DiscreteField
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.fields.continuous import Field
from hysop.domain.submesh import SubMesh
import numpy.linalg as la
-from hysop.mpi import MPI
+from hysop.core.mpi import MPI
class Subset(object):
@@ -137,7 +137,7 @@ class Subset(object):
Create the list of indices for points inside the subset
for a given topo.
- :param topo: :class:`hysop.mpi.topology.Cartesian`
+ :param topo: :class:`hysop.core.mpi.topology.Cartesian`
Returns
-------
@@ -158,7 +158,7 @@ class Subset(object):
"""Build a subset from a group of subsets
Parameters
----------
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
union : bool, optional
compute union of subsets if True, else intersection
"""
@@ -187,8 +187,8 @@ class Subset(object):
self.max_subcoords[topo] = None
if self.on_proc[topo]:
self.max_subcoords[topo] = topo.proc_coords.copy()
- self.subcomm[topo].Allreduce(topo.proc_coords,
- self.max_subcoords[topo],
+ self.subcomm[topo].Allreduce(topo.proc_coords.handle(),
+ self.max_subcoords[topo].handle(),
op=MPI.MAX)
@staticmethod
@@ -198,7 +198,7 @@ class Subset(object):
Parameters
----------
slist : a list of :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
-------
@@ -216,7 +216,7 @@ class Subset(object):
Parameters
----------
slist : a list of :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
-------
@@ -242,7 +242,7 @@ class Subset(object):
Parameters
----------
s1, s2 : lists of :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
-------
@@ -260,7 +260,7 @@ class Subset(object):
Parameters
----------
slist : list of :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
--------
@@ -278,7 +278,7 @@ class Subset(object):
Parameters
----------
slist : list of :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
--------
@@ -304,7 +304,7 @@ class Subset(object):
Parameters
----------
s1, s2 : :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
--------
@@ -320,7 +320,7 @@ class Subset(object):
Parameters
----------
s1, s2 : :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
--------
@@ -338,7 +338,7 @@ class Subset(object):
Parameters
----------
s1, s2 : list of :class:`~hysop.domain.subsets.Subset`
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
Returns
--------
@@ -355,7 +355,7 @@ class Subset(object):
----------
field : :class:`~hysop.fields.continuous.Field`
a field to be integrated on the box
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
root : int, optional
rank of the leading mpi process (to collect data)
@@ -366,14 +366,14 @@ class Subset(object):
a numpy array, with res[i] = integral of component i
of the input field over the current subset.
"""
- res = npw.zeros(field.nb_components)
+ res = npw.zeros(field.nb_components)
gres = npw.zeros(field.nb_components)
for i in xrange(res.size):
res[i] = self.integrate_field_on_proc(field, topo, component=i)
if root is None:
- topo.comm.Allreduce(res, gres)
+ topo.comm.Allreduce(res.handle(), gres.handle())
else:
- topo.comm.Reduce(res, gres, root=root)
+ topo.comm.Reduce(res.handle(), gres.handle(), root=root)
return gres
@@ -384,7 +384,7 @@ class Subset(object):
----------
field : :class:`~hysop.fields.continuous.Field`
a field to be integrated on the box
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
component : int, optional
number of the field component to be integrated
@@ -410,7 +410,7 @@ class Subset(object):
----------
field : :class:`~hysop.fields.continuous.Field`
a field to be integrated on the box
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
component : int, optional
number of the field component to be integrated
@@ -450,9 +450,9 @@ class Subset(object):
for i in xrange(res.size):
res[i] = self.integrate_dfield_on_proc(field, component=i)
if root is None:
- field.topology.comm.Allreduce(res, gres)
+ field.topology.comm.Allreduce(res.handle(), gres.handle())
else:
- field.topology.comm.Reduce(res, gres, root=root)
+ field.topology.comm.Reduce(res.handle(), gres.handle(), root=root)
return gres
@@ -730,7 +730,7 @@ class SubBox(Subset):
"""
Compute a local submesh on the subset, for a given topology
- :param topo: :class:`~hysop.mpi.topology.Cartesian`
+ :param topo: :class:`~hysop.core.mpi.topology.Cartesian`
"""
assert isinstance(topo, Cartesian)
if topo in self.mesh:
@@ -741,10 +741,10 @@ class SubBox(Subset):
gstart = topo.mesh.global_indices(self.origin)
gend = topo.mesh.global_indices(self.origin + self.length)
# create a submesh
- self.mesh[topo] = SubMesh(topo.mesh, gstart, gend)
+ self.mesh[topo] = SubMesh(topo.mesh, gstart, gend)
self.real_length[topo] = self.mesh[topo].global_length
- self.real_orig[topo] = self.mesh[topo].global_origin
- self.ind[topo] = [self.mesh[topo].compute_index]
+ self.real_orig[topo] = self.mesh[topo].global_origin
+ self.ind[topo] = [self.mesh[topo].compute_index]
self._reduce_topology(topo)
return self.ind[topo]
@@ -778,8 +778,10 @@ class SubBox(Subset):
self.max_subcoords[topo] = None
if self.on_proc[topo]:
self.max_subcoords[topo] = topo.proc_coords.copy()
- self.subcomm[topo].Allreduce(topo.proc_coords,
- self.max_subcoords[topo],
+ print topo.proc_coords.__class__
+ print topo.proc_coords.__array_interface__
+ self.subcomm[topo].Allreduce(topo.proc_coords.handle(),
+ self.max_subcoords[topo].handle(),
op=MPI.MAX)
def integrate_field_on_proc(self, field, topo, component=0):
@@ -789,7 +791,7 @@ class SubBox(Subset):
----------
field : :class:`~hysop.field.continuous.Field`
a field to be integrated on the box
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
component : int, optional
number of the field component to be integrated
@@ -815,7 +817,7 @@ class SubBox(Subset):
Parameters
----------
func: python function of space coordinates
- topo: :class:`~hysop.mpi.topology.Cartesian`
+ topo: :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
nbc : int
number of components of the return value from func
@@ -831,9 +833,9 @@ class SubBox(Subset):
for i in xrange(res.size):
res[i] = self.integrate_func_on_proc(func, topo)
if root is None:
- topo.comm.Allreduce(res, gres)
+ topo.comm.Allreduce(res.handle(), gres.handle())
else:
- topo.comm.Reduce(res, gres, root=root)
+ topo.comm.Reduce(res.handle(), gres.handle(), root=root)
return gres
def integrate_func_on_proc(self, func, topo):
@@ -842,7 +844,7 @@ class SubBox(Subset):
Parameters
----------
func: python function of space coordinates
- topo: :class:`~hysop.mpi.topology.Cartesian`
+ topo: :class:`~hysop.core.mpi.topology.Cartesian`
set mesh/topology used for integration
Returns
diff --git a/hysop/domain/tests/test_box.py b/hysop/domain/tests/test_box.py
index 24a12f79a52c1a6222ea2fd973dce23fb8b16332..49eb8a7139787c01322783dfdc75a767f5194966 100755
--- a/hysop/domain/tests/test_box.py
+++ b/hysop/domain/tests/test_box.py
@@ -1,11 +1,11 @@
"""
Testing hysop.domain.box.Box
"""
-from hysop.constants import PERIODIC, DEFAULT_TASK_ID
+from hysop.constants import BoundaryCondition, HYSOP_DEFAULT_TASK_ID
from hysop.domain.box import Box
from numpy import allclose, ones_like, zeros_like
-import hysop.tools.numpywrappers as npw
-from hysop.mpi import main_size, main_rank
+from hysop.tools.numpywrappers import npw
+from hysop.core.mpi import main_size, main_rank
def test_create_box1():
@@ -13,8 +13,8 @@ def test_create_box1():
assert dom.dimension == 3
assert allclose(dom.length, ones_like(dom.length))
assert allclose(dom.origin, zeros_like(dom.origin))
- assert [b == PERIODIC for b in dom.boundaries]
- cond = [dom.tasks_on_proc(i) == DEFAULT_TASK_ID for i in range(main_size)]
+ assert [b == BoundaryCondition.PERIODIC for b in dom.boundaries]
+ cond = [dom.tasks_on_proc(i) == HYSOP_DEFAULT_TASK_ID for i in range(main_size)]
cond = npw.asboolarray(cond)
assert cond.all()
@@ -26,8 +26,8 @@ def test_create_box2():
assert dom.dimension == 2
assert allclose(dom.length, length)
assert allclose(dom.origin, ori)
- assert [b == PERIODIC for b in dom.boundaries]
- cond = [dom.tasks_on_proc(i) == DEFAULT_TASK_ID for i in range(main_size)]
+ assert [b == BoundaryCondition.PERIODIC for b in dom.boundaries]
+ cond = [dom.tasks_on_proc(i) == HYSOP_DEFAULT_TASK_ID for i in range(main_size)]
cond = npw.asboolarray(cond)
assert cond.all()
@@ -38,8 +38,8 @@ def test_create_box3():
assert dom.dimension == 3
assert allclose(dom.length, npw.asrealarray(length))
assert allclose(dom.origin, zeros_like(length))
- assert [b == PERIODIC for b in dom.boundaries]
- cond = [dom.tasks_on_proc(i) == DEFAULT_TASK_ID for i in range(main_size)]
+ assert [b == BoundaryCondition.PERIODIC for b in dom.boundaries]
+ cond = [dom.tasks_on_proc(i) == HYSOP_DEFAULT_TASK_ID for i in range(main_size)]
cond = npw.asboolarray(cond)
assert cond.all()
@@ -72,12 +72,12 @@ GPU = 29
proc_tasks = [CPU] * main_size
if main_size > 1:
proc_tasks[-1] = GPU
-from hysop.mpi import main_comm
+from hysop.core.mpi import main_comm
comm_s = main_comm.Split(color=proc_tasks[main_rank], key=main_rank)
mpCPU = MPIParams(comm=comm_s, task_id=CPU)
mpGPU = MPIParams(comm=comm_s, task_id=GPU)
-from hysop.mpi.topology import Cartesian
+from hysop.core.mpi.topology import Cartesian
def test_topo_standard():
@@ -122,6 +122,8 @@ def test_topo_plane():
def test_topo_from_mesh():
+ """Build a topology from a previoulsy defined mesh.
+ """
# e.g. for fftw
dom = Box(proc_tasks=proc_tasks)
from hysop import __FFTW_ENABLED__
diff --git a/hysop/domain/tests/test_control_box.py b/hysop/domain/tests/test_control_box.py
index 8feb3b925b4f7e00266eebc15ddd4e44403908f4..3caa80381f769091badac6b56a771a854f59499d 100755
--- a/hysop/domain/tests/test_control_box.py
+++ b/hysop/domain/tests/test_control_box.py
@@ -4,7 +4,7 @@ from hysop.tools.parameters import Discretization
from hysop import Field, Box
import numpy as np
import math
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
Nx = 128
diff --git a/hysop/domain/tests/test_mesh.py b/hysop/domain/tests/test_mesh.py
index 261abb444423a07bbd0ac43020e35a782a3f8d1a..2a932d2b581ffb90a05d4b4b819ecd0a9e573611 100755
--- a/hysop/domain/tests/test_mesh.py
+++ b/hysop/domain/tests/test_mesh.py
@@ -3,8 +3,8 @@
from hysop.domain.box import Box
from hysop.fields.continuous import Field
from hysop.tools.parameters import Discretization
-from hysop.mpi import main_size, main_rank
-import hysop.tools.numpywrappers as npw
+from hysop.core.mpi import main_size, main_rank
+from hysop.tools.numpywrappers import npw
import numpy as np
Nx = Ny = Nz = 32
diff --git a/hysop/domain/tests/test_porous.py b/hysop/domain/tests/test_porous.py
index 39dd869dd276e04531a3ef3814bc2c1ac651f066..4eaea1cda723839058cda1e6de55e611bd59b0a6 100755
--- a/hysop/domain/tests/test_porous.py
+++ b/hysop/domain/tests/test_porous.py
@@ -1,10 +1,10 @@
""" Tests for porous subsets module"""
from hysop import Field, Box, Discretization, IOParams
-from hysop.mpi.topology import Cartesian
+from hysop.core.mpi.topology import Cartesian
from hysop.domain.subsets import HemiSphere, Sphere
from hysop.domain.subsets import Cylinder, HemiCylinder
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
from hysop.domain.porous import BiPole, QuadriPole,\
Ring, RingPole, Porous
@@ -20,7 +20,7 @@ import math
ldom = npw.asrealarray([math.pi * 2., ] * 3)
xdom = npw.asrealarray([0.1, -0.3, 0.5])
import os
-working_dir = os.getcwd() + "/"
+src_dir = os.path.dirname(__file__) + '/ref_files/'
xpos = npw.asrealarray(ldom * 0.5)
xpos[-1] += 0.1
@@ -31,7 +31,7 @@ def init_model(dref, filename):
dom = Box(dimension=dim, length=ldom[:dim], origin=xdom[:dim])
topo = dom.create_topology(dref)
sref = Field(domain=dom, name='scal')
- iop = IOParams(working_dir + filename)
+ iop = IOParams(src_dir + filename)
# read sref from reference file
wr = HDF_Reader(variables={sref: topo}, io_params=iop, restart=0)
wr.discretize()
diff --git a/hysop/domain/tests/test_regular_subset.py b/hysop/domain/tests/test_regular_subset.py
index 78c161c9ebc781d06f8fb1c59a009c2459a5b3e4..762b8a604ed035d3bf5054874528c1a2b33dfe5a 100755
--- a/hysop/domain/tests/test_regular_subset.py
+++ b/hysop/domain/tests/test_regular_subset.py
@@ -1,7 +1,7 @@
from hysop.domain.subsets import SubBox
from hysop.tools.parameters import Discretization
from hysop import Field, Box
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
import math
diff --git a/hysop/domain/tests/test_submesh.py b/hysop/domain/tests/test_submesh.py
index b4efae725daad40d11b7d4cc6c51e570ae6a9070..d6844d113c760d3dd9db0255f2a914774b180b9e 100755
--- a/hysop/domain/tests/test_submesh.py
+++ b/hysop/domain/tests/test_submesh.py
@@ -6,7 +6,7 @@ from hysop.tools.parameters import Discretization
from hysop.domain.submesh import SubMesh
from hysop.tools.misc import Utils
import numpy as np
-from hysop.mpi import main_rank
+from hysop.core.mpi import main_rank
Nx = Ny = Nz = 32
g = 2
diff --git a/hysop/domain/tests/test_subset.py b/hysop/domain/tests/test_subset.py
index 8f3de686d3983a3ceb67fbbdd0ac7ad16a78b60b..131e06601719f4e8ea1173bc01ef4de7b782d2fa 100755
--- a/hysop/domain/tests/test_subset.py
+++ b/hysop/domain/tests/test_subset.py
@@ -8,8 +8,8 @@ from hysop.operator.hdf_io import HDF_Reader
from hysop.tools.parameters import Discretization
from hysop.tools.io_utils import IOParams
from hysop import Field, Box
-from hysop.mpi.topology import Cartesian
-import hysop.tools.numpywrappers as npw
+from hysop.core.mpi.topology import Cartesian
+from hysop.tools.numpywrappers import npw
import numpy as np
import math
@@ -29,7 +29,7 @@ xdef = npw.asrealarray(xdom + 0.2)
xpos = npw.asrealarray(ldom * 0.5)
xpos[-1] += 0.1
import os
-working_dir = os.getcwd() + "/"
+src_dir = os.path.dirname(__file__) + '/ref_files/'
def check_subset(discr, fileref, class_name):
@@ -40,7 +40,7 @@ def check_subset(discr, fileref, class_name):
topo = dom.create_topology(discr)
vref = Field(domain=topo.domain, name='vref')
vd = vref.discretize(topo)
- iop = IOParams(working_dir + fileref)
+ iop = IOParams(src_dir + fileref)
reader = HDF_Reader(variables={vref: topo}, io_params=iop, restart=0)
reader.discretize()
reader.setup()
@@ -94,7 +94,7 @@ def init_multi(discr, fileref):
topo = dom.create_topology(discr)
vref = Field(domain=topo.domain, name='vref', is_vector=False)
vd = vref.discretize(topo)
- iop = IOParams(working_dir + fileref)
+ iop = IOParams(src_dir + fileref)
reader = HDF_Reader(variables={vref: topo}, io_params=iop, restart=0)
reader.discretize()
reader.setup()
diff --git a/hysop/f2py/fftw2py.pyf b/hysop/f2py/fftw2py.pyf
deleted file mode 100644
index 860933a2d28a0c960fa8c4840d51a18d3ddf21e7..0000000000000000000000000000000000000000
--- a/hysop/f2py/fftw2py.pyf
+++ /dev/null
@@ -1,130 +0,0 @@
-! -*- f90 -*-
-! Note: the context of this file is case sensitive.
-
-module fftw2py ! in fftw2py.f90
- use fft3d
- !use mpi
- use client_data
- use hysopparam
- use fft2d
- subroutine init_fftw_solver(resolution,lengths,comm,datashape,offset,dim,fftw_type_real) ! in fftw2py.f90:fftw2py
- integer dimension(dim),intent(in) :: resolution
- real(kind=pk) dimension(dim),intent(in),depend(dim) :: lengths
- integer intent(in) :: comm
- integer(kind=ik) dimension(dim),intent(out),depend(dim) :: datashape
- integer(kind=ik) dimension(dim),intent(out),depend(dim) :: offset
- integer, optional,intent(hide),check(len(resolution)>=dim),depend(resolution) :: dim=len(resolution)
- logical, optional,intent(in) :: fftw_type_real=1
- end subroutine init_fftw_solver
- subroutine init_fftw_solver_scalar(resolution,lengths,comm,datashape,offset,dim,fftw_type_real) ! in fftw2py.f90:fftw2py
- integer dimension(dim),intent(in) :: resolution
- real(kind=pk) dimension(dim),intent(in),depend(dim) :: lengths
- integer intent(in) :: comm
- integer(kind=ik) dimension(dim),intent(out),depend(dim) :: datashape
- integer(kind=ik) dimension(dim),intent(out),depend(dim) :: offset
- integer, optional,intent(hide),check(len(resolution)>=dim),depend(resolution) :: dim=len(resolution)
- logical, optional,intent(in) :: fftw_type_real=1
- end subroutine init_fftw_solver_scalar
- subroutine clean_fftw_solver(dim) ! in fftw2py.f90:fftw2py
- integer intent(in) :: dim
- end subroutine clean_fftw_solver
- subroutine solve_poisson_2d(omega,velocity_x,velocity_y,ghosts_vort,ghosts_velo) ! in fftw2py.f90:fftw2py
- real(kind=pk) dimension(:,:),intent(in) :: omega
- real(kind=pk) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_x
- real(kind=pk) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_y
- integer dimension(2),intent(in) :: ghosts_vort
- integer dimension(2),intent(in) :: ghosts_velo
- end subroutine solve_poisson_2d
- subroutine solve_diffusion_2d(nudt,omega,ghosts_vort) ! in fftw2py.f90:fftw2py
- real(kind=pk) intent(in) :: nudt
- real(kind=pk) dimension(:,:),intent(in,out) :: omega
- integer dimension(2),intent(in) :: ghosts_vort
- end subroutine solve_diffusion_2d
- subroutine solve_poisson_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z,ghosts_vort,ghosts_velo) ! in fftw2py.f90:fftw2py
- real(kind=pk) dimension(:,:,:),intent(in) :: omega_x
- real(kind=pk) dimension(:,:,:),intent(in) :: omega_y
- real(kind=pk) dimension(:,:,:),intent(in) :: omega_z
- real(kind=pk) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_x
- real(kind=pk) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_y
- real(kind=pk) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_z
- integer dimension(3),intent(in) :: ghosts_vort
- integer dimension(3),intent(in) :: ghosts_velo
- end subroutine solve_poisson_3d
- subroutine solve_poisson_2d_c(omega,velocity_x,velocity_y) ! in fftw2py.f90:fftw2py
- complex(kind=pk) dimension(:,:),intent(in) :: omega
- complex(kind=pk) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_x
- complex(kind=pk) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_y
- end subroutine solve_poisson_2d_c
- subroutine solve_poisson_3d_c(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z) ! in fftw2py.f90:fftw2py
- complex(kind=pk) dimension(:,:,:),intent(in) :: omega_x
- complex(kind=pk) dimension(:,:,:),intent(in) :: omega_y
- complex(kind=pk) dimension(:,:,:),intent(in) :: omega_z
- complex(kind=pk) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_x
- complex(kind=pk) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_y
- complex(kind=pk) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_z
- end subroutine solve_poisson_3d_c
- subroutine solve_curl_diffusion_3d(nudt,velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
- real(kind=pk) intent(in) :: nudt
- real(kind=pk) dimension(:,:,:),intent(in) :: velocity_x
- real(kind=pk) dimension(:,:,:),intent(in) :: velocity_y
- real(kind=pk) dimension(:,:,:),intent(in) :: velocity_z
- real(kind=pk) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_x
- real(kind=pk) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_y
- real(kind=pk) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_z
- integer dimension(3),intent(in) :: ghosts_velo
- integer dimension(3),intent(in) :: ghosts_vort
- end subroutine solve_curl_diffusion_3d
- subroutine solve_diffusion_3d(nudt,omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
- real(kind=pk) intent(in) :: nudt
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_x
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_y
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_z
- integer dimension(3),intent(in) :: ghosts
- end subroutine solve_diffusion_3d
- subroutine projection_om_3d(omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_x
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_y
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_z
- integer dimension(3),intent(in) :: ghosts
- end subroutine projection_om_3d
- subroutine multires_om_3d(dxf,dyf,dzf,omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
- real(kind=pk) intent(in) :: dxf
- real(kind=pk) intent(in) :: dyf
- real(kind=pk) intent(in) :: dzf
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_x
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_y
- real(kind=pk) dimension(:,:,:),intent(in,out) :: omega_z
- integer dimension(3),intent(in) :: ghosts
- end subroutine multires_om_3d
- subroutine pressure_3d(pressure,ghosts) ! in fftw2py.f90:fftw2py
- real(kind=pk) dimension(:,:,:),intent(in,out) :: pressure
- integer dimension(3),intent(in) :: ghosts
- end subroutine pressure_3d
- subroutine solve_curl_3d(velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
- real(kind=pk) dimension(:,:,:),intent(in) :: velocity_x
- real(kind=pk) dimension(:,:,:),intent(in) :: velocity_y
- real(kind=pk) dimension(:,:,:),intent(in) :: velocity_z
- real(kind=pk) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_x
- real(kind=pk) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_y
- real(kind=pk) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_z
- integer dimension(3),intent(in) :: ghosts_velo
- integer dimension(3),intent(in) :: ghosts_vort
- end subroutine solve_curl_3d
- subroutine solve_curl_2d(velocity_x,velocity_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
- real(kind=pk) dimension(:,:),intent(in) :: velocity_x
- real(kind=pk) dimension(:,:),intent(in) :: velocity_y
- real(kind=pk) dimension(size(velocity_x,1),size(velocity_x,2)),intent(in,out),depend(velocity_x,velocity_x) :: omega_z
- integer dimension(2),intent(in) :: ghosts_velo
- integer dimension(2),intent(in) :: ghosts_vort
- end subroutine solve_curl_2d
- subroutine spectrum_3d(field,spectrum,wavelengths,ghosts,length) ! in fftw2py.f90:fftw2py
- real(kind=pk) dimension(:,:,:),intent(in) :: field
- real(kind=pk) dimension(:),intent(in,out) :: spectrum
- real(kind=pk) dimension(:),intent(in,out) :: wavelengths
- integer dimension(3),intent(in) :: ghosts
- real(kind=pk) intent(in) :: length
- end subroutine spectrum_3d
-end module fftw2py
-
-! This file was auto-generated with f2py (version:2).
-! See http://cens.ioc.ee/projects/f2py2e/
diff --git a/hysop/f2py/parameters.f90 b/hysop/f2py/parameters.f90
deleted file mode 100755
index aa0ad767d0cf935d1a06ed384aa0c89275977ee9..0000000000000000000000000000000000000000
--- a/hysop/f2py/parameters.f90
+++ /dev/null
@@ -1,25 +0,0 @@
-!> Global parameters for f2py interface.
-!!
-!! see https://github.com/numpy/numpy/issues/2428
-!! for some issues
-module hysopparam
-
- implicit none
-
- ! double precision kind
- integer, parameter :: pk = 8
- ! integer precision kind
- integer, parameter :: ik = 8
-
-end module hysopparam
-
-module hysopparam_sp
-
- implicit none
-
- ! single precision kind
- integer, parameter :: pk = 4
- ! integer precision kind
- integer, parameter :: ik = 8
-
-end module hysopparam_sp
diff --git a/hysop/f2py/parameters.pyf b/hysop/f2py/parameters.pyf
deleted file mode 100644
index caefb2e4fd8de7978f125e0bd76d227072b60866..0000000000000000000000000000000000000000
--- a/hysop/f2py/parameters.pyf
+++ /dev/null
@@ -1,14 +0,0 @@
-! -*- f90 -*-
-! Note: the context of this file is case sensitive.
-
-module hysopparam ! in parameters.f90
- integer, parameter,optional :: pk=8
- integer, parameter,optional :: ik=8
-end module hysopparam
-module hysopparam_sp ! in parameters.f90
- integer, parameter,optional :: pk=4
- integer, parameter,optional :: ik=8
-end module hysopparam_sp
-
-! This file was auto-generated with f2py (version:2).
-! See http://cens.ioc.ee/projects/f2py2e/
diff --git a/hysop/fakef2py/fftw2py/__init__.py b/hysop/fakef2py/fftw2py/__init__.py
deleted file mode 100644
index 95df2255c1722b1a16cd39a6452fe5d94a7385cb..0000000000000000000000000000000000000000
--- a/hysop/fakef2py/fftw2py/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-msg = " ==== Import f2py.fftw2py warning ==== \n"
-msg += "The package is empty since you disable "
-msg += "fftw when installing HySoP. \n"
-msg += "Whatever you'll do with this will probably failed."
-print (msg)
diff --git a/hysop/fakef2py/scales2py/__init__.py b/hysop/fakef2py/scales2py/__init__.py
deleted file mode 100644
index 58ba76d2f7aceb911bb77628ceefced262357ce7..0000000000000000000000000000000000000000
--- a/hysop/fakef2py/scales2py/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-msg = " ==== Import f2py.scales2py warning ==== \n"
-msg += "The package is empty since you disable "
-msg += "scales when installing HySoP. \n"
-msg += "Whatever you'll do with this will probably failed."
-print (msg)
diff --git a/hysop/fields/continuous.py b/hysop/fields/continuous.py
old mode 100755
new mode 100644
index 8e9700a2615e7b04a8885aa27be03c70eb415911..3a4e8f95762101d291a3c9b2530f407d1d6e2b58
--- a/hysop/fields/continuous.py
+++ b/hysop/fields/continuous.py
@@ -13,14 +13,14 @@ Examples
.. currentmodule:: hysop
"""
-from hysop.constants import debug
-from hysop.fields.discrete import DiscreteField
-from hysop.mpi import main_rank
-from hysop.tools.profiler import Profiler, profile
-from hysop.tools.io_utils import IOParams, IO
-from hysop.operator.hdf_io import HDF_Writer, HDF_Reader
-from hysop.mpi.topology import Cartesian
-
+from hysop.deps import np
+from hysop.constants import HYSOP_REAL, HYSOP_BOOL
+from hysop.fields.discrete import DiscreteField
+from hysop.core.mpi import main_rank
+from hysop.tools.profiler import Profiler, profile
+from hysop.tools.io_utils import IOParams, IO
+from hysop.tools.decorators import debug
+from hysop.core.mpi.topology import Cartesian
class Field(object):
"""
@@ -32,15 +32,15 @@ class Field(object):
discretize it.
Example :
- if topo1 and topo2 are two hysop.mpi.topology.Cartesian objects::
+ if topo1 and topo2 are two hysop.core.mpi.topology.Cartesian objects::
scal = Field(domain=dom, name='Scalar')
# Discretize scal on two different topologies
scal.discretize(topo1)
scal.discretize(topo2)
# Access to the discrete fields :
- scal_discr1 = scal.discreteFields[topo1]
- scal_discr2 = scal.discreteFields[topo2]
+ scal_discr1 = scal.discrete_fields[topo1]
+ scal_discr2 = scal.discrete_fields[topo2]
# or in a more straightforward way:
scal_discr2 = scal.discretize(topo2)
@@ -53,7 +53,7 @@ class Field(object):
@debug
@profile
def __init__(self, domain, name, formula=None, is_vector=False,
- nb_components=None, vectorize_formula=False):
+ nb_components=None, vectorize_formula=False, dtype=HYSOP_REAL):
"""Defines a continuous field (scalar or vector) on a domain.
Parameters
@@ -63,8 +63,8 @@ class Field(object):
physical domain where this field is defined.
name : string
a name for the variable. Required because of h5py i/o.
- formula : python function, optional
- a user-defined python function. See notes for details.
+ formula : python function, optional
+ a user-defined python function. See notes for details.
is_vector : bool, optional
true if the field is a vector.
nb_components : int, optional
@@ -72,6 +72,8 @@ class Field(object):
vectorize_formula : bool, optional
true if formula must be vectorized
(i.e. is of type 'user_func_2')
+ dtype: np.dtype, optional, defaults to HYSOP_REAL
+ underlying data type of this field
Notes
------
@@ -87,6 +89,13 @@ class Field(object):
... return res
"""
+
+ if dtype==np.bool:
+ import warnings
+ msg='Parameter dtype=np.bool has been converted to HYSOP_BOOL={}.'.format(HYSOP_BOOL.__name__)
+ warnings.warn(msg, UserWarning)
+ dtype = HYSOP_BOOL
+ self.dtype = dtype
# Physical domain of definition of the variable.
self.domain = domain
@@ -95,14 +104,14 @@ class Field(object):
# Id
self.name = name
# Dictionnary of all the discretizations of this field.
- # Key = hysop.mpi.topology.Cartesian,
+ # Key = hysop.core.mpi.topology.Cartesian,
# value =hysop.fields.discrete.DiscreteField.
- # Example : vel = discreteFields[topo]
- self.discreteFields = {}
+ # Example : vel = discrete_fields[topo]
+ self.discrete_fields = {}
# Analytic formula.
self.formula = formula
# A list of extra parameters, used in _formula
- self.extraParameters = tuple([])
+ self.extra_parameters = tuple([])
# Number of components of the field
if nb_components is None:
self.nb_components = self.dimension if is_vector else 1
@@ -122,7 +131,7 @@ class Field(object):
def get_profiling_info(self):
"""Update profiler"""
- for d in self.discreteFields.values():
+ for d in self.discrete_fields.values():
self.profiler += d.profiler
@debug
@@ -144,16 +153,17 @@ class Field(object):
"""
assert isinstance(topo, Cartesian)
- if topo in self.discreteFields:
- return self.discreteFields[topo]
+ if topo in self.discrete_fields:
+ return self.discrete_fields[topo]
else:
- self.discreteFields[topo] = DiscreteField(
+ self.discrete_fields[topo] = DiscreteField(
topo,
is_vector=self.nb_components > 1,
name=self.name + '_' + str(topo.get_id()),
- nb_components=self.nb_components)
+ nb_components=self.nb_components,
+ dtype=self.dtype)
- return self.discreteFields[topo]
+ return self.discrete_fields[topo]
def set_formula(self, formula, vectorize_formula):
"""Set a user-defined function to compute field values on the domain.
@@ -191,13 +201,13 @@ class Field(object):
"""
if topo is None:
- for df in self.discreteFields.values():
+ for df in self.discrete_fields.values():
df.initialize(self.formula, self._vectorize, time,
- *self.extraParameters)
+ *self.extra_parameters)
else:
df = self.discretize(topo)
df.initialize(self.formula, self._vectorize, time,
- *self.extraParameters)
+ *self.extra_parameters)
@profile
def randomize(self, topo):
@@ -210,7 +220,7 @@ class Field(object):
"""
df = self.discretize(topo)
df.randomize()
- return self.discreteFields[topo]
+ return self.discrete_fields[topo]
def copy(self, field_in, topo):
"""Initialize a field on topo with values from another field.
@@ -261,7 +271,7 @@ class Field(object):
else:
s += 'scalar field '
s += 'with the following (local) discretizations :\n'
- for f in self.discreteFields.values():
+ for f in self.discrete_fields.values():
s += f.__str__()
return s
@@ -291,7 +301,7 @@ class Field(object):
"""
if topo is None:
return None
- return self.discreteFields[topo].norm()
+ return self.discrete_fields[topo].norm()
def normh(self, topo):
"""Compute a 'grid-norm' for the discrete field
@@ -321,7 +331,7 @@ class Field(object):
"""
if topo is None:
return None
- return self.discreteFields[topo].normh()
+ return self.discrete_fields[topo].normh()
def set_formula_parameters(self, *args):
"""Set values for (optional) list of extra parameters
@@ -330,7 +340,7 @@ class Field(object):
:params args: tuple
the extra parameters to set.
"""
- self.extraParameters = args
+ self.extra_parameters = args
def init_writer(self, discretization, io_params=None):
"""Create an hdf writer for a given discretization
@@ -338,25 +348,26 @@ class Field(object):
Parameters
----------
discretization : :class:`~hysop.tools.params.Discretization` or
- :class:`~hysop.mpi.topology.Cartesian`
+ :class:`~hysop.core.mpi.topology.Cartesian`
set a data distribution description for the output, i.e.
choose the space discretisation used for hdf file.
io_params : :class:`~hysop.tools.io_utils.IOParams`, optional
output file description
"""
+ from hysop.operator.hdf_io import HDF_Writer
if io_params is None:
io_params = IOParams(self.name, fileformat=IO.HDF5)
wr = HDF_Writer(variables={self: discretization}, io_params=io_params)
wr.discretize()
wr.setup()
- self.writer[self.discreteFields[wr.topology]] = wr
+ self.writer[self.discrete_fields[wr.topology]] = wr
def hdf_dump(self, topo, simu):
"""Save field data into hdf file
Parameters
----------
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
data distribution description
simu : :class:`~hysop.problem.simulation.Simulation`
time discretisation
@@ -373,7 +384,7 @@ class Field(object):
Parameters
----------
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
data distribution description
io_params : :class:`~hysop.tools.io_utils.IOParams`, optional
output file description
@@ -395,6 +406,7 @@ class Field(object):
dataset_name='field1')
"""
+ from hysop.operator.hdf_io import HDF_Reader
if dataset_name is None:
var_names = None
else:
@@ -410,11 +422,11 @@ class Field(object):
def zero(self, topo=None):
"""Reset to 0.0 all components of this field.
- :param topo : :class:`~hysop.mpi.topology.Cartesian`, optional
- if given, only discreteFields[topo] is set to zero
+ :param topo : :class:`~hysop.core.mpi.topology.Cartesian`, optional
+ if given, only discrete_fields[topo] is set to zero
"""
if topo is not None:
- self.discreteFields[topo].zero()
+ self.discrete_fields[topo].zero()
else:
- for dfield in self.discreteFields.values():
+ for dfield in self.discrete_fields.values():
dfield.zero()
diff --git a/hysop/fields/discrete.py b/hysop/fields/discrete.py
old mode 100755
new mode 100644
index 264e1f5e41f0a79c4b2fba8fdf5f4d2275abe1ab..76e5ac512dcca5a0feefb4f88428856a0dbb7547
--- a/hysop/fields/discrete.py
+++ b/hysop/fields/discrete.py
@@ -5,14 +5,16 @@
Documentation and examples can be found in :ref:`fields`.
"""
-from hysop.constants import debug, ORDER
from itertools import count
+from hysop import vprint
+from hysop.deps import np
+from hysop.constants import HYSOP_ORDER, Backend
+from hysop.tools.decorators import debug
+from hysop.tools.types import check_instance
from hysop.tools.profiler import Profiler, profile
-import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.core.arrays.all import ArrayBackend, HostArrayBackend, OpenClArrayBackend
import numpy.linalg as la
-
class DiscreteField(object):
"""
Discrete representation of scalar or vector fields,
@@ -28,14 +30,14 @@ class DiscreteField(object):
return object.__new__(cls, *args, **kw)
@debug
- def __init__(self, topology, is_vector=False, name=None,
+ def __init__(self, topology, name, dtype, is_vector=False,
nb_components=None):
"""Creates a discrete field for a given topology.
Parameters
----------
- topology : :class:`~hysop.mpi.topology.Cartesian`
+ topology : :class:`~hysop.core.mpi.topology.Cartesian`
is_vector : bool
True to create a vector field
name : string
@@ -45,9 +47,9 @@ class DiscreteField(object):
Attributes
----------
- topology : :class:`~hysop.mpi.topology.Cartesian`
+ topology : :class:`~hysop.core.mpi.topology.Cartesian`
description of the mpi distribution for data
- domain : :class:`~hysop.mpi.domain.box.Box`
+ domain : :class:`~hysop.core.mpi.domain.box.Box`
where the field is defined
Note:
@@ -60,21 +62,19 @@ class DiscreteField(object):
"""
# Topology used to distribute/discretize the present field.
- self.topology = topology
+ self._topology = topology
# Id (unique) for the field
self.__id = self.__field_counter.next()
# Field name.
- if name is not None:
- self.name = name
- else:
- self.name = 'unamed'
- #: Field dimension.
- self.dimension = topology.domain.dimension
- # Field resolution.
- self.resolution = self.topology.mesh.resolution
- # Application domain of the variable.
- self.domain = self.topology.domain
+ self.name = name
+ self.dtype = dtype
+ # Field domain, dimension and resolution.
+ self.domain = self.topology.domain
+ self.dimension = topology.domain.dimension
+ self.resolution = self.topology.mesh.resolution
+ self.compute_resolution = self.topology.mesh.compute_resolution
+ self.ghosts = self.topology.mesh.discretization.ghosts
# Object to store computational times
self.profiler = Profiler(self, self.domain.comm_task)
# Number of components of the field
@@ -83,23 +83,80 @@ class DiscreteField(object):
else:
self.nb_components = nb_components
# The memory space for data ...
- self.data = [npw.zeros(self.resolution)
- for _ in xrange(self.nb_components)]
+ backend = topology.backend
+
+ msg='\nAllocation of field {} on backend {}'
+ msg+='(compute_resolution={}, ghosts={}, nb_components={}, dtype={})'
+ msg=msg.format(name, backend.kind, self.compute_resolution,
+ self.ghosts, self.nb_components, self.dtype.__name__)
+ vprint(msg)
+ self._data = tuple(backend.zeros(shape=self.resolution, dtype=dtype)
+ for _ in xrange(self.nb_components))
+
+ def get_topology(self):
+ return self._topology
+ def get_backend(self):
+ return self._topology._backend
+
+ def set_data(self, new_data):
+ if (self.nb_components==1) and not isinstance(new_data,(list,tuple)):
+ new_data = [new_data]
+ check_instance(new_data, (list,tuple))
+ new_data = list(new_data)
+
+ backend = self.backend
+ for i,var in enumerate(new_data):
+ if backend.can_wrap(var):
+ new_data[i] = backend.wrap(var)
+ else:
+ msg='Unknown data type {} for backend {}.'
+ msg=msg.format(var.__class__, backend.kind)
+ raise ValueError(msg)
+
+ for dst, src in zip(self._data, new_data):
+ dst.copy_from(src)
+
+ def get_data(self, *ids):
+ if ids:
+ return tuple([self._data[_id] for _id in ids])
+ else:
+ return self._data
+
+ def get_buffer(self, *ids):
+ if self.backend.kind != Backend.OPENCL:
+ return self.get_data(ids)
+
+ if ids:
+ return [self._data[_id].data for _id in ids]
+ else:
+ return [d.data for d in self._data]
+
+ def get_transposition_state(self):
+ return self._data[0].transposition_state()
+ def get_basis(self):
+ return [Basis.CARTESIAN]*self.dimension
+
+ topology = property(get_topology)
+ backend = property(get_backend)
+ data = property(get_data, set_data)
+ buffers = property(get_buffer)
+
+ transposition_state = property(get_transposition_state)
+ basis = property(get_basis)
def __getitem__(self, i):
"""Access to the content of the field.
:param i : int
requested index.
- :returns npw.array:
+ :returns ArrayBackend.Array:
component i of the field.
"""
- return self.data[i]
+ return self.get_data(i)[0]
def __setitem__(self, i, value):
"""Set all values of a component
-
"""
- self.data[i][...] = value
+ return self.get_data(i)[0].fill(value=value)
def initialize(self, formula=None, vectorize_formula=False,
time=0., *args):
@@ -116,59 +173,46 @@ class DiscreteField(object):
time : real, optional
time value used to call formula
args : extra argument, optional, depends on formula
-
"""
+ backend = self.backend
if formula is not None:
- # Argument of formula. Usually : x, y, z, t, extras
- arg_list = self.topology.mesh.coords + (time,) + args
- if vectorize_formula:
- # input formula is not defined for numpy arrays
- if isinstance(formula, np.lib.function_base.vectorize):
- v_formula = formula
- else:
- v_formula = np.vectorize(formula)
- if len(self.data) == 1:
- self.data[0][...] = v_formula(*arg_list)
- elif len(self.data) == 2:
- self.data[0][...], self.data[1][...] = v_formula(*arg_list)
- elif len(self.data) == 3:
- self.data[0][...], self.data[1][...], self.data[2][...] = \
- v_formula(*arg_list)
- else:
- # Warning : in this case, self.data[i] memory will
- # be reallocated.
- print ("Warning : reallocation of memory for fields data\
- during initialisation. See hysop.fields\
- documentation for details.")
+ if backend.kind == Backend.HOST:
+ # Argument of formula. Usually : x, y, z, t, extras
+ arg_list = self.topology.mesh.coords + (time,) + args
+ if vectorize_formula:
+ # input formula is not defined for numpy arrays
+ if isinstance(formula, np.lib.function_base.vectorize):
+ v_formula = formula
+ else:
+ v_formula = np.vectorize(formula)
self.data = v_formula(*arg_list)
- # Ensure that data is of the right type,
- # in the right order.
- for i in xrange(self.nb_components):
- self.data[i][...] = npw.asrealarray(self.data[i])
-
+ else:
+ # In that cas, we assume that formula has been properly
+ # defined as a function of (res, x, y, ...),
+ # res[i], x, y ... being numpy arrays.
+ self.data = formula(self.data, *arg_list)
else:
- # In that cas, we assume that formula has been properly
- # defined as a function of (res, x, y, ...),
- # res[i], x, y ... being numpy arrays.
- self.data = formula(self.data, *arg_list)
+ #TODO fix for opencl backend
+ msg='Formula initialization for backend {}.'
+ msg=msg.format(self.topology.backend.kind)
+ raise NotImplemented(msg)
else:
- # No formula, set all components to zero"
- for d in xrange(self.nb_components):
- self.data[d][...] = 0.0
+ # No formula, set all components to zero
+ self.zero()
+
assert all([(s == self.resolution).all()
for s in [dat.shape for dat in self.data]]),\
"WARNING: The shape of " + self.name + " has changed during"\
" field initialisation."
@profile
- def randomize(self):
+ def randomize(self, **kargs):
"""Initialize a the with random values.
-
"""
for d in xrange(self.nb_components):
- self.data[d][...] = np.random.random(self.topology.mesh.resolution)
+ self.array_backend.rand(out=self.data[d], **kargs)
- def copy(self, field_in):
+ def copy(self, field_in, **kargs):
"""Initialize a field on topo with values from another field.
Parameters
@@ -177,9 +221,10 @@ class DiscreteField(object):
field to be copied
"""
for d in xrange(self.nb_components):
- self.data[d][...] = field_in.data[d].copy(order=ORDER)
+ self.array_backend.memcpy(dst=self.data[d], src=field_in[d], **kargs)
def norm(self):
+ #TODO fix for opencl backend
"""Compute the euclidian norm of the discrete field
p-norm = (sum data[d](i,...)**p)**1/p for d = 1..dim
sum on all grid points excluding ghosts.
@@ -199,6 +244,7 @@ class DiscreteField(object):
return gresult ** 0.5
def normh(self):
+ #TODO fix for opencl backend
"""
Compute a 'grid-norm' for the discrete field
norm = ( hd * sum data[d](i,...)**2)**0.5 for d = 1..dim
@@ -214,10 +260,14 @@ class DiscreteField(object):
self.topology.comm.Allreduce(result, gresult)
return gresult ** 0.5
- def zero(self):
+ def fill(self, value, **kargs):
+ """ set all commponents to specified value """
+ for d in xrange(self.nb_components):
+ self.data[d].fill(value=value, **kargs)
+
+ def zero(self, **kargs):
""" set all components to zero"""
- for dim in xrange(self.nb_components):
- self.data[dim][...] = 0.0
+ self.fill(value=0, **kargs)
def get_profiling_info(self):
"""update profiler"""
diff --git a/hysop/fields/field_requirements.py b/hysop/fields/field_requirements.py
new file mode 100644
index 0000000000000000000000000000000000000000..22863874d6b712db8191a482139268ebe3bbda84
--- /dev/null
+++ b/hysop/fields/field_requirements.py
@@ -0,0 +1,427 @@
+
+from hysop import __DEBUG__
+from hysop.deps import np, it
+from hysop.constants import Basis, transposition_states
+from hysop.tools.types import to_list, check_instance
+from hysop.tools.numpywrappers import npw
+from hysop.tools.decorators import debug
+from hysop.core.mpi.topology import Topology
+from hysop.core.mpi.topology_descriptor import TopologyDescriptor
+from hysop.core.graph.computational_node import ComputationalGraphNode
+from hysop.fields.continuous import Field
+from hysop.fields.discrete import DiscreteField
+
+def can_convert_basis_inplace(lbasis, rbasis):
+ return False
+
+def can_transpose_inplace(ltranspose, rtranspose):
+ return True
+
+
+class DiscreteFieldRequirements(object):
+
+ _registered_requirements = set()
+
+ def __init__(self, operator, variables, field,
+ min_ghosts=None,
+ max_ghosts=None,
+ can_split=None,
+ basis=None,
+ transposition_states=None,
+ _register=True,
+ **kwds):
+
+ if _register:
+ key = (id(operator), id(variables), id(field))
+ if key in self._registered_requirements:
+ msg='Operator {} has already registered requirements for field {} to variables id {}.'
+ msg=msg.format(operator.name, field.name, id(variables))
+ raise RuntimeError(msg)
+ else:
+ if __DEBUG__:
+ msg='Operator {} registered requirements of field {} to variables id {}.'
+ msg=msg.format(operator.name, field.name, id(variables))
+ print msg
+ self._registered_requirements.update(key)
+
+ super(DiscreteFieldRequirements, self).__init__(**kwds)
+
+ check_instance(operator, ComputationalGraphNode)
+ check_instance(field, Field)
+ check_instance(variables, dict, keys=Field, values=(Topology,TopologyDescriptor))
+
+ self._operator = operator
+ self._field = field
+ self._variables = variables
+ self._topology_descriptor = variables[field]
+ self.header = '::{}[{}] requirements::\n'.format(operator.name, field.name)
+
+ self.min_ghosts = min_ghosts
+ self.max_ghosts = max_ghosts
+ self.can_split = can_split
+ self.basis = basis
+ self.transposition_states = transposition_states
+
+ def is_default(self):
+ return (self == self._default())
+
+ def _default(self):
+ return DiscreteFieldRequirements(self._operator, self._variables, self._field, _register=False)
+
+ def __eq__(self, other):
+ eq = (self.operator is other.operator)
+ eq &= (self.variables is other.variables)
+ eq &= (self.field is other.field)
+ eq &= (self.min_ghosts == other.min_ghosts).all()
+ eq &= (self.max_ghosts == other.max_ghosts).all()
+ eq &= (self.basis == other.basis)
+ eq &= (self.transposition_states == other.transposition_states)
+ return eq
+
+ def __hash__(self):
+ return id(self.operator) ^ id(self.variables) ^ id(self.field)
+
+ def __str__(self):
+ def arraystr(array):
+ inf = u'+\u221e'
+ vals = [u''+str(x) if np.isfinite(x) else inf for x in array]
+ return u'[{}]'.format(u','.join(vals)).encode('utf-8').strip()
+
+ return '{:15s} {:>10s}<=ghosts<{:<10s} can_split={} basis={} tstates={}'.format(
+ '{}::{}'.format(self.operator.name, self.field.name),
+ arraystr(self.min_ghosts), arraystr(self.max_ghosts+1),
+ self.can_split.view(np.int8),
+ '[{}]'.format(','.join(str(basis) for basis in self.basis)),
+ '[{}]'.format(','.join(str(ts) for ts in self.transposition_states)))
+
+ def get_transposition_states(self):
+ return self._transposition_states
+ def set_transposition_states(self, tstate):
+ check_instance(tstate, set, values=transposition_states[self.workdim], allow_none=True)
+ self._transposition_states = tstate or set([transposition_states[self.workdim].default])
+
+ def get_basis(self):
+ return self._basis
+ def set_basis(self, basis):
+ check_instance(basis, list, values=Basis, allow_none=True)
+ self._basis = basis or (Basis.NATURAL,)*self.workdim
+
+ def get_min_ghosts(self):
+ return self._min_ghosts
+ def set_min_ghosts(self, min_ghosts):
+ self._min_ghosts = np.asarray(to_list(min_ghosts)
+ if (min_ghosts is not None) else [0]*self.workdim)
+ assert self.min_ghosts.size == self.workdim
+
+ def get_max_ghosts(self):
+ return self._max_ghosts
+ def set_max_ghosts(self, max_ghosts):
+ self._max_ghosts = np.asarray(to_list(max_ghosts)
+ if (max_ghosts is not None) else [np.inf]*self.workdim)
+ assert self.max_ghosts.size == self.workdim
+
+ def get_can_split(self):
+ return self._can_split
+ def set_can_split(self, can_split):
+ self._can_split = np.asarray(to_list(can_split)
+ if (can_split is not None) else [1]*self.workdim, dtype=np.bool_)
+ assert self.can_split.size == self.workdim
+
+ def get_work_dim(self):
+ return self._topology_descriptor.domain.dimension
+ def get_operator(self):
+ return self._operator
+ def get_field(self):
+ return self._field
+ def get_variables(self):
+ return self._variables
+ def get_topology_descriptor(self):
+ return self._topology_descriptor
+
+ can_split = property(get_can_split, set_can_split)
+ min_ghosts = property(get_min_ghosts, set_min_ghosts)
+ max_ghosts = property(get_max_ghosts, set_max_ghosts)
+ basis = property(get_basis, set_basis)
+ transposition_states = property(get_transposition_states,
+ set_transposition_states)
+ workdim = property(get_work_dim)
+ operator = property(get_operator)
+ field = property(get_field)
+ variables = property(get_variables)
+ topology_descriptor = property(get_topology_descriptor)
+
+ def is_compatible_with(self, other):
+ assert self.field == other.field, 'field mismatch.'
+ if isinstance(other, DiscreteFieldRequirements):
+ others=set([other])
+ elif isinstance(other, MultiFieldRequirements):
+ if self.topology_descriptor in other.requirements.keys():
+ others=other.requirements[self.topology_descriptor]
+ else:
+ return True
+ else:
+ msg='Unknown type {}.'.format(other.__class__)
+
+ for other in others:
+ assert self.workdim == other.workdim, 'workdim mismatch.'
+ assert self.topology_descriptor == other.topology_descriptor, \
+ 'topology_descriptor mismatch.'
+ if (other.max_ghosts < self.min_ghosts).any():
+ return False
+ if (other.min_ghosts > self.max_ghosts).any():
+ return False
+ if not (other.can_split * self.can_split).any():
+ return False
+ if (other.basis != self.basis) and \
+ not can_convert_basis_inplace(
+ other.basis, self.basis):
+ return False
+ if (other.transposition_states != self.transposition_states) and \
+ not can_transpose_inplace(
+ other.transposition_states,
+ self.transposition_states):
+ return False
+ return True
+
+ def check_topology(self, topology=None):
+ topology = topology or self.variables[self.field]
+ check_instance(topology, Topology)
+ if topology.domain.dimension != self.field.dimension:
+ msg='{} Dimension mismatch between field and topology.\n field={}d, topology={}d.'
+ msg=msg.format(self.header, self.field.dimension, topology.dimension)
+ raise RuntimeError(msg)
+ if (topology.mesh.discretization.resolution != self.topology_descriptor.discretization.resolution).any():
+ msg='{} Discretisation mismatch between requirement and topology.\n '
+ msg+=' requirement={}\n topology={}'
+ msg=msg.format(self.header,
+ self.topology_descriptor.discretization.resolution,
+ topology.mesh.discretization.resolution)
+ raise RuntimeError(msg)
+ if (topology.ghosts < self.min_ghosts).any():
+ msg='{} min ghosts constraint was not met.\n min={}, actual={}.'
+ msg=msg.format(self.header, self.min_ghosts, topology.ghosts)
+ raise RuntimeError(msg)
+ if (topology.ghosts > self.max_ghosts).any():
+ msg='{} max ghosts constraint was not met.\n max={}, actual={}.'
+ msg=msg.format(self.header, self.max_ghosts, topology.ghosts)
+ raise RuntimeError(msg)
+
+ def set_and_check_topology(self, topology):
+ """
+ Check topology and replace a TopologyDescriptor by a Topology instance in
+ self.variables[self.field].
+ """
+ assert isinstance(topology, Topology)
+ assert not isinstance(self.variables[self.field], Topology) \
+ or (self.variables[self.field] == topology)
+ self.check_topology(topology)
+ self.variables[self.field] = topology
+
+ def check_state(self, dfield):
+ check_instance(dfield, DiscreteField)
+ self.check_topology(dfield.topology)
+
+ if dfield.basis != self.basis:
+ msg=' basis constraint was not met.\n required={}, actual={}.'
+ msg=msg.format(self.header, self.basis, dfield.basis)
+ raise RuntimeError(msg)
+ if dfield.transposition_state not in self.transposition_states:
+ msg=' transposition state constraint was not met.\n required={}, actual={}.'
+ msg=msg.format(self.header, self.transposition_states,
+ dfield.transposition_state)
+ raise RuntimeError(msg)
+
+class MultiFieldRequirements(object):
+ def __init__(self, field):
+ self.field = field
+ self.requirements = {}
+ self.built = False
+
+ def nrequirements(self):
+ return sum(len(lreqs) for lreqs in self.requirements.values())
+
+ def update(self, *update_reqs):
+ for update_req in update_reqs:
+ if isinstance(update_req, MultiFieldRequirements):
+ tds = update_req.requirements.keys()
+ reqs = update_req.requirements.values()
+ else:
+ tds = [update_req.topology_descriptor]
+ reqs = [[update_req]]
+ for td, reqs in zip(tds, reqs):
+ td_reqs = self.requirements.setdefault(td, set()).update(reqs)
+
+ def build_topologies(self):
+ if self.built:
+ return
+ for compatible_reqs in self._split():
+ compatible_reqs._build_compatible_topologies()
+ self.built = True
+
+ def all_compatible(self):
+ for topology_descriptor in self.requirements:
+ requirements = self.requirements[topology_descriptor]
+ assert len(requirements)>0
+ for req0, req1 in it.combinations(requirements, 2):
+ if not req0.is_compatible_with(req1):
+ return False
+ return True
+
+ def _split(self):
+ sub_field_requirements = []
+ for lreq in self.requirements.values():
+ for req in lreq:
+ ok = False
+ for multi_reqs in sub_field_requirements:
+ if req.is_compatible_with(multi_reqs):
+ multi_reqs.update(req)
+ ok=True
+ break
+ if not ok:
+ new_group = MultiFieldRequirements(self.field)
+ new_group.update(req)
+ sub_field_requirements.append(new_group)
+ assert self.nrequirements() == sum(sf.nrequirements() for sf in sub_field_requirements)
+ return sub_field_requirements
+
+ def _build_compatible_topologies(self):
+ assert self.all_compatible()
+ for topology_descriptor, reqs in self.requirements.iteritems():
+ ghosts = npw.integer_zeros(shape=(topology_descriptor.dim(),))
+ can_split = npw.integer_ones(shape=(topology_descriptor.dim(),))
+ known_topologies = []
+ unknown_topologies = []
+
+ for req in reqs:
+ if isinstance(req.topology_descriptor, Topology):
+ req.check_topology()
+ known_topologies.append(topology)
+ else:
+ ghosts = np.maximum(ghosts, req.min_ghosts)
+ can_split *= req.can_split
+ unknown_topologies.append(req)
+
+ assert can_split.any()
+
+ for req in unknown_topologies:
+ topo = req.topology_descriptor.choose_or_create_topology(known_topologies,
+ ghosts=ghosts, cutdir=can_split)
+ known_topologies.append(topo)
+ req.set_and_check_topology(topo)
+
+
+class OperatorFieldRequirements(object):
+
+ def __init__(self, input_field_requirements=None, output_field_requirements=None, **kwds):
+ super(OperatorFieldRequirements, self).__init__(**kwds)
+
+ check_instance(input_field_requirements, dict, keys=Field, values=MultiFieldRequirements, allow_none=True)
+ self._input_field_requirements = input_field_requirements or dict()
+
+ check_instance(output_field_requirements, dict, keys=Field, values=MultiFieldRequirements, allow_none=True)
+ self._output_field_requirements = output_field_requirements or dict()
+
+ def get_input_field_requirements(self):
+ return self._input_field_requirements
+ def get_output_field_requirements(self):
+ return self._output_field_requirements
+
+ input_field_requirements = property(get_input_field_requirements)
+ output_field_requirements = property(get_output_field_requirements)
+
+ def update(self, requirements):
+ check_instance(requirements, OperatorFieldRequirements)
+ self.update_inputs(requirements._input_field_requirements)
+ self.update_outputs(requirements._output_field_requirements)
+
+ def update_inputs(self, input_field_requirements):
+ check_instance(input_field_requirements, dict, keys=Field,
+ values=(DiscreteFieldRequirements,MultiFieldRequirements))
+ for ifield,ireqs in input_field_requirements.iteritems():
+ if not isinstance(ireqs, MultiFieldRequirements):
+ _ireqs = ireqs
+ ireqs = MultiFieldRequirements(ifield)
+ ireqs.update(_ireqs)
+ if ifield in self._input_field_requirements:
+ self._input_field_requirements[ifield].update(ireqs)
+ else:
+ self._input_field_requirements[ifield] = ireqs
+
+ def update_outputs(self, output_field_requirements):
+ check_instance(output_field_requirements, dict, keys=Field,
+ values=(DiscreteFieldRequirements,MultiFieldRequirements))
+ for ofield,oreqs in output_field_requirements.iteritems():
+ if not isinstance(oreqs, MultiFieldRequirements):
+ _oreqs = oreqs
+ oreqs = MultiFieldRequirements(ofield)
+ oreqs.update(_oreqs)
+ if ofield in self._output_field_requirements:
+ self._output_field_requirements[ofield].update(oreqs)
+ else:
+ self._output_field_requirements[ofield] = oreqs
+
+ def iter_input_requirements(self):
+ """
+ Iterates over (field, topology_descriptor, field_requirement) for all input requirements.
+ """
+ for (field,freqs) in self.input_field_requirements.iteritems():
+ freqs = freqs.requirements
+ for (td,reqs) in freqs.iteritems():
+ for req in reqs:
+ yield field, td, req
+
+ def iter_output_requirements(self):
+ """
+ Iterates over (field, topology_descriptor, field_requirement) for all output requirements.
+ """
+ for (field,freqs) in self.output_field_requirements.iteritems():
+ freqs = freqs.requirements
+ for (td,reqs) in freqs.iteritems():
+ for req in reqs:
+ yield (field, td, req)
+
+ def iter_requirements(self):
+ """
+ Iterates over (is_input, field, topology_descriptor, field_requirement) for all inputs and outputs.
+ """
+ it0 = it.izip_longest((True,), self.iter_input_requirements())
+ it1 = it.izip_longest((False,), self.iter_output_requirements())
+ return it.chain(it0, it1)
+
+ def _get_requirement(self, field, field_requirements):
+ """
+ Get unique requirement and topology descriptor for given field, if it exists.
+ This is a facility for ComputationalGraphOperators to retrieve their unique per field requirements.
+ If field is not an hysop.fields.continuous.Field, a TypeError is raised.
+ If field is not known, an Attribute error is raised.
+ If multiple topology_descriptors or requirements are present (ie. there is not unicity),
+ raise a RuntimeError.
+ """
+ check_instance(field, Field)
+ if field not in field_requirements:
+ msg='No requirements found for field {}.'.format(field.name)
+ raise AttributeError(msg)
+ freqs = field_requirements[field].requirements
+ if len(freqs.keys())>1:
+ msg='Multiple topology descriptors are present for field {}.'.format(field.name)
+ raise RuntimeError(msg)
+ td = freqs.keys()[0]
+ reqs = freqs[td]
+ if len(reqs)>1:
+ msg='Multiple requirements are present for field {}.'.format(field.name)
+ raise RuntimeError(msg)
+ return (td, next(iter(reqs)))
+
+ def get_input_requirement(self, field):
+ return self._get_requirement(field, self._input_field_requirements)
+ def get_output_requirement(self, field):
+ return self._get_requirement(field, self._output_field_requirements)
+
+ @debug
+ def build_topologies(self):
+ if self._input_field_requirements:
+ for field_reqs in self.input_field_requirements.values():
+ field_reqs.build_topologies()
+ if self._output_field_requirements:
+ for field_reqs in self.output_field_requirements.values():
+ field_reqs.build_topologies()
diff --git a/hysop/fields/tests/func_for_tests.py b/hysop/fields/tests/func_for_tests.py
old mode 100755
new mode 100644
index 3e2eaf562a1fdc3560b039510e0a6274851d4a2d..5dc679504773b72ebb1588e2ababe349358acd45
--- a/hysop/fields/tests/func_for_tests.py
+++ b/hysop/fields/tests/func_for_tests.py
@@ -121,3 +121,17 @@ def w_TG(res, x, y, z, t):
res[1][...] = - sin(x) * cos(y) * sin(z)
res[2][...] = 2. * sin(x) * sin(y) * cos(z)
return res
+
+
+def v_TG_2d(res, x, y, t):
+ """Taylor-Green-like 2d velocity"""
+ res[0][...] = sin(x) * cos(y)
+ res[1][...] = - cos(x) * sin(y)
+ return res
+
+
+# Function to compute reference vorticity
+def w_TG_2d(res, x, y, t):
+ """Taylor-Green-like vorticity, 2d domain"""
+ res[0][...] = - cos(x) * sin(y)
+ return res
diff --git a/hysop/fields/tests/test_field.py b/hysop/fields/tests/test_field.py
old mode 100755
new mode 100644
index dc119c8ca0d3f5798da64d4ba7737983dc222283..ed350c51473ca6ba876972897bc9a5455c2da216
--- a/hysop/fields/tests/test_field.py
+++ b/hysop/fields/tests/test_field.py
@@ -1,18 +1,18 @@
"""Test fields build and usage (discrete and continuous)
"""
-from hysop import Simulation, Box, Field, Discretization, IOParams, IO
-import numpy as np
-import os
+import shutil
+from numpy import allclose
+
+from hysop.deps import np, os
+from hysop import Simulation, Box, Field, Discretization, IO, IOParams
+from hysop.core.mpi import main_rank
from hysop.fields.tests.func_for_tests import func_scal_1, func_scal_2, \
func_vec_1, func_vec_2, func_vec_3, func_vec_4, func_vec_5, func_vec_6,\
v_time_3d, v_time_2d
-from numpy import allclose
-import shutil
-from hysop.mpi import main_rank
-d3d = Discretization([33, 33, 33])
-d2d = Discretization([33, 33])
+d3d = Discretization([17, 17, 17])
+d2d = Discretization([17, 17])
nbc = 4
@@ -67,14 +67,14 @@ def test_discretization():
topo = dom.create_topology(r3d)
csf.discretize(topo)
cvf.discretize(topo)
- assert np.equal(csf.discreteFields[topo].resolution,
- csf.discreteFields[topo].data[0].shape).all()
- assert np.equal(cvf.discreteFields[topo].resolution,
- cvf.discreteFields[topo].data[0].shape).all()
- assert np.equal(cvf.discreteFields[topo].resolution,
- cvf.discreteFields[topo].data[1].shape).all()
- assert np.equal(cvf.discreteFields[topo].resolution,
- cvf.discreteFields[topo].data[2].shape).all()
+ assert np.equal(csf.discrete_fields[topo].resolution,
+ csf.discrete_fields[topo].data[0].shape).all()
+ assert np.equal(cvf.discrete_fields[topo].resolution,
+ cvf.discrete_fields[topo].data[0].shape).all()
+ assert np.equal(cvf.discrete_fields[topo].resolution,
+ cvf.discrete_fields[topo].data[1].shape).all()
+ assert np.equal(cvf.discrete_fields[topo].resolution,
+ cvf.discrete_fields[topo].data[2].shape).all()
# Non-Vectorized formula for a scalar
@@ -415,3 +415,40 @@ def test_hdf_dump_load_2d():
def test_hdf_dump_load_3d():
hdf_dump_load(d3d, v_time_3d)
+if __name__ == '__main__':
+ print 'continuous'
+ test_continuous()
+ print 'analytical'
+ test_analytical()
+ print 'analytical_reset'
+ test_analytical_reset()
+ print 'discretization'
+ test_discretization()
+ print 'analytical_field_1'
+ test_analytical_field_1()
+ print 'analytical_field_2'
+ test_analytical_field_2()
+ print 'analytical_field_3'
+ test_analytical_field_3()
+ print 'analytical_field_4'
+ test_analytical_field_4()
+ print 'analytical_field_5'
+ test_analytical_field_5()
+ print 'analytical_field_6'
+ test_analytical_field_6()
+ print 'analytical_field_7'
+ test_analytical_field_7()
+ print 'analytical_field_8'
+ test_analytical_field_8()
+ print 'analytical_field_9'
+ test_analytical_field_9()
+ print 'analytical_field_10'
+ test_analytical_field_10()
+ print 'copy'
+ test_copy()
+ print 'randomize'
+ test_randomize()
+ print 'hdf_dump_load_2d'
+ test_hdf_dump_load_2d()
+ print 'hdf_dump_load_3d'
+ test_hdf_dump_load_3d()
diff --git a/hysop/fields/tests/test_variable.py b/hysop/fields/tests/test_variable.py
old mode 100755
new mode 100644
index 8068ecd51c0d990f95f6c2cbb688e5b8b3d19efb..42048201dc7c7f6db7f5e405b9540e17c9f118b8
--- a/hysop/fields/tests/test_variable.py
+++ b/hysop/fields/tests/test_variable.py
@@ -1,13 +1,16 @@
"""Test simulation dependent parameters.
"""
+from hysop import Simulation
from hysop.fields.variable_parameter import VariableParameter
-from hysop.problem.simulation import Simulation
from math import sin, cos
import numpy as np
def test_constant_var():
+ """Declare and update a 'variable' holding
+ constant values
+ """
uinf = 1.
var = VariableParameter(data=uinf)
var.data *= 3
@@ -21,11 +24,16 @@ def test_constant_var():
def func(s):
+ """test function, depends on simu
+ """
time = s.time
return np.asarray((sin(time), cos(time)))
def test_time_var():
+ """Set and test variable parameter defined
+ with a function
+ """
var = VariableParameter(formula=func)
simu = Simulation(start=0., end=1., time_step=0.1)
simu.initialize()
@@ -33,4 +41,3 @@ def test_time_var():
var.update(simu)
assert np.allclose(var.data, [sin(simu.time), cos(simu.time)])
simu.advance()
-
diff --git a/hysop/fields/variable_parameter.py b/hysop/fields/variable_parameter.py
index d4f1b788c7ebb577ae447abfd30242a5928b75be..a2131b48ca0e66cf32788a17ad0f8e603ba9bc1b 100644
--- a/hysop/fields/variable_parameter.py
+++ b/hysop/fields/variable_parameter.py
@@ -46,8 +46,11 @@ class VariableParameter(object):
self.data = data
# Formula used to compute data (a python function)
if formula is None:
- formula = lambda simu: self.data
- self.formula = formula
+ def _formula(simu):
+ return self.data
+ self.formula = _formula
+ else:
+ self.formula = formula
def update(self, simu=None):
"""Update parameter value for the current simulation
diff --git a/hysop/fortran/arnoldi2py.pyf b/hysop/fortran/arnoldi2py.pyf
deleted file mode 100644
index 6de3250e8665d2c260478dcd69baabd939ca45e4..0000000000000000000000000000000000000000
--- a/hysop/fortran/arnoldi2py.pyf
+++ /dev/null
@@ -1,16 +0,0 @@
-! -*- f90 -*-
-! Note: the context of this file is case sensitive.
-
-module arnoldi2py ! in arnoldi2py.f90
- use arnoldi
- use hysopparam
- use mpi
- subroutine arnoldi3d(solutions,ncli,ntot,nfp,nmodes,tps) ! in arnoldi2py.f90:arnoldi2py
- real(kind=pk) dimension(:,:),intent(inout) :: solutions
- integer intent(in) :: ncli
- integer intent(in) :: ntot
- integer intent(in) :: nfp
- integer intent(in) :: nmodes
- real(kind=pk) intent(in) :: tps
- end subroutine arnoldi3d
-end module arnoldi2py
diff --git a/hysop/fortran/template.pyf b/hysop/fortran/template.pyf
deleted file mode 100644
index 1564dabe01205ce1ca54ef2de8c54484b2eb47fc..0000000000000000000000000000000000000000
--- a/hysop/fortran/template.pyf
+++ /dev/null
@@ -1,13 +0,0 @@
-! -*- f90 -*-
-! Note: the context of this file is case sensitive.
-
-module template_f2py ! in template.f95
- integer, parameter,optional :: var1=12
- subroutine check_f2py(input,output) ! in template.f95:template_f2py
- real(kind=8), dimension(:, :), intent(in) :: input
- real(kind=8), dimension(size(input,1), size(input,2)), intent(in,out), depend(input,input) :: output
- end subroutine check_f2py
-end module template_f2py
-
-! This file was auto-generated with f2py (version:2).
-! See http://cens.ioc.ee/projects/f2py2e/
diff --git a/hysop/gpu/__init__.py b/hysop/gpu/__init__.py
deleted file mode 100644
index bec377bbf37ac1472399f56c07a3390ec22a3f45..0000000000000000000000000000000000000000
--- a/hysop/gpu/__init__.py
+++ /dev/null
@@ -1,47 +0,0 @@
-"""Everything concerning GPU in hysop.
-
-OpenCL sources are located in the cl_src directory and organized as follows
- - kernels/
- Contains kernels src
- - advection.cl
- - remeshing.cl
- - advection_and_remeshing.cl
- - rendering.cl
- Functions used by kernels
- - advection/
- - builtin.cl
- - builtin_noVec.cl
- - remeshing/
- - basic.cl
- - basic_noVec.cl
- - private.cl
- - weights.cl
- - weights_builtin.cl
- - weights_noVec.cl
- - weights_noVec_builtin.cl
- - common.cl
-
-Sources are parsed at build to handle several OpenCL features
-see hysop.gpu.tools.parse_file
-
-"""
-import pyopencl
-import pyopencl.tools
-import pyopencl.array
-import pyopencl.characterize
-
-## open cl underlying implementation
-cl = pyopencl
-## PyOpenCL tools
-clTools = pyopencl.tools
-## PyOpenCL arrays
-clArray = pyopencl.array
-## PyOpenCL characterize
-clCharacterize = pyopencl.characterize
-
-import os
-## GPU deflault sources
-GPU_SRC = os.path.join(__path__[0], "cl_src", '')
-
-## If use OpenCL profiling events to time computations
-CL_PROFILE = False
diff --git a/hysop/gpu/kernel_autotuner.py b/hysop/gpu/kernel_autotuner.py
deleted file mode 100644
index 954deecf6ac230c31972103876bfcb4b410fe816..0000000000000000000000000000000000000000
--- a/hysop/gpu/kernel_autotuner.py
+++ /dev/null
@@ -1,334 +0,0 @@
-
-from hysop.constants import __DEBUG__, __VERBOSE__
-from hysop.tools.io_utils import IO
-from hysop.tools.misc import Utils
-
-from hysop.constants import np
-from hysop.gpu import cl
-
-import os, itertools, hashlib, gzip, pickle
-
-class OpenClKernelStatistics(object):
- """Execution statistics from kernel events.
- """
- def __init__(self,nruns=0,events=None,):
- if events is not None:
- p0 = events[0].profile
- t0 = p0.end - p0.start
- total = 0
- maxi = t0
- mini = t0
- for evt in events:
- dt = evt.profile.end - evt.profile.start
- total += dt
- if dt<mini:
- mini = dt
- if dt>maxi:
- maxi = dt
-
- self.tot = total
- self.min = mini
- self.max = maxi
- self.mean = total/len(events)
- else:
- self.tot = 0
- self.min = 0
- self.max = 0
- self.mean = 0
- self.nruns = nruns
-
- def __str__(self):
- mini = self.min * 1e-6
- maxi = self.max * 1e-6
- total = self.tot * 1e-6
- mean = self.mean * 1e-6
- return 'min={:.2f}ms, max={:.2f}ms, mean={:.2f}ms (nruns={})'.format(mini,maxi,mean,self.nruns)
-
- @staticmethod
- def cmp(lhs,rhs):
- if lhs.mean==rhs.mean:
- if lhs.max==rhs.max:
- if lhs.min==rhs.min:
- return 0
- elif lhs.min>rhs.min:
- return 1
- else:
- return -1
- elif lhs.max > rhs.max:
- return 1
- else:
- return -1
- elif lhs.mean>rhs.mean:
- return 1
- else:
- return -1
- def __lt__(self, other):
- return self.cmp(self, other) < 0
- def __gt__(self, other):
- return self.cmp(self, other) > 0
- def __eq__(self, other):
- return self.cmp(self, other) == 0
- def __le__(self, other):
- return self.cmp(self, other) <= 0
- def __ge__(self, other):
- return self.cmp(self, other) >= 0
- def __ne__(self, other):
- return self.cmp(self, other) != 0
-
-
-class KernelAutotuner(object):
- cache_dir = IO.cache_path() + '/autotune'
- config_file = cache_dir+'/configs.pklz'
- if not os.path.exists(cache_dir):
- os.makedirs(cache_dir)
-
- """OpenCl kernel work group size autotuner.
- """
- def __init__(self,name,work_dim,fbtype,build_opts,
- nruns=10,force_renew_cache=False):
- """Initialize a KernelAutotuner.
-
- Parameters
- ----------
- work_dim: int
- Work dimension used in targetted OpenCL kernels.
- nruns:
- Number of runs used to bench kernels.
- """
-
- self.name = name
- self.work_dim = work_dim
- self.fbtype = fbtype
- self.build_opts = build_opts
- self.nruns = nruns
- self.force_renew_cache = force_renew_cache
-
- self._init_and_load_cache()
- self._load_default_filters()
-
- @staticmethod
- def _hash_func():
- return hashlib.new('sha256')
-
- @staticmethod
- def _load_configs():
- configs = {}
- if os.path.isfile(KernelAutotuner.config_file):
- with gzip.open(KernelAutotuner.config_file, 'rb') as f:
- configs.update(pickle.loads(f.read()))
- return configs
-
- @staticmethod
- def _make_config_key(platform, device, fbtype, build_opts):
- concat_unique_list = lambda L: '['+'_'.join([str(val) for val in frozenset(L)])+']'
- hasher = KernelAutotuner._hash_func()
- hasher.update('{}_{}_{}_{}'.format(platform.name,device.name,fbtype,concat_unique_list(build_opts)))
- return hasher.hexdigest()
-
- def _update_configs(self):
- configs = KernelAutotuner._load_configs()
- if configs.keys() != self.configs.keys():
- configs.update(self.configs)
- with gzip.open(KernelAutotuner.config_file, 'wb') as f:
- pickle.dump(configs,f)
- self.configs = configs
-
- def _init_and_load_cache(self):
- cache_file = '{}/{}.pklz'.format(KernelAutotuner.cache_dir,self.name.replace(' ','_'))
- if os.path.isfile(cache_file):
- with gzip.open(cache_file, 'rb') as f:
- self.results = pickle.loads(f.read())
- else:
- self.results = {}
- self.configs = KernelAutotuner._load_configs()
- self.cache_file = cache_file
-
- def _dump_cache(self):
- with gzip.open(self.cache_file, 'wb') as f:
- pickle.dump(self.results,f)
-
- def add_filter(self,fname, f):
- self.filters[fname] = f
- return self
-
- def get_candidates(self,**kargs):
- return np.asarray([c for c in self._get_wi_candidates(**kargs)])
-
- def bench(self,ctx,platform,device,global_size,kernel_args,
- kernel=None,kernel_generator=None,
- **kargs):
-
- global_size = np.asarray(global_size)
-
- if not isinstance(kernel_args, list):
- msg='kernel_args should be a list.'
- raise ValueError(msg)
- if not ((kernel is None) ^ (kernel_generator is None)):
- raise ValueError('Either kernel or kernel_generator should not be None!')
-
- # create kernel_generator function from kernel if not given
- if (kernel_generator is None):
- kernel_generator = lambda **kargs: (kernel, kernel_args, 0)
-
- if __VERBOSE__:
- print '== Kernel {} Autotuning =='.format(self.name)
- print 'platform: {}'.format(platform.name)
- print 'device: {}'.format(device.name)
- print 'ctx: {}'.format(ctx)
- print 'global_size: {}'.format(global_size)
- print 'fbtype: {}'.format(self.fbtype)
- print 'build_opts: {}'.format(self.build_opts)
-
- config = KernelAutotuner._make_config_key(platform,device,self.fbtype,self.build_opts)
- if config not in self.configs.keys():
- self.configs[config] = {'ctx':str(ctx),'device':str(device),'fbtype':self.fbtype,'build_opts':self.build_opts}
- self._update_configs()
- if config not in self.results.keys():
- self.results[config] = {}
- results = self.results[config]
-
- dump_cache = False
- best_local_size = None
- best_stats = None
-
- candidates = self.get_candidates(ctx=ctx,device=device,global_size=global_size,**kargs)
- N = candidates.shape[0]
- nruns=self.nruns
- step=0
- while candidates.shape[0]>1:
- stats = []
- keep = candidates.shape[0]//2
- if __VERBOSE__:
- print '\n\tStep {} :: keeping {}/{} best mean results over {} runs:'.format(step,keep,N,nruns)
- #print '\t Candidates are: \n\t\t{}'.format('\n\t\t'.join(candidates.__str__().split('\n')))
-
- for local_size in candidates:
- global_size = np.asarray(global_size)
- local_size = np.asarray(local_size)
-
- gwi = tuple(((global_size+local_size-1)/local_size)*local_size)
- lwi = tuple(local_size)
-
- if (not self.force_renew_cache) and (config in self.results.keys()
- and gwi in self.results[config].keys() and lwi in self.results[config][gwi].keys()):
- stat = self.results[config][gwi][lwi]
- if stat.nruns >= nruns:
- if __VERBOSE__:
- print '\t {} {} => {} (cached)'.format(gwi, lwi, stat)
- stats.append(stat)
- continue
-
- (_kernel,_kernel_args,_cached_bytes) = kernel_generator(ctx=ctx,device=device,
- global_size=gwi,local_size=lwi,
- build_opts=self.build_opts, kernel_args=kernel_args,
- **kargs)
- if __DEBUG__:
- print '\t\tKernel arguments:'
- for i,arg in enumerate(_kernel_args):
- if isinstance(arg,cl.Buffer):
- buf = '{} -> {} dtype={} shape={}'.format(i,arg,arg.hostbuf.dtype,arg.hostbuf.shape)
- elif isinstance(arg,np.ndarray):
- buf = '{} -> {} dtype={} shape={}'.format(i,arg,arg.dtype,arg.shape)
- else:
- buf = '{} -> {}'.format(i,arg)
- print '\t\t'+buf
- print
-
- stat = self._bench_one(ctx,device,gwi,lwi,_kernel,_kernel_args,nruns)
- stats.append(stat)
-
- if __VERBOSE__:
- print '\t {} {} => {} (new)'.format(gwi, lwi, stat)
- if gwi not in results.keys():
- results[gwi] = {}
- results[gwi][lwi] = stat
- dump_cache = True
-
- if len(stats)!=candidates.shape[0]:
- raise RuntimeError()
-
- best_ids=Utils.argsort(stats)[:keep]
- candidates=candidates[best_ids,:]
- nruns *= 2
- step += 1
-
- if candidates.shape[0]!=1 or len(best_ids)!=1:
- raise RuntimeError()
- best_id = best_ids[0]
- best_stats = stats[best_id]
- best_candidate = candidates[0]
-
- best_local_size = best_candidate
- best_global_size = tuple(((global_size+best_local_size-1)/best_local_size)*best_local_size)
- if __VERBOSE__ or True:
- print '\tBEST: {} {} => {}'.format(best_global_size, best_local_size, best_stats)
-
- if dump_cache:
- self.results[config] = results
- self._dump_cache()
-
- return (best_global_size, best_local_size, best_stats)
-
-
- def _bench_one(self,ctx,device,global_size,local_size,kernel,kernel_args,nruns):
- evts = []
- with cl.CommandQueue(ctx,device,cl.command_queue_properties.PROFILING_ENABLE) as queue:
- kernel.set_args(*kernel_args)
- for i in xrange(nruns):
- evt = cl.enqueue_nd_range_kernel(queue, kernel, global_size, local_size)
- evts.append(evt)
- stats = OpenClKernelStatistics(events=evts,nruns=nruns)
- return stats
-
- def _get_wi_candidates(self,ctx,device,global_size,**kargs):
- pows = []
- size = 1
- while(size<=device.max_work_group_size):
- pows.append(size)
- size <<= 1
-
- candidates = itertools.product(pows, repeat=3)
- for fname,f in self.filters.iteritems():
- F = f(ctx=ctx,device=device,global_size=global_size,**kargs)
- candidates = itertools.ifilter(F, candidates)
- return candidates
-
- def _load_default_filters(self):
- self.filters = {}
- self.add_filter('dim_reqs',self._dim_filter)
- self.add_filter('minmax_wi',self._minmax_workitems_filter)
-
- #default filters
- def _dim_filter(self,device,**kargs):
- work_dim = self.work_dim
- max_wi_dim = device.max_work_item_dimensions
- return lambda local_size: (work_dim<=max_wi_dim) and \
- (work_dim==3
- or (work_dim==2 and local_size[2]==1)
- or (work_dim==1 and local_size[1]==1 and local_size[2]==1))
- def _minmax_workitems_filter(self, device, min_load_factor=4, **kargs):
- def filter(local_size, **kargs):
- max_wg_size = device.max_work_group_size
- wi=1
- for i in xrange(3):
- wi*=local_size[i]
- return (wi>=max_wg_size/min_load_factor) and (wi<=max_wg_size)
- return filter
-
- #user available filters
- def ordering_filter(self, **kargs):
- return lambda local_size: (local_size[2]<=local_size[1]) and (local_size[1]<=local_size[0])
- def min_workitems_per_direction(self, min_local_size, **kargs):
- work_dim = self.work_dim
- if np.isscalar(min_local_size):
- min_local_size = [min_local_size]*work_dim
- min_local_size = np.asarray(min_local_size)
- return lambda local_size,**kargs: (local_size>=min_local_size).all()
- def max_workitems_per_direction(self, max_local_size, **kargs):
- work_dim = self.work_dim
- if np.isscalar(max_local_size):
- max_local_size = [max_local_size]*work_dim
- max_local_size = np.asarray(max_local_size)
- return lambda local_size,**kargs: (local_size<=max_local_size).all()
-
-
diff --git a/hysop/methods.py b/hysop/methods.py
index f4483e73c740841eccfde4134e4e32271230320d..d3268d89e76abb51eac79859b598e5fdbe05b6ce 100644
--- a/hysop/methods.py
+++ b/hysop/methods.py
@@ -1,69 +1,31 @@
-"""Some shortcuts to numerical methods available in HySoP that may be used
-to set methods attribute in operators.
+"""A list of authorized keys that may be used to set methods
+in operators.
-Usage:
+Usage
+------
method = {key: value, ...}
-Keys must be one of the constants given in methods_keys.py.
+Key must be one of the constants given below. Value is usually a class name.
+See details in each operator.
-Value is usually a class name
-and sometimes a string. See details in each operator.
+Example
+--------
+For the stretching case, you may use:
-For example, consider the stretching case where time-integration
-is done with Runge-Kutta 3, order 4 finite-difference scheme is used
-for space discretisation and the default formulation is conservative::
+.. code::
method = {TimeIntegrator: RK3, Formulation: Conservative,
- SpaceDiscretisation: FDC4}
+ SpaceDiscretization: FDC4}
-Note FP: to avoid cycling, this file must never be imported
-inside an HySoP module. It's only a review of all the methods
-that can be imported by final user.
-"""
-
-import hysop.numerics.odesolvers as odesolvers
-RK2 = odesolvers.RK2
-"""Runge-Kutta 2 integration"""
-
-RK3 = odesolvers.RK3
-"""Runge-Kutta 3 integration"""
-
-RK4 = odesolvers.RK4
-"""Runge-Kutta 4 integration"""
-
-Euler = odesolvers.Euler
-"""Euler integration"""
-# Remesh
-import hysop.numerics.remeshing as remesh
-L2_1 = remesh.L2_1
-L2_2 = remesh.L2_2
-L2_3 = remesh.L2_3
-L2_4 = remesh.L2_4
-L4_2 = remesh.L4_2
-L4_3 = remesh.L4_3
-L4_4 = remesh.L4_4
-L6_3 = remesh.L6_3
-L6_4 = remesh.L6_4
-L6_5 = remesh.L6_5
-L6_6 = remesh.L6_6
-L8_4 = remesh.L8_4
-M8Prime = remesh.M8Prime
-Rmsh_Linear = remesh.Linear
-# A completer ...
-
-# Interpolation
-import hysop.numerics.interpolation as interpolation
-Linear = interpolation.Linear
-
-# Finite differences
-import hysop.numerics.finite_differences as fd
-FDC4 = fd.FDC4
-FDC2 = fd.FDC2
-FD2C2 = fd.FD2C2
-
-# Stretching formulations
-import hysop.operator.discrete.stretching as strd
-Conservative = strd.Conservative
-GradUW = strd.GradUW
+"""
+from hysop.constants import Backend, Precision, BoundaryCondition, \
+ TimeIntegratorsOptimisationLevel, FieldProjection, \
+ StretchingFormulation, SpaceDiscretization
+from hysop.numerics.interpolation.interpolation import Interpolation
+from hysop.numerics.odesolvers.runge_kutta import TimeIntegrator
+from hysop.numerics.remesh.remesh import Remesh
+from hysop.numerics.splitting.strang import StrangOrder
+
+from hysop.backend.device.kernel_config import KernelConfig
diff --git a/hysop/methods_keys.py b/hysop/methods_keys.py
deleted file mode 100644
index ec4601ed3d02e5d1432c25dd7f519beeee090b69..0000000000000000000000000000000000000000
--- a/hysop/methods_keys.py
+++ /dev/null
@@ -1,45 +0,0 @@
-"""
-@file methods_keys.py
-A list of authorized keys that may be used to set methods
-in operators.
-Usage:
-method = {key: value, ...}
-Key must be one of the constants given below. Value is usually a class name
-and sometimes a string. See details in each operator.
-
-Example, the stretching case :
-method = {TimeIntegrator: RK3, Formulation: Conservative,
- SpaceDiscretisation: FDC4}
-
-
-"""
-## Authorized keys for method.
-## Time integrator scheme (see hysop.numerics.integrators for
-## available names)
-TimeIntegrator = 11111
-## Remeshing scheme (hysop.numerics.remeshing)
-Remesh = 22222
-## Interpolation scheme (hysop.numerics.interpolation)
-Interpolation = 33333
-## Formulation (example in stretching : either Conservative or GradUW)
-Formulation = 44444
-## Space discretisation method
-## (see for example hysop.numerics.finite_differences)
-SpaceDiscretisation = 55555
-## Scales method parameters
-Scales = 66666
-## Splitting method
-Splitting = 77777
-## Device (either GPU or CPU)
-Support = 88888
-## method[GhostUpdate] = True if the operator deals with
-## its ghost points update
-GhostUpdate = 99999
-## List of criterions for adaptative time step computation
-dtCrit = 0
-## Multiscale method for multiscale advection
-MultiScale = 12345
-## Float precision for advection
-Precision = 12346
-## Extra arguments for discrete operators
-ExtraArgs = 9876
diff --git a/hysop/mpi/__init__.py b/hysop/mpi/__init__.py
deleted file mode 100644
index f4f4d7a38df05d5ab505e6280302c0a3877c44e9..0000000000000000000000000000000000000000
--- a/hysop/mpi/__init__.py
+++ /dev/null
@@ -1,40 +0,0 @@
-"""Hysop interface to the mpi implementation.
-
-It contains :
-
-* mpi basic variables (main communicator, rank, size ...)
-* :class:`hysop.mpi.topology.Cartesian` : mpi process distribution + local mesh
-
-
-This package is used to hide the underlying mpi interface
-in order to make any change of this interface, if required, easiest.
-
-At the time we use mpi4py : http://mpi4py.scipy.org
-
-"""
-
-# Everything concerning the chosen mpi implementation is hidden from hysop
-# main interface.
-# Why? --> to avoid that things like mpi4py. ... spread everywhere in the
-# soft so to ease a change of this implementation (if needed).
-from mpi4py import MPI as MPI
-"""MPI interface"""
-
-main_comm = MPI.COMM_WORLD.Dup()
-"""Main communicator"""
-
-main_rank = main_comm.Get_rank()
-"""Rank of the current process in main communicator"""
-
-main_size = main_comm.Get_size()
-"""Number of mpi process in main communicator"""
-
-Wtime = MPI.Wtime
-"""Function to return elapsed time since some time in the past.
-
-Usage:
-tref = Wtime()
-# proceed with some computations ...
-elapsed = Wtime() - tref
-# -> elapsed == time for 'some computations' on the current mpi process
-"""
diff --git a/hysop/numerics/extras_f/arnoldi.f95 b/hysop/numerics/extras_f/arnoldi.f95
new file mode 100644
index 0000000000000000000000000000000000000000..0fef4f5fca58717d404424588688dff57cbf7d60
--- /dev/null
+++ b/hysop/numerics/extras_f/arnoldi.f95
@@ -0,0 +1,220 @@
+!=========================================================================
+!Computation of global modes using a time stepping (snapshots) technique
+!=========================================================================
+!=========================================================================
+!Reads snapshots, constructs the Hessenberg matrix
+!and computes the eigen-values/eigen-functions
+!=========================================================================
+module arnoldi
+
+ use precision
+ use parameters
+
+ implicit none
+
+contains
+
+ !======================
+ subroutine arnoldi3d(Mu,ncli,nt,nfp,nmodes,Tps)
+ implicit none
+ integer, intent(in) :: ncli ! number of snapshot
+ integer, intent(in) :: nt ! total number of points per snapshot
+ integer, intent(in) :: nmodes ! number of desired modes
+ integer, intent(in) :: nfp ! number of desired eigen functions
+ real(wp), intent(in) :: Tps ! sampling time step
+ real(wp), dimension(:,:), intent(inout) :: Mu ! snapshots
+
+ real(wp), dimension(:,:), allocatable :: un ! orthonomalized Krylov basis
+ real(wp), dimension(:,:), allocatable :: Hessenberg ! Hessenberg matrix
+ complex(wp), dimension(:), allocatable :: VP ! eigenvalues
+ complex(wp), dimension(:,:), allocatable :: FP, FP_J ! eigen functions
+ real(wp), dimension(:), allocatable :: reslog, res ! residuals
+ integer, dimension(:), allocatable :: t ! sorting array
+ real(wp), dimension(:), allocatable :: tab !
+ real(wp) :: norm, prod, error !
+
+ integer :: i,j,nmax
+
+ allocate(un(nt,ncli),Hessenberg(ncli,ncli-1),VP(ncli-1),FP(ncli-1,ncli-1),FP_J(nt,ncli))
+
+ nmax=0
+ VP=(0.,0.); FP=(0.,0.); FP_J=(0.,0.)
+ Hessenberg=0.
+
+ !==================================
+ ! Arnoldi method
+ !==================================
+
+ norm = dot_product(Mu(:,1),Mu(:,1))
+ norm = sqrt(norm)
+ un(:,1) = Mu(:,1)/norm ! first normalized vector u1
+
+ do j=2,ncli ! construct a normalized base u2... un
+ un(:,j)=Mu(:,j) ! w=Mu_j (We have Mu_j=U(:,j+1))
+ do i=1,j-1
+ Hessenberg(i,j-1)=dot_product(un(:,i),un(:,j))
+ un(:,j)=un(:,j)-un(:,i)*Hessenberg(i,j-1)
+ enddo
+
+ norm = dot_product(un(:,j),un(:,j))
+ Hessenberg(j,j-1) = sqrt(norm)
+
+ un(:,j) = un(:,j)/Hessenberg(j,j-1)! normalization
+
+ enddo
+
+ ! do i=1,nt
+ ! print *, 'Krylov basis:', un(i,:)
+ ! enddo
+
+ do i=1,ncli-1
+ print *, 'Hessenberg matrix:', Hessenberg(i,:)
+ enddo
+
+
+ !Check orthonormalization
+ !==================================
+
+ print *,'check ortho'
+
+ prod=0.
+ do i=1,ncli
+ do j=1,ncli
+ prod=dot_product(un(:,j),un(:,i))
+ if (abs(prod).gt.1e-14) then
+ print *,i,j,abs(prod)
+ endif
+ enddo
+ enddo
+
+
+ !Eigen-values and Eigen-functions related to Hessenberg matrix
+ ! +
+ !Eigen-values related to Jacobian matrix ==> spectra
+ !==============================================================
+
+ open(unit=10, file='spectrum.dat')
+ open(unit=11, file='spectrum_log.dat')
+
+ call spectrum(Hessenberg(1:ncli-1,:),ncli-1,VP,FP)
+
+ do i=1,ncli-1
+ write(10,*) dble(VP(i)), aimag(VP(i))
+ write(11,*) dble(log(VP(i)))/Tps, ATAN(aimag(VP(i)/DBLE(VP(i))))/Tps
+ enddo
+ close(10)
+ close(11)
+
+ !Eigen-functions related to Jacobian matrix
+ !==========================================
+ FP_J(1:nt,1:ncli-1)=matmul(un(1:nt,1:ncli-1),FP(1:ncli-1,1:ncli-1))
+ ! do i=1,nt
+ ! print *, 'FP_J', (FP_J(i,j),j=1,ncli-1)
+ ! enddo
+
+ !Residual calculation with respect to each mode
+ !==============================================
+
+ allocate(res(ncli-1),reslog(ncli-1))
+ error = Hessenberg(ncli,ncli-1)
+ print *,'last Hess',Hessenberg(ncli,ncli-1)
+
+ do i=1,ncli-1
+ res(i) = abs(FP(ncli-1,i))*error
+ reslog(i)=-log10(res(i))
+ print *,'residual',reslog(i),res(i)
+ enddo
+
+
+ !Modes are sorted with respect to residual
+ !==========================================
+ allocate(t(ncli-1))
+
+ do i=1,ncli-1
+ t(i)=i
+ enddo
+
+ call sort(reslog,ncli-1,t)
+
+ open(unit=201,file='spectrum_res.dat')
+ write(201,*)'VARIABLES ="WR","WI","RES"'
+
+ do i=1,nmodes
+ write(201,100) dble(log(VP(t(i))))/Tps,&
+ ATAN(aimag(VP(t(i))/DBLE(VP(t(i)))))/Tps,&
+ res(t(i))
+ enddo
+ close(201)
+ !
+ !Write the associated eigen functions
+ !====================================
+ ! allocate(tab(nfp))
+ !
+ ! open(unit=107, file='table.dat')
+ ! open(unit=108, file='spectrum_sorted.dat')
+ !
+ ! do i=1,nfp
+ !! call ecriture(FP_J(:,t(h)))
+ ! write(108,*) ATAN(aimag(VP(t(i))/DBLE(VP(t(i)))))/Tps,&
+ ! dble(log(VP(t(i))))/Tps
+ ! enddo
+ ! close(108)
+ !
+100 format (5(2x,e19.13))
+
+ end subroutine arnoldi3d
+
+ !===================
+ !Spectrum subroutine
+ !===================
+ subroutine spectrum(A,n,VP,VR)
+ implicit none
+ integer :: INFO
+ integer :: n,LWORK
+ real(wp), dimension(n,n) :: A
+ real(wp), dimension(:), allocatable :: RWORK
+ complex(wp), dimension(1,n) :: VL
+ complex(wp), dimension(n,n) :: VR
+ complex(wp), dimension(:), allocatable :: WORK
+ complex(wp), dimension(n):: VP
+
+ LWORK=4*n
+ allocate(WORK(LWORK),RWORK(2*n))
+ call ZGEEV('N','V', n, A*(1.,0.), n, VP, VL, 1, VR, n,&
+ WORK, LWORK, RWORK, INFO )
+ print *, 'VP', VP
+
+ end subroutine spectrum
+
+ !==================
+ !Sorting subroutine
+ !==================
+ subroutine sort(t,n,ind)
+ implicit none
+ integer :: i, j, n, tp1
+ real(wp), dimension(1:n) :: t
+ real(wp) :: temp
+ integer, dimension(1:n) :: ind
+
+ do i=1,n
+ do j=i+1,n
+ if ((t(i))<(t(j))) then
+
+ temp=t(i)
+ tp1=ind(i)
+
+ t(i)=t(j)
+ ind(i)=ind(j)
+
+ t(j)=temp
+ ind(j)=tp1
+
+ endif
+ enddo
+ enddo
+
+ return
+
+ end subroutine sort
+
+end module arnoldi
diff --git a/hysop/numerics/extras_f/arnoldi2py.pyf b/hysop/numerics/extras_f/arnoldi2py.pyf
new file mode 100644
index 0000000000000000000000000000000000000000..7a2d95d5a161228a6d589f69cfe143f43619a8c2
--- /dev/null
+++ b/hysop/numerics/extras_f/arnoldi2py.pyf
@@ -0,0 +1,14 @@
+! -*- f90 -*-
+! Note: the context of this file is case sensitive.
+
+module arnoldi ! in arnoldi2py.f90
+ use precision
+ subroutine arnoldi3d(Mu,ncli,nt,nfp,nmodes,Tps) ! in arnoldi2py.f90:arnoldi2py
+ real(kind=wp) dimension(:,:),intent(inout) :: Mu
+ integer intent(in) :: ncli
+ integer intent(in) :: nt
+ integer intent(in) :: nfp
+ integer intent(in) :: nmodes
+ real(kind=wp) intent(in) :: Tps
+ end subroutine arnoldi3d
+end module arnoldi
diff --git a/hysop/numerics/fftw_f/fft2d.f90 b/hysop/numerics/fftw_f/fft2d.f90
new file mode 100755
index 0000000000000000000000000000000000000000..4a0a708d6c6989cbab7142aafebec699694ea541
--- /dev/null
+++ b/hysop/numerics/fftw_f/fft2d.f90
@@ -0,0 +1,617 @@
+!> Fast Fourier Transform routines (Fortran, based on fftw)
+!! to solve 2d Poisson and diffusion problems.
+!!
+!! This module provides :
+!! \li 1 - fftw routines for the "complex to complex" case :
+!! solves the problem for
+!! complex input/output. The names of these routines contain "c2c".
+!! \li 2 - fftw routines for the "real to complex" case :
+!! solves the problem for
+!! input fields which are real. The names of these routines contain "r2c".
+!! \li 3 - fftw routines for the "real to complex" case :
+!! solves the problem for
+!! input fields which are real and using the "many" interface of the fftw.
+!! It means that transforms are applied to the 2 input fields at the same time.
+!! Names of these routines contain "many".
+!!
+!! Obviously, all the above cases should lead to the same results. By default
+!! case 2 must be chosen (if input is real). Case 1 and 3 are more or less
+!! dedicated to tests and validation.
+module fft2d
+
+ use, intrinsic :: iso_c_binding
+ use precision
+ use parameters
+ implicit none
+ include 'fftw3-mpi.f03'
+
+ private
+
+ public :: init_c2c_2d,init_r2c_2d, r2c_scalar_2d, c2c_2d,c2r_2d,c2r_scalar_2d,&
+ r2c_2d,cleanFFTW_2d, filter_poisson_2d, filter_curl_2d, getParamatersTopologyFFTW2d, &
+ filter_diffusion_2d, init_r2c_2dBIS
+
+
+ !> plan for fftw "c2c" forward or r2c transform
+ type(C_PTR) :: plan_forward1, plan_forward2
+ !> plan for fftw "c2c" backward or c2r transform
+ type(C_PTR) :: plan_backward1,plan_backward2
+ !> memory buffer for fftw
+ !! (input and output buffer will point to this location)
+ type(C_PTR) :: cbuffer1
+ !> second memory buffer for fftw (used for backward transform)
+ type(C_PTR) :: cbuffer2
+ !! Note Franck : check if local declarations of datain/out works and improve perfs.
+ !> Field (complex values) for fftw input
+ complex(C_DOUBLE_COMPLEX), pointer :: datain1(:,:),datain2(:,:)
+ !> Field (real values) for fftw input
+ real(C_DOUBLE), pointer :: rdatain1(:,:)
+ !> Field (complex values) for fftw (forward) output
+ complex(C_DOUBLE_COMPLEX), pointer :: dataout1(:,:)
+ !> Field (real values) for fftw output
+ real(C_DOUBLE), pointer :: rdatain2(:,:)
+ !> Field (complex values) for fftw (forward) output
+ complex(C_DOUBLE_COMPLEX), pointer :: dataout2(:,:)
+ !> GLOBAL number of points in each direction
+ integer(C_INTPTR_T),pointer :: fft_resolution(:)
+ !> LOCAL resolution
+ integer(c_INTPTR_T),dimension(2) :: local_resolution
+ !> Offset in the direction of distribution
+ integer(c_INTPTR_T),dimension(2) :: local_offset
+ !> wave numbers for fft in x direction
+ real(C_DOUBLE), pointer :: kx(:)
+ !> wave numbers for fft in y direction
+ real(C_DOUBLE), pointer :: ky(:)
+ !> log file for fftw
+ character(len=20),parameter :: filename ="hysopfftw.log"
+ !> normalization factor
+ real(C_DOUBLE) :: normFFT
+ !> true if all the allocation stuff for global variables has been done.
+ logical :: is2DUpToDate = .false.
+
+contains
+ !========================================================================
+ ! Complex to complex transforms
+ !========================================================================
+
+ !> Initialisation of the fftw context for complex
+ !! to complex transforms (forward and backward)
+ !! @param[in] resolution global domain resolution
+ subroutine init_c2c_2d(resolution,lengths)
+
+ !! global domain resolution
+ integer(kind=ip), dimension(2), intent(in) :: resolution
+ real(wp),dimension(2), intent(in) :: lengths
+
+ !! Size of the local memory required for fftw (cbuffer)
+ integer(C_INTPTR_T) :: alloc_local
+
+ if(is2DUpToDate) return
+
+ ! init fftw mpi context
+ call fftw_mpi_init()
+
+ if(rank==0) open(unit=21,file=filename,form="formatted")
+
+ ! set fft resolution
+ allocate(fft_resolution(2))
+ fft_resolution = resolution-1
+
+ ! compute "optimal" size (according to fftw) for local date
+ ! (warning : dimension reversal)
+ alloc_local = fftw_mpi_local_size_2d_transposed(fft_resolution(c_Y), &
+ fft_resolution(c_X),main_comm, local_resolution(c_Y), &
+ local_offset(c_Y), local_resolution(c_X),local_offset(c_X));
+
+ ! allocate local buffer (used to save datain/dataout1
+ ! ==> in-place transform!!)
+ cbuffer1 = fftw_alloc_complex(alloc_local)
+ ! link datain and dataout1 to cbuffer, setting the right dimensions
+ call c_f_pointer(cbuffer1, datain1, &
+ [fft_resolution(c_X),local_resolution(c_Y)])
+ call c_f_pointer(cbuffer1, dataout1, &
+ [fft_resolution(c_Y),local_resolution(c_X)])
+
+ ! second buffer used for backward transform. Used to copy dataout1
+ ! into dataout2 (input for backward transform and filter)
+ ! and to save (in-place) the transform of the second component
+ ! of the velocity
+ cbuffer2 = fftw_alloc_complex(alloc_local)
+ call c_f_pointer(cbuffer2, datain2,&
+ [fft_resolution(c_X),local_resolution(c_Y)])
+ call c_f_pointer(cbuffer2, dataout2, [fft_resolution(c_Y),local_resolution(c_X)])
+
+ ! create MPI plan for in-place forward/backward DFT (note dimension reversal)
+ plan_forward1 = fftw_mpi_plan_dft_2d(fft_resolution(c_Y), fft_resolution(c_X),datain1,dataout1,&
+ main_comm,FFTW_FORWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward1 = fftw_mpi_plan_dft_2d(fft_resolution(c_Y),fft_resolution(c_X),dataout1,datain1,&
+ main_comm,FFTW_BACKWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ plan_backward2 = fftw_mpi_plan_dft_2d(fft_resolution(c_Y),fft_resolution(c_X),dataout2,datain2,&
+ main_comm,FFTW_BACKWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+
+ call computeKxC(lengths(c_X))
+ call computeKy(lengths(c_Y))
+ normFFT = ONE/(fft_resolution(c_X)*fft_resolution(c_Y))
+ !! call fft2d_diagnostics(alloc_local)
+
+ is2DUpToDate = .true.
+
+!!$ write(*,'(a,i5,a,16f10.4)') 'kx[',rank,'] ', kx
+!!$ write(*,'(a,i5,a,16f10.4)') 'ky[',rank,'] ', ky
+!!$
+ end subroutine init_c2c_2d
+
+ !> Execute fftw forward transform, according to the pre-defined plans.
+ subroutine c2c_2d(inputData,velocity_x,velocity_y)
+ complex(wp),dimension(:,:) :: velocity_x,velocity_y
+ complex(wp),dimension(:,:),intent(in) :: inputData
+
+ integer(C_INTPTR_T) :: i, j
+
+ do j = 1, local_resolution(c_Y)
+ do i = 1, fft_resolution(c_X)
+ datain1(i, j) = inputData(i,j)
+ end do
+ end do
+
+ ! compute transform (as many times as desired)
+ call fftw_mpi_execute_dft(plan_forward1, datain1, dataout1)
+
+!!$ do i = 1, fft_resolution(c_Y)
+!!$ write(*,'(a,i5,a,16f10.4)') 'out[',rank,'] ', dataout1(i,1:local_resolution(c_X))
+!!$ end do
+!!$
+ call filter_poisson_2d()
+
+ call fftw_mpi_execute_dft(plan_backward1, dataout1, datain1)
+ call fftw_mpi_execute_dft(plan_backward2,dataout2,datain2)
+ do j = 1, local_resolution(c_Y)
+ do i = 1, fft_resolution(c_X)
+ velocity_x(i,j) = datain1(i,j)*normFFT
+ velocity_y(i,j) = datain2(i,j)*normFFT
+ end do
+ end do
+
+!!$ do i = 1, fft_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'vxx[',rank,'] ', velocity_x(i,1:local_resolution(c_Y))
+!!$ end do
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+!!$ do i = 1, fft_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'vyy[',rank,'] ', velocity_y(i,1:local_resolution(c_Y))
+!!$ end do
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+!!$
+ end subroutine c2c_2d
+
+ !========================================================================
+ ! Real to complex transforms
+ !========================================================================
+
+ !> Initialisation of the fftw context for real to complex transforms (forward and backward)
+ !! @param[in] resolution global domain resolution
+ subroutine init_r2c_2d(resolution,lengths)
+
+ integer(kind=ip), dimension(2), intent(in) :: resolution
+ real(wp),dimension(2), intent(in) :: lengths
+ !! Size of the local memory required for fftw (cbuffer)
+ integer(C_INTPTR_T) :: alloc_local,halfLength
+
+ if(is2DUpToDate) return
+
+ ! init fftw mpi context
+ call fftw_mpi_init()
+
+ if(rank==0) open(unit=21,file=filename,form="formatted")
+
+ allocate(fft_resolution(2))
+ fft_resolution(:) = resolution(:)-1
+ halfLength = fft_resolution(c_X)/2+1
+ ! allocate local buffer (used to save datain/dataout1 ==> in-place transform!!)
+ alloc_local = fftw_mpi_local_size_2d_transposed(fft_resolution(c_Y),halfLength,main_comm,local_resolution(c_Y),&
+ local_offset(c_Y),local_resolution(c_X),local_offset(c_X));
+
+ ! allocate local buffer (used to save datain/dataout1 ==> in-place transform!!)
+ cbuffer1 = fftw_alloc_complex(alloc_local)
+
+ ! link rdatain1 and dataout1 to cbuffer, setting the right dimensions for each
+ call c_f_pointer(cbuffer1, rdatain1, [2*halfLength,local_resolution(c_Y)])
+ call c_f_pointer(cbuffer1, dataout1, [fft_resolution(c_Y),local_resolution(c_X)])
+
+ ! second buffer used for backward transform. Used to copy dataout1 into dataout2 (input for backward transform and filter)
+ ! and to save (in-place) the transform of the second component of the velocity
+ cbuffer2 = fftw_alloc_complex(alloc_local)
+
+ call c_f_pointer(cbuffer2, rdatain2, [2*halfLength,local_resolution(c_Y)])
+ call c_f_pointer(cbuffer2, dataout2, [fft_resolution(c_Y),local_resolution(c_X)])
+
+ ! create MPI plans for in-place forward/backward DFT (note dimension reversal)
+ plan_forward1 = fftw_mpi_plan_dft_r2c_2d(fft_resolution(c_Y), fft_resolution(c_X), rdatain1, dataout1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward1 = fftw_mpi_plan_dft_c2r_2d(fft_resolution(c_Y), fft_resolution(c_X), dataout1, rdatain1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ plan_backward2 = fftw_mpi_plan_dft_c2r_2d(fft_resolution(c_Y), fft_resolution(c_X), dataout2, rdatain2, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+
+ call computeKx(lengths(c_X))
+ call computeKy(lengths(c_Y))
+ normFFT = ONE/(fft_resolution(c_X)*fft_resolution(c_Y))
+ !! call fft2d_diagnostics(alloc_local)
+!!$
+!!$ write(*,'(a,i5,a,16f10.4)') 'kx[',rank,'] ', kx
+!!$ write(*,'(a,i5,a,16f10.4)') 'ky[',rank,'] ', ky
+!!$
+ is2DUpToDate = .true.
+
+ end subroutine init_r2c_2d
+
+
+ !> forward transform - The result is saved in local buffers
+ !! @param input data
+ subroutine r2c_scalar_2d(inputData, ghosts)
+
+ real(wp),dimension(:,:), intent(in) :: inputData
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
+
+ integer(C_INTPTR_T) :: i, j, ig, jg
+ ! init
+ do j = 1, local_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ rdatain1(i, j) = inputData(ig,jg)
+ end do
+ end do
+
+!!$ do i = 1, fft_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'rr[',rank,'] ', rdatain1(i,1:local_resolution(c_Y))
+!!$ end do
+!!$
+ ! compute transform (as many times as desired)
+ call fftw_mpi_execute_dft_r2c(plan_forward1, rdatain1, dataout1)
+
+!!$ do i = 1, fft_resolution(c_Y)
+!!$ write(*,'(a,i5,a,16f10.4)') 'aaaa[',rank,'] ', dataout1(i,1:local_resolution(c_X))
+!!$ end do
+
+ end subroutine r2c_scalar_2d
+
+ !> forward transform - The result is saved in local buffers
+ !! @param[in] input data
+ subroutine r2c_2d(input_x, input_y, ghosts)
+
+ real(wp),dimension(:,:), intent(in) :: input_x, input_y
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
+
+ integer(C_INTPTR_T) :: i, j, ig, jg
+ ! init
+ do j = 1, local_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ rdatain1(i, j) = input_x(ig,jg)
+ rdatain2(i, j) = input_y(ig,jg)
+ end do
+ end do
+
+ ! compute transform (as many times as desired)
+ call fftw_mpi_execute_dft_r2c(plan_forward1, rdatain1, dataout1)
+ call fftw_mpi_execute_dft_r2c(plan_forward2, rdatain2, dataout2)
+
+ end subroutine r2c_2d
+
+ !> Backward transform
+ subroutine c2r_2d(velocity_x,velocity_y, ghosts)
+ real(wp),dimension(:,:),intent(inout) :: velocity_x,velocity_y
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
+ integer(C_INTPTR_T) :: i, j, ig, jg
+
+ call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
+ call fftw_mpi_execute_dft_c2r(plan_backward2,dataout2,rdatain2)
+ do j = 1, local_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ velocity_x(ig,jg) = rdatain1(i,j)*normFFT
+ velocity_y(ig,jg) = rdatain2(i,j)*normFFT
+ end do
+ end do
+
+!!$
+!!$ do i = 1, fft_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'xx[',rank,'] ', velocity_x(i,1:local_resolution(c_Y))
+!!$ end do
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+!!$ do i = 1, fft_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'yy[',rank,'] ', velocity_y(i,1:local_resolution(c_Y))
+!!$ end do
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+
+
+ end subroutine c2r_2d
+
+ !> Backward transform for scalar field
+ subroutine c2r_scalar_2d(omega, ghosts)
+ real(wp),dimension(:,:),intent(inout) :: omega
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
+ integer(C_INTPTR_T) :: i, j, ig, jg
+
+ call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
+ do j = 1, local_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ omega(ig,jg) = rdatain1(i,j)*normFFT
+ end do
+ end do
+
+!!$
+!!$ do i = 1, fft_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'xx[',rank,'] ', velocity_x(i,1:local_resolution(c_Y))
+!!$ end do
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+!!$ do i = 1, fft_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'yy[',rank,'] ', velocity_y(i,1:local_resolution(c_Y))
+!!$ end do
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+
+
+ end subroutine c2r_scalar_2d
+
+
+ !========================================================================
+ ! Common (r2c, c2c) subroutines
+ !========================================================================
+
+ !> Computation of frequencies coeff, over the distributed direction in the real/complex case
+ !> @param lengths size of the domain
+ subroutine computeKx(length)
+
+ real(wp),intent(in) :: length
+
+ !! Local loops indices
+ integer(C_INTPTR_T) :: i
+
+ !! Compute filter coefficients
+ allocate(kx(local_resolution(c_X)))
+
+ do i = local_offset(c_X)+1,local_offset(c_X)+local_resolution(c_X) !! global index
+ kx(i-local_offset(c_X)) = 2.*pi/length*(i-1)
+ end do
+
+ end subroutine computeKx
+
+ !> Computation of frequencies coeff, over the distributed direction in the complex/complex case
+ !> @param lengths size of the domain
+ subroutine computeKxC(length)
+
+ real(wp),intent(in) :: length
+
+ !! Local loops indices
+ integer(C_INTPTR_T) :: i
+
+ !! Compute filter coefficients
+ allocate(kx(local_resolution(c_X)))
+
+ !! x frequencies (distributed over proc)
+ !! If we deal with positive frequencies only
+ if(local_offset(c_X)+local_resolution(c_X) <= fft_resolution(c_X)/2+1 ) then
+ do i = 1,local_resolution(c_X)
+ kx(i) = 2.*pi/length*(local_offset(c_X)+i-1)
+ end do
+
+ else
+ !! else if we deal with negative frequencies only
+ if(local_offset(c_X)+1 > fft_resolution(c_X)/2+1 ) then
+ do i = 1,local_resolution(c_X)
+ kx(i) = 2.*pi/length*(local_offset(c_X)+i-1-fft_resolution(c_X))
+ end do
+ !! final case : start positive freq, end in negative ones
+ else
+ do i = local_offset(c_X)+1, fft_resolution(c_X)/2+1 !! global index
+ kx(i-local_offset(c_X)) = 2.*pi/length*(i-1)
+ end do
+ do i = fft_resolution(c_X)/2+2,local_resolution(c_X)+local_offset(c_X)
+ kx(i-local_offset(c_X)) = 2.*pi/length*(i-1-fft_resolution(c_X))
+ end do
+ end if
+ end if
+
+ end subroutine computeKxC
+
+ !> Computation of frequencies coeff, over non-distributed direction(s)
+ !> @param lengths size of the domain
+ subroutine computeKy(length)
+ real(wp), intent(in) :: length
+
+ !! Local loops indices
+ integer(C_INTPTR_T) :: i
+ allocate(ky(fft_resolution(c_Y)))
+
+ do i = 1, fft_resolution(c_Y)/2+1
+ ky(i) = 2.*pi/length*(i-1)
+ end do
+ do i = fft_resolution(c_Y)/2+2,fft_resolution(c_Y)
+ ky(i) = 2.*pi/length*(i-fft_resolution(c_Y)-1)
+ end do
+
+ end subroutine computeKy
+
+ subroutine filter_poisson_2d()
+
+ integer(C_INTPTR_T) :: i, j
+ complex(C_DOUBLE_COMPLEX) :: coeff
+ if(local_offset(c_X)==0) then
+ if(local_offset(c_Y) == 0) then
+ dataout1(1,1) = 0.0
+ dataout2(1,1) = 0.0
+ else
+ coeff = Icmplx/(kx(1)**2+ky(1)**2)
+ dataout2(1,1) = -coeff*kx(1)*dataout1(1,1)
+ dataout1(1,1) = coeff*ky(1)*dataout1(1,1)
+ endif
+
+ do j = 2, fft_resolution(c_Y)
+ coeff = Icmplx/(kx(1)**2+ky(j)**2)
+ dataout2(j,1) = -coeff*kx(1)*dataout1(j,1)
+ dataout1(j,1) = coeff*ky(j)*dataout1(j,1)
+ end do
+ do i = 2,local_resolution(c_X)
+ do j = 1, fft_resolution(c_Y)
+ coeff = Icmplx/(kx(i)**2+ky(j)**2)
+ dataout2(j,i) = -coeff*kx(i)*dataout1(j,i)
+ dataout1(j,i) = coeff*ky(j)*dataout1(j,i)
+ end do
+ end do
+ else
+ do i = 1,local_resolution(c_X)
+ do j = 1, fft_resolution(c_Y)
+ coeff = Icmplx/(kx(i)**2+ky(j)**2)
+ dataout2(j,i) = -coeff*kx(i)*dataout1(j,i)
+ dataout1(j,i) = coeff*ky(j)*dataout1(j,i)
+ end do
+ end do
+ end if
+
+!!$ do i = 1,local_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'xx[',rank,'] ', dataout1(1:fft_resolution(c_Y),i)
+!!$ end do
+!!$
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+!!$ do i = 1,local_resolution(c_X)
+!!$ write(*,'(a,i5,a,16f10.4)') 'yy[',rank,'] ', dataout2(1:fft_resolution(c_Y),i)
+!!$ end do
+!!$ write(*,'(a,i5,a)') '[',rank,'] ==============================='
+
+ end subroutine filter_poisson_2d
+
+ subroutine filter_diffusion_2d(nudt)
+
+ real(C_DOUBLE), intent(in) :: nudt
+ integer(C_INTPTR_T) :: i, j
+ complex(C_DOUBLE_COMPLEX) :: coeff
+
+ do i = 1,local_resolution(c_X)
+ do j = 1, fft_resolution(c_Y)
+ coeff = ONE/(ONE + nudt * (kx(i)**2+ky(j)**2))
+ dataout1(j,i) = coeff*dataout1(j,i)
+ end do
+ end do
+
+ end subroutine filter_diffusion_2d
+
+ !> Clean fftw context (free memory, plans ...)
+ subroutine cleanFFTW_2d()
+ is2DUpToDate = .false.
+ call fftw_destroy_plan(plan_forward1)
+ call fftw_destroy_plan(plan_backward1)
+ !call fftw_destroy_plan(plan_forward2)
+ !call fftw_destroy_plan(plan_backward2)
+ call fftw_free(cbuffer1)
+ call fftw_free(cbuffer2)
+ call fftw_mpi_cleanup()
+ deallocate(fft_resolution)
+ if(rank==0) close(21)
+ end subroutine cleanFFTW_2d
+
+ !> Solve curl problem in the Fourier space :
+ !! \f{eqnarray*} \omega &=& \nabla \times v
+ subroutine filter_curl_2d()
+
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+
+ !! mind the transpose -> index inversion between y and z
+ do j = 1,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx
+ dataout1(j,i) = coeff*(kx(i)*dataout2(j,i) - ky(j)*dataout1(j,i))
+ end do
+ end do
+ end do
+
+ end subroutine filter_curl_2d
+
+ subroutine fft2d_diagnostics(nbelem)
+ integer(C_INTPTR_T), intent(in) :: nbelem
+ complex(C_DOUBLE_COMPLEX) :: memoryAllocated
+ memoryAllocated = real(nbelem*sizeof(memoryAllocated),wp)*1e-6
+ write(*,'(a,i5,a,i12,f10.2)') '[',rank,'] size of each buffer (elements / memory in MB):', &
+ nbelem, memoryAllocated
+ write(*,'(a,i5,a,2i12)') '[',rank,'] size of kx,y,z vectors (number of elements):', &
+ size(kx), size(ky)
+ write(*,'(a,i5,a,4i5)') '[',rank,'] local resolution and offset :', local_resolution, local_offset
+ memoryAllocated = 2*memoryAllocated + real(sizeof(kx) + sizeof(ky), wp)*1e-6
+ write(*,'(a,i5,a,f10.2)') '[',rank,'] Total memory used for fftw buffers (MB):', memoryAllocated
+
+ end subroutine fft2d_diagnostics
+
+ !> Get local size of input and output field on fftw topology
+ !! @param datashape local shape of the input field for the fftw process
+ !! @param offset index of the first component of the local field (in each dir) in the global set of indices
+ subroutine getParamatersTopologyFFTW2d(datashape,offset)
+ integer(kind=ip), intent(out),dimension(2) :: datashape
+ integer(kind=ip), intent(out),dimension(2) :: offset
+ integer(C_INTPTR_T) :: offsetx = 0
+ datashape = (/fft_resolution(c_X), local_resolution(c_Y)/)
+ offset = (/ offsetx, local_offset(c_Y)/)
+
+ end subroutine getParamatersTopologyFFTW2d
+ !> Initialisation of the fftw context for real to complex transforms (forward and backward)
+ !! @param[in] resolution global domain resolution
+ subroutine init_r2c_2dBIS(resolution,lengths)
+
+ integer(kind=ip), dimension(2), intent(in) :: resolution
+ real(wp),dimension(2), intent(in) :: lengths
+ !! Size of the local memory required for fftw (cbuffer)
+ integer(C_INTPTR_T) :: alloc_local,halfLength,howmany
+ integer(C_INTPTR_T), dimension(2) :: n
+
+ !> Field (real values) for fftw input
+ real(C_DOUBLE), pointer :: rdatain1Many(:,:,:)
+
+ ! init fftw mpi context
+ call fftw_mpi_init()
+ howmany = 1
+ if(rank==0) open(unit=21,file=filename,form="formatted")
+
+ allocate(fft_resolution(2))
+ fft_resolution(:) = resolution(:)-1
+ halfLength = fft_resolution(c_X)/2+1
+ n(1) = fft_resolution(2)
+ n(2) = halfLength
+ ! allocate local buffer (used to save datain/dataout1 ==> in-place transform!!)
+ alloc_local = fftw_mpi_local_size_many_transposed(2,n,howmany,FFTW_MPI_DEFAULT_BLOCK,&
+ FFTW_MPI_DEFAULT_BLOCK,main_comm,local_resolution(c_Y),&
+ local_offset(c_Y),local_resolution(c_X),local_offset(c_X));
+
+ ! allocate local buffer (used to save datain/dataout1 ==> in-place transform!!)
+ cbuffer1 = fftw_alloc_complex(alloc_local)
+
+ ! link rdatain1 and dataout1 to cbuffer, setting the right dimensions for each
+ call c_f_pointer(cbuffer1, rdatain1Many, [howmany,2*halfLength,local_resolution(c_Y)])
+ call c_f_pointer(cbuffer1, dataout1, [fft_resolution(c_Y),local_resolution(c_X)])
+
+ ! second buffer used for backward transform. Used to copy dataout1 into dataout2 (input for backward transform and filter)
+ ! and to save (in-place) the transform of the second component of the velocity
+ cbuffer2 = fftw_alloc_complex(alloc_local)
+
+ call c_f_pointer(cbuffer2, rdatain1Many, [howmany,2*halfLength,local_resolution(c_Y)])
+ call c_f_pointer(cbuffer2, dataout2, [fft_resolution(c_Y),local_resolution(c_X)])
+
+ ! create MPI plans for in-place forward/backward DFT (note dimension reversal)
+ plan_forward1 = fftw_mpi_plan_dft_r2c_2d(fft_resolution(c_Y), fft_resolution(c_X), rdatain1Many, dataout1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward1 = fftw_mpi_plan_dft_c2r_2d(fft_resolution(c_Y), fft_resolution(c_X), dataout1, rdatain1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ plan_backward2 = fftw_mpi_plan_dft_c2r_2d(fft_resolution(c_Y), fft_resolution(c_X), dataout2, rdatain2, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+
+ call computeKx(lengths(c_X))
+ call computeKy(lengths(c_Y))
+ normFFT = ONE/(fft_resolution(c_X)*fft_resolution(c_Y))
+ !! call fft2d_diagnostics(alloc_local)
+
+ end subroutine init_r2c_2dBIS
+
+end module fft2d
diff --git a/hysop/numerics/fftw_f/fft3d.f90 b/hysop/numerics/fftw_f/fft3d.f90
new file mode 100755
index 0000000000000000000000000000000000000000..c839f1752a9a2d510bc00faca0738283be900c83
--- /dev/null
+++ b/hysop/numerics/fftw_f/fft3d.f90
@@ -0,0 +1,1107 @@
+!> Fast Fourier Transform routines (Fortran, based on fftw) to solve 3d Poisson and diffusion problems.
+!!
+!! This module provides :
+!! \li 1 - fftw routines for the "complex to complex" case : solves the problem for
+!! complex input/output. The names of these routines contain "c2c".
+!! \li 2 - fftw routines for the "real to complex" case : solves the problem for
+!! input fields which are real. The names of these routines contain "r2c".
+!! \li 3 - fftw routines for the "real to complex" case : solves the problem for
+!! input fields which are real and using the "many" interface of the fftw.
+!! It means that transforms are applied to the 3 input fields at the same time.
+!! Names of these routines contain "many".
+!!
+!! Obviously, all the above cases should lead to the same results. By default
+!! case 2 must be chosen (if input is real). Case 1 and 3 are more or less
+!! dedicated to tests and validation.
+module fft3d
+
+ use, intrinsic :: iso_c_binding
+ use mpi
+ use precision
+ use parameters
+
+ implicit none
+ include 'fftw3-mpi.f03'
+
+ private
+
+ public :: init_r2c_3d,init_c2c_3d,init_r2c_scalar_3d, r2c_3d,r2c_scalar_3d,c2c_3d,c2r_3d,c2r_scalar_3d,cleanFFTW_3d,&
+ getParamatersTopologyFFTW3d,filter_poisson_3d,filter_curl_diffusion_3d, &
+ init_r2c_3d_many, r2c_3d_many, c2r_3d_many, filter_diffusion_3d_many,&
+ filter_poisson_3d_many, filter_diffusion_3d, filter_curl_3d, filter_projection_om_3d,&
+ filter_multires_om_3d, filter_pressure_3d, r2c_3d_scal, filter_spectrum_3d
+
+ !> plan for fftw "c2c" forward or r2c transform
+ type(C_PTR) :: plan_forward1, plan_forward2, plan_forward3
+ !> plan for fftw "c2c" backward or c2r transform
+ type(C_PTR) :: plan_backward1, plan_backward2, plan_backward3
+ !> memory buffer for fftw (input and output buffer will point to this location)
+ type(C_PTR) :: cbuffer1
+ !> second memory buffer for fftw
+ type(C_PTR) :: cbuffer2
+ !> third memory buffer for fftw
+ type(C_PTR) :: cbuffer3
+ !! Note Franck : check if local declarations of datain/out works and improve perfs.
+ !> Field (complex values) for fftw input
+ complex(C_DOUBLE_COMPLEX), pointer :: datain1(:,:,:)=>NULL(), datain2(:,:,:)=>NULL(), datain3(:,:,:)=>NULL()
+ !> Field (real values) for fftw input (these are only pointers to the cbuffers)
+ real(C_DOUBLE), pointer :: rdatain1(:,:,:)=>NULL() ,rdatain2(:,:,:)=>NULL() ,rdatain3(:,:,:)=>NULL()
+ !> Field (real values) for fftw input in the fftw-many case
+ real(C_DOUBLE), pointer :: rdatain_many(:,:,:,:)=>NULL()
+ !> Field (complex values) for fftw (forward) output
+ complex(C_DOUBLE_COMPLEX), pointer :: dataout1(:,:,:)=>NULL() ,dataout2(:,:,:)=>NULL() ,dataout3(:,:,:)=>NULL()
+ !> Field (complex values) for fftw (forward) output in the fftw-many case
+ complex(C_DOUBLE_COMPLEX), pointer :: dataout_many(:,:,:,:)=>NULL()
+ !> GLOBAL number of points in each direction on which fft is applied (--> corresponds to "real" resolution - 1)
+ integer(C_INTPTR_T),pointer :: fft_resolution(:)=>NULL()
+ !> LOCAL number of points for fft
+ integer(c_INTPTR_T),dimension(3) :: local_resolution
+ !> Offset in the direction of distribution
+ integer(c_INTPTR_T),dimension(3) :: local_offset
+ !> wave numbers for fft in x direction
+ real(C_DOUBLE), pointer :: kx(:)
+ !> wave numbers for fft in y direction
+ real(C_DOUBLE), pointer :: ky(:)
+ !> wave numbers for fft in z direction
+ real(C_DOUBLE), pointer :: kz(:)
+ !> log file for fftw
+ character(len=20),parameter :: filename ="hysopfftw.log"
+ !> normalization factor
+ real(C_DOUBLE) :: normFFT
+ !> true if we use fftw-many routines
+ logical :: manycase
+ !> true if all the allocation stuff for global variables has been done.
+ logical :: is3DUpToDate = .false.
+
+contains
+ !========================================================================
+ ! Complex to complex transforms
+ !========================================================================
+
+ !> Initialisation of the fftw context for complex to complex transforms (forward and backward)
+ !! @param[in] resolution global domain resolution
+ !! @param[in] lengths width of each side of the domain
+ subroutine init_c2c_3d(resolution,lengths)
+
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
+
+ !! Size of the local memory required for fftw (cbuffer)
+ integer(C_INTPTR_T) :: alloc_local
+
+ if(is3DUpToDate) return
+
+ ! init fftw mpi context
+ call fftw_mpi_init()
+
+ if(rank==0) open(unit=21,file=filename,form="formatted")
+
+ ! set fft resolution
+ allocate(fft_resolution(3))
+ fft_resolution(:) = resolution(:)-1
+
+ ! compute "optimal" size (according to fftw) for local data (warning : dimension reversal)
+ alloc_local = fftw_mpi_local_size_3d_transposed(fft_resolution(c_Z),fft_resolution(c_Y),fft_resolution(c_X),main_comm,&
+ local_resolution(c_Z),local_offset(c_Z),local_resolution(c_Y),local_offset(c_Y));
+
+ ! Set a default value for c_X components.
+ local_offset(c_X) = 0
+ local_resolution(c_X) = fft_resolution(c_X)
+
+ ! allocate local buffer (used to save datain/dataout ==> in-place transform!!)
+ cbuffer1 = fftw_alloc_complex(alloc_local)
+ ! link datain and dataout to cbuffer, setting the right dimensions for each
+ call c_f_pointer(cbuffer1, datain1, [fft_resolution(c_X),fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer1, dataout1, [fft_resolution(c_X),fft_resolution(c_Z),local_resolution(c_Y)])
+
+ ! second buffer used for backward transform. Used to copy dataout into dataout2 (input for backward transform and filter)
+ ! and to save (in-place) the transform of the second component of the velocity
+ cbuffer2 = fftw_alloc_complex(alloc_local)
+ call c_f_pointer(cbuffer2, datain2, [fft_resolution(c_X),fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer2, dataout2, [fft_resolution(c_X),fft_resolution(c_Z),local_resolution(c_Y)])
+
+ ! second buffer used for backward transform. Used to copy dataout into dataout2 (input for backward transform and filter)
+ ! and to save (in-place) the transform of the second component of the velocity
+ cbuffer3 = fftw_alloc_complex(alloc_local)
+ call c_f_pointer(cbuffer3, datain3, [fft_resolution(c_X),fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer3, dataout3, [fft_resolution(c_X),fft_resolution(c_Z),local_resolution(c_Y)])
+
+ ! create MPI plan for in-place forward/backward DFT (note dimension reversal)
+ plan_forward1 = fftw_mpi_plan_dft_3d(fft_resolution(c_Z), fft_resolution(c_Y), fft_resolution(c_X),datain1,dataout1,&
+ main_comm,FFTW_FORWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward1 = fftw_mpi_plan_dft_3d(fft_resolution(c_Z),fft_resolution(c_Y),fft_resolution(c_X),dataout1,datain1,&
+ main_comm,FFTW_BACKWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ plan_forward2 = fftw_mpi_plan_dft_3d(fft_resolution(c_Z), fft_resolution(c_Y), fft_resolution(c_X),datain2,dataout2,&
+ main_comm,FFTW_FORWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward2 = fftw_mpi_plan_dft_3d(fft_resolution(c_Z),fft_resolution(c_Y),fft_resolution(c_X),dataout2,datain2,&
+ main_comm,FFTW_BACKWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ plan_forward3 = fftw_mpi_plan_dft_3d(fft_resolution(c_Z), fft_resolution(c_Y), fft_resolution(c_X),datain3,dataout3,&
+ main_comm,FFTW_FORWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward3 = fftw_mpi_plan_dft_3d(fft_resolution(c_Z),fft_resolution(c_Y),fft_resolution(c_X),dataout3,datain3,&
+ main_comm,FFTW_BACKWARD,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+
+ call computeKx(lengths(c_X))
+ call computeKy(lengths(c_Y))
+ call computeKz(lengths(c_Z))
+
+ !! call fft3d_diagnostics(alloc_local)
+
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ manycase = .false.
+
+ is3DUpToDate = .true.
+
+ end subroutine init_c2c_3d
+
+ !> Solve poisson problem for complex input and output vector fields
+ !! @param[in] omega_x 3d scalar field, x-component of the input vector field
+ !! @param[in] omega_y 3d scalar field, y-component of the input vector field
+ !! @param[in] omega_z 3d scalar field, z-component of the input vector field
+ !! @param[in] velocity_x 3d scalar field, x-component of the output vector field
+ !! @param[in] velocity_y 3d scalar field, y-component of the output vector field
+ !! @param[in] velocity_z 3d scalar field, z-component of the output vector field
+ subroutine c2c_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z)
+ complex(wp),dimension(:,:,:) :: velocity_x,velocity_y,velocity_z
+ complex(wp),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
+
+ integer(C_INTPTR_T) :: i,j,k
+ ! Copy input data into the fftw buffer
+ do k = 1, local_resolution(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ do i = 1, fft_resolution(c_X)
+ datain1(i,j,k) = omega_x(i,j,k)
+ datain2(i,j,k) = omega_y(i,j,k)
+ datain3(i,j,k) = omega_z(i,j,k)
+ end do
+ end do
+ end do
+ ! compute transform (as many times as desired)
+ call fftw_mpi_execute_dft(plan_forward1, datain1, dataout1)
+ call fftw_mpi_execute_dft(plan_forward2, datain2, dataout2)
+ call fftw_mpi_execute_dft(plan_forward3, datain3, dataout3)
+
+ ! apply poisson filter
+ call filter_poisson_3d()
+
+ ! inverse transform to retrieve velocity
+ call fftw_mpi_execute_dft(plan_backward1, dataout1,datain1)
+ call fftw_mpi_execute_dft(plan_backward2,dataout2,datain2)
+ call fftw_mpi_execute_dft(plan_backward3,dataout3,datain3)
+ do k =1, local_resolution(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ do i = 1, fft_resolution(c_X)
+ velocity_x(i,j,k) = datain1(i,j,k)*normFFT
+ velocity_y(i,j,k) = datain2(i,j,k)*normFFT
+ velocity_z(i,j,k) = datain3(i,j,k)*normFFT
+ end do
+ end do
+ end do
+
+ end subroutine c2c_3d
+
+ !========================================================================
+ ! Real to complex transforms
+ !========================================================================
+
+ !> Initialisation of the fftw context for real to complex transforms (forward and backward)
+ !! @param[in] resolution global domain resolution
+ !! @param[in] lengths width of each side of the domain
+ subroutine init_r2c_3d(resolution,lengths)
+
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
+ !! Size of the local memory required for fftw (cbuffer)
+ integer(C_INTPTR_T) :: alloc_local,halfLength
+
+ if(is3DUpToDate) return
+
+ ! init fftw mpi context
+ call fftw_mpi_init()
+
+ if(rank==0) open(unit=21,file=filename,form="formatted")
+ allocate(fft_resolution(3))
+ fft_resolution(:) = resolution(:)-1
+ halfLength = fft_resolution(c_X)/2+1
+
+ ! compute "optimal" size (according to fftw) for local data (warning : dimension reversal)
+ alloc_local = fftw_mpi_local_size_3d_transposed(fft_resolution(c_Z),fft_resolution(c_Y),halfLength,&
+ main_comm,local_resolution(c_Z),local_offset(c_Z),local_resolution(c_Y),local_offset(c_Y));
+
+ ! init c_X part. This is required to compute kx with the same function in 2d and 3d cases.
+ local_offset(c_X) = 0
+ local_resolution(c_X) = halfLength
+
+ ! allocate local buffer (used to save datain/dataout ==> in-place transform!!)
+ cbuffer1 = fftw_alloc_complex(alloc_local)
+ cbuffer2 = fftw_alloc_complex(alloc_local)
+ cbuffer3 = fftw_alloc_complex(alloc_local)
+
+ ! link rdatain and dataout to cbuffer, setting the right dimensions for each
+ call c_f_pointer(cbuffer1, rdatain1, [2*halfLength,fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer1, dataout1, [halfLength, fft_resolution(c_Z), local_resolution(c_Y)])
+ call c_f_pointer(cbuffer2, rdatain2, [2*halfLength,fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer2, dataout2, [halfLength, fft_resolution(c_Z), local_resolution(c_Y)])
+ call c_f_pointer(cbuffer3, rdatain3, [2*halfLength,fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer3, dataout3, [halfLength, fft_resolution(c_Z), local_resolution(c_Y)])
+
+ rdatain1 = 0.0
+ rdatain2 = 0.0
+ rdatain3 = 0.0
+
+ ! create MPI plans for in-place forward/backward DFT (note dimension reversal)
+ plan_forward1 = fftw_mpi_plan_dft_r2c_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), rdatain1, dataout1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward1 = fftw_mpi_plan_dft_c2r_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), dataout1, rdatain1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ plan_forward2 = fftw_mpi_plan_dft_r2c_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), rdatain2, dataout2, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward2 = fftw_mpi_plan_dft_c2r_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), dataout2, rdatain2, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ plan_forward3 = fftw_mpi_plan_dft_r2c_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), rdatain3, dataout3, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward3 = fftw_mpi_plan_dft_c2r_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), dataout3, rdatain3, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+
+ call computeKx(lengths(c_X))
+ call computeKy(lengths(c_Y))
+ call computeKz(lengths(c_Z))
+
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ !! call fft3d_diagnostics(alloc_local)
+ manycase = .false.
+ is3DUpToDate = .true.
+
+ end subroutine init_r2c_3d
+
+ !> Initialisation of the fftw context for real to complex transforms (forward and backward)
+ !! @param[in] resolution global domain resolution
+ !! @param[in] lengths width of each side of the domain
+ subroutine init_r2c_scalar_3d(resolution,lengths)
+
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
+ !! Size of the local memory required for fftw (cbuffer)
+ integer(C_INTPTR_T) :: alloc_local,halfLength
+
+ if(is3DUpToDate) return
+
+ ! init fftw mpi context
+ call fftw_mpi_init()
+
+ if(rank==0) open(unit=21,file=filename,form="formatted")
+ allocate(fft_resolution(3))
+ fft_resolution(:) = resolution(:)-1
+ halfLength = fft_resolution(c_X)/2+1
+
+ ! compute "optimal" size (according to fftw) for local data (warning : dimension reversal)
+ alloc_local = fftw_mpi_local_size_3d_transposed(fft_resolution(c_Z),fft_resolution(c_Y),halfLength,&
+ main_comm,local_resolution(c_Z),local_offset(c_Z),local_resolution(c_Y),local_offset(c_Y));
+
+ ! init c_X part. This is required to compute kx with the same function in 2d and 3d cases.
+ local_offset(c_X) = 0
+ local_resolution(c_X) = halfLength
+
+ ! allocate local buffer (used to save datain/dataout ==> in-place transform!!)
+ cbuffer1 = fftw_alloc_complex(alloc_local)
+
+ ! link rdatain and dataout to cbuffer, setting the right dimensions for each
+ call c_f_pointer(cbuffer1, rdatain1, [2*halfLength,fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer1, dataout1, [halfLength, fft_resolution(c_Z), local_resolution(c_Y)])
+
+ rdatain1 = 0.0
+
+ ! create MPI plans for in-place forward/backward DFT (note dimension reversal)
+ plan_forward1 = fftw_mpi_plan_dft_r2c_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), rdatain1, dataout1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward1 = fftw_mpi_plan_dft_c2r_3d(fft_resolution(c_Z),fft_resolution(c_Y), fft_resolution(c_X), dataout1, rdatain1, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+
+ call computeKx(lengths(c_X))
+ call computeKy(lengths(c_Y))
+ call computeKz(lengths(c_Z))
+
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ !! call fft3d_diagnostics(alloc_local)
+ manycase = .false.
+ is3DUpToDate = .true.
+
+ end subroutine init_r2c_scalar_3d
+
+ !> forward transform - The result is saved in local buffers
+ !! @param[in] omega_x 3d scalar field, x-component of the input vector field
+ !! @param[in] omega_y 3d scalar field, y-component of the input vector field
+ !! @param[in] omega_z 3d scalar field, z-component of the input vector field
+ !! @param[in] ghosts, number of points in the ghost layer of input fields.
+ subroutine r2c_3d(omega_x,omega_y,omega_z, ghosts)
+
+ real(wp),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ !real(wp) :: start
+ integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
+
+ ! ig, jg, kg are used to take into account
+ ! ghost points in input fields
+
+ ! init
+ do k =1, local_resolution(c_Z)
+ kg = k + ghosts(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ rdatain1(i,j,k) = omega_x(ig,jg,kg)
+ rdatain2(i,j,k) = omega_y(ig,jg,kg)
+ rdatain3(i,j,k) = omega_z(ig,jg,kg)
+ end do
+ end do
+ end do
+
+ ! compute transforms for each component
+ !start = MPI_WTIME()
+ call fftw_mpi_execute_dft_r2c(plan_forward1, rdatain1, dataout1)
+ call fftw_mpi_execute_dft_r2c(plan_forward2, rdatain2, dataout2)
+ call fftw_mpi_execute_dft_r2c(plan_forward3, rdatain3, dataout3)
+ !!print *, "r2c time = ", MPI_WTIME() - start
+
+ end subroutine r2c_3d
+
+ !> Backward fftw transform
+ !! @param[in,out] velocity_x 3d scalar field, x-component of the output vector field
+ !! @param[in,out] velocity_y 3d scalar field, y-component of the output vector field
+ !! @param[in,out] velocity_z 3d scalar field, z-component of the output vector field
+ !! @param[in] ghosts, number of points in the ghost layer of in/out velocity field.
+ subroutine c2r_3d(velocity_x,velocity_y,velocity_z, ghosts)
+ real(wp),dimension(:,:,:),intent(inout) :: velocity_x,velocity_y,velocity_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp) :: start
+ integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
+ start = MPI_WTIME()
+ call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
+ call fftw_mpi_execute_dft_c2r(plan_backward2,dataout2,rdatain2)
+ call fftw_mpi_execute_dft_c2r(plan_backward3,dataout3,rdatain3)
+!! print *, "c2r time : ", MPI_WTIME() -start
+ ! copy back to velocity and normalisation
+ do k =1, local_resolution(c_Z)
+ kg = k + ghosts(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ velocity_x(ig,jg,kg) = rdatain1(i,j,k)*normFFT
+ velocity_y(ig,jg,kg) = rdatain2(i,j,k)*normFFT
+ velocity_z(ig,jg,kg) = rdatain3(i,j,k)*normFFT
+ end do
+ end do
+ end do
+
+ end subroutine c2r_3d
+
+ !> forward transform - The result is saved in a local buffer
+ !! @param[in] omega 3d scalar field, x-component of the input vector field
+ !! @param[in] ghosts, number of points in the ghost layer of input field.
+ subroutine r2c_scalar_3d(scalar, ghosts)
+
+ real(wp),dimension(:,:,:),intent(in) :: scalar
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp) :: start
+ integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
+
+ ! ig, jg, kg are used to take into account
+ ! ghost points in input fields
+
+ ! init
+ do k =1, local_resolution(c_Z)
+ kg = k + ghosts(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ rdatain1(i,j,k) = scalar(ig,jg,kg)
+ end do
+ end do
+ end do
+
+ ! compute transforms for each component
+ start = MPI_WTIME()
+ call fftw_mpi_execute_dft_r2c(plan_forward1, rdatain1, dataout1)
+ !!print *, "r2c time = ", MPI_WTIME() - start
+
+ end subroutine r2c_scalar_3d
+
+ !> Backward fftw transform
+ !! @param[in,out] scalar 3d scalar field
+ !! @param[in] ghosts, number of points in the ghost layer of in/out scalar field.
+ subroutine c2r_scalar_3d(scalar, ghosts)
+ real(wp),dimension(:,:,:),intent(inout) :: scalar
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp) :: start
+ integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
+ start = MPI_WTIME()
+ call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
+!! print *, "c2r time : ", MPI_WTIME() -start
+ ! copy back to velocity and normalisation
+ do k =1, local_resolution(c_Z)
+ kg = k + ghosts(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ scalar(ig,jg,kg) = rdatain1(i,j,k)*normFFT
+ end do
+ end do
+ end do
+
+ end subroutine c2r_scalar_3d
+
+ !========================================================================
+ ! Real to complex transforms based on "many" fftw routines
+ !========================================================================
+
+ !> Initialisation of the fftw context for real to complex transforms (forward and backward)
+ !! @param[in] resolution global domain resolution
+ !! @param[in] lengths width of each side of the domain
+ subroutine init_r2c_3d_many(resolution,lengths)
+
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
+ !! Size of the local memory required for fftw (cbuffer)
+ integer(C_INTPTR_T) :: alloc_local,halfLength,howmany, blocksize
+ integer(C_INTPTR_T),dimension(3) :: n
+
+ ! init fftw mpi context
+ call fftw_mpi_init()
+ blocksize = FFTW_MPI_DEFAULT_BLOCK
+ if(rank==0) open(unit=21,file=filename,form="formatted")
+ allocate(fft_resolution(3))
+ fft_resolution(:) = resolution(:)-1
+ halfLength = fft_resolution(c_X)/2+1
+ n(1) = fft_resolution(c_Z)
+ n(2) = fft_resolution(c_Y)
+ n(3) = halfLength
+ howmany = 3
+ ! compute "optimal" size (according to fftw) for local data (warning : dimension reversal)
+ alloc_local = fftw_mpi_local_size_many_transposed(3,n,howmany,blocksize,blocksize,&
+ main_comm,local_resolution(c_Z),local_offset(c_Z),local_resolution(c_Y),local_offset(c_Y));
+
+ ! init c_X part. This is required to compute kx with the same function in 2d and 3d cases.
+ local_offset(c_X) = 0
+ local_resolution(c_X) = halfLength
+
+ ! allocate local buffer (used to save datain/dataout ==> in-place transform!!)
+ cbuffer1 = fftw_alloc_complex(alloc_local)
+
+ ! link rdatain and dataout to cbuffer, setting the right dimensions for each
+ call c_f_pointer(cbuffer1, rdatain_many, [howmany,2*halfLength,fft_resolution(c_Y),local_resolution(c_Z)])
+ call c_f_pointer(cbuffer1, dataout_many, [howmany,halfLength, fft_resolution(c_Z), local_resolution(c_Y)])
+
+ ! create MPI plans for in-place forward/backward DFT (note dimension reversal)
+ n(3) = fft_resolution(c_X)
+
+ plan_forward1 = fftw_mpi_plan_many_dft_r2c(3,n,howmany,blocksize,blocksize, rdatain_many, dataout_many, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_OUT))
+ plan_backward1 = fftw_mpi_plan_many_dft_c2r(3,n,howmany,blocksize,blocksize, dataout_many, rdatain_many, &
+ main_comm,ior(FFTW_MEASURE,FFTW_MPI_TRANSPOSED_IN))
+ call computeKx(lengths(c_X))
+ call computeKy(lengths(c_Y))
+ call computeKz(lengths(c_Z))
+
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ !! call fft3d_diagnostics(alloc_local,1)
+ manycase = .true.
+
+ is3DUpToDate = .true.
+
+ end subroutine init_r2c_3d_many
+
+ !> forward transform - The result is saved in local buffers
+ !! @param[in] omega_x 3d scalar field, x-component of the input vector field
+ !! @param[in] omega_y 3d scalar field, y-component of the input vector field
+ !! @param[in] omega_z 3d scalar field, z-component of the input vector field
+ !! @param input data
+ subroutine r2c_3d_many(omega_x,omega_y,omega_z)
+
+ real(wp),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
+ real(wp) :: start
+ integer(C_INTPTR_T) :: i,j,k
+
+ ! init
+ do k =1, local_resolution(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ do i = 1, fft_resolution(c_X)
+ rdatain_many(1,i,j,k) = omega_x(i,j,k)
+ rdatain_many(2,i,j,k) = omega_y(i,j,k)
+ rdatain_many(3,i,j,k) = omega_z(i,j,k)
+ end do
+ end do
+ end do
+
+ ! compute transform (as many times as desired)
+ start = MPI_WTIME()
+ call fftw_mpi_execute_dft_r2c(plan_forward1, rdatain_many, dataout_many)
+!! print *, "r2c time = ", MPI_WTIME() - start
+
+ end subroutine r2c_3d_many
+
+ !> Backward fftw transform
+ !! @param[in,out] velocity_x 3d scalar field, x-component of the output vector field
+ !! @param[in,out] velocity_y 3d scalar field, y-component of the output vector field
+ !! @param[in,out] velocity_z 3d scalar field, z-component of the output vector field
+ subroutine c2r_3d_many(velocity_x,velocity_y,velocity_z)
+ real(wp),dimension(:,:,:),intent(inout) :: velocity_x,velocity_y,velocity_z
+ real(wp) :: start
+ integer(C_INTPTR_T) :: i,j,k
+
+ start = MPI_WTIME()
+ call fftw_mpi_execute_dft_c2r(plan_backward1,dataout_many,rdatain_many)
+!! print *, "c2r time : ", MPI_WTIME() -start
+ do k =1, local_resolution(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ do i = 1, fft_resolution(c_X)
+ velocity_x(i,j,k) = rdatain_many(1,i,j,k)*normFFT
+ velocity_y(i,j,k) = rdatain_many(2,i,j,k)*normFFT
+ velocity_z(i,j,k) = rdatain_many(2,i,j,k)*normFFT
+ end do
+ end do
+ end do
+
+ end subroutine c2r_3d_many
+
+ !========================================================================
+ ! Common (r2c, c2c) subroutines
+ !========================================================================
+
+ !> Computation of frequencies coeff, over the distributed direction in the real/complex case
+ !> @param lengths size of the domain
+ subroutine computeKx(length)
+
+ real(wp),intent(in) :: length
+
+ !! Local loops indices
+ integer(C_INTPTR_T) :: i
+
+ !! Compute filter coefficients
+ allocate(kx(local_resolution(c_X)))
+ do i = 1, fft_resolution(c_X)/2+1
+ kx(i) = 2.*pi/length*(i-1)
+ end do
+ !! write(*,'(a,i5,a,i5,i5)') '[',rank,'] kx size', size(kx),i
+ do i = fft_resolution(c_X)/2+2,local_resolution(c_X)
+ kx(i) = 2.*pi/length*(i-fft_resolution(c_X)-1)
+ end do
+ end subroutine computeKx
+
+ !> Computation of frequencies coeff, over distributed direction(s)
+ !> @param lengths size of the domain
+ subroutine computeKy(length)
+ real(C_DOUBLE), intent(in) :: length
+
+ !! Local loops indices
+ integer(C_INTPTR_T) :: i
+ allocate(ky(local_resolution(c_Y)))
+
+ !! y frequencies (distributed over proc)
+ !! If we deal with positive frequencies only
+ if(local_offset(c_Y)+local_resolution(c_Y) <= fft_resolution(c_Y)/2+1 ) then
+ do i = 1,local_resolution(c_Y)
+ ky(i) = 2.*pi/length*(local_offset(c_Y)+i-1)
+ end do
+ else
+ !! else if we deal with negative frequencies only
+ if(local_offset(c_Y)+1 > fft_resolution(c_Y)/2+1 ) then
+ do i = 1,local_resolution(c_Y)
+ ky(i) = 2.*pi/length*(local_offset(c_Y)+i-1-fft_resolution(c_Y))
+ end do
+ !! final case : start positive freq, end in negative ones
+ else
+ do i = local_offset(c_Y)+1, fft_resolution(c_Y)/2+1 !! global index
+ ky(i-local_offset(c_Y)) = 2.*pi/length*(i-1)
+ end do
+ do i = fft_resolution(c_Y)/2+2,local_resolution(c_Y)+local_offset(c_Y)
+ ky(i-local_offset(c_Y)) = 2.*pi/length*(i-1-fft_resolution(c_Y))
+ end do
+ end if
+ end if
+
+ end subroutine computeKy
+
+ !> Computation of frequencies coeff, over non-distributed direction(s)
+ !> @param length size of the domain
+ subroutine computeKz(length)
+ real(wp),intent(in) :: length
+
+ !! Local loops indices
+ integer(C_INTPTR_T) :: i
+ allocate(kz(fft_resolution(c_Z)))
+ do i = 1, fft_resolution(c_Z)/2+1
+ kz(i) = 2.*pi/length*(i-1)
+ end do
+ do i = fft_resolution(c_Z)/2+2,fft_resolution(c_Z)
+ kz(i) = 2.*pi/length*(i-fft_resolution(c_Z)-1)
+ end do
+
+ end subroutine computeKz
+
+ !> Solve Poisson problem in the Fourier space :
+ !! \f{eqnarray*} \Delta \psi &=& - \omega \\ v = \nabla\times\psi \f}
+ subroutine filter_poisson_3d()
+
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+ complex(C_DOUBLE_COMPLEX) :: buffer1,buffer2
+
+ ! Set first coeff (check for "all freq = 0" case)
+ if(local_offset(c_Y) == 0) then
+ dataout1(1,1,1) = 0.0
+ dataout2(1,1,1) = 0.0
+ dataout3(1,1,1) = 0.0
+ else
+ coeff = Icmplx/(ky(1)**2)
+ buffer1 = dataout1(1,1,1)
+ dataout1(1,1,1) = coeff*ky(1)*dataout3(1,1,1)
+ dataout2(1,1,1) = 0.0
+ dataout3(1,1,1) = -coeff*ky(1)*buffer1
+ endif
+
+ ! !! mind the transpose -> index inversion between y and z
+ do i = 2, local_resolution(c_X)
+ coeff = Icmplx/(kx(i)**2+ky(1)**2)
+ buffer1 = dataout1(i,1,1)
+ buffer2 = dataout2(i,1,1)
+ dataout1(i,1,1) = coeff*ky(1)*dataout3(i,1,1)
+ dataout2(i,1,1) = -coeff*kx(i)*dataout3(i,1,1)
+ dataout3(i,1,1) = coeff*(kx(i)*buffer2-ky(1)*buffer1)
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do k = 2, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx/(kx(i)**2+ky(1)**2+kz(k)**2)
+ buffer1 = dataout1(i,k,1)
+ buffer2 = dataout2(i,k,1)
+ dataout1(i,k,1) = coeff*(ky(1)*dataout3(i,k,1)-kz(k)*dataout2(i,k,1))
+ dataout2(i,k,1) = coeff*(kz(k)*buffer1-kx(i)*dataout3(i,k,1))
+ dataout3(i,k,1) = coeff*(kx(i)*buffer2-ky(1)*buffer1)
+ end do
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do j = 2,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx/(kx(i)**2+ky(j)**2+kz(k)**2)
+ buffer1 = dataout1(i,k,j)
+ buffer2 = dataout2(i,k,j)
+ dataout1(i,k,j) = coeff*(ky(j)*dataout3(i,k,j)-kz(k)*dataout2(i,k,j))
+ dataout2(i,k,j) = coeff*(kz(k)*buffer1-kx(i)*dataout3(i,k,j))
+ dataout3(i,k,j) = coeff*(kx(i)*buffer2-ky(j)*buffer1)
+ end do
+ end do
+ end do
+
+ end subroutine filter_poisson_3d
+
+ !> Solve diffusion problem in the Fourier space :
+ !! \f{eqnarray*} \omega &=& \nabla \times v \\ \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
+ !! @param[in] nudt \f$ \nu\times dt\f$, diffusion coefficient times current time step
+ subroutine filter_curl_diffusion_3d(nudt)
+
+ real(C_DOUBLE), intent(in) :: nudt
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+ complex(C_DOUBLE_COMPLEX) :: buffer1,buffer2
+
+ !! mind the transpose -> index inversion between y and z
+ do j = 1,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx/(one + nudt * (kx(i)**2+ky(j)**2+kz(k)**2))
+ buffer1 = dataout1(i,k,j)
+ buffer2 = dataout2(i,k,j)
+ dataout1(i,k,j) = coeff*(ky(j)*dataout3(i,k,j)-kz(k)*dataout2(i,k,j))
+ dataout2(i,k,j) = coeff*(kz(k)*buffer1-kx(i)*dataout3(i,k,j))
+ dataout3(i,k,j) = coeff*(kx(i)*buffer2-ky(j)*buffer1)
+ end do
+ end do
+ end do
+
+ end subroutine filter_curl_diffusion_3d
+
+ !> Solve diffusion problem in the Fourier space :
+ !! \f{eqnarray*} \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
+ !! @param[in] nudt \f$ \nu\times dt\f$, diffusion coefficient times current time step
+ subroutine filter_diffusion_3d(nudt)
+
+ real(C_DOUBLE), intent(in) :: nudt
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+
+ !! mind the transpose -> index inversion between y and z
+ do j = 1,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = one/(one + nudt * (kx(i)**2+ky(j)**2+kz(k)**2))
+ dataout1(i,k,j) = coeff*dataout1(i,k,j)
+ dataout2(i,k,j) = coeff*dataout2(i,k,j)
+ dataout3(i,k,j) = coeff*dataout3(i,k,j)
+ end do
+ end do
+ end do
+
+ end subroutine filter_diffusion_3d
+
+ !> Solve curl problem in the Fourier space :
+ !! \f{eqnarray*} \omega &=& \nabla \times v
+ subroutine filter_curl_3d()
+
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+ complex(C_DOUBLE_COMPLEX) :: buffer1,buffer2
+
+ !! mind the transpose -> index inversion between y and z
+ do j = 1,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx
+ buffer1 = dataout1(i,k,j)
+ buffer2 = dataout2(i,k,j)
+ dataout1(i,k,j) = coeff*(ky(j)*dataout3(i,k,j)-kz(k)*dataout2(i,k,j))
+ dataout2(i,k,j) = coeff*(kz(k)*buffer1-kx(i)*dataout3(i,k,j))
+ dataout3(i,k,j) = coeff*(kx(i)*buffer2-ky(j)*buffer1)
+ end do
+ end do
+ end do
+
+ end subroutine filter_curl_3d
+
+ !> Perform solenoidal projection to ensure divergence free vorticity field
+ !! \f{eqnarray*} \omega ' &=& \omega - \nabla\pi \f}
+ subroutine filter_projection_om_3d()
+
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+ complex(C_DOUBLE_COMPLEX) :: buffer1,buffer2,buffer3
+
+ ! Set first coeff (check for "all freq = 0" case)
+ if(local_offset(c_Y) == 0) then
+ dataout1(1,1,1) = dataout1(1,1,1)
+ dataout2(1,1,1) = dataout2(1,1,1)
+ dataout3(1,1,1) = dataout3(1,1,1)
+ else
+ coeff = one/(ky(1)**2)
+ buffer2 = dataout2(1,1,1)
+ dataout1(1,1,1) = dataout1(1,1,1)
+ dataout2(1,1,1) = dataout2(1,1,1) - coeff*ky(1)*(ky(1)*buffer2)
+ dataout3(1,1,1) = dataout3(1,1,1)
+ endif
+
+ ! !! mind the transpose -> index inversion between y and z
+ do i = 2, local_resolution(c_X)
+ coeff = one/(kx(i)**2+ky(1)**2+kz(1)**2)
+ buffer1 = dataout1(i,1,1)
+ buffer2 = dataout2(i,1,1)
+ buffer3 = dataout3(i,1,1)
+ dataout1(i,1,1) = dataout1(i,1,1) - coeff*kx(i)*(kx(i)*buffer1+ky(1)*buffer2+kz(1)*buffer3)
+ dataout2(i,1,1) = dataout2(i,1,1) - coeff*ky(1)*(kx(i)*buffer1+ky(1)*buffer2+kz(1)*buffer3)
+ dataout3(i,1,1) = dataout3(i,1,1) - coeff*kz(1)*(kx(i)*buffer1+ky(1)*buffer2+kz(1)*buffer3)
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do k = 2, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = one/(kx(i)**2+ky(1)**2+kz(k)**2)
+ buffer1 = dataout1(i,k,1)
+ buffer2 = dataout2(i,k,1)
+ buffer3 = dataout3(i,k,1)
+ dataout1(i,k,1) = dataout1(i,k,1) - coeff*kx(i)*(kx(i)*buffer1+ky(1)*buffer2+kz(k)*buffer3)
+ dataout2(i,k,1) = dataout2(i,k,1) - coeff*ky(1)*(kx(i)*buffer1+ky(1)*buffer2+kz(k)*buffer3)
+ dataout3(i,k,1) = dataout3(i,k,1) - coeff*kz(k)*(kx(i)*buffer1+ky(1)*buffer2+kz(k)*buffer3)
+ end do
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do j = 2,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = one/(kx(i)**2+ky(j)**2+kz(k)**2)
+ buffer1 = dataout1(i,k,j)
+ buffer2 = dataout2(i,k,j)
+ buffer3 = dataout3(i,k,j)
+ dataout1(i,k,j) = dataout1(i,k,j) - coeff*kx(i)*(kx(i)*buffer1+ky(j)*buffer2+kz(k)*buffer3)
+ dataout2(i,k,j) = dataout2(i,k,j) - coeff*ky(j)*(kx(i)*buffer1+ky(j)*buffer2+kz(k)*buffer3)
+ dataout3(i,k,j) = dataout3(i,k,j) - coeff*kz(k)*(kx(i)*buffer1+ky(j)*buffer2+kz(k)*buffer3)
+ end do
+ end do
+ end do
+
+ end subroutine filter_projection_om_3d
+
+ !> Projects vorticity values from fine to coarse grid :
+ !> the smallest modes of vorticity are nullified
+ !! @param[in] dxf, dyf, dzf: grid filter size = domainLength/(CoarseRes-1)
+ subroutine filter_multires_om_3d(dxf, dyf, dzf)
+
+ real(C_DOUBLE), intent(in) :: dxf, dyf, dzf
+ integer(C_INTPTR_T) :: i,j,k
+ real(C_DOUBLE) :: kxc, kyc, kzc
+
+ kxc = pi / dxf
+ kyc = pi / dyf
+ kzc = pi / dzf
+
+ !! mind the transpose -> index inversion between y and z
+ do j = 2,local_resolution(c_Y)
+ do k = 2, fft_resolution(c_Z)
+ do i = 2, local_resolution(c_X)
+ if ((abs(kx(i))>kxc) .and. (abs(ky(j))>kyc) .and. (abs(kz(k))>kzc)) then
+ dataout1(i,k,j) = 0.
+ dataout2(i,k,j) = 0.
+ dataout3(i,k,j) = 0.
+ endif
+ end do
+ end do
+ end do
+
+ end subroutine filter_multires_om_3d
+
+ !> Solve the Poisson problem allowing to recover
+ !! pressure from velocity in the Fourier space
+ subroutine filter_pressure_3d()
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+
+ ! Set first coeff (check for "all freq = 0" case)
+ if(local_offset(c_Y) == 0) then
+ dataout1(1,1,1) = 0.0
+ else
+ coeff = -one/(ky(1)**2)
+ dataout1(1,1,1) = coeff*dataout1(1,1,1)
+ endif
+
+ ! !! mind the transpose -> index inversion between y and z
+ do i = 2, local_resolution(c_X)
+ coeff = -one/(kx(i)**2+ky(1)**2)
+ dataout1(i,1,1) = coeff*dataout1(i,1,1)
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do k = 2, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = -one/(kx(i)**2+ky(1)**2+kz(k)**2)
+ dataout1(i,k,1) = coeff*dataout1(i,k,1)
+ end do
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do j = 2,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = -one/(kx(i)**2+ky(j)**2+kz(k)**2)
+ dataout1(i,k,j) = coeff*dataout1(i,k,j)
+ end do
+ end do
+ end do
+ end subroutine filter_pressure_3d
+
+ !> Solve Poisson problem in the Fourier space :
+ !! \f{eqnarray*} \Delta \psi &=& - \omega \\ v &=& \nabla\times\psi \f}
+ subroutine filter_poisson_3d_many()
+
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+ complex(C_DOUBLE_COMPLEX) :: buffer1,buffer2
+
+ ! Set first coeff (check for "all freq = 0" case)
+ if(local_offset(c_Y) == 0) then
+ dataout_many(:,1,1,1) = 0.0
+ else
+ coeff = Icmplx/(ky(1)**2)
+ buffer1 = dataout_many(1,1,1,1)
+ dataout_many(1,1,1,1) = coeff*ky(1)*dataout_many(3,1,1,1)
+ dataout_many(2,1,1,1) = 0.0
+ dataout_many(3,1,1,1) = -coeff*ky(1)*buffer1
+ endif
+
+ ! !! mind the transpose -> index inversion between y and z
+ do i = 2, local_resolution(c_X)
+ coeff = Icmplx/(kx(i)**2+ky(1)**2)
+ buffer1 = dataout_many(1,i,1,1)
+ buffer2 = dataout_many(2,i,1,1)
+ dataout_many(1,i,1,1) = coeff*ky(1)*dataout_many(3,i,1,1)
+ dataout_many(2,i,1,1) = -coeff*kx(i)*dataout_many(3,i,1,1)
+ dataout_many(3,i,1,1) = coeff*(kx(i)*buffer2-ky(1)*buffer1)
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do k = 2, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx/(kx(i)**2+ky(1)**2+kz(k)**2)
+ buffer1 = dataout_many(1,i,k,1)
+ buffer2 = dataout_many(2,i,k,1)
+ dataout_many(1,i,k,1) = coeff*(ky(1)*dataout_many(3,i,k,1)-kz(k)*dataout_many(2,i,k,1))
+ dataout_many(2,i,k,1) = coeff*(kz(k)*buffer1-kx(i)*dataout_many(3,i,k,1))
+ dataout_many(3,i,k,1) = coeff*(kx(i)*buffer2-ky(1)*buffer1)
+ end do
+ end do
+
+ ! !! mind the transpose -> index inversion between y and z
+ do j = 2,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx/(kx(i)**2+ky(j)**2+kz(k)**2)
+ buffer1 = dataout_many(1,i,k,j)
+ buffer2 = dataout_many(2,i,k,j)
+ dataout_many(1,i,k,j) = coeff*(ky(j)*dataout_many(3,i,k,j)-kz(k)*dataout_many(2,i,k,j))
+ dataout_many(2,i,k,j) = coeff*(kz(k)*buffer1-kx(i)*dataout_many(3,i,k,j))
+ dataout_many(3,i,k,j) = coeff*(kx(i)*buffer2-ky(j)*buffer1)
+ end do
+ end do
+ end do
+
+ end subroutine filter_poisson_3d_many
+
+ !> Solve diffusion problem in the Fourier space :
+ !! \f{eqnarray*} \omega &=& \nabla \times v \\ \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
+ !! @param[in] nudt \f$ \nu\times dt\f$, diffusion coefficient times current time step
+ subroutine filter_diffusion_3d_many(nudt)
+
+ real(C_DOUBLE), intent(in) :: nudt
+ integer(C_INTPTR_T) :: i,j,k
+ complex(C_DOUBLE_COMPLEX) :: coeff
+ complex(C_DOUBLE_COMPLEX) :: buffer1,buffer2
+
+ !! mind the transpose -> index inversion between y and z
+ do j = 1,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ coeff = Icmplx/(one + nudt * kx(i)**2+ky(j)**2+kz(k)**2)
+ buffer1 = dataout_many(1,i,k,j)
+ buffer2 = dataout_many(2,i,k,j)
+ dataout_many(1,i,k,j) = coeff*(ky(j)*dataout_many(3,i,k,j)-kz(k)*dataout_many(2,i,k,j))
+ dataout_many(2,i,k,j) = coeff*(kz(k)*buffer1-kx(i)*dataout_many(3,i,k,j))
+ dataout_many(3,i,k,j) = coeff*(kx(i)*buffer2-ky(j)*buffer1)
+ end do
+ end do
+ end do
+
+ end subroutine filter_diffusion_3d_many
+
+ !> Clean fftw context (free memory, plans ...)
+ subroutine cleanFFTW_3d()
+ is3DUpToDate = .false.
+ call fftw_destroy_plan(plan_forward1)
+ call fftw_destroy_plan(plan_backward1)
+ if(.not.manycase) then
+ call fftw_destroy_plan(plan_forward2)
+ call fftw_destroy_plan(plan_backward2)
+ call fftw_destroy_plan(plan_forward3)
+ call fftw_destroy_plan(plan_backward3)
+ call fftw_free(cbuffer2)
+ call fftw_free(cbuffer3)
+ endif
+ call fftw_free(cbuffer1)
+ call fftw_mpi_cleanup()
+ deallocate(fft_resolution)
+ deallocate(kx,ky,kz)
+ if(rank==0) close(21)
+ end subroutine cleanFFTW_3d
+
+ !> some information about memory alloc, arrays sizes and so on
+ subroutine fft3d_diagnostics(nbelem,howmany)
+ integer(C_INTPTR_T), intent(in) :: nbelem
+ ! number of buffers used for fftw
+ integer, optional,intent(in) :: howmany
+ complex(C_DOUBLE_COMPLEX) :: memoryAllocated
+
+ integer :: nbFields
+ if(present(howmany)) then
+ nbFields = howmany
+ else
+ nbFields = 3
+ end if
+ memoryAllocated = real(nbelem*sizeof(memoryAllocated),wp)*1e-6
+ write(*,'(a,i5,a,i12,f10.2)') '[',rank,'] size of each buffer (elements / memory in MB):', &
+ nbelem, memoryAllocated
+ write(*,'(a,i5,a,3i12)') '[',rank,'] size of kx,y,z vectors (number of elements):', &
+ size(kx), size(ky),size(kz)
+ write(*,'(a,i5,a,6i5)') '[',rank,'] local resolution and offset :', local_resolution, local_offset
+ memoryAllocated = nbFields*memoryAllocated + real(sizeof(kx) + sizeof(ky) + sizeof(kz), wp)*1e-6
+ write(*,'(a,i5,a,f10.2)') '[',rank,'] Total memory used for fftw buffers (MB):', memoryAllocated
+
+ end subroutine fft3d_diagnostics
+
+ !> Get local size of input and output field on fftw topology
+ !! @param datashape local shape of the input field for the fftw process
+ !! @param offset index of the first component of the local field (in each dir) in the global set of indices
+ subroutine getParamatersTopologyFFTW3d(datashape,offset)
+ integer(kind=ip), intent(out),dimension(3) :: datashape
+ integer(kind=ip), intent(out),dimension(3) :: offset
+ integer(C_INTPTR_T) :: i_zero = 0
+ datashape = (/fft_resolution(c_X), fft_resolution(c_Y), local_resolution(c_Z)/)
+ offset = (/i_zero, i_zero, local_offset(c_Z)/)
+ end subroutine getParamatersTopologyFFTW3d
+
+ !> forward transform - The result is saved in local buffers
+ !! @param[in] field 3d scalar field, x-component of the input vector field
+ !! @param[in] ghosts, number of points in the ghost layer of input fields.
+ subroutine r2c_3d_scal(field, ghosts)
+
+ real(wp),dimension(:,:,:),intent(in) :: field
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ !real(8) :: start
+ integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
+
+ ! ig, jg, kg are used to take into account
+ ! ghost points in input fields
+ ! init
+ do k =1, local_resolution(c_Z)
+ kg = k + ghosts(c_Z)
+ do j = 1, fft_resolution(c_Y)
+ jg = j + ghosts(c_Y)
+ do i = 1, fft_resolution(c_X)
+ ig = i + ghosts(c_X)
+ rdatain1(i,j,k) = field(ig,jg,kg)
+ end do
+ end do
+ end do
+
+ ! compute transforms for each component
+ !start = MPI_WTIME()
+ call fftw_mpi_execute_dft_r2c(plan_forward1, rdatain1, dataout1)
+ !!print *, "r2c time = ", MPI_WTIME() - start
+
+ end subroutine r2c_3d_scal
+
+ !> Compute spectrum of the given data
+ subroutine filter_spectrum_3d(spectrum,wavelengths,length)
+
+ real(wp),dimension(:),intent(inout) :: spectrum
+ real(wp),dimension(:),intent(inout) :: wavelengths
+ real(wp),intent(in) :: length
+ integer(C_INTPTR_T) :: i,j,k
+ real(wp) :: c
+ real(wp) :: kk,dk,kc,eps
+ integer(C_INTPTR_T) :: indk
+ spectrum = 0
+ dk = 2.0_wp*pi/length
+ kc = pi*fft_resolution(c_X)/length
+ eps=kc/1000000.0_wp
+
+ !! mind the transpose -> index inversion between y and z
+ c = one/real(fft_resolution(c_Z)*fft_resolution(c_Y)*fft_resolution(c_X),wp)
+ c = c * c
+ do j = 1,local_resolution(c_Y)
+ do k = 1, fft_resolution(c_Z)
+ do i = 1, local_resolution(c_X)
+ kk=sqrt(kx(i)**2+ky(j)**2+kz(k)**2)
+ if ((kk.gt.eps).and.(kk.le.kc)) then
+ indk=1+int(kk/dk+0.5_wp)
+ spectrum(indk) = spectrum(indk) + real(dataout1(i,j,k)*conjg(dataout1(i,j,k)), wp) * c
+ end if
+ end do
+ end do
+ end do
+ wavelengths(:) = kx
+
+ end subroutine filter_spectrum_3d
+
+end module fft3d
diff --git a/hysop/f2py/fftw2py.f90 b/hysop/numerics/fftw_f/fftw2py.f90
similarity index 77%
rename from hysop/f2py/fftw2py.f90
rename to hysop/numerics/fftw_f/fftw2py.f90
index 040262cf56905fa2a4f1d992d32de0deb5b1e78b..09517a4ca3034a9800a76e99c94ff9656963e2a9 100755
--- a/hysop/f2py/fftw2py.f90
+++ b/hysop/numerics/fftw_f/fftw2py.f90
@@ -4,17 +4,18 @@
!> Interface to mpi-fftw (fortran) utilities
module fftw2py
- use client_data
- use hysopparam
+ use precision
+ use parameters
!> 2d case
- use fft2d
+ use fft2d
!> 3d case
use fft3d
- use mpi
+ use, intrinsic :: iso_c_binding
+ use mpi, only : mpi_comm_dup, mpi_wtime
implicit none
contains
-
+
!> Initialisation of fftw context : create plans and memory buffers
!! @param[in] resolution global resolution of the discrete domain
!! @param[in] lengths width of each side of the domain
@@ -24,10 +25,10 @@ contains
subroutine init_fftw_solver(resolution,lengths,comm,datashape,offset,dim,fftw_type_real)
integer, intent(in) :: dim
- integer, dimension(dim),intent(in) :: resolution
- real(pk),dimension(dim), intent(in) :: lengths
- integer(ik), dimension(dim), intent(out) :: datashape
- integer(ik), dimension(dim), intent(out) :: offset
+ integer(kind=ip), dimension(dim),intent(in) :: resolution
+ real(wp),dimension(dim), intent(in) :: lengths
+ integer(kind=ip), dimension(dim), intent(out) :: datashape
+ integer(kind=ip), dimension(dim), intent(out) :: offset
integer, intent(in) :: comm
logical, optional :: fftw_type_real
!f2py optional :: dim=len(resolution)
@@ -74,10 +75,10 @@ contains
subroutine init_fftw_solver_scalar(resolution,lengths,comm,datashape,offset,dim,fftw_type_real)
integer, intent(in) :: dim
- integer, dimension(dim),intent(in) :: resolution
- real(pk),dimension(dim), intent(in) :: lengths
- integer(ik), dimension(dim), intent(out) :: datashape
- integer(ik), dimension(dim), intent(out) :: offset
+ integer(kind=ip), dimension(dim),intent(in) :: resolution
+ real(wp),dimension(dim), intent(in) :: lengths
+ integer(kind=ip), dimension(dim), intent(out) :: datashape
+ integer(kind=ip), dimension(dim), intent(out) :: offset
integer, intent(in) :: comm
logical, optional :: fftw_type_real
!f2py optional :: dim=len(resolution)
@@ -111,9 +112,9 @@ contains
!! \f[ \nabla (\nabla \times velocity) = - \omega \f]
!! velocity being a 2D vector field and omega a 2D scalar field.
subroutine solve_poisson_2d(omega,velocity_x,velocity_y, ghosts_vort, ghosts_velo)
- real(pk),dimension(:,:),intent(in):: omega
- real(pk),dimension(size(omega,1),size(omega,2)),intent(out) :: velocity_x,velocity_y
- integer, dimension(2), intent(in) :: ghosts_vort, ghosts_velo
+ real(wp),dimension(:,:),intent(in):: omega
+ real(wp),dimension(size(omega,1),size(omega,2)),intent(out) :: velocity_x,velocity_y
+ integer(kind=ip), dimension(2), intent(in) :: ghosts_vort, ghosts_velo
!f2py intent(in,out) :: velocity_x,velocity_y
call r2c_scalar_2d(omega, ghosts_vort)
@@ -129,9 +130,9 @@ contains
!! \f{eqnarray*} \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
!! omega being a 2D scalar field.
subroutine solve_diffusion_2d(nudt, omega, ghosts_vort)
- real(pk), intent(in) :: nudt
- real(pk),dimension(:,:),intent(inout):: omega
- integer, dimension(2), intent(in) :: ghosts_vort
+ real(wp), intent(in) :: nudt
+ real(wp),dimension(:,:),intent(inout):: omega
+ integer(kind=ip), dimension(2), intent(in) :: ghosts_vort
!f2py intent(in,out) :: omega
call r2c_scalar_2d(omega, ghosts_vort)
@@ -146,10 +147,10 @@ contains
!! \f{eqnarray*} \Delta \psi &=& - \omega \\ velocity = \nabla\times\psi \f}
!! velocity and omega being 3D vector fields.
subroutine solve_poisson_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z, ghosts_vort, ghosts_velo)
- real(pk),dimension(:,:,:),intent(in):: omega_x,omega_y,omega_z
- real(pk),dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(out) :: velocity_x,velocity_y,velocity_z
- integer, dimension(3), intent(in) :: ghosts_vort, ghosts_velo
- real(pk) :: start
+ real(wp),dimension(:,:,:),intent(in):: omega_x,omega_y,omega_z
+ real(wp),dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(out) :: velocity_x,velocity_y,velocity_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts_vort, ghosts_velo
+ real(wp) :: start
!f2py intent(in,out) :: velocity_x,velocity_y,velocity_z
start = MPI_WTime()
call r2c_3d(omega_x,omega_y,omega_z, ghosts_vort)
@@ -165,8 +166,8 @@ contains
!! \f{eqnarray*} \Delta \psi &=& - \omega \\ velocity = \nabla\times\psi \f}
!! velocity being a 2D complex vector field and omega a 2D complex scalar field.
subroutine solve_poisson_2d_c(omega,velocity_x,velocity_y)
- complex(pk),dimension(:,:),intent(in):: omega
- complex(pk),dimension(size(omega,1),size(omega,2)),intent(out) :: velocity_x,velocity_y
+ complex(wp),dimension(:,:),intent(in):: omega
+ complex(wp),dimension(size(omega,1),size(omega,2)),intent(out) :: velocity_x,velocity_y
!f2py intent(in,out) :: velocity_x,velocity_y
call c2c_2d(omega,velocity_x,velocity_y)
@@ -177,8 +178,8 @@ contains
!! \f{eqnarray*} \Delta \psi &=& - \omega \\ velocity = \nabla\times\psi \f}
!! velocity and omega being 3D complex vector fields.
subroutine solve_poisson_3d_c(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_Z)
- complex(pk),dimension(:,:,:),intent(in):: omega_x,omega_y,omega_z
- complex(pk),dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(out) :: velocity_x,velocity_y,velocity_z
+ complex(wp),dimension(:,:,:),intent(in):: omega_x,omega_y,omega_z
+ complex(wp),dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(out) :: velocity_x,velocity_y,velocity_z
!f2py intent(in,out) :: velocity_x,velocity_y,velocity_z
call c2c_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z)
@@ -189,10 +190,10 @@ contains
!! \f{eqnarray*} \omega &=& \nabla \times v \\ \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
!! velocity and omega being 3D vector fields.
subroutine solve_curl_diffusion_3d(nudt,velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z, ghosts_velo, ghosts_vort)
- real(pk), intent(in) :: nudt
- real(pk),dimension(:,:,:),intent(in):: velocity_x,velocity_y,velocity_z
- real(pk),dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(out) :: omega_x,omega_y,omega_z
- integer, dimension(3), intent(in) :: ghosts_vort, ghosts_velo
+ real(wp), intent(in) :: nudt
+ real(wp),dimension(:,:,:),intent(in):: velocity_x,velocity_y,velocity_z
+ real(wp),dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(out) :: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts_vort, ghosts_velo
!f2py intent(in,out) :: omega_x,omega_y,omega_z
call r2c_3d(velocity_x,velocity_y,velocity_z, ghosts_velo)
@@ -207,9 +208,9 @@ contains
!! \f{eqnarray*} \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
!! omega being 3D vector field.
subroutine solve_diffusion_3d(nudt,omega_x,omega_y,omega_z, ghosts)
- real(pk), intent(in) :: nudt
- real(pk),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
- integer, dimension(3), intent(in) :: ghosts
+ real(wp), intent(in) :: nudt
+ real(wp),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
!f2py intent(in,out) :: omega_x,omega_y,omega_z
call r2c_3d(omega_x,omega_y,omega_z, ghosts)
@@ -224,8 +225,8 @@ contains
!! \f{eqnarray*} \omega ' &=& \omega - \nabla\pi \f}
!! omega being a 3D vector field.
subroutine projection_om_3d(omega_x,omega_y,omega_z, ghosts)
- real(pk),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
- integer, dimension(3), intent(in) :: ghosts
+ real(wp),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
!f2py intent(in,out) :: omega_x,omega_y,omega_z
call r2c_3d(omega_x,omega_y,omega_z, ghosts)
@@ -240,9 +241,9 @@ contains
!! @param[in] dxf, dyf, dzf: grid filter size = domainLength/(CoarseRes-1)
!! in the following, omega is the 3D vorticity vector field.
subroutine multires_om_3d(dxf, dyf, dzf, omega_x,omega_y,omega_z, ghosts)
- real(pk), intent(in) :: dxf, dyf, dzf
- real(pk),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
- integer, dimension(3), intent(in) :: ghosts
+ real(wp), intent(in) :: dxf, dyf, dzf
+ real(wp),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
!f2py intent(in,out) :: omega_x,omega_y,omega_z
@@ -260,8 +261,8 @@ contains
!! @param[in, out] pressure
!! in the following, pressure is used as inout parameter. It must contains the rhs of poisson equation.
subroutine pressure_3d(pressure, ghosts)
- integer, dimension(3), intent(in) :: ghosts
- real(pk),dimension(:,:,:),intent(inout):: pressure
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp),dimension(:,:,:),intent(inout):: pressure
!f2py intent(in,out) :: pressure
call r2c_scalar_3d(pressure, ghosts)
@@ -276,9 +277,9 @@ contains
!! \f{eqnarray*} \omega &=& \nabla \times v
!! velocity and omega being 3D vector fields.
subroutine solve_curl_3d(velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z, ghosts_velo, ghosts_vort)
- real(pk),dimension(:,:,:),intent(in):: velocity_x,velocity_y,velocity_z
- real(pk),dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(out) :: omega_x,omega_y,omega_z
- integer, dimension(3), intent(in) :: ghosts_velo, ghosts_vort
+ real(wp),dimension(:,:,:),intent(in):: velocity_x,velocity_y,velocity_z
+ real(wp),dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(out) :: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts_velo, ghosts_vort
!f2py intent(in,out) :: omega_x,omega_y,omega_z
call r2c_3d(velocity_x,velocity_y,velocity_z, ghosts_velo)
@@ -294,9 +295,9 @@ contains
!! \f{eqnarray*} \omega &=& \nabla \times v
!! velocity and omega being 2D vector and scalar fields.
subroutine solve_curl_2d(velocity_x,velocity_y, omega_z, ghosts_velo, ghosts_vort)
- real(pk), dimension(:,:), intent(in):: velocity_x,velocity_y
- real(pk), dimension(size(velocity_x,1), size(velocity_x,2)), intent(out) :: omega_z
- integer, dimension(2), intent(in) :: ghosts_velo, ghosts_vort
+ real(wp), dimension(:,:), intent(in):: velocity_x,velocity_y
+ real(wp), dimension(size(velocity_x,1), size(velocity_x,2)), intent(out) :: omega_z
+ integer(kind=ip), dimension(2), intent(in) :: ghosts_velo, ghosts_vort
!f2py intent(in,out) :: omega_z
call r2c_2d(velocity_x,velocity_y, ghosts_velo)
@@ -311,11 +312,11 @@ contains
!! @param[in] field
!! @param[out] spectrum
subroutine spectrum_3d(field, spectrum, wavelengths, ghosts, length)
- real(pk),dimension(:,:,:),intent(in):: field
- integer, dimension(3), intent(in) :: ghosts
- real(pk),dimension(:), intent(inout) :: spectrum
- real(pk),dimension(:), intent(inout) :: wavelengths
- real(pk),intent(in) :: length
+ real(wp),dimension(:,:,:),intent(in):: field
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp),dimension(:), intent(inout) :: spectrum
+ real(wp),dimension(:), intent(inout) :: wavelengths
+ real(wp),intent(in) :: length
!f2py intent(in) :: field
!f2py intent(inout) :: spectrum
!f2py intent(inout) :: wavelengths
diff --git a/hysop/numerics/fftw_f/fftw2py.pyf b/hysop/numerics/fftw_f/fftw2py.pyf
new file mode 100644
index 0000000000000000000000000000000000000000..74ac41ee1c12458b18ea26880d940ab6f0a52d9f
--- /dev/null
+++ b/hysop/numerics/fftw_f/fftw2py.pyf
@@ -0,0 +1,131 @@
+! -*- f90 -*-
+! Note: the context of this file is case sensitive.
+
+module fftw2py ! in fftw2py.f90
+ use fft2d
+ use fft3d
+ use precision
+ use parameters
+ use mpi
+ subroutine init_fftw_solver(resolution,lengths,comm,datashape,offset,dim,fftw_type_real) ! in fftw2py.f90:fftw2py
+ integer(kind=ip), dimension(dim),intent(in) :: resolution
+ real(kind=wp) dimension(dim),intent(in),depend(dim) :: lengths
+ integer intent(in) :: comm
+ integer(kind=ip) dimension(dim),intent(out),depend(dim) :: datashape
+ integer(kind=ip) dimension(dim),intent(out),depend(dim) :: offset
+ integer, optional,intent(hide), depend(resolution) :: dim=len(resolution)
+ logical, optional,intent(in) :: fftw_type_real=1
+ end subroutine init_fftw_solver
+ subroutine init_fftw_solver_scalar(resolution,lengths,comm,datashape,offset,dim,fftw_type_real) ! in fftw2py.f90:fftw2py
+ integer(kind=ip) dimension(dim),intent(in) :: resolution
+ real(kind=wp) dimension(dim),intent(in),depend(dim) :: lengths
+ integer intent(in) :: comm
+ integer(ip) dimension(dim),intent(out),depend(dim) :: datashape
+ integer(ip) dimension(dim),intent(out),depend(dim) :: offset
+ integer, optional,intent(hide), ,depend(resolution) :: dim=len(resolution)
+ logical, optional,intent(in) :: fftw_type_real=1
+ end subroutine init_fftw_solver_scalar
+ subroutine clean_fftw_solver(dim) ! in fftw2py.f90:fftw2py
+ integer intent(in) :: dim
+ end subroutine clean_fftw_solver
+ subroutine solve_poisson_2d(omega,velocity_x,velocity_y,ghosts_vort,ghosts_velo) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:),intent(in) :: omega
+ real(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_x
+ real(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_y
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_vort
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_velo
+ end subroutine solve_poisson_2d
+ subroutine solve_diffusion_2d(nudt,omega,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: nudt
+ real(kind=wp) dimension(:,:),intent(in,out) :: omega
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_vort
+ end subroutine solve_diffusion_2d
+ subroutine solve_poisson_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z,ghosts_vort,ghosts_velo) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in) :: omega_z
+ real(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_x
+ real(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_y
+ real(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_vort
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_velo
+ end subroutine solve_poisson_3d
+ subroutine solve_poisson_2d_c(omega,velocity_x,velocity_y) ! in fftw2py.f90:fftw2py
+ complex(kind=wp) dimension(:,:),intent(in) :: omega
+ complex(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_x
+ complex(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_y
+ end subroutine solve_poisson_2d_c
+ subroutine solve_poisson_3d_c(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z) ! in fftw2py.f90:fftw2py
+ complex(kind=wp) dimension(:,:,:),intent(in) :: omega_x
+ complex(kind=wp) dimension(:,:,:),intent(in) :: omega_y
+ complex(kind=wp) dimension(:,:,:),intent(in) :: omega_z
+ complex(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_x
+ complex(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_y
+ complex(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_z
+ end subroutine solve_poisson_3d_c
+ subroutine solve_curl_diffusion_3d(nudt,velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: nudt
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_x
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_y
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_z
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_x
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_y
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_velo
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_vort
+ end subroutine solve_curl_diffusion_3d
+ subroutine solve_diffusion_3d(nudt,omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: nudt
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine solve_diffusion_3d
+ subroutine projection_om_3d(omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine projection_om_3d
+ subroutine multires_om_3d(dxf,dyf,dzf,omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: dxf
+ real(kind=wp) intent(in) :: dyf
+ real(kind=wp) intent(in) :: dzf
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine multires_om_3d
+ subroutine pressure_3d(pressure,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: pressure
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine pressure_3d
+ subroutine solve_curl_3d(velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_x
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_y
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_z
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_x
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_y
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_velo
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_vort
+ end subroutine solve_curl_3d
+ subroutine solve_curl_2d(velocity_x,velocity_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:),intent(in) :: velocity_x
+ real(kind=wp) dimension(:,:),intent(in) :: velocity_y
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_x,2)),intent(in,out),depend(velocity_x,velocity_x) :: omega_z
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_velo
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_vort
+ end subroutine solve_curl_2d
+ subroutine spectrum_3d(field,spectrum,wavelengths,ghosts,length) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in) :: field
+ real(kind=wp) dimension(:),intent(in,out) :: spectrum
+ real(kind=wp) dimension(:),intent(in,out) :: wavelengths
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ real(kind=wp) intent(in) :: length
+ end subroutine spectrum_3d
+
+end module fftw2py
+
+! This file was auto-generated with f2py (version:2).
+! See http://cens.ioc.ee/projects/f2py2e/
diff --git a/hysop/numerics/interpolation.py b/hysop/numerics/interpolation.py
deleted file mode 100644
index 5b7f4c157a56d129acbf9ebfced42af48fef7ff7..0000000000000000000000000000000000000000
--- a/hysop/numerics/interpolation.py
+++ /dev/null
@@ -1,118 +0,0 @@
-"""
-@file interpolation.py
-"""
-from hysop.constants import np, HYSOP_INTEGER, ORDER
-from hysop.numerics.method import NumMethod
-
-
-class Linear(NumMethod):
- """Linear interpolation of a field"""
-
- def __init__(self, tab, direction, topo, work, iwork):
- """
- @param var : numpy array to interpolate
- @param dx : space grid step
- @param origin : grid lower point coordinates
- @param work : Work arrays (floats)
- @param iwork : Work arrays (integers)
- work must be a list containing (1 element):
- - numpy float array like y[0]
- iwork must be a list containing (dim elements):
- - numpy integer array of shape like y[0]
- - numpy integer array of shape like y[0] (if in 2D and 3D)
- - numpy integer array of shape like y[0] (if in 3D)
- """
- NumMethod.__init__(self)
- self.name = 'LinearInterpolation'
- self.tab = tab
- self.topo = topo
- dimension = self.topo.domain.dimension
- self.work = work
- for iw in iwork:
- assert iw.dtype == HYSOP_INTEGER
- self.iwork = iwork
- assert len(self.work) == 1
- assert len(self.iwork) == dimension
- self.dir = direction
- if dimension == 3:
- if self.dir == 0:
- self._affect_working_arrays = self._affect_work_3D_X
- if self.dir == 1:
- self._affect_working_arrays = self._affect_work_3D_Y
- if self.dir == 2:
- self._affect_working_arrays = self._affect_work_3D_Z
- if dimension == 2:
- if self.dir == 0:
- self._affect_working_arrays = self._affect_work_2D_X
- if self.dir == 1:
- self._affect_working_arrays = self._affect_work_2D_Y
- if dimension == 1:
- if self.dir == 0:
- self._affect_working_arrays = self._affect_work_1D
-
- @staticmethod
- def getWorkLengths(nb_components=None, domain_dim=1):
- return 1, domain_dim
-
- def _affect_work_1D(self, resol):
- return (self.work[0], tuple(self.iwork))
-
- def _affect_work_2D_X(self, resol):
- self.iwork[1][...] = np.indices((resol[1],))[0][np.newaxis, :]
- return (self.work[0], tuple(self.iwork))
-
- def _affect_work_2D_Y(self, resol):
- self.iwork[0][...] = np.indices((resol[0],))[0][:, np.newaxis]
- return (self.work[0], tuple(self.iwork))
-
- def _affect_work_3D_X(self, resol):
- self.iwork[1][...] = np.indices((resol[1],))[0][np.newaxis,
- :, np.newaxis]
- self.iwork[2][...] = np.indices((resol[2],))[0][np.newaxis,
- np.newaxis, :]
- return (self.work[0], tuple(self.iwork))
-
- def _affect_work_3D_Y(self, resol):
- self.iwork[0][...] = np.indices((resol[0],))[0][:,
- np.newaxis, np.newaxis]
- self.iwork[2][...] = np.indices((resol[2],))[0][np.newaxis,
- np.newaxis, :]
- return (self.work[0], tuple(self.iwork))
-
- def _affect_work_3D_Z(self, resol):
- self.iwork[0][...] = np.indices((resol[0],))[0][:,
- np.newaxis, np.newaxis]
- self.iwork[1][...] = np.indices((resol[1],))[0][np.newaxis,
- :, np.newaxis]
- return (self.work[0], tuple(self.iwork))
-
- def __call__(self, t, y, result):
- """
- Computational core for interpolation.
- """
- origin = self.topo.domain.origin
- mesh = self.topo.mesh
- dx = mesh.space_step
- resolution = mesh.discretization.resolution
- x = y[0]
- res = result[0]
- i_y, index = self._affect_working_arrays(mesh.resolution)
-
- floor = res # use res array as working array
- floor[...] = (x - origin[self.dir]) / dx[self.dir]
- i_y[...] = floor
- floor[...] = np.floor(floor)
- i_y[...] -= floor
- # use res as the result (no more uses to floor variable)
-
- index[self.dir][...] = np.asarray(
- floor, dtype=HYSOP_INTEGER, order=ORDER) % (resolution[self.dir] - 1)
-
- res[...] = self.tab[index] * (1. - i_y)
-
- index[self.dir][...] = (index[self.dir] + 1) \
- % (resolution[self.dir] - 1)
-
- res[...] += self.tab[index] * i_y
-
- return [res, ]
diff --git a/hysop/numerics/interpolation/__init__.py b/hysop/numerics/interpolation/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/numerics/interpolation/interpolation.py b/hysop/numerics/interpolation/interpolation.py
new file mode 100644
index 0000000000000000000000000000000000000000..ec44cf182ab1b32afa7aa7bfe43f2d916b659d1c
--- /dev/null
+++ b/hysop/numerics/interpolation/interpolation.py
@@ -0,0 +1,5 @@
+
+from hysop.tools.enum import EnumFactory
+
+Interpolation = EnumFactory.create('Interpolation',
+ ['LINEAR', 'CUBIC', 'CHEBYSHEV'])
diff --git a/hysop/numerics/odesolvers/__init__.py b/hysop/numerics/odesolvers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/codegen/maths/runge_kutta/runge_kutta.py b/hysop/numerics/odesolvers/runge_kutta.py
similarity index 79%
rename from hysop/codegen/maths/runge_kutta/runge_kutta.py
rename to hysop/numerics/odesolvers/runge_kutta.py
index d76767d61a98066776cda113803014c3eef98b4e..b5a302537df7e684080cc6f5d2c16f428d40d603 100644
--- a/hysop/codegen/maths/runge_kutta/runge_kutta.py
+++ b/hysop/numerics/odesolvers/runge_kutta.py
@@ -1,7 +1,6 @@
import numpy as np
-from runge_kutta_coeffs import Itype,Qtype,rk_params, available_methods
-
+from hysop.numerics.odesolvers.runge_kutta_coeffs import Itype,Qtype,rk_params, available_methods
# default methods to dump rational and integers expression to string
def Q_dump(q):
@@ -9,8 +8,11 @@ def Q_dump(q):
def I_dump(i):
return '{}'.format(z)
+class TimeIntegrator(object):
+ def __str__(self):
+ return self.name()
-class RungeKutta(object):
+class RungeKutta(TimeIntegrator):
pass
# Tni = Tn + alpha_i*dt
@@ -22,8 +24,10 @@ class ExplicitRungeKutta(RungeKutta):
def __init__(self,method,I_dump=I_dump,Q_dump=Q_dump):
if method not in available_methods():
- raise ValueError('{} was not implemented yet! Valid values are {}.'.format(name,implemented_methods.keys()))
-
+ msg='{} was not implemented yet! Valid values are {}.'
+ msg=msg.format(name,implemented_methods.keys())
+ raise ValueError(msg)
+
params = rk_params[method]
self.method = method
@@ -38,6 +42,9 @@ class ExplicitRungeKutta(RungeKutta):
self.I_dump = I_dump
self.Q_dump = Q_dump
+ def name(self):
+ return self.method
+
def dump(self,val):
if isinstance(val,Itype):
return self.I_dump(val)
@@ -73,7 +80,7 @@ class ExplicitRungeKutta(RungeKutta):
return _sum
def Xni(self, i,Xn,dt):
if i>0:
- _sum = Xni_sum(i)
+ _sum = self.Xni_sum(i)
return '{} + {}*({})'.format(Xn,dt,_sum)
else:
return '{}'.format(Xn)
@@ -96,6 +103,12 @@ class ExplicitRungeKutta(RungeKutta):
return '{} + {}*({})'.format(Xn,dt,self.step_sum())
+Euler = ExplicitRungeKutta('Euler')
+RK1 = ExplicitRungeKutta('RK1')
+RK2 = ExplicitRungeKutta('RK2')
+RK3 = ExplicitRungeKutta('RK3')
+RK4 = ExplicitRungeKutta('RK4')
+RK4_38 = ExplicitRungeKutta('RK4_38')
if __name__ == '__main__':
R = ExplicitRungeKutta('RK4')
@@ -107,5 +120,3 @@ if __name__ == '__main__':
print
print R.step(Xn='Xo',dt='dt')
-
-
diff --git a/hysop/codegen/maths/runge_kutta/runge_kutta_coeffs.py b/hysop/numerics/odesolvers/runge_kutta_coeffs.py
similarity index 59%
rename from hysop/codegen/maths/runge_kutta/runge_kutta_coeffs.py
rename to hysop/numerics/odesolvers/runge_kutta_coeffs.py
index 3f952fc0fda212bb764fb4836ac5de7fb981ffe0..4b1e7e9ec0ec80320513839c98eb923b366b7efc 100644
--- a/hysop/codegen/maths/runge_kutta/runge_kutta_coeffs.py
+++ b/hysop/numerics/odesolvers/runge_kutta_coeffs.py
@@ -22,7 +22,7 @@ RK1['alpha'] = [Z]
RK1['beta'] = [I(1)]
RK1['gamma'] = [[]]
rk_params['RK1'] = RK1
-rk_params['euler'] = RK1
+rk_params['Euler'] = RK1
RK2 = {}
RK2['order'] = 2
@@ -32,6 +32,30 @@ RK2['beta'] = [Z,I(1)]
RK2['gamma'] = [[Q(1,2)]]
rk_params['RK2'] = RK2
+RK2_Heun = {}
+RK2_Heun['order'] = 2
+RK2_Heun['stages'] = 2
+RK2_Heun['alpha'] = [Z,I(1)]
+RK2_Heun['beta'] = [Q(1,2),Q(1,2)]
+RK2_Heun['gamma'] = [[I(1)]]
+rk_params['RK2_Heun'] = RK2_Heun
+
+RK2_Ralston = {}
+RK2_Ralston['order'] = 2
+RK2_Ralston['stages'] = 2
+RK2_Ralston['alpha'] = [Z,Q(2,3)]
+RK2_Ralston['beta'] = [Q(1,4),Q(3,4)]
+RK2_Ralston['gamma'] = [[Q(2,3)]]
+rk_params['RK2_Ralston'] = RK2_Ralston
+
+RK3 = {}
+RK3['order'] = 3
+RK3['stages'] = 3
+RK3['alpha'] = [Z,Q(1,2),I(1)]
+RK3['beta'] = [Q(1,6),Q(2,3),Q(1,6)]
+RK3['gamma'] = [[Q(1,2), Z ],
+ [I(-1), I(2)]]
+rk_params['RK3'] = RK3
RK4 = {}
RK4['order'] = 4
@@ -43,6 +67,16 @@ RK4['gamma'] = [[Q(1,2), Z, Z ],
[Z, Z, I(1)]]
rk_params['RK4'] = RK4
+RK4_38 = {}
+RK4_38['order'] = 4
+RK4_38['stages'] = 4
+RK4_38['alpha'] = [Z,Q(1,3),Q(2,3),I(1)]
+RK4_38['beta'] = [Q(1,8), Q(3,8), Q(3,8), Q(1,8)]
+RK4_38['gamma'] = [[Q(+1,3), Z, Z ],
+ [Q(-1,3), I(+1), Z ],
+ [I(1), I(-1), I(1)]]
+rk_params['RK4_38'] = RK4_38
+
# check and wrap in numpy arrays
for m in rk_params:
diff --git a/hysop/numerics/remesh/__init__.py b/hysop/numerics/remesh/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/codegen/maths/interpolation/kernel_generator.py b/hysop/numerics/remesh/kernel_generator.py
similarity index 63%
rename from hysop/codegen/maths/interpolation/kernel_generator.py
rename to hysop/numerics/remesh/kernel_generator.py
index 2509599ef59edb7c262e649e4c042d66cfe9872a..c0088c5441eacd0a5911cb0bbd6b4c342f90f216 100644
--- a/hysop/codegen/maths/interpolation/kernel_generator.py
+++ b/hysop/numerics/remesh/kernel_generator.py
@@ -1,43 +1,30 @@
-import stencil
-import os, hashlib, pickle
+from hysop.deps import os, hashlib, pickle, sm, np, gzip, sp
+from hysop.tools.io_utils import IO
+from hysop.tools.numerics import mpq,mpfr,mpqize,f2q
-import numpy as np
-import matplotlib.pyplot as plt
-
-import scipy as sp
-import scipy.interpolate
-
-import sympy as sm
-import sympy.abc, sympy.polys, sympy.solvers, sympy.functions
-
-import gmpy2 as gmp
-from gmpy2 import mpq,mpfr,f2q
-mpqize = np.vectorize(lambda x: f2q(x))
-
-
-user_home = os.path.expanduser('~')
-hysop_cache_folder = user_home + '/.cache/hysop'
-kernels_cache_file = hysop_cache_folder + '/' + 'kernels.bin'
+_cache_dir = IO.cache_path() + '/numerics'
+_cache_file = _cache_dir + '/remesh.pklz'
def _load_cached_kernels():
- if not os.path.exists(hysop_cache_folder):
- os.makedirs(hysop_cache_folder)
- if not os.path.isfile(kernels_cache_file):
- return {}
+ if not os.path.exists(_cache_dir):
+ os.makedirs(_cache_dir)
+ if not os.path.isfile(_cache_file):
+ data = {}
else:
- with open(kernels_cache_file, 'rb') as f:
- return pickle.load(f)
+ try:
+ with gzip.open(_cache_file, 'rb') as f:
+ data = pickle.load(f)
+ except IOError, EOFError:
+ print 'warning: Could not read remeshing kernel cache.'
+ os.remove(_cache_file)
+ data = {}
+ return data
def _export_kernels():
- with open(kernels_cache_file, 'wb') as f:
+ with gzip.open(_cache_file, 'wb') as f:
pickle.dump(_cached_kernels,f)
-def _clear_kernel_cache():
- _cached_kernels = {}
- if os.path.isfile(kernels_cache_file):
- os.remove(kernels_cache_file)
-
def _hash_kernel_key(n,r,deg,Ms,H,remesh):
s = '{}_{}_{}_{}_{}_{}'.format(n,r,deg,Ms,H,int(remesh))
return hashlib.sha256(s).hexdigest()
@@ -46,8 +33,13 @@ _cached_kernels = _load_cached_kernels()
class Kernel(object):
-
def __init__(self,register=False,verbose=False,split_polys=False,**kargs):
+ """
+ Use SymmetricKernelGenerator or KernelGenerator to generate a kernel.
+ Do not call directly.
+
+ split_polys: Split each polynomial in two, to gain precision.
+ """
dic = kargs
for var in ['n','r','deg','Ms','Mh','H','remesh','P']:
@@ -68,14 +60,15 @@ class Kernel(object):
Ms = self.Ms
deg = self.deg
P = self.P
+ self.Px = P
if verbose:
- print '\t=> Substitution in Polynomials'
+ print ' => Substitution in Polynomials'
for Pix in P:
- print '\t',Pix.all_coeffs()[::-1]
+ print ' ',Pix.all_coeffs()[::-1]
print
for Pix in P:
- print '\t',sm.horner(Pix)
+ print ' ',sm.horner(Pix)
print
#split polynomials
@@ -92,29 +85,46 @@ class Kernel(object):
Cr[:,i] = np.asarray(Pit_r.all_coeffs(), dtype=float)
Pt_l.append(Pit_l)
Pt_r.append(Pit_r)
+ self.Cl = Cl
+ self.Cr = Cr
+ self.Pt_l = Pt_l
+ self.Pt_r = Pt_r
if verbose:
- print '\t=> Splitting polynomials'
+ print ' => Splitting polynomials'
for p in Pt_l:
- print '\t',p.all_coeffs()
+ print ' ',p.all_coeffs()
print
for p in Pt_r:
- print '\t',p.all_coeffs()
+ print ' ',p.all_coeffs()
print
print
for p in Pt_l:
- print '\t',sm.horner(p)
+ print ' ',sm.horner(p)
print
for p in Pt_r:
- print '\t',sm.horner(p)
+ print ' ',sm.horner(p)
else:
+ Pt = []
C = np.empty(shape=(deg+1,2*Ms),dtype=float)
for i,Pix in enumerate(P):
- C[:,i] = np.asarray(Pix.all_coeffs(), dtype=float)
+ Pit = Pix.xreplace({x:t+X[i]})
+ C[:,i] = np.asarray(Pit.all_coeffs(), dtype=float)
+ Pt.append(Pit)
+ self.Pt = Pt
+ self.C = C
+
+ if verbose:
+ print ' => Substituing x = t+i'
+ for Pit in Pt:
+ print ' ',Pit.all_coeffs()[::-1]
+ print
+ for Pit in Pt:
+ print ' ',sm.horner(Pit)
+ print
if verbose:
- print
- print '\t=> Generating lambdas'
+ print ' => Generating lambdas'
if split_polys:
gamma_l = sp.interpolate.PPoly(Cl,X,extrapolate=False)
@@ -136,7 +146,7 @@ class Kernel(object):
self.poly_splitted = False
if verbose:
- print '\tAll done!'
+ print ' All done.'
def _register(self,dic):
h = _hash_kernel_key(self.n,self.r,self.deg,self.Ms,self.H,self.remesh)
@@ -150,14 +160,19 @@ class Kernel(object):
return np.logical_and(x>-Ms,x<Ms)*self.gamma(x)
-class KernelGenerator(object):
+class SymmetricKernelGenerator(object):
+ """
+ Generate a symmetric piecewise polynomial that
+ preserves the first discrete moments of a given symmetric stencil H.
+ If H is None, an interpolation stencil is generated.
+ """
def __init__(self,verbose=False):
self.verbose = verbose
self.configured = False
def configure(self,n,H=None):
- assert n>0 and n%2==0, 'n not even or n<=0!'
+ assert n>0 and n%2==0, 'n not even or n<=0.'
Ms = n//2+1
if H is None:
@@ -187,9 +202,9 @@ class KernelGenerator(object):
return self
- def solve(self, r, override_cache=False):
- assert self.configured, 'KernelGenerator has not been configured!'
- assert r>=0, 'r<0!'
+ def solve(self, r, override_cache=False, split_polys=False, no_wrap=False):
+ assert self.configured, 'SymmetricKernelGenerator has not been configured.'
+ assert r>=0, 'r<0.'
deg = 2*r+1
n = self.n
@@ -200,17 +215,21 @@ class KernelGenerator(object):
remesh = self.remesh
verbose = self.verbose
+ if no_wrap:
+ cls = dict
+ else:
+ cls = Kernel
if verbose:
- print 'KernerlGenerator::Solve'
- print '\tn = {}'.format(n)
- print '\tr = {}'.format(r)
- print '\tMs = {}'.format(Ms)
- print '\tdeg = {}'.format(deg)
+ print '\nSymmetricKernelGenerator was called with the following parameters:'
+ print ' n = {} (preserved discrete moments)'.format(n)
+ print ' r = {} (overall kernel regularity)'.format(r)
+ print ' Ms = {} (piecewise polynomial count)'.format(Ms)
+ print ' deg = {} (local polynomial regularity)'.format(deg)
print
- print '\tH = ['+','.join([h.__str__() for h in H])+']'
+ print ' H = ['+','.join([h.__str__() for h in H])+']'
if not self.remesh:
- print '\tMh = ['+','.join([m.__str__() for m in Mh])+']'
+ print ' Mh = ['+','.join([m.__str__() for m in Mh])+']'
print
H = mpqize(np.asarray(H))
@@ -218,25 +237,25 @@ class KernelGenerator(object):
Mh = mpqize(np.asarray(Mh))
# check if kernel was not already cached
+ h = _hash_kernel_key(n,r,deg,Ms,H,remesh)
if override_cache:
if verbose:
- print '\tCache overwrite requested!'
+ print ' Cache overwrite requested.'
else:
if verbose:
- print '\tChecking if kernel was already computed... ',
- h = _hash_kernel_key(n,r,deg,Ms,H,remesh)
+ print ' Checking if kernel was already computed... ',
if h in _cached_kernels:
if verbose:
print 'True'
- print '\tLoading kernel from cache!'
- print
- kernel = Kernel(verbose=verbose,register=False,**_cached_kernels[h])
+ print ' Loading kernel from cache.'
+ data = _cached_kernels[h]
+ if (data is None):
+ raise RuntimeError('Could not solve linear system.')
+ kernel = cls(verbose=verbose,register=False,split_polys=split_polys,**data)
return kernel
elif verbose:
print 'False'
- print '\tBuilding linear system!'
- print
-
+ print ' Building linear system...'
#polynom symbolic variable
x = sm.abc.x
@@ -322,50 +341,58 @@ class KernelGenerator(object):
eqs.append(Cmi-M[m][i])
if verbose:
- print
- print '\t=> System built.'
+ print ' => System built.'
- unknowns = [c for cl in coeffs for c in cl]+[m for ml in M for m in ml if isinstance(m,sm.Symbol)]
+ unknowns = [c for cl in coeffs for c in cl]\
+ +[m for ml in M for m in ml if isinstance(m,sm.Symbol)]
if verbose:
- print '\tUnknowns: ',unknowns
+ print ' Unknowns: ',unknowns
sol = sm.solve(eqs,unknowns)
if len(sol)!=len(unknowns):
if verbose:
print 'sol=',sol
- raise RuntimeError('Could not solve linear system!')
+ _cached_kernels[h] = None
+ _export_kernels()
+ raise RuntimeError('Could not solve linear system.')
elif verbose:
- print
- print '\t=> System solved.'
- print '\t',sol
- print
-
+ print ' => System solved.'
+ for k in sorted(sol.keys(), key=lambda x: x.name):
+ print ' {}: {}'.format(k, sol[k])
+
for i,Pix in enumerate(P):
P[i] = Pix.xreplace(sol)
-
- kernel = Kernel(n=n,r=r,deg=deg,Ms=Ms,
+
+ kernel = cls(n=n,r=r,deg=deg,Ms=Ms,
H=H, Mh=Mh, remesh=remesh,
- P=P, register=True, verbose=verbose)
+ P=P, register=True, verbose=verbose,
+ split_polys=split_polys)
return kernel
-
if __name__=='__main__':
+ from hysop.numerics.stencil.stencil_generator import StencilGenerator
+ from matplotlib import pyplot as plt
verbose=True
+
+ sg = StencilGenerator()
+ sg.configure(dim=1, derivative=2)
- #H = stencil.SymmetricStencil1D().generate(L=3,k=2,order=1).add_zeros(1,1)
for i in xrange(1,5):
p = 2*i
- kg = KernelGenerator(verbose).configure(p)
+ H = sg.generate_exact_stencil(order=p-1, origin=i)
+ print H.coeffs
+ assert H.is_centered()
+ H = [0] + H.coeffs.tolist() + [0]
+ kg = SymmetricKernelGenerator(verbose).configure(p, H=H)
kernels = []
- for r in [1,2,4]:#,8,16,32]:
+ for r in [1,2,4,8]:
try:
- kernels.append(kg.solve(r))
- except:
- pass
-
+ kernels.append(kg.solve(r,override_cache=False))
+ except RuntimeError:
+ print 'Solver failed fro p={} and r={}.'.format(p,r)
+
if len(kernels)==0:
continue
- continue
k0 = kernels[0]
fig = plt.figure()
@@ -382,5 +409,5 @@ if __name__=='__main__':
s.set_ylim(ylim[0]-axe_scaling*Ly,ylim[1]+axe_scaling*Ly)
s.legend()
- plt.show()
- plt.savefig('out/gamma_{}_r'.format(p))
+ plt.show(block=True)
+ # plt.savefig('out/gamma_{}_r'.format(p))
diff --git a/hysop/numerics/remesh/remesh.py b/hysop/numerics/remesh/remesh.py
new file mode 100644
index 0000000000000000000000000000000000000000..bdc0a14c6fbc784478ae0effb5eef818d86a7144
--- /dev/null
+++ b/hysop/numerics/remesh/remesh.py
@@ -0,0 +1,85 @@
+
+from hysop.constants import __VERBOSE__
+from hysop.tools.enum import EnumFactory
+from hysop.tools.types import check_instance
+from hysop.numerics.remesh.kernel_generator import Kernel, SymmetricKernelGenerator
+
+Remesh = EnumFactory.create('Remesh',
+ ['L2_1','L2_2','L4_2','L4_4','L6_4','L6_6','L8_4',
+ 'L2_1s','L2_2s','L4_2s','L4_4s','L6_4s','L6_6s','L8_4s'])
+
+class RemeshKernelGenerator(SymmetricKernelGenerator):
+ def configure(self,n):
+ return super(RemeshKernelGenerator,self).configure(n=n, H=None)
+
+class RemeshKernel(Kernel):
+
+ def __init__(self, moments, regularity,
+ verbose = __VERBOSE__,
+ split_polys=False,
+ override_cache=False):
+
+ generator = RemeshKernelGenerator(verbose=verbose)
+ generator.configure(n=moments)
+
+ kargs = generator.solve(r=regularity, override_cache=override_cache,
+ split_polys=split_polys, no_wrap=True)
+
+ super(RemeshKernel,self).__init__(**kargs)
+
+ @staticmethod
+ def from_enum(remesh):
+ check_instance(remesh, Remesh)
+ remesh = str(remesh)
+ assert remesh[0]=='L'
+ remesh=remesh[1:]
+ if remesh[-1] == 's':
+ remesh = remesh[:-1]
+ split_polys=True
+ else:
+ split_polys=False
+ remesh = [int(x) for x in remesh.split('_')]
+ assert len(remesh) == 2
+ assert remesh[0] >= 2
+ assert remesh[1] >= 1
+ return RemeshKernel(remesh[0], remesh[1], split_polys)
+
+ def __str__(self):
+ return 'RemeshKernel(n={}, r={}, split={})'.format(self.n, self.r, self.poly_splitted)
+
+
+if __name__=='__main__':
+ import numpy as np
+ from matplotlib import pyplot as plt
+ verbose=True
+
+ for i in xrange(1,5):
+ p = 2*i
+ kernels = []
+ for r in [1,2,4,8]:
+ try:
+ kernel = RemeshKernel(p,r)
+ kernels.append(kernel)
+ except RuntimeError:
+ print 'Solver failed for p={} and r={}.'.format(p,r)
+
+ if len(kernels)==0:
+ continue
+ k0 = kernels[0]
+
+ fig = plt.figure()
+ plt.xlabel(r'$x$')
+ plt.ylabel(r'$\Lambda_{'+'{},{}'.format(p,'r')+'}$')
+ X = np.linspace(-k0.Ms,+k0.Ms,1000)
+ s = plt.subplot(1,1,1)
+ for i,k in enumerate(kernels):
+ s.plot(X,k(X),label=r'$\Lambda_{'+'{},{}'.format(p,k.r)+'}$')
+ s.plot(k0.I,k0.H,'or')
+ axe_scaling = 0.10
+ ylim = s.get_ylim()
+ Ly = ylim[1] - ylim[0]
+ s.set_ylim(ylim[0]-axe_scaling*Ly,ylim[1]+axe_scaling*Ly)
+ s.legend()
+
+ plt.show(block=True)
+ # plt.savefig('out/gamma_{}_r'.format(p))
diff --git a/hysop/numerics/splitting/__init__.py b/hysop/numerics/splitting/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/numerics/splitting/directional_splitting.py b/hysop/numerics/splitting/directional_splitting.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ef00243245d934425d0ade205665e3338dbf22e
--- /dev/null
+++ b/hysop/numerics/splitting/directional_splitting.py
@@ -0,0 +1,38 @@
+
+from hysop.tools.decorators import debug
+from hysop.core.graph.graph import not_implemented, not_initialized
+from hysop.core.graph.computational_graph import ComputationalGraph
+from hysop.operator.directional.directional import DirectionalOperator
+
+class DirectionalSplitting(ComputationalGraph):
+
+ @debug
+ def __init__(self, splitting_dim, **kargs):
+ super(DirectionalSplitting,self).__init__(**kargs)
+ self.splitting_dim = splitting_dim
+ self.directional_operators = []
+
+ supported_dimensions = self.supported_dimensions()
+ if not isinstance(supported_dimensions, tuple):
+ msg='{}.supported_dimensions() should return a tuple of ints, got a {}.'
+ msg=msg.format(self.__class__, supported_dimensions.__class__)
+ raise TypeError(msg)
+ if (splitting_dim not in supported_dimensions):
+ msg = '{}D is not supported by this splitting, supported dimensions are {}.'
+ msg=msg.format(dim,supported_dimensions)
+ raise ValueError(msg)
+
+ @debug
+ @not_initialized
+ def push_operators(self, *operators):
+ for op in operators:
+ if not isinstance(op, DirectionalOperator):
+ msg='Given operator is not a DirectionalOperator, got {}.'
+ msg=msg.format(op.__class__)
+ raise TypeError(msg)
+ self.directional_operators.append(op)
+
+ @classmethod
+ @not_implemented
+ def supported_dimensions(cls):
+ pass
diff --git a/hysop/numerics/splitting/strang.py b/hysop/numerics/splitting/strang.py
new file mode 100644
index 0000000000000000000000000000000000000000..c4e442002cff7d809dee22af50d34145f61719cc
--- /dev/null
+++ b/hysop/numerics/splitting/strang.py
@@ -0,0 +1,47 @@
+
+from hysop.tools.decorators import debug
+from hysop.tools.types import to_tuple, check_instance
+from hysop.tools.enum import EnumFactory
+from hysop.numerics.splitting.directional_splitting import DirectionalSplitting,\
+ DirectionalOperator
+
+StrangOrder = EnumFactory.create('StrangOrder',
+ ['STRANG_FIRST_ORDER','STRANG_SECOND_ORDER'])
+
+class StrangSplitting(DirectionalSplitting):
+
+ @debug
+ def __init__(self, splitting_dim, order, **kargs):
+ super(StrangSplitting,self).__init__(splitting_dim=splitting_dim, **kargs)
+ self.spatial_order = order
+
+ check_instance(order, StrangOrder)
+ if order == StrangOrder.STRANG_FIRST_ORDER:
+ order = 1
+ elif order == StrangOrder.STRANG_SECOND_ORDER:
+ order = 2
+ else:
+ msg='Unsupported spatial order requested {}.'
+ msg=msg.format(order)
+ raise ValueError(msg)
+
+ directions = range(splitting_dim)
+ if order==2:
+ directions += range(splitting_dim-2,-1,-1)
+ self.directions = directions
+
+
+ @classmethod
+ def supported_dimensions(cls):
+ return (1,2,3,)
+
+ @debug
+ def pre_initialize(self):
+ splitting_dim = self.splitting_dim
+ for op in self.directional_operators:
+ op.generate(splitting_dim=splitting_dim)
+ for dir_ in self.directions:
+ for op in self.directional_operators:
+ operators = op.get_direction(dir_)
+ self.push_nodes(operators)
+
diff --git a/hysop/numerics/splitting/test/test_strang.py b/hysop/numerics/splitting/test/test_strang.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6ef1a7306b3b7091c701860057f2a49989a02c9
--- /dev/null
+++ b/hysop/numerics/splitting/test/test_strang.py
@@ -0,0 +1,98 @@
+
+from hysop.problem import Problem
+from hysop.operators import DirectionalAdvection, Poisson
+from hysop.numerics.splitting.strang import StrangSplitting
+
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology import Cartesian
+from hysop.tools.parameters import Discretization
+from hysop.simulation import Simulation
+
+from hysop.methods import *
+from hysop.backend.device.kernel_autotuner import AutotunerConfig, AutotunerFlags
+# from hysop.constants import callback_profiler
+
+class TestStrang(object):
+
+ @classmethod
+ def setup_class(cls):
+ pass
+
+ @classmethod
+ def teardown_class(cls):
+ pass
+
+ def setup_method(self, method):
+ pass
+
+ def teardown_method(self, method):
+ pass
+
+ def make_fields(self, dim, nscalars):
+ # Domain
+ box = Box(length=[1.0]*dim, origin=[0.0]*dim)
+
+ ## Fields
+ velo = Field(domain=box, formula=None,
+ name='V', is_vector=True)
+ if dim==2:
+ vorti = Field(domain=box, name='W')
+ else:
+ vorti = Field(domain=box, formula=None,
+ name='W', is_vector=True)
+
+ scalars = [ Field(domain=box, name='S{}'.format(i))
+ for i in xrange(nscalars)]
+
+ return box, velo, vorti, tuple(scalars)
+
+ def _test_strang_nd(self, dim, n):
+ ## Simulation
+ simu = Simulation(start=0.0, end=1.0, max_iter=100, time_step=0.1)
+ simu.initialize()
+
+ ## Domain and continuous fields
+ box, velo, vorti, scalars = self.make_fields(dim,2)
+
+ ## Discretizations and topologies
+ resolution = (n,)*dim
+ dnd = Discretization(resolution=resolution, ghosts=None)
+ topo = Cartesian(box,dnd,dim)
+
+ ## Operators
+ advec = DirectionalAdvection(
+ name='advec',
+ velocity = velo,
+ advected_fields = (vorti,)+scalars,
+ variables = { velo: topo, vorti: topo,
+ scalars[0]: topo, scalars[1]: topo},
+ split_fields=(vorti, scalars)
+ )
+
+ poisson = Poisson(name='poisson',
+ velocity=velo, vorticity=vorti,
+ topology=topo)
+
+ ## Graph
+ splitting = StrangSplitting(dim=dim, order=StrangOrder.STRANG_FIRST_ORDER)
+ splitting.push_operator(advec)
+
+ problem = Problem()
+ problem.insert(splitting)
+ problem.insert(poisson)
+ problem.build()
+
+ problem.display()
+ problem.finalize()
+
+ def test_strang_2d(self, n=33):
+ self._test_strang_nd(dim=2, n=n)
+ def test_strang_3d(self, n=33):
+ self._test_strang_nd(dim=3, n=n)
+
+if __name__ == '__main__':
+ test = TestStrang()
+ test.setup_class()
+ test.test_strang_3d()
+ test.teardown_class()
diff --git a/hysop/numerics/stencil/__init__.py b/hysop/numerics/stencil/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/numerics/stencil/stencil.py b/hysop/numerics/stencil/stencil.py
new file mode 100644
index 0000000000000000000000000000000000000000..11ea9b256e013b26ede2347e4d0ab8daef77ff8c
--- /dev/null
+++ b/hysop/numerics/stencil/stencil.py
@@ -0,0 +1,380 @@
+
+"""Finite differences stencil inteface used in various numerical methods.
+
+* :class:`~hysop.numerics.stencil.stencil.Stencil`
+* :class:`~hysop.numerics.stencil.stencil.CenteredStencil`
+* :class:`~hysop.numerics.stencil_generator.StencilGenerator`
+* :class:`~hysop.numerics.stencil_generator.CenteredStencilGenerator`
+
+"""
+
+from hysop.deps import sm, sp, it, np, hashlib
+from hysop.tools.sympy_utils import recurse_expression_tree
+
+class Stencil(object):
+ """
+ Stencil used for finite abitrary dimension differences.
+ """
+
+ def __init__(self, coeffs, origin, order,
+ dx=sm.Symbol('dx'), factor=1, error=None):
+ """
+ Stencil used for finite differences schemes (n-dimensional).
+
+ Parameters
+ ----------
+ coeffs: array_like
+ Coefficients of the stencil.
+ origin: array_like
+ Origin of the stencil from left-most point.
+ order: int
+ Order of the stencil.
+
+ Other Parameters
+ ----------------
+ dx: sympy.Symbol or array_like of sympy.Symbol
+ Spatial spacing symbols.
+ factor: dtype or sympy.Expr
+ Common leading factors for all coefficients.
+ error: sympy.Expr
+ Exact error if known.
+
+ Attributes
+ ----------
+ coeffs: np.ndarray
+ Coefficients of the stencil.
+ origin: np.ndarray
+ Origin of the stencil from left-most point.
+ order: int
+ Spatial order of the stencil.
+ dim: int
+ Spatial dimension of the stencil.
+ shape: np.ndarray
+ Shape of the stencil.
+ L: np.ndarray
+ Distance from origin to left-most point included in stencil support.
+ R: np.ndarray
+ Distance from origin to right-most point included in stencil support.
+ dx: sympy.Symbol or array_like of sympy.Symbol
+ Spatial spacing symbols.
+ factor: dtype or sympy.Expr
+ Leading factor of all coefficients.
+ error: sympy.Expr
+ Exact error term if known or else None.
+
+ Raises
+ ------
+ ValueError
+ Raised if one component of `origin` is negative.
+
+ See Also
+ --------
+ :class:`CenteredStencil`: Centered version of a stencil.
+ :class:`StencilGenerator`: Generate Stencil objects.
+ """
+
+ coeffs = np.atleast_1d(coeffs)
+ origin = np.atleast_1d(origin)
+ order = np.atleast_1d(order)
+ dx = np.atleast_1d(dx)
+
+ if (origin<0).any():
+ raise ValueError('Origin component < 0!\norigin={}'.format(origin))
+
+ self.dx = dx[0] if dx.size==1 else dx
+ self.error = error
+
+ self.origin = origin[0] if origin.size==1 else origin
+ self.order = order[0] if order.size==1 else order
+ self.factor = factor
+ self.coeffs = self._delete_zeros(coeffs)
+
+ self._update_attributes()
+
+ def has_factor(self):
+ return (self.factor!=1)
+
+ def non_zero_coefficients(self):
+ return np.sum(self.coeffs!=0)
+
+ def replace_symbols(self, dic):
+ if isinstance(self.factor,sm.Basic):
+ self.factor = self.factor.xreplace(dic)
+ coeffs = self.coeffs.ravel()
+ for i,coeff in enumerate(coeffs):
+ if isinstance(coeff,sm.Basic):
+ coeffs[i] = coeff.xreplace(dic)
+
+
+ def _update_attributes(self):
+ self.dim = self.coeffs.ndim
+ self.shape = self.coeffs.shape
+ self.L = np.asarray([self.origin] if np.isscalar(self.origin) else self.origin)
+ self.R = self.shape-self.origin-1
+
+ def _delete_zeros(self, coeffs):
+ dim = coeffs.ndim
+ shape = list(coeffs.shape)
+ dtype = coeffs.dtype
+ if dtype in [np.float16, np.float32, np.float64]:
+ mask = np.isclose(coeffs,0, atol=2*np.finfo(dtype).eps)
+ else:
+ mask = (coeffs==0)
+ keep_mask = np.ones_like(coeffs,dtype=bool)
+ for d in xrange(dim):
+ laccess = [slice(None)]*dim
+ raccess = [slice(None)]*dim
+ laccess[d] = slice(0,1)
+ raccess[d] = slice(-1,None)
+ ldel = mask[laccess].all()
+ rdel = mask[raccess].all()
+ if ldel:
+ keep_mask[laccess] = False
+ if dim==1:
+ self.origin-=1
+ else:
+ self.origin[d]-=1
+ shape[d]-=1
+ if rdel:
+ shape[d]-=1
+ keep_mask[raccess] = False
+ coeffs = coeffs[keep_mask].reshape(shape)
+ return coeffs
+
+ def accuracy(self):
+ """
+ Accuracy of the stencil with bigO notation.
+
+ Returns
+ -------
+ accuracy: sympy.Expr
+ Accuracy in bigO notation.
+ """
+ expr = 0
+ done = []
+ if self.dim!=1:
+ for dx,order in zip(self.dx,self.order):
+ if dx not in done:
+ expr += sm.O(dx**int(order))
+ done.append(dx)
+ else:
+ expr += sm.O(self.dx**int(self.order))
+ return expr
+
+ def variables(self):
+ """
+ Symbolic variables used by the stencil.
+
+ Returns
+ -------
+ vars: set of sympy.Expr
+ """
+
+ _vars = set()
+ def op(expr):
+ if isinstance(expr, sm.Symbol):
+ _vars.add(expr)
+
+ recurse_expression_tree(op,self.factor)
+ for coeff in self.coeffs.flatten():
+ recurse_expression_tree(op,coeff)
+ return _vars
+
+ def coo_stencil(self):
+ """
+ Return a 2d stencil as a sparse coordinate matrix.
+
+ Returns
+ -------
+ coo_stencil: scipy.sparse.coo_matrix
+ Sparse Coordinate Matrix of the stencil.
+
+ Raises
+ ------
+ RuntimeError
+ Raised if stencil is not 2d.
+ """
+ if self.dim!=2:
+ raise RuntimeError('Stencil is not 2d !')
+ return sp.sparse.coo_matrix(self.coeffs,shape=self.shape,dtype=self.dtype)
+
+ def iteritems(self,include_factor=True):
+ """
+ Return an (offset,coefficient) iterator iterating on all **non zero** coefficients.
+ Offset is taken from origin.
+
+ Returns
+ -------
+ it : itertools.iterator
+ Zipped offset and coefficient iterator.
+ """
+ factor = self.factor if include_factor else 1
+ def mapfun(x):
+ offset = x-self.origin
+ value = factor*self.coeffs[x]
+ return (offset,value)
+ iterator = np.ndindex(self.shape)
+ iterator = it.imap(mapfun, iterator)
+ iterator = it.ifilter(lambda x: x[1]!=0, iterator)
+ return iterator
+
+ def refactor(self, factor):
+ """
+ Factorize the stencil by a new numeric or symbolic value.
+
+ Parameters
+ ----------
+ factor : :attr:`dtype` or sympy.Expr
+ New factor to be applied.
+
+ Returns
+ -------
+ self : :class:`Stencil`
+ """
+ old_factor = self.factor
+
+ cfactor = (old_factor/factor)
+ coeffs = self.coeffs
+ for idx, coeff in np.ndenumerate(coeffs):
+ coeffs[idx] = sm.simplify(coeff*cfactor)
+
+ self.factor = factor
+ self.coeffs = coeffs
+ return self
+
+ def hash(self, keep_only=16):
+ """
+ Hash the stencil with its origin, order and coefficients.
+ The hash algorithm used is sha1.
+ By default only the 16 first chars are kept from the generated hash.
+
+ Parameters
+ ----------
+ keep_only : int
+ Number of chars kept from the hashed hexedecimal string.
+
+ Returns
+ -------
+ hash : string
+ Hexadecimal hash string of size :attr:`keep_only`.
+ """
+ coeffs = self.coeffs
+ m = hashlib.sha1()
+ m.update(self.origin)
+ m.update(self.order)
+ for d in coeffs:
+ m.update(str(d))
+ return m.hexdigest()[:keep_only]
+
+ def is_symbolic(self):
+ """
+ Check if either the stencil leading factor or the stencil coefficients
+ contains symbolic values.
+
+ Returns
+ -------
+ is_symbolic : bool
+ """
+ return len(self.variables())!=0
+
+
+ def is_centered(self,axe=None):
+ """
+ Check if the stencil is centered (ie. stencil generate a centered
+ finite differences scheme).
+
+ Returns
+ -------
+ is_centered : bool
+ """
+ L,R = self.L, self.R
+ if axe==None:
+ return (L==R).all()
+ else:
+ return (L[axe]==R[axe]).all()
+
+ def is_cross(self):
+ """
+ Check if the stencil is a cross (zeros everywhere except on a
+ n-dimensional axis aligned cross).
+
+ Examples:
+ oo+oo o+oo
+ oo+oo ++++
+ +++++ o+oo
+ oo+oo o+oo
+
+ Returns
+ -------
+ is_cross : bool
+ """
+ mask = np.ones(self.shape,dtype=bool)
+
+ if self.dim == 1:
+ return True
+ else:
+ access = self.origin.tolist()
+ for i in xrange(self.dim):
+ acc = [x for x in access]
+ acc[i] = slice(0,self.shape[i])
+ mask[acc] = False
+ return not np.any((self.coeffs!=0)*mask)
+
+ def __str__(self):
+ return \
+'''
+== {}D Stencil ==
+origin: {}
+order: {}
+accuracy: {}
+error: {}
+shape: {}
+centered: {}
+cross: {}
+symbolic: {}
+variables: {}
+factor: {}
+coeffs:
+{}
+=================
+'''.format(self.dim,self.origin,self.order,self.accuracy(),self.error,
+ self.shape,
+ self.is_centered(), self.is_cross(), self.is_symbolic(),
+ self.variables(),
+ self.factor,self.coeffs)
+
+
+
+class CenteredStencil(Stencil):
+ """
+ Centered stencil used for finite abitrary dimension differences.
+ """
+
+ def __init__(self, coeffs, origin, order,
+ dx=sm.Symbol('dx'), factor=1, error=None):
+ """
+ Centered stencil used for finite abitrary dimension differences.
+
+ See also
+ --------
+ :class:`CenteredStencilGenerator`: Centered stencil generator.
+ """
+ shape = np.asarray(coeffs.shape)
+ if (shape%2==0).any():
+ raise ValueError('Shape compnonent even!')
+ if (origin!=(shape-1)/2).any():
+ print origin
+ print (shape-1)/2
+ raise ValueError('Origin is not centered!')
+ super(CenteredStencil,self).__init__(coeffs, origin, order, dx, factor, error)
+
+ def is_centered(self):
+ return True
+
+ @staticmethod
+ def from_stencil(stencil):
+ s = stencil
+ if not s.is_centered():
+ raise ValueError('Given stencil is not centered!')
+ return CenteredStencil(s.coeffs, s.origin, s.order, s.dx, s.factor, s.error)
+
diff --git a/hysop/numerics/stencil.py b/hysop/numerics/stencil/stencil_generator.py
similarity index 53%
rename from hysop/numerics/stencil.py
rename to hysop/numerics/stencil/stencil_generator.py
index a0514b1bef0e7640fd20515fe8a8ce3eba79c51d..6071766ee7309887b656b70c5db2b007efa98727 100644
--- a/hysop/numerics/stencil.py
+++ b/hysop/numerics/stencil/stencil_generator.py
@@ -5,392 +5,38 @@
"""
-import sys, os, math
-import pickle, hashlib, gzip
-import itertools as it
+from hysop.deps import it, np, sp, sm, os, copy, math, gzip, pickle
+from hysop.tools.misc import prod
+from hysop.tools.io_utils import IO
+from hysop.tools.numerics import MPQ, MPZ, MPFR, F2Q, mpqize
+from hysop.tools.types import extend_array
+from hysop.tools.sympy_utils import tensor_symbol, tensor_xreplace, \
+ factor_split, build_eqs_from_dicts
-import numpy as np
-import sympy as sm
+from hysop.numerics.stencil.stencil import Stencil, CenteredStencil
-import scipy as sp
-import scipy.linalg
-
-import gmpy2 as gmp
-from gmpy2 import mpq
-
-MPQ = mpq().__class__
-def _mpqize(x):
- return mpq(x.p,x.q)
-mpqize = np.vectorize(_mpqize)
-
-from hysop.tools.io_utils import IO
-
-class Stencil(object):
- """
- Stencil used for finite abitrary dimension differences.
- """
-
- def __init__(self, coeffs, origin, order,
- dx=sm.Symbol('dx'), factor=1, error=None):
- """
- Stencil used for finite abitrary dimension differences.
-
- Attributes
- ----------
- coeffs: np.ndarray
- Coefficients of the stencil.
- origin: np.ndarray
- Origin of the stencil from left-most point.
- order: int
- Order of the stencil.
- dim: int
- Spatial dimension of the stencil.
- shape: np.ndarray
- Shape of the stencil.
- L: np.ndarray
- Distance from origin to left-most point included in stencil support.
- R: np.ndarray
- Distance from origin to right-most point included in stencil support.
- dx: sympy.Symbol or array_like of sympy.Symbol
- Spatial spacing symbols.
- factor: dtype or sympy.Expr
- Leading factor of all coefficients.
- error: sympy.Expr
- Exact error if known.
-
- Parameters
- ----------
- coeffs: array_like
- Coefficients of the stencil.
- origin: array_like
- Origin of the stencil from left-most point.
- order: int
- Order of the stencil.
-
- Other Parameters
- ----------------
- dx: sympy.Symbol or array_like of sympy.Symbol
- Spatial spacing symbols.
- factor: dtype or sympy.Expr
- Common leading factors for all coefficients.
- error: sympy.Expr
- Exact error if known.
-
- Raises
- ------
- ValueError
- Raised if one component of `origin` is negative.
-
- See Also
- --------
- :class:`CenteredStencil`: Centered version of a stencil.
- :class:`StencilGenerator`: Generate Stencil objects.
- """
-
- if (origin<0).any():
- raise ValueError('Origin component < 0!\norigin={}'.format(origin))
-
- if coeffs.ndim==1:
- origin = origin if np.isscalar(origin) else origin[0]
- order = order if np.isscalar(order) else order[0]
- dx = dx if isinstance(dx,sm.Symbol) else dx[0]
- else:
- coeffs = np.asarray(coeffs)
- origin = np.asarray(origin)
- order = np.asarray(order)
-
- if isinstance(dx, list):
- dx = np.asarray(dx)
- self.dx = dx
- self.error = error
-
- self.origin = origin
- self.order = order
- self.factor = factor
- self.coeffs = self._delete_zeros(coeffs)
-
- self._update_attributes()
-
- def _update_attributes(self):
- self.dim = self.coeffs.ndim
- self.shape = self.coeffs.shape
- self.L = np.asarray([self.origin] if np.isscalar(self.origin) else self.origin)
- self.R = self.shape-self.origin-1
-
- def _delete_zeros(self, coeffs):
- dim = coeffs.ndim
- shape = list(coeffs.shape)
- mask = (coeffs==0)
- keep_mask = np.ones_like(coeffs,dtype=bool)
- for d in xrange(dim):
- laccess = [slice(None)]*dim
- raccess = [slice(None)]*dim
- laccess[d] = slice(0,1)
- raccess[d] = slice(-1,None)
- ldel = mask[laccess].all()
- rdel = mask[raccess].all()
- if ldel:
- keep_mask[laccess] = False
- if dim==1:
- self.origin-=1
- else:
- self.origin[d]-=1
- shape[d]-=1
- if rdel:
- shape[d]-=1
- keep_mask[raccess] = False
- coeffs = coeffs[keep_mask].reshape(shape)
- return coeffs
-
- def accuracy(self):
- """
- Accuracy of the stencil with bigO notation.
-
- Returns
- -------
- accuracy: sympy.Expr
- Accuracy in bigO notation.
- """
- expr = 0
- done = []
- if self.dim!=1:
- for dx,order in zip(self.dx,self.order):
- if dx not in done:
- expr += sm.O(dx**int(order))
- done.append(dx)
- else:
- expr += sm.O(self.dx**int(self.order))
- return expr
-
- def variables(self):
- """
- Symbolic variables used by the stencil.
-
- Returns
- -------
- vars: set of sympy.Expr
- """
- from hysop.tools.sympy_utils import recurse_expression_tree
-
- _vars = set()
- def op(expr):
- if isinstance(expr, sm.Symbol):
- _vars.add(expr)
-
- recurse_expression_tree(op,self.factor)
- for coeff in self.coeffs.flatten():
- recurse_expression_tree(op,coeff)
- return _vars
-
- def coo_stencil(self):
- """
- Return a 2d stencil as a sparse coordinate matrix.
-
- Returns
- -------
- coo_stencil: scipy.sparse.coo_matrix
- Sparse Coordinate Matrix of the stencil.
-
- Raises
- ------
- RuntimeError
- Raised if stencil is not 2d.
- """
- if self.dim!=2:
- raise RuntimeError('Stencil is not 2d !')
- return sp.sparse.coo_matrix(self.coeffs,shape=self.shape,dtype=self.dtype)
-
- def iteritems(self,svars={},include_factor=True):
- """
- Return an (offset,coefficient) iterator iterating on all **non zero** coefficients.
- Offset is taken from origin.
-
- Returns
- -------
- it : itertools.iterator
- Zipped offset and coefficient iterator.
- """
- factor = self.factor if include_factor else 1
- def mapfun(x):
- offset = x-self.origin
- value = factor*self.coeffs[x]
- if isinstance(value, sm.Expr):
- value = value.xreplace(svars)
- return (offset,value)
- iterator = np.ndindex(self.shape)
- iterator = it.imap(mapfun, iterator)
- iterator = it.ifilter(lambda x: x[1]!=0, iterator)
- return iterator
-
- def refactor(self, factor):
- """
- Factorize the stencil by a new numeric or symbolic value.
-
- Parameters
- ----------
- factor : :attr:`dtype` or sympy.Expr
- New factor to be applied.
-
- Returns
- -------
- self : :class:`Stencil`
- """
- old_factor = self.factor
-
- cfactor = (old_factor/factor)
- coeffs = self.coeffs
- for idx, coeff in np.ndenumerate(coeffs):
- coeffs[idx] = sm.simplify(coeff*cfactor)
-
- self.factor = factor
- self.coeffs = coeffs
- return self
-
- def hash(self, keep_only=8):
- """
- Hash the stencil with its origin, order and coefficients.
- The hash algorithm used is sha1.
- By default only the 8 first chars are kept from the generated hash.
-
- Parameters
- ----------
- keep_only : int
- Number of chars kept from the hashed hexedecimal string.
-
- Returns
- -------
- hash : string
- Hexadecimal hash string of size :attr:`keep_only`.
- """
- coeffs = self.coeffs
- m = hashlib.sha1()
- m.update(self.origin)
- m.update(self.order)
- for d in coeffs:
- m.update(str(d))
- return m.hexdigest()[:keep_only]
-
- def is_symbolic(self):
- """
- Check if either the stencil leading factor or the stencil coefficients
- contains symbolic values.
-
- Returns
- -------
- is_symbolic : bool
- """
- return len(self.variables())!=0
-
-
- def is_centered(self,axe=None):
- """
- Check if the stencil is centered.
-
- Returns
- -------
- is_centered : bool
- """
- L,R = self.L, self.R
- if axe==None:
- return (L==R).all()
- else:
- return (L[axe]==R[axe]).all()
-
- def is_cross(self):
- """
- Check if the stencil is a cross (zeros everywhere except on a nd cross).
-
- Returns
- -------
- is_cross : bool
- """
- mask = np.ones(self.shape,dtype=bool)
-
- if self.dim == 1:
- return True
- else:
- access = self.origin.tolist()
- for i in xrange(self.dim):
- acc = [x for x in access]
- acc[i] = slice(0,self.shape[i])
- mask[acc] = False
- return not np.any((self.coeffs!=0)*mask)
-
- def __str__(self):
- return \
-'''
-== {}D Stencil ==
-origin: {}
-order: {}
-accuracy: {}
-error: {}
-shape: {}
-centered: {}
-cross: {}
-symbolic: {}
-variables: {}
-factor: {}
-coeffs:
-{}
-=================
-'''.format(self.dim,self.origin,self.order,self.accuracy(),self.error,
- self.shape,
- self.is_centered(), self.is_cross(), self.is_symbolic(),
- self.variables(),
- self.factor,self.coeffs)
-
-class CenteredStencil(Stencil):
- """
- Centered stencil used for finite abitrary dimension differences.
- """
-
- def __init__(self, coeffs, origin, order,
- dx=sm.Symbol('dx'), factor=1, error=None):
- """
- Centered stencil used for finite abitrary dimension differences.
-
- See also
- --------
- :class:`CenteredStencilGenerator`: Centered stencil generator.
- """
- shape = np.asarray(coeffs.shape)
- if (shape%2==0).any():
- raise ValueError('Shape compnonent even!')
- if (origin!=(shape-1)/2).any():
- print origin
- print (shape-1)/2
- raise ValueError('Origin is not centered!')
- super(CenteredStencil,self).__init__(coeffs, origin, order, dx, factor, error)
-
- def is_centered(self):
- return True
-
- @staticmethod
- def from_stencil(stencil):
- s = stencil
- if not s.is_centered():
- raise ValueError('Given stencil is not centered!')
- return CenteredStencil(s.coeffs, s.origin, s.order, s.dx, s.factor, s.error)
-
class StencilGeneratorConfiguration(object):
def __init__(self):
- self.dim = 1
+ self.dim = 1
self.dtype = MPQ
- self.dx=sm.Symbol('dx')
+ self.dx = sm.Symbol('dx')
self.user_eqs = {}
self.derivative = 1
self.order = 1
- self.mask_type = StencilGenerator.CROSS
- self._mask = None
+ self.mask_type = StencilGenerator.CROSS
+ self._mask = None
self._format_inputs()
def configure(self, dim=None, dtype=None, dx=None, user_eqs=None,
- derivative=None, order=None,
- mask=None,mask_type=None):
+ derivative=None, order=None,
+ mask=None,mask_type=None):
+ """
+ Configure the stencil generator.
+ """
self.dim = dim if (dim is not None) else self.dim
self.dtype = dtype if (dtype is not None) else self.dtype
@@ -398,8 +44,8 @@ class StencilGeneratorConfiguration(object):
self.user_eqs = user_eqs if (user_eqs is not None) else self.user_eqs
self.derivative = derivative if (derivative is not None) else self.derivative
self.order = order if (order is not None) else self.order
- self._mask = mask if (mask is not None) else self._mask
self.mask_type = mask_type if (mask_type is not None) else self.mask_type
+ self._mask = mask if (mask is not None) else self._mask
self._format_inputs()
return self
@@ -407,17 +53,18 @@ class StencilGeneratorConfiguration(object):
if (self.derivative is None) or (self.order is None):
raise RuntimeError('First set derivative and order with configure!')
return self.derivative + self.order
+
def L(self,origin):
StencilGeneratorConfiguration._check_origin(origin,self.dim)
shape = self.shape()
return origin
+
def R(self,origin):
StencilGeneratorConfiguration._check_origin(origin,self.dim)
shape = self.shape()
return shape-origin-1
def copy(self):
- import copy
return copy.deepcopy(self)
def mask(self,origin,custom_mask=None):
@@ -436,33 +83,23 @@ class StencilGeneratorConfiguration(object):
return mask
def symbolic_derivatives(self,extra_size=0):
- from hysop.tools.sympy_utils import tensor_symbol
df,df_vars = tensor_symbol(prefix='f',shape=self.shape()+extra_size)
return df,df_vars
def symbolic_stencil(self, origin):
- from hysop.tools.sympy_utils import tensor_symbol
StencilGeneratorConfiguration._check_origin(origin,self.dim)
- S,svars = tensor_symbol(prefix='S',mask=self.mask(origin),shape=self.shape(),origin=origin)
+ S,svars = tensor_symbol(prefix='S',mask=self.mask(origin),shape=self.shape(),
+ origin=origin)
return S,svars
def _format_inputs(self):
if isinstance(self.dx,sm.Symbol) or isinstance(self.dx,sm.Expr) or np.isscalar(self.dx):
self.dx = np.asarray([self.dx]*self.dim)
-
- def to_ndarray(value,dim,dtype):
- if np.isscalar(value):
- value = [value]*dim
- if isinstance(value, list):
- value = np.asarray(value+[value[-1]]*(dim-len(value)), dtype=dtype)
- if isinstance(value, np.ndarray):
- value = np.asarray(np.concatenate( (value, [value[-1]]*(dim-value.size) ) ), dtype=dtype)
- return value
dim = self.dim
- self.derivative = to_ndarray(self.derivative, dim, int)
- self.order = to_ndarray(self.order, dim, int)
- self.dx = to_ndarray(self.dx, dim, object)
+ self.derivative = extend_array(self.derivative, dim, dtype=int)
+ self.order = extend_array(self.order, dim, dtype=int)
+ self.dx = extend_array(self.dx, dim, dtype=object)
def _check_and_raise(self):
self._format_inputs()
@@ -639,8 +276,12 @@ class StencilGenerator(object):
@staticmethod
def _load_cache():
if os.path.isfile(StencilGenerator._cache_file):
- with gzip.open(StencilGenerator._cache_file, 'rb') as f:
- results = pickle.loads(f.read())
+ try:
+ with gzip.open(StencilGenerator._cache_file, 'rb') as f:
+ results = pickle.loads(f.read())
+ except EOFError, IOError:
+ os.remove(StencilGenerator._cache_file)
+ results = {}
else:
results = {}
return results
@@ -659,17 +300,32 @@ class StencilGenerator(object):
def get_config(self):
+ """
+ Get current stencil generator configuration state.
+ """
return self._config
+
def cache_override(self):
+ """
+ Get caching override flag.
+ """
return self._cache_override
def configure(self, config=None, **kargs):
+ """
+ Push a new stencil generator configuration by keyword arguments (see
+ StencilGeneratorConfiguration.configure() or by StencilGeneratorConfiguration instance.
+ """
if config is not None:
self._config = config
self._config.configure(**kargs)
return self
def generate_approximative_stencil(self, origin, **kargs):
+ """
+ Generate a stencil using hardware floating point arithmetic (fast).
+ dtype can be np.float16, np.float32, np.float64
+ """
config = self._config.copy()
config.configure(**kargs)
@@ -678,39 +334,56 @@ class StencilGenerator(object):
if (dim!=1):
raise ValueError('Bad dimension for approximation stencil generation!')
- if dtype not in [float, np.float32, np.float64]:
- raise TypeError('Bad dtype!')
+ if dtype not in [np.float16, np.float32, np.float64]:
+ solve_dtype = np.float64
+ else:
+ solve_dtype = dtype
dx = config.dx[0]
k = config.derivative[0]
order = config.order[0]
-
+
N = config.shape()[0]
origin = StencilGenerator._format_origin(origin,N)
L = config.L(origin)
R = config.R(origin)
- A = np.zeros((N,N),dtype=dtype)
- b = np.zeros(N,dtype=dtype)
+ A = np.zeros((N,N),dtype=solve_dtype)
+ b = np.zeros(N,dtype=solve_dtype)
for i in xrange(N):
- b[i] = dtype(i==k)
+ b[i] = solve_dtype(i==k)
for j in xrange(N):
- A[i,j] = dtype(j-origin)**i
-
+ A[i,j] = solve_dtype(j-origin)**i
+
try:
- S = scipy.linalg.solve(A,b,overwrite_a=True,overwrite_b=True)
+ S = sp.linalg.solve(A,b,overwrite_a=True,overwrite_b=True)
+ S *= math.factorial(k)
except:
- raise RuntimeError('Error: Cannot generate stencil (singular system)!')
-
- S *= dtype(math.factorial(k))
+ print '\nError: Cannot generate stencil (singular system).\n'
+ raise
+
+ if dtype!=solve_dtype:
+ if dtype==MPQ:
+ import fractions
+ from hysop.tools.numerics import mpq
+ def convert(x):
+ frac = fractions.Fraction(x).limit_denominator((1<<32)-1)
+ return mpq(frac.numerator, frac.denominator)
+ S = np.vectorize(convert)(S)
+ else:
+ RuntimeError('Type conversion not implemented yet.')
+
return Stencil(S,origin,order,factor=1/(dx**k), dx=dx)
def generate_exact_stencil(self, origin, **kargs):
- from hysop.tools.sympy_utils import tensor_symbol, tensor_xreplace, \
- factor_split, build_eqs_from_dicts, prod
-
+ """
+ Generate a stencil using quotients (slower).
+ Yield exact solutions by using symbolic calculation
+ and quotient arithmetic.
+ Do not use on high order stencils.
+ """
config = self._config.copy()
config.configure(**kargs)
@@ -834,7 +507,8 @@ class CenteredStencilGenerator(StencilGenerator):
shape = config.shape()
origin = (shape-1)/2
- stencil = super(CenteredStencilGenerator,self).generate_exact_stencil(origin, **kargs)
+ stencil = super(CenteredStencilGenerator,self)\
+ .generate_exact_stencil(origin, **kargs)
if stencil.is_centered():
return CenteredStencil.from_stencil(stencil)
else:
@@ -845,8 +519,9 @@ class CenteredStencilGenerator(StencilGenerator):
config.configure(**kargs)
shape = config.shape()
- origin = (self.shape-1)/2
- stencil = super(CenteredStencilGenerator,self).generate_approximative_stencil(origin, **kargs)
+ origin = (shape-1)/2
+ stencil = super(CenteredStencilGenerator,self)\
+ .generate_approximative_stencil(origin, **kargs)
if stencil.is_centered():
return CenteredStencil.from_stencil(stencil)
else:
@@ -856,34 +531,48 @@ class CenteredStencilGenerator(StencilGenerator):
if __name__ == '__main__':
- import hysop
+ from hysop.tools.contexts import printoptions
sg = StencilGenerator()
- sg.configure(dtype=np.float64,derivative=1,order=2)
- for i in xrange(sg.get_config().shape()):
- stencil = sg.generate_approximative_stencil(origin=i)
- print '{} . {}'.format(stencil.factor, stencil.coeffs)
-
- sg.configure(dtype=MPQ,derivative=2,order=4)
- for i in xrange(sg.get_config().shape()):
- stencil = sg.generate_exact_stencil(origin=i)
- print '{} . {}'.format(stencil.factor, stencil.coeffs)
-
- sg.configure(dim=2, order=2)
- laplacian = sg.generate_exact_stencil(origin=1)
- print laplacian.coeffs
+ sg.configure(dim=1, derivative=2, order=2, dtype=np.float64)
- laplacian = sg.generate_exact_stencil(origin=1, dx=[sm.Symbol('dy'), sm.Symbol('dx')])
- print laplacian.coeffs
-
- df,_ = sg.get_config().symbolic_derivatives()
- user_eqs = {df[0][2] : sm.Symbol('Cx'), df[2][0] : sm.Symbol('Cy')}
- stencil = sg.generate_exact_stencil(origin=1,user_eqs=user_eqs)
- print stencil.coeffs
-
- sg = CenteredStencilGenerator()
- sg.configure(derivative=2)
- for i in xrange(1,4):
- stencil = sg.generate_exact_stencil(order=2*i)
- print stencil.coeffs
+ with printoptions(precision=4):
+ print '\ndim=1, 2nd order first derivative, np.float64, approximative:'
+ for i in xrange(sg.get_config().shape()):
+ stencil = sg.generate_approximative_stencil(origin=i)
+ print ' origin: {} => {} . {}'.format(i, stencil.factor, stencil.coeffs)
+
+ print '\ndim=1, 2nd order first derivative, np.float64, exact:'
+ sg.configure(dtype=MPQ)
+ for i in xrange(sg.get_config().shape()):
+ stencil = sg.generate_exact_stencil(origin=i)
+ print ' origin: {} => {} . {}'.format(i, stencil.factor, stencil.coeffs)
+
+ print '\n 2D Laplacian, 2nd order'
+ sg.configure(dim=2, order=2)
+ laplacian = sg.generate_exact_stencil(origin=1)
+ print laplacian.coeffs
+
+ laplacian = sg.generate_exact_stencil(origin=1, dx=[sm.Symbol('dy'), sm.Symbol('dx')])
+ print '\n',laplacian.coeffs
+
+ df,_ = sg.get_config().symbolic_derivatives()
+ user_eqs = {df[0][2] : sm.Symbol('Cx'), df[2][0] : sm.Symbol('Cy')}
+ stencil = sg.generate_exact_stencil(origin=1,user_eqs=user_eqs)
+ print '\n',stencil.coeffs
+
+ sg = CenteredStencilGenerator()
+ sg.configure(derivative=2)
+ print '\nCentered second order derivative stencils:'
+ for i in xrange(1,4):
+ stencil = sg.generate_approximative_stencil(order=2*i, dtype=np.float16)
+ print ' {}'.format(stencil.coeffs)
+ print
+ for i in xrange(1,4):
+ stencil = sg.generate_approximative_stencil(order=2*i, dtype=MPQ)
+ print ' {}'.format(stencil.coeffs)
+ print
+ for i in xrange(1,4):
+ stencil = sg.generate_exact_stencil(order=2*i)
+ print ' {}'.format(stencil.coeffs)
diff --git a/hysop/numerics/tests/test_update_ghosts.py b/hysop/numerics/tests/test_update_ghosts.py
deleted file mode 100755
index b4cfaf2ee219b5729c2d26d594a25338f51f99a2..0000000000000000000000000000000000000000
--- a/hysop/numerics/tests/test_update_ghosts.py
+++ /dev/null
@@ -1,154 +0,0 @@
-from hysop.numerics.update_ghosts import UpdateGhosts, UpdateGhostsFull
-from hysop.domain.box import Box
-from hysop.fields.continuous import Field
-from hysop.tools.parameters import Discretization
-import numpy as np
-
-
-def _setup(ghosts, topo_dim):
- dom = Box()
-
- f = Field(dom, is_vector=True, name='f')
- resolTopo = Discretization([33, 33, 33], ghosts=ghosts)
- topo = dom.create_topology(resolTopo, dim=topo_dim)
- f.discretize(topo)
- df = f.discreteFields[topo]
- for i, dfd in enumerate(df.data):
- dfd[...] = 0.
- dfd[topo.mesh.compute_index] = 1. * (i + 1)
- return df, topo
-
-
-def verify(df, gh):
- sli = (
- (slice(0, gh[0]), slice(gh[1], -gh[1]), slice(gh[2], -gh[2])),
- (slice(-gh[0], None), slice(gh[1], -gh[1]), slice(gh[2], -gh[2])),
- (slice(gh[0], -gh[0]), slice(0, gh[1]), slice(gh[2], -gh[2])),
- (slice(gh[0], -gh[0]), slice(-gh[1], None), slice(gh[2], -gh[2])),
- (slice(gh[0], -gh[0]), slice(gh[1], -gh[1]), slice(0, gh[2])),
- (slice(gh[0], -gh[0]), slice(gh[1], -gh[1]), slice(-gh[2], None)))
- slni = (
- (slice(0, gh[0]), slice(0, gh[1]), slice(None)),
- (slice(0, gh[0]), slice(None), slice(0, gh[2])),
- (slice(None), slice(0, gh[1]), slice(0, gh[2])),
- (slice(-gh[0], None), slice(-gh[1], None), slice(None)),
- (slice(-gh[0], None), slice(None), slice(-gh[2], None)),
- (slice(None), slice(-gh[1], None), slice(-gh[2], None)))
- for i, dfd in enumerate(df.data):
- for s in sli:
- assert np.max(dfd[s]) == np.min(dfd[s]) and \
- np.max(dfd[s]) == 1. * (i + 1)
- for s in slni:
- assert np.max(dfd[s]) == np.min(dfd[s]) and \
- np.max(dfd[s]) == 0.
-
-
-def verify_full(df, gh):
- for i, dfd in enumerate(df.data):
- for s in ((slice(0, gh[0]), slice(None), slice(None)),
- (slice(-gh[0], None), slice(None), slice(None)),
- (slice(None), slice(0, gh[1]), slice(None)),
- (slice(None), slice(-gh[1], None), slice(None)),
- (slice(None), slice(None), slice(0, gh[2])),
- (slice(None), slice(None), slice(-gh[2], None))):
- assert np.max(dfd[s]) == np.min(dfd[s]) and \
- np.max(dfd[s]) == 1. * (i + 1)
- assert np.max(dfd) == np.min(dfd) and \
- np.max(dfd) == 1. * (i + 1)
-
-
-def test_update_ghosts_simple_1D():
- gh = [1, 1, 1]
- df, topo, = _setup(gh, 1)
- update = UpdateGhosts(topo, 3)
- update(df.data)
- verify(df, gh)
-
-
-def test_update_ghosts_simple_2D():
- gh = [1, 1, 1]
- df, topo, = _setup(gh, 2)
- update = UpdateGhosts(topo, 3)
- update(df.data)
- verify(df, gh)
-
-
-def test_update_ghosts_simple_3D():
- gh = [1, 1, 1]
- df, topo, = _setup(gh, 3)
- update = UpdateGhosts(topo, 3)
- update(df.data)
- verify(df, gh)
-
-
-def test_update_ghosts_1D():
- gh = [2, 3, 4]
- df, topo, = _setup(gh, 1)
- update = UpdateGhosts(topo, 3)
- update(df.data)
- verify(df, gh)
-
-
-def test_update_ghosts_2D():
- gh = [2, 3, 4]
- df, topo, = _setup(gh, 2)
- update = UpdateGhosts(topo, 3)
- update(df.data)
- verify(df, gh)
-
-
-def test_update_ghosts_3D():
- gh = [2, 3, 4]
- df, topo, = _setup(gh, 3)
- update = UpdateGhosts(topo, 3)
- update(df.data)
- verify(df, gh)
-
-
-def test_update_ghosts_full_simple_1D():
- gh = [1, 1, 1]
- df, topo, = _setup(gh, 1)
- update = UpdateGhostsFull(topo, 3)
- update(df.data)
- verify_full(df, gh)
-
-
-def test_update_ghosts_full_simple_2D():
- gh = [1, 1, 1]
- df, topo, = _setup(gh, 2)
- update = UpdateGhostsFull(topo, 3)
- update(df.data)
- verify_full(df, gh)
-
-
-def test_update_ghosts_full_simple_3D():
- gh = [1, 1, 1]
- df, topo, = _setup(gh, 3)
- update = UpdateGhostsFull(topo, 3)
- update(df.data)
- verify_full(df, gh)
-
-
-def test_update_ghosts_full_1D():
- gh = [2, 3, 4]
- df, topo, = _setup(gh, 1)
- update = UpdateGhostsFull(topo, 3)
- update(df.data)
- verify_full(df, gh)
-
-
-def test_update_ghosts_full_2D():
- gh = [2, 3, 4]
- df, topo, = _setup(gh, 2)
- update = UpdateGhostsFull(topo, 3)
- update(df.data)
- verify_full(df, gh)
-
-
-def test_update_ghosts_full_3D():
- gh = [2, 3, 4]
- df, topo, = _setup(gh, 3)
- update = UpdateGhostsFull(topo, 3)
- update(df.data)
- verify_full(df, gh)
-
diff --git a/hysop/gpu/QtRendering.py b/hysop/old/gpu.old/QtRendering.py
similarity index 95%
rename from hysop/gpu/QtRendering.py
rename to hysop/old/gpu.old/QtRendering.py
index 305d42d2bdc4d18c9706201405391fcf7b5691fb..27b9d310f0c259b776edd25e254f9f3da253a94a 100644
--- a/hysop/gpu/QtRendering.py
+++ b/hysop/old/gpu.old/QtRendering.py
@@ -8,13 +8,13 @@ import sys
from PyQt4 import QtGui, QtCore
from PyQt4.QtOpenGL import QGLWidget
import OpenGL.GL as gl
-from hysop.gpu.tools import get_opengl_shared_environment
-from hysop.gpu import cl
-from hysop.gpu.gpu_discrete import GPUDiscreteField
-from hysop.gpu.gpu_kernel import KernelLauncher
-from hysop.mpi import main_rank
+from hysop.backend.device.opencl.opencl_tools import get_opengl_shared_environment
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.core.mpi import main_rank
from hysop.operator.computational import Computational
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
class QtOpenGLRendering(Computational):
@@ -73,8 +73,8 @@ class QtOpenGLRendering(Computational):
Pass buffers to QGLWidget and compile OpenCL kernels.
"""
## GPU scalar field
- for df in self.variables[0].discreteFields.values():
- if isinstance(df, GPUDiscreteField):
+ for df in self.variables[0].discrete_fields.values():
+ if isinstance(df, OpenClDiscreteField):
self.gpu_field = df
# Create OpenGL VBOs
## VBO for coordinates
@@ -138,11 +138,11 @@ class QtOpenGLRendering(Computational):
gwi = self.gpu_field.data[self.component].shape
else:
gwi = self.gpu_field.data[0].shape
- self.initCoordinates = KernelLauncher(
+ self.initCoordinates = OpenClKernelLauncher(
self.prg.initPointCoordinates, self.window.widget.cl_env.queue,
gwi, None)
## OpenCL kernel for computing colors
- self.numMethod = KernelLauncher(
+ self.numMethod = OpenClKernelLauncher(
self.prg.colorize, self.window.widget.cl_env.queue,
gwi, None)
diff --git a/hysop/old/gpu.old/__init__.py b/hysop/old/gpu.old/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..8100c6042e1580efbffda9c752ade8bd27434272
--- /dev/null
+++ b/hysop/old/gpu.old/__init__.py
@@ -0,0 +1,97 @@
+"""Everything concerning GPU in hysop.
+
+OpenCL sources are located in the cl_src directory and organized as follows
+ - kernels/
+ Contains kernels src
+ - advection.cl
+ - remeshing.cl
+ - advection_and_remeshing.cl
+ - rendering.cl
+ Functions used by kernels
+ - advection/
+ - builtin.cl
+ - builtin_noVec.cl
+ - remeshing/
+ - basic.cl
+ - basic_noVec.cl
+ - private.cl
+ - weights.cl
+ - weights_builtin.cl
+ - weights_noVec.cl
+ - weights_noVec_builtin.cl
+ - common.cl
+
+Some sources are parsed at build to handle several OpenCL features.
+Other sources are generated and optimized at runtime.
+see hysop.gpu.tools.parse_file
+see hysop.backend.device.codegen
+
+"""
+import os
+import pyopencl
+import pyopencl.tools
+import pyopencl.array
+import pyopencl.characterize
+import pyopencl.reduction
+import pyopencl.clrandom
+import pyopencl.elementwise
+import pyopencl.scan
+
+from hysop import __DEFAULT_PLATFORM_ID__, __DEFAULT_DEVICE_ID__, __VERBOSE__
+
+## open cl underlying implementation
+cl = pyopencl
+"""open cl underlying implementation"""
+
+clTools = pyopencl.tools
+"""PyOpencl tools"""
+
+clArray = pyopencl.array
+"""PyOpenCL arrays"""
+
+clRandom = pyopencl.clrandom
+"""PyOpenCL random"""
+
+clReduction = pyopencl.reduction
+"""PyOpenCL reductions"""
+
+clScan = pyopencl.scan
+"""PyOpenCL scan"""
+
+clElementwise = pyopencl.elementwise
+"""PyOpenCL reductions"""
+
+clCharacterize = pyopencl.characterize
+"""PyOpenCL characterize"""
+
+GPU_SRC = os.path.join(__path__[0], "cl_src", '')
+"""Default path to cl kernels source files"""
+
+KERNEL_DUMP_FOLDER='generated_kernels'
+"""Default folder to dump debug opencl kernel sources"""
+
+CL_PROFILE = False
+"""Boolean, true to enable OpenCL profiling events to time computations"""
+
+if __DEFAULT_PLATFORM_ID__ < len(cl.get_platforms()):
+ default_cl_platform = cl.get_platforms()[__DEFAULT_PLATFORM_ID__]
+else:
+ default_cl_platform = cl.get_platforms()[0]
+ msg= 'Warning: default opencl platform not available,'
+ msg+=' switched to platform {}.'.format(default_cl_platform.name)
+ print msg
+
+if __DEFAULT_DEVICE_ID__ < len(default_cl_platform.get_devices()):
+ default_cl_device = default_cl_platform.get_devices()[__DEFAULT_DEVICE_ID__]
+else:
+ default_cl_device = default_cl_platform.get_devices()[0]
+ msg= 'Warning: default device not available,'
+ msg+=' switched to device {}.'.format(default_cl_device.name)
+ print msg
+
+default_cl_context = cl.Context(devices=[default_cl_device])
+default_cl_queue = cl.CommandQueue(context=default_cl_context, device=default_cl_device)
+
+default_cl_allocator = clTools.ImmediateAllocator(queue=default_cl_queue,
+ mem_flags=cl.mem_flags.READ_WRITE)
+default_cl_pool = clTools.MemoryPool(default_cl_allocator)
diff --git a/hysop/old/gpu.old/cl_src/advection/basic_rk2.cl b/hysop/old/gpu.old/cl_src/advection/basic_rk2.cl
new file mode 100644
index 0000000000000000000000000000000000000000..559638ff61919ef65d8a5e6c6013320f56976495
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/basic_rk2.cl
@@ -0,0 +1,72 @@
+/**
+ * @file advection/basic.cl
+ * Advection function, vectorized version, no use of builtins functions.
+ */
+
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity cache.
+ * @return Particle position.
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ */
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float__N__ v, /* Velocity at point */
+ vp, /* Velocity at right point */
+ p, /* Intermediary position */
+ c, /* initial coordinate */
+ hdt = (float__N__)(0.5*dt); /* half time step */
+ int__N__ i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+ c = (float__N__)((i+__NN__)*mesh->dx.x,
+ );
+ c = c + mesh->min_position;
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ v = (float__N__)(velocity_cache[noBC_id(i+__NN__)],
+ );
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ v = (p*(vp-v) + v);
+#endif
+
+ p = (c + hdt * v) * mesh->v_invdx;
+
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ v = (p*(vp-v) + v);
+
+ return c + dt * v;
+}
diff --git a/hysop/old/gpu.old/cl_src/advection/basic_rk2_noVec.cl b/hysop/old/gpu.old/cl_src/advection/basic_rk2_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..a635dd9d4d064de1157d853e2758b0f18d1eeb7f
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/basic_rk2_noVec.cl
@@ -0,0 +1,63 @@
+/**
+ * @file advection/basic_noVec.cl
+ * Advection function, basic version
+ */
+
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param gvelo Global velocity field.
+ * @return Particle position
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ */
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float v, /* Velocity at point */
+ vp, /* Velocity at right point */
+ p, /* Normalized intermediary position */
+ c = i * mesh->dx.x + mesh->min_position, /* initial coordinate */
+ hdt = 0.5 * dt; /* half time step */
+ int i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ v = velocity_cache[noBC_id(i)]; /* k = k1 */
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+#endif
+
+ p = (c + hdt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+
+ v = velocity_cache[noBC_id(i_ind)];
+ vp = velocity_cache[noBC_id(i_ind_p)];
+ v = (p*(vp-v) + v);
+
+ return c + dt * v;
+}
+/* Operations number : */
+/* - 2 positions = 2 * 2 */
+/* - 1 iterpolation = 9 */
+/* Total = 13 */
diff --git a/hysop/old/gpu.old/cl_src/advection/basic_rk4.cl b/hysop/old/gpu.old/cl_src/advection/basic_rk4.cl
new file mode 100644
index 0000000000000000000000000000000000000000..853873ba47e171acfffef036b37c7eafd72388ac
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/basic_rk4.cl
@@ -0,0 +1,109 @@
+/**
+ * @file basic_rk4.cl
+ * Advection function (RK4 scheme), vectorized version, no use of builtins functions.
+ */
+
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity cache.
+ * @return Particle position.
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ */
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float__N__ v, /* Velocity at point */
+ vp, /* Velocity at right point */
+ p, /* Intermediary position */
+ k, /* rk averaged velocity */
+ kn, /* rk intermediate velocity */
+ c, /* initial coordinate */
+ hdt = (float__N__)(0.5*dt); /* half time step */
+ int__N__ i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+ c = (float__N__)((i+__NN__)*mesh->dx.x,
+ );
+ c = c + mesh->min_position;
+
+ //k1 = f(t,y)
+ //k2 = f(t + dt/2, y + dt/2 * k1)
+ //k3 = f(t + dt/2, y + dt/2 * k2)
+ //k4 = f(t + dt, y + dt * k3)
+ //result = y + dt/6( k1 + 2 * k2 + 2 * k3 + k4)
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ k = (float__N__)(velocity_cache[noBC_id(i+__NN__)],
+ );
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ k = p*(vp-v) + v;
+#endif
+
+ p = (c + hdt * k) * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ kn = p*(vp-v) + v;
+
+ k += 2.0 * kn;
+
+ p = (c + hdt * kn) * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ kn = p*(vp-v) + v;
+
+ k += 2.0 * kn;
+
+ p = (c + dt * kn) * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ kn = p*(vp-v) + v;
+
+ k += kn;
+
+
+ return c + (float__N__)(dt *0.16666666666666666) * k;
+}
diff --git a/hysop/old/gpu.old/cl_src/advection/basic_rk4_noVec.cl b/hysop/old/gpu.old/cl_src/advection/basic_rk4_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..7b7d4b2752c7611d3c58c0eddfd08ca78fdc58a6
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/basic_rk4_noVec.cl
@@ -0,0 +1,93 @@
+/**
+ * @file basic_rk4_noVec.cl
+ * Advection function (RK4 scheme), basic version
+ */
+
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity field.
+ * @return Particle position
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ */
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float v, /* Velocity at point */
+ vp, /* Velocity at right point */
+ p, /* Intermediary position */
+ k, /* rk averaged velocity */
+ kn, /* rk intermediate velocity */
+ c = i * mesh->dx.x + mesh->min_position, /* initial coordinate */
+ hdt = 0.5 * dt; /* half time step */
+ int i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+ //k1 = f(t,y)
+ //k2 = f(t + dt/2, y + dt/2 * k1)
+ //k3 = f(t + dt/2, y + dt/2 * k2)
+ //k4 = f(t + dt, y + dt * k3)
+ //result = y + dt/6( k1 + 2 * k2 + 2 * k3 + k4)
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ k = velocity_cache[noBC_id(i)]; /* k = k1 */
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ k = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+#endif
+
+ p = (c + hdt * k) * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = velocity_cache[noBC_id(i_ind)];
+ vp = velocity_cache[noBC_id(i_ind_p)];
+ kn = p*(vp-v) + v; /* kn = k2 */
+
+ k += 2.0 * kn; /* k = k1 + 2*k2 */
+
+ p = (c + hdt * kn) * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = velocity_cache[noBC_id(i_ind)];
+ vp = velocity_cache[noBC_id(i_ind_p)];
+ kn = p*(vp-v) + v; /* kn = k3 */
+
+ k += 2.0 * kn; /* k = k1 + 2*k2 + 2*k3 */
+
+ p = (c + dt * kn) * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = velocity_cache[noBC_id(i_ind)];
+ vp = velocity_cache[noBC_id(i_ind_p)];
+ kn = p*(vp-v) + v; /* kn = k4 */
+
+ k += kn; /* k = k1 + 2*k2 + 2*k3 + k4 */
+
+ return c + dt * k*0.16666666666666666;
+}
+/* Operations number : */
+/* - 4 positions = 4 * 2 + 3 */
+/* - 3 iterpolation = 3 * 9 */
+/* - velocity weights = 5*/
+/* Total = 41 */
diff --git a/hysop/old/gpu.old/cl_src/advection/builtin_euler_noVec.cl b/hysop/old/gpu.old/cl_src/advection/builtin_euler_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..aecb5ff383230c6c454733a3ebb564acba7c7e7f
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/builtin_euler_noVec.cl
@@ -0,0 +1,51 @@
+/**
+ * @file builtin_noVec.cl
+ * Advection function, basic version
+ */
+
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity field.
+ * @return Particle position
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ */
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float v, /* Velocity at point */
+ c = fma(i, mesh->dx.x, mesh->min_position); /* initial coordinate */
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ v = velocity_cache[noBC_id(i)];
+#else
+ float p;
+ int i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+#endif
+
+ return fma(dt, v, c);
+}
+/* Operations number : */
+/* - 3 positions = 3 * fma */
+/* - 1 iterpolation = 2 + 1 * mix */
+/* - dt/2 = 1 */
+/* 1mix <=> 3flop : mix(x,y,a) = x+(y-x)*a */
+/* Total = 3 fma + 1 mix + 3 = 12flop */
diff --git a/hysop/old/gpu.old/cl_src/advection/builtin_rk2.cl b/hysop/old/gpu.old/cl_src/advection/builtin_rk2.cl
new file mode 100644
index 0000000000000000000000000000000000000000..c45d5cee4b78861d35ecb891efc51a3116bbc1af
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/builtin_rk2.cl
@@ -0,0 +1,68 @@
+/**
+ * @file builtin.cl
+ * Advection function, vectorized version.
+ */
+
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity cache.
+ * @return Particle position.
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ */
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float__N__ v, /* Velocity at point */
+ vp, /* Velocity at right point */
+ p, /* Intermediary position */
+ c, /* initial coordinate */
+ hdt = (float__N__)(0.5*dt); /* half time step */
+ int__N__ i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+ c = (float__N__)((i+__NN__)*mesh->dx.x,
+ );
+ c = c + mesh->min_position;
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ v = (float__N__)(velocity_cache[noBC_id(i+__NN__)],
+ );
+ p = fma(hdt, v, c) * mesh->v_invdx;
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ p = fma(hdt, mix(v,vp,p), c) * v_invdx;
+#endif
+
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ return fma(mix(v,vp,p),dt,c);
+}
diff --git a/hysop/old/gpu.old/cl_src/advection/builtin_rk2_noVec.cl b/hysop/old/gpu.old/cl_src/advection/builtin_rk2_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..415eec1d1b257836c576b6928015c5dabb2c41a2
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/builtin_rk2_noVec.cl
@@ -0,0 +1,62 @@
+/**
+ * @file builtin_noVec.cl
+ * Advection function, basic version
+ */
+
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity field.
+ * @return Particle position
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ */
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float v, /* Velocity at point */
+ p, /* Intermediary position */
+ c = i*mesh->dx.x, //fma(i, mesh->dx.x, mesh->min_position), /* initial coordinate */
+ hdt = 0.5 * dt; /* half time step */
+ int i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ v = velocity_cache[noBC_id(i)];
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+#endif
+
+ p = fma(hdt, v, c) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+
+ return fma(dt, v, c) + mesh->min_position;
+}
+/* Operations number : */
+/* - 3 positions = 3 * fma */
+/* - 1 iterpolation = 2 + 1 * mix */
+/* - dt/2 = 1 */
+/* 1mix <=> 3flop : mix(x,y,a) = x+(y-x)*a */
+/* Total = 3 fma + 1 mix + 3 = 12flop */
diff --git a/hysop/old/gpu.old/cl_src/advection/builtin_rk4.cl b/hysop/old/gpu.old/cl_src/advection/builtin_rk4.cl
new file mode 100644
index 0000000000000000000000000000000000000000..2dcc7dc1e77817fa753a0cc48a15929f03e360f9
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/builtin_rk4.cl
@@ -0,0 +1,103 @@
+/**
+ * @file builtin_rk4.cl
+ * Advection function, vectorized version.
+ */
+
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity cache.
+ * @return Particle position.
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ */
+float__N__ advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float__N__ v, /* Velocity at point */
+ vp, /* Velocity at right point */
+ p, /* Intermediary position */
+ k, /* rk averaged velocity */
+ kn, /* rk intermediate velocity */
+ c, /* initial coordinate */
+ hdt = (float__N__)(0.5*dt); /* half time step */
+ int__N__ i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+ c = (float__N__)((i+__NN__)*mesh->dx.x,
+ );
+ c = c + mesh->min_position;
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ v = (float__N__)(velocity_cache[noBC_id(i+__NN__)],
+ );
+ p = fma(hdt, v, c) * mesh->v_invdx;
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ p = fma(hdt, mix(v,vp,p), c) * mesh->v_invdx;
+#endif
+
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ kn = mix(v,vp,p);
+
+ k += 2.0 * kn;
+
+ p = fma(hdt, kn, c) * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ kn = mix(v,vp,p);
+
+ k += 2.0 * kn;
+
+ p = fma((float__N__)(dt), kn, c) * mesh->v_invdx;
+ i_ind = convert_int__N___rtn(p);
+ p = p - convert_float__N__(i_ind);
+
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ v = (float__N__)(velocity_cache[noBC_id(i_ind.s__NN__)],
+ );
+ vp = (float__N__)(velocity_cache[noBC_id(i_ind_p.s__NN__)],
+ );
+ kn = mix(v,vp,p);
+
+ k += kn;
+
+
+ return fma(k,(float__N__)(dt*0.16666666666666666),c);
+}
diff --git a/hysop/old/gpu.old/cl_src/advection/builtin_rk4_noVec.cl b/hysop/old/gpu.old/cl_src/advection/builtin_rk4_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..170fa90c81026c26b8e61396a0e14c8b471d4d91
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/builtin_rk4_noVec.cl
@@ -0,0 +1,90 @@
+/**
+ * @file builtin_rk4_noVec.cl
+ * Advection function, basic version
+ */
+
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity field.
+ * @return Particle position
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ */
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float p, /* Intermediary position */
+ k, /* rk averaged velocity */
+ kn, /* rk intermediate velocity */
+ c = fma(i, mesh->dx.x, mesh->min_position), /* initial coordinate */
+ hdt = 0.5 * dt; /* half time step */
+ int i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+ //k1 = f(t,y)
+ //k2 = f(t + dt/2, y + dt/2 * k1)
+ //k3 = f(t + dt/2, y + dt/2 * k2)
+ //k4 = f(t + dt, y + dt * k3)
+ //result = y + dt/6( k1 + 2 * k2 + 2 * k3 + k4)
+
+#if !(ADVEC_IS_MULTISCALE)
+ // single-scale:
+ k = velocity_cache[noBC_id(i)]; /* k = k1 */
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind + V_GHOSTS_NB;
+ i_ind_p = i_ind + 1;
+ k = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+#endif
+
+ p = fma(hdt, k, c) * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ kn = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p); /* kn = k2 */
+
+ k += 2.0 * kn; /* k = k1 + 2*k2 */
+
+ p = fma(hdt, kn, c) * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ kn = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p); /* kn = k3 */
+
+ k += 2.0 * kn; /* k = k1 + 2*k2 + 2*k3 */
+
+ p = fma(dt, kn, c) * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = ((i_ind + V_GHOSTS_NB + V_NB_I) % V_NB_I);
+ i_ind_p = ((i_ind + 1) % V_NB_I);
+ kn = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p); /* kn = k4 */
+
+ k += kn; /* k = k1 + 2*k2 + 2*k3 + k4 */
+
+ return fma(k, dt*0.16666666666666666, c);
+}
+
+/* Operations number : */
+/* - 5 positions = 5 * fma*/
+/* - 3 iterpolation = 3 * (1 * mix + 2) */
+/* - velocity weights = 7 */
+/* - dt/2, dt/6 = 2 */
+/* Total = 5 fma + 3 mix + 13 = 32flop */
diff --git a/hysop/old/gpu.old/cl_src/advection/comm_basic_rk2_noVec.cl b/hysop/old/gpu.old/cl_src/advection/comm_basic_rk2_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..037d19052fe5b1627b36080d852a9100cbd024bb
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/comm_basic_rk2_noVec.cl
@@ -0,0 +1,74 @@
+/**
+ * @file advection/comm_basic_noVec.cl
+ * Advection function, basic version, mpi communications on the host side
+ */
+
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix.
+ *
+ * @param i Particle index.
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity field.
+ * @return Particle position
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ * @remark T_NB_I: global points number in the 1st direction (mpi cutted direction)
+ * @remark START_INDEX Global staring index for computational points
+ * @remark STOP_INDEX Global stop index for computational points
+ */
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float v, /* Velocity at point */
+ vp, /* Velocity at right point */
+ p, /* Normalized intermediary position */
+ c = i * mesh->dx.x + mesh->min_position, /* initial coordinate */
+ hdt = 0.5 * dt; /* half time step */
+ int i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+#if (V_NB_I-2*V_GHOSTS_NB) == NB_I
+ // single-scale:
+ v = velocity_cache[noBC_id(i + V_GHOSTS_NB)]; /* k = k1 */
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB);
+ i_ind_p = i_ind + 1;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+#endif
+ p = (c + hdt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p);
+ if( i_ind>=(V_START_INDEX-MS_INTERPOL_SHIFT) && i_ind < (V_STOP_INDEX-V_GHOSTS_NB))
+ {
+ p = p - convert_float(i_ind);
+
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB);
+ i_ind_p = i_ind + 1;
+
+ v = velocity_cache[noBC_id(i_ind)];
+ vp = velocity_cache[noBC_id(i_ind_p)];
+ v = (p*(vp-v) + v);
+
+ p = c + dt * v;
+ }
+ else
+ {
+ p = (1000*T_NB_I)*1.0 + p;
+ }
+
+ return p;
+}
+/* Operations number : */
+/* - 2 positions = 2 * 2 */
+/* - 1 iterpolation = 9 */
+/* Total = 13 */
diff --git a/hysop/old/gpu.old/cl_src/advection/comm_builtin_rk2_noVec.cl b/hysop/old/gpu.old/cl_src/advection/comm_builtin_rk2_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..a9a717f8088de07317e5eac2c46d787442880f0f
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/comm_builtin_rk2_noVec.cl
@@ -0,0 +1,72 @@
+/**
+ * @file comm_builtin_noVec.cl
+ * Advection function, basic version, mpi communications on the host side
+ */
+
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Compute the position of a particle with a RK2 integration scheme. Velocity is linearly interpolated from the global field.
+ * Use of builtin OpenCL functions fma and mix.
+ *
+ * @param i Particle index (without velocity ghosts considering).
+ * @param dt Time step.
+ * @param dx Space step.
+ * @param invdx 1/dx.
+ * @param velocity_cache Local velocity field.
+ * @return Particle position
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ * @remark T_NB_I: global points number in the 1st direction (mpi cutted direction)
+ * @remark START_INDEX Global staring index for computational points
+ * @remark STOP_INDEX Global stop index for computational points
+ */
+float advection(uint i, float dt, __local float* velocity_cache, __constant struct AdvectionMeshInfo* mesh)
+{
+ float v, /* Velocity at point */
+ p, /* Intermediary position */
+ c = i * dx + min_position, /* initial coordinate */
+ hdt = 0.5 * dt; /* half time step */
+ int i_ind, /* Interpolation left point */
+ i_ind_p; /* Interpolation right point */
+
+#if (V_NB_I-2*V_GHOSTS_NB) == NB_I
+ // single scale:
+ v = velocity_cache[noBC_id(i + V_GHOSTS_NB)];
+#else
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB);
+ i_ind_p = i_ind + 1;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+#endif
+
+ p = fma(hdt, v, c) * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ if( i_ind>=(V_START_INDEX-MS_INTERPOL_SHIFT) && i_ind < (V_STOP_INDEX-V_GHOSTS_NB))
+ {
+ p = p - convert_float(i_ind);
+
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB);
+ i_ind_p = i_ind + 1;
+
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind_p)],p);
+
+ p = fma(dt, v, c);
+ }
+ else
+ {
+ p = (1000*T_NB_I)*1.0 + p;
+ }
+
+ return p;
+}
+/* Operations number : */
+/* - 2 positions = 2 * fma */
+/* - 1 iterpolation = 6 + 1 * mix */
+/* Total = 2 fma + 1 mix + 6 */
diff --git a/hysop/old/gpu.old/cl_src/advection/velocity_cache.cl b/hysop/old/gpu.old/cl_src/advection/velocity_cache.cl
new file mode 100644
index 0000000000000000000000000000000000000000..6fd4ae6e6046ca8d3db8c2472c18b0dcd7483ad9
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/velocity_cache.cl
@@ -0,0 +1,217 @@
+void fill_velocity_cache(__global const float* gvelo,
+ uint gidX, uint gidY, uint gidZ,
+ __local float* gvelo_loc,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh);
+
+void fill_velocity_cache(__global const float* gvelo,
+ uint gidX, uint gidY, uint gidZ,
+ __local float* velocity_cache,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint i;
+ float__N__ v;
+#if !(ADVEC_IS_MULTISCALE)
+ // Single scale : Velocity and scalar grids are identical : cache is just read from global
+ uint line_index = gidY*V_NB_I + gidZ*V_NB_I*V_NB_II; /* Current 1D problem index */
+ for(i=gidX*__N__; i<V_NB_I; i+=(WI_NB*__N__))
+ {
+ /* Read velocity */
+ v = vload__N__((i+line_index)/__N__, gvelo);
+ /* Fill the cache */
+ velocity_cache[noBC_id(i+__NN__)] = v.s__NN__;
+ }
+#else
+ // Multi-scale: Velocity cache is interpolated from global
+
+#if NB_III == 1
+ // 2D case
+
+
+ float line_posY, hY;
+ int indY;
+#if MS_FORMULA == MS_LINEAR
+ int2 v_line_index;
+ float2 wY;
+#elif MS_FORMULA == MS_L2_1
+ int4 v_line_index;
+ float4 wY;
+#elif MS_FORMULA == MS_L4_2 || MS_FORMULA == MS_L4_4
+ // Only the 6 first elements will be used
+ int8 v_line_index;
+ float8 wY;
+#endif
+
+ line_posY = (gidY * mesh->dx.y) * inv_v_dx_y;// mesh->v_dx.y;
+ indY = convert_int_rtn(line_posY);
+ hY = line_posY - convert_float(indY);
+
+#if MS_FORMULA == MS_LINEAR
+ wY.s1 = hY;
+ wY.s0 = 1.0 - wY.s1;
+#else
+ wY.s0 = MS_INTERPOL(alpha)(hY);
+ wY.s1 = MS_INTERPOL(beta)(hY);
+ wY.s2 = MS_INTERPOL(gamma)(hY);
+#if MS_INTERPOL_SHIFT > 1
+ wY.s3 = MS_INTERPOL(delta)(hY);
+ wY.s4 = MS_INTERPOL(eta)(hY);
+ wY.s5 = 1.0 - wY.s0 - wY.s1 - wY.s2 - wY.s3 - wY.s4;
+#else
+ wY.s3 = 1.0 - wY.s0 - wY.s1 - wY.s2;
+#endif
+#endif
+
+ indY = indY + V_GHOSTS_NB - MS_INTERPOL_SHIFT;
+
+ v_line_index.s0 = indY * V_NB_I;
+ v_line_index.s1 = (indY + 1) * V_NB_I;
+#if MS_INTERPOL_SHIFT > 0
+ v_line_index.s2 = (indY + 2) * V_NB_I;
+ v_line_index.s3 = (indY + 3) * V_NB_I;
+#elif MS_INTERPOL_SHIFT > 1
+ v_line_index.s4 = (indY + 4) * V_NB_I;
+ v_line_index.s5 = (indY + 5) * V_NB_I;
+#endif
+
+ for(i=gidX*__N__; i<V_NB_I; i+=(WI_NB*__N__))
+ {
+ gvelo_loc[noBC_id(i)] = wY.s0 * gvelo[i + v_line_index.s0];
+ gvelo_loc[noBC_id(i)] += wY.s1 * gvelo[i + v_line_index.s1];
+#if MS_INTERPOL_SHIFT > 0
+ gvelo_loc[noBC_id(i)] += wY.s2 * gvelo[i + v_line_index.s2];
+ gvelo_loc[noBC_id(i)] += wY.s3 * gvelo[i + v_line_index.s3];
+#elif MS_INTERPOL_SHIFT > 1
+ gvelo_loc[noBC_id(i)] += wY.s4 * gvelo[i + v_line_index.s4];
+ gvelo_loc[noBC_id(i)] += wY.s5 * gvelo[i + v_line_index.s5];
+#endif
+ }
+
+#else
+ // 3D case
+
+
+ float line_posY, hY;
+ float line_posZ, hZ;
+ int indY, indZ;
+#if MS_FORMULA == MS_LINEAR
+ int2 v_line_indexY, v_line_indexZ;
+ float2 wY, wZ;
+#elif MS_FORMULA == MS_L2_1
+ int4 v_line_indexY, v_line_indexZ;
+ float4 wY, wZ;
+#elif MS_FORMULA == MS_L4_2 || MS_FORMULA == MS_L4_4
+ int8 v_line_indexY, v_line_indexZ;
+ float8 wY, wZ;
+#endif
+
+ line_posY = (gidY * mesh->dx.y) * inv_v_dx_y;// mesh->v_dx.y;
+ line_posZ = (gidZ * mesh->dx.z) * inv_v_dx_z;// mesh->v_dx.z;
+ indY = convert_int_rtn(line_posY);
+ indZ = convert_int_rtn(line_posZ);
+ hY = line_posY - convert_float(indY);
+ hZ = line_posZ - convert_float(indZ);
+
+#if MS_FORMULA == MS_LINEAR
+ wY.s1 = hY;
+ wY.s0 = 1.0 - wY.s1;
+ wZ.s1 = hZ;
+ wZ.s0 = 1.0 - wZ.s1;
+#else
+ wY.s0 = MS_INTERPOL(alpha)(hY);
+ wY.s1 = MS_INTERPOL(beta)(hY);
+ wY.s2 = MS_INTERPOL(gamma)(hY);
+ wZ.s0 = MS_INTERPOL(alpha)(hZ);
+ wZ.s1 = MS_INTERPOL(beta)(hZ);
+ wZ.s2 = MS_INTERPOL(gamma)(hZ);
+#if MS_INTERPOL_SHIFT > 1
+ wY.s3 = MS_INTERPOL(delta)(hY);
+ wY.s4 = MS_INTERPOL(eta)(hY);
+ wY.s5 = 1.0 - wY.s0 - wY.s1 - wY.s2 - wY.s3 - wY.s4;
+ wZ.s3 = MS_INTERPOL(delta)(hZ);
+ wZ.s4 = MS_INTERPOL(eta)(hZ);
+ wZ.s5 = 1.0 - wZ.s0 - wZ.s1 - wZ.s2 - wZ.s3 - wZ.s4;
+#else
+ wY.s3 = 1.0 - wY.s0 - wY.s1 - wY.s2;
+ wZ.s3 = 1.0 - wZ.s0 - wZ.s1 - wZ.s2;
+#endif
+#endif
+
+ indY = indY + V_GHOSTS_NB - MS_INTERPOL_SHIFT;
+ indZ = indZ + V_GHOSTS_NB - MS_INTERPOL_SHIFT;
+
+ v_line_indexY.s0 = indY * V_NB_I;
+ v_line_indexY.s1 = (indY + 1) * V_NB_I;
+ v_line_indexZ.s0 = indZ * V_NB_I * V_NB_II;
+ v_line_indexZ.s1 = (indZ + 1) * V_NB_I * V_NB_II;
+#if MS_INTERPOL_SHIFT > 0
+ v_line_indexY.s2 = (indY + 2) * V_NB_I;
+ v_line_indexY.s3 = (indY + 3) * V_NB_I;
+ v_line_indexZ.s2 = (indZ + 2) * V_NB_I * V_NB_II;
+ v_line_indexZ.s3 = (indZ + 3) * V_NB_I * V_NB_II;
+#elif MS_INTERPOL_SHIFT > 1
+ v_line_indexY.s4 = (indY + 4) * V_NB_I;
+ v_line_indexY.s5 = (indY + 5) * V_NB_I;
+ v_line_indexZ.s4 = (indZ + 4) * V_NB_I * V_NB_II;
+ v_line_indexZ.s5 = (indZ + 5) * V_NB_I * V_NB_II;
+#endif
+
+
+ for(i=gidX*__N__; i<V_NB_I; i+=(WI_NB*__N__))
+ {
+ gvelo_loc[noBC_id(i)] = wY.s0 * wZ.s0 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s1 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s0 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s1 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s1];
+#if MS_INTERPOL_SHIFT > 0
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s2 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s3 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s3];
+
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s2 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s3 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s3];
+
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s0 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s1 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s2 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s3 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s3];
+
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s0 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s1 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s2 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s3 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s3];
+#elif MS_INTERPOL_SHIFT > 1
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s4 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s5 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s4 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s5 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s4 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s5 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s4 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s5 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s0 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s1 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s2 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s3 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s3];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s4 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s5 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s0 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s1 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s2 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s3 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s3];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s4 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s5 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s5];
+#endif
+ }
+#endif
+#endif
+}
diff --git a/hysop/old/gpu.old/cl_src/advection/velocity_cache_noVec.cl b/hysop/old/gpu.old/cl_src/advection/velocity_cache_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..1677b2546e42b36ebc28dacf7288989461c9c559
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/advection/velocity_cache_noVec.cl
@@ -0,0 +1,231 @@
+void fill_velocity_cache(__global const float* gvelo,
+ uint gidX, uint gidY, uint gidZ,
+ __local float* gvelo_loc,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh);
+
+void fill_velocity_cache(__global const float* gvelo,
+ uint gidX, uint gidY, uint gidZ,
+ __local float* gvelo_loc,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint i;
+
+ // ********************************
+ // ** Single Scale
+ // ********************************
+#if !(ADVEC_IS_MULTISCALE)
+ // Single scale : Velocity and scalar grids are identical : cache is just read from global
+ uint line_index = gidY*V_NB_I + gidZ*V_NB_I*V_NB_II; /* Current 1D problem index */
+ for(i=gidX; i<V_NB_I; i+=(WI_NB))
+ {
+ /* Read velocity */
+ /* Fill velocity cache */
+ gvelo_loc[noBC_id(i)] = gvelo[i+line_index];
+ }
+
+ // ********************************
+ // ** Multi-Scale
+ // ********************************
+ // Velocity cache is interpolated from global memory
+#else
+
+
+#if NB_III == 1
+ // Multi-Scale (2D)
+
+ float line_posY, hY;
+ int indY;
+#if MS_FORMULA == LINEAR
+ int2 v_line_index;
+ float2 wY;
+#elif MS_FORMULA == L2_1
+ int4 v_line_index;
+ float4 wY;
+#elif MS_FORMULA == L4_2 || MS_FORMULA == L4_4
+ // Only the 6 first elements will be used
+ int8 v_line_index;
+ float8 wY;
+#endif
+
+ line_posY = (gidY * mesh->dx.y) * inv_v_dx_y; // mesh->v_dx.y;
+ indY = convert_int_rtn(line_posY);
+ hY = line_posY - convert_float(indY);
+
+
+#if MS_FORMULA == LINEAR
+ wY.s1 = hY;
+ wY.s0 = 1.0 - wY.s1;
+#else
+ wY.s0 = MS_INTERPOL(alpha)(hY);
+ wY.s1 = MS_INTERPOL(beta)(hY);
+ wY.s2 = MS_INTERPOL(gamma)(hY);
+#if MS_INTERPOL_SHIFT > 1
+ wY.s3 = MS_INTERPOL(delta)(hY);
+ wY.s4 = MS_INTERPOL(eta)(hY);
+ wY.s5 = 1.0 - wY.s0 - wY.s1 - wY.s2 - wY.s3 - wY.s4;
+#else
+ wY.s3 = 1.0 - wY.s0 - wY.s1 - wY.s2;
+#endif
+#endif
+
+ indY = indY + V_GHOSTS_NB - MS_INTERPOL_SHIFT;
+
+ v_line_index.s0 = indY * V_NB_I;
+ v_line_index.s1 = (indY + 1) * V_NB_I;
+#if MS_INTERPOL_SHIFT > 0
+ v_line_index.s2 = (indY + 2) * V_NB_I;
+ v_line_index.s3 = (indY + 3) * V_NB_I;
+#elif MS_INTERPOL_SHIFT > 1
+ v_line_index.s4 = (indY + 4) * V_NB_I;
+ v_line_index.s5 = (indY + 5) * V_NB_I;
+#endif
+
+
+ for(i=gidX; i<V_NB_I; i+=(WI_NB)){
+ gvelo_loc[noBC_id(i)] = wY.s0 * gvelo[i + v_line_index.s0];
+ gvelo_loc[noBC_id(i)] += wY.s1 * gvelo[i + v_line_index.s1];
+#if MS_INTERPOL_SHIFT > 0
+ gvelo_loc[noBC_id(i)] += wY.s2 * gvelo[i + v_line_index.s2];
+ gvelo_loc[noBC_id(i)] += wY.s3 * gvelo[i + v_line_index.s3];
+#elif MS_INTERPOL_SHIFT > 1
+ gvelo_loc[noBC_id(i)] += wY.s4 * gvelo[i + v_line_index.s4];
+ gvelo_loc[noBC_id(i)] += wY.s5 * gvelo[i + v_line_index.s5];
+#endif
+ }
+ /* nombre d'opérations 2D Linéaire:
+ - calcul des poids de ligne : 4flop (par wi)
+ - calcul de la vitesse : 3flop par point de grille de vitesse
+ */
+
+
+#else
+ // Multi-Scale (3D)
+
+ float line_posY, hY;
+ float line_posZ, hZ;
+ int indY, indZ;
+#if MS_FORMULA == LINEAR
+ int2 v_line_indexY, v_line_indexZ;
+ float2 wY, wZ;
+#elif MS_FORMULA == L2_1
+ int4 v_line_indexY, v_line_indexZ;
+ float4 wY, wZ;
+#elif MS_FORMULA == L4_2 || MS_FORMULA == L4_4
+ int8 v_line_indexY, v_line_indexZ;
+ float8 wY, wZ;
+#endif
+
+ line_posY = (gidY * mesh->dx.y) * inv_v_dx_y; // mesh->v_dx.y;
+ line_posZ = (gidZ * mesh->dx.z) * inv_v_dx_z;// mesh->v_dx.z;
+ indY = convert_int_rtn(line_posY);
+ indZ = convert_int_rtn(line_posZ);
+ hY = line_posY - convert_float(indY);
+ hZ = line_posZ - convert_float(indZ);
+
+#if MS_FORMULA == LINEAR
+ wY.s1 = hY;
+ wY.s0 = 1.0 - wY.s1;
+ wZ.s1 = hZ;
+ wZ.s0 = 1.0 - wZ.s1;
+#else
+ wY.s0 = MS_INTERPOL(alpha)(hY);
+ wY.s1 = MS_INTERPOL(beta)(hY);
+ wY.s2 = MS_INTERPOL(gamma)(hY);
+ wZ.s0 = MS_INTERPOL(alpha)(hZ);
+ wZ.s1 = MS_INTERPOL(beta)(hZ);
+ wZ.s2 = MS_INTERPOL(gamma)(hZ);
+#if MS_INTERPOL_SHIFT > 1
+ wY.s3 = MS_INTERPOL(delta)(hY);
+ wY.s4 = MS_INTERPOL(eta)(hY);
+ wY.s5 = 1.0 - wY.s0 - wY.s1 - wY.s2 - wY.s3 - wY.s4;
+ wZ.s3 = MS_INTERPOL(delta)(hZ);
+ wZ.s4 = MS_INTERPOL(eta)(hZ);
+ wZ.s5 = 1.0 - wZ.s0 - wZ.s1 - wZ.s2 - wZ.s3 - wZ.s4;
+#else
+ wY.s3 = 1.0 - wY.s0 - wY.s1 - wY.s2;
+ wZ.s3 = 1.0 - wZ.s0 - wZ.s1 - wZ.s2;
+#endif
+#endif
+
+ indY = indY + V_GHOSTS_NB - MS_INTERPOL_SHIFT;
+ indZ = indZ + V_GHOSTS_NB - MS_INTERPOL_SHIFT;
+
+ v_line_indexY.s0 = indY * V_NB_I;
+ v_line_indexY.s1 = (indY + 1) * V_NB_I;
+ v_line_indexZ.s0 = indZ * V_NB_I * V_NB_II;
+ v_line_indexZ.s1 = (indZ + 1) * V_NB_I * V_NB_II;
+#if MS_INTERPOL_SHIFT > 0
+ v_line_indexY.s2 = (indY + 2) * V_NB_I;
+ v_line_indexY.s3 = (indY + 3) * V_NB_I;
+ v_line_indexZ.s2 = (indZ + 2) * V_NB_I * V_NB_II;
+ v_line_indexZ.s3 = (indZ + 3) * V_NB_I * V_NB_II;
+#elif MS_INTERPOL_SHIFT > 1
+ v_line_indexY.s4 = (indY + 4) * V_NB_I;
+ v_line_indexY.s5 = (indY + 5) * V_NB_I;
+ v_line_indexZ.s4 = (indZ + 4) * V_NB_I * V_NB_II;
+ v_line_indexZ.s5 = (indZ + 5) * V_NB_I * V_NB_II;
+#endif
+
+ for(i=gidX; i<V_NB_I; i+=(WI_NB)){
+ gvelo_loc[noBC_id(i)] = wY.s0 * wZ.s0 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s1 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s0 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s1 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s1];
+#if MS_INTERPOL_SHIFT > 0
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s2 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s3 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s3];
+
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s2 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s3 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s3];
+
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s0 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s1 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s2 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s3 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s3];
+
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s0 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s1 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s2 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s3 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s3];
+#elif MS_INTERPOL_SHIFT > 1
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s4 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s0 * wZ.s5 * gvelo[i + v_line_indexY.s0 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s4 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s1 * wZ.s5 * gvelo[i + v_line_indexY.s1 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s4 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s2 * wZ.s5 * gvelo[i + v_line_indexY.s2 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s4 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s3 * wZ.s5 * gvelo[i + v_line_indexY.s3 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s0 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s1 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s2 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s3 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s3];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s4 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s4 * wZ.s5 * gvelo[i + v_line_indexY.s4 + v_line_indexZ.s5];
+
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s0 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s0];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s1 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s1];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s2 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s2];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s3 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s3];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s4 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s4];
+ gvelo_loc[noBC_id(i)] += wY.s5 * wZ.s5 * gvelo[i + v_line_indexY.s5 + v_line_indexZ.s5];
+#endif
+ }
+ /* nombre d'opérations 3D Linéaire:
+ - calcul des poids de ligne : 8flop (par wi)
+ - calcul de la vitesse : 11flop par point de grille de vitesse
+ */
+
+#endif
+#endif
+}
diff --git a/hysop/old/gpu.old/cl_src/common.cl b/hysop/old/gpu.old/cl_src/common.cl
new file mode 100644
index 0000000000000000000000000000000000000000..4f67d2aa000011e2dc5fe8b875e5c5521107a283
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/common.cl
@@ -0,0 +1,166 @@
+/**
+ * @file common.cl
+ * Common parameters for advection and remeshing kernels.
+ */
+
+inline uint noBC_id(int id);
+
+#ifdef WITH_NOBC
+/**
+ * Mapping to local memory arrays to avoir banck conflics.
+ * 1D buffer is taken as 2D one with wor-items vs. particles.
+ *
+ * @param id 1D index
+ *
+ * @return 2D index
+ */
+inline uint noBC_id(int id){
+ return (id%PART_NB_PER_WI)*WI_NB+(id/PART_NB_PER_WI);
+}
+#else
+/**
+ * Leave mapping unchanged, 1D.
+ *
+ * @param id 1D index
+ *
+ * @return 1D index
+ */
+inline uint noBC_id(int id){
+ return id;
+}
+#endif
+
+/**
+ * Constants for remeshing formulas:
+ * - L2_1 1
+ * - L2_2 2
+ * - L2_3 3
+ * - L2_4 4
+ * - L4_2 5
+ * - L4_3 6
+ * - L4_4 7
+ * - L6_3 8
+ * - L6_4 9
+ * - L6_5 10
+ * - L6_6 11
+ * - L8_4 12
+ * - M8PRIME 13
+ */
+#define L2_1 1
+#define L2_2 2
+#define L2_3 3
+#define L2_4 4
+#define L4_2 5
+#define L4_3 6
+#define L4_4 7
+#define L6_3 8
+#define L6_4 9
+#define L6_5 10
+#define L6_6 11
+#define L8_4 12
+#define M8PRIME 13
+#define LINEAR 14
+
+/**
+ * Remeshing configuration
+ */
+#if FORMULA == L2_1
+#define REMESH_SHIFT 1
+#define REMESH(greek) greek##_l2_1
+#elif FORMULA == L2_2
+#define REMESH_SHIFT 1
+#define REMESH(greek) greek##_l2_2
+#elif FORMULA == L2_3
+#define REMESH_SHIFT 1
+#define REMESH(greek) greek##_l2_3
+#elif FORMULA == L2_4
+#define REMESH_SHIFT 1
+#define REMESH(greek) greek##_l2_4
+
+#elif FORMULA == L4_2
+#define REMESH_SHIFT 2
+#define REMESH(greek) greek##_l4_2
+#elif FORMULA == L4_3
+#define REMESH_SHIFT 2
+#define REMESH(greek) greek##_l4_3
+#elif FORMULA == L4_4
+#define REMESH_SHIFT 2
+#define REMESH(greek) greek##_l4_4
+
+#elif FORMULA == M8PRIME
+#define REMESH_SHIFT 3
+#define REMESH(greek) greek##_M8p
+#elif FORMULA == L6_3
+#define REMESH_SHIFT 3
+#define REMESH(greek) greek##_l6_3
+#elif FORMULA == L6_4
+#define REMESH_SHIFT 3
+#define REMESH(greek) greek##_l6_4
+#elif FORMULA == L6_5
+#define REMESH_SHIFT 3
+#define REMESH(greek) greek##_l6_5
+#elif FORMULA == L6_6
+#define REMESH_SHIFT 3
+#define REMESH(greek) greek##_l6_6
+
+#elif FORMULA == L8_4
+#define REMESH_SHIFT 4
+#define REMESH(greek) greek##_l8_4
+#endif
+
+
+/**
+ * Multi-scale configuration
+ */
+
+#ifndef ADVEC_IS_MULTISCALE
+#define ADVEC_IS_MULTISCALE (V_NB_I-2*V_GHOSTS_NB) != NB_I
+#endif
+
+#if MS_FORMULA == LINEAR
+#define MS_INTERPOL_SHIFT 0
+// MS_INTERPOL not used
+#elif MS_FORMULA == L2_1
+#define MS_INTERPOL_SHIFT 1
+#define MS_INTERPOL(greek) greek##_l2_1
+#elif MS_FORMULA == L4_2
+#define MS_INTERPOL_SHIFT 2
+#define MS_INTERPOL(greek) greek##_l4_2
+#elif MS_FORMULA == L4_4
+#define MS_INTERPOL_SHIFT 2
+#define MS_INTERPOL(greek) greek##_l4_4
+#else
+//Default case for single-scale (only used in comm advection)
+#define MS_INTERPOL_SHIFT 0
+#endif
+
+/*
+a minmax element is a 12 int defined as follows:
+*/
+#define L_MIN_X 0
+#define L_MAX_X 1
+#define L_MIN_Y 2
+#define L_MAX_Y 3
+#define L_MIN_Z 4
+#define L_MAX_Z 5
+#define R_MIN_X 6
+#define R_MAX_X 7
+#define R_MIN_Y 8
+#define R_MAX_Y 9
+#define R_MIN_Z 10
+#define R_MAX_Z 11
+
+/* Structure to store __constants advection parameters */
+typedef struct AdvectionMeshInfo
+{
+ float4 dx; /* Mesh step (advected grid) */
+ float4 v_dx; /* Mesh step (velocity) */
+ float min_position; /* Domain minimum coordinate in current direction */
+ float invdx; /* Store 1./dx.x */
+ float v_invdx; /* Store 1./v_dx.x */
+ float x; /* Padding */
+} AdvectionMeshInfo;
+
+/* Finite differences constants */
+#define FD_C_2 88
+#define FD_C_4 99
diff --git a/hysop/old/gpu.old/cl_src/kernels/advection.cl b/hysop/old/gpu.old/cl_src/kernels/advection.cl
new file mode 100644
index 0000000000000000000000000000000000000000..2e9e341e3df1cbc898a89b882e7ee83ddf4c2a77
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/advection.cl
@@ -0,0 +1,77 @@
+/**
+ * @file advection.cl
+ * Advection kernel, vectorized version.
+ */
+
+/**
+ * Computes particles positions from the velocity field.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group. Computations of 1D problems are placed in loops over gidY and gidZ to adjust local workload and handle the work-item maximum size.
+ * Each work-item computes <code>NB_I/WI_NB</code> particles positions in each 1D problem.
+ * Particle are computed through OpenCL vector types of length 2, 4 or 8.
+ * Velocity data are copied to a local buffer as a cache.
+ *
+ * @param gvelo Velocity.
+ * @param ppos Particle position.
+ * @param dt Time step.
+ * @param mesh Mesh description.
+ * @param inv_v_dx_y velocity grid 1/dy
+ * @param inv_v_dx_z velocity grid 1/dz
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>NB_X</code>, <code>NB_Y</code>, <code>NB_Z</code> : points number in physical space directions.
+ * @remark <code>WI_NB</code> corresponds to the work-item number.
+ * @remark <code>ADVEC_IS_MULTISCALE</code> is a flag for multiscale.
+ * @remark <code>V_NB_I</code>, <code>V_NB_II</code>, <code>V_NB_III</code> : points number for velocity grid in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void advection_kernel(__global const float* gvelo,
+ __global float* ppos,
+ float dt,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ uint i; /* Particle index in 1D problem */
+ float__N__ p; /* Particle position */
+ uint line_index; /* Current 1D problem index */
+
+ __local float velocity_cache[V_NB_I]; /* Velocity cache */
+
+ for(gidZ=get_global_id(2);
+#ifdef NB_Z
+ gidZ<NB_III;
+#else
+ gidZ<=get_global_id(2); // Single element loop
+#endif
+ gidZ+=get_global_size(2)) {
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+
+ // 1D problem computations
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+#if ADVEC_IS_MULTISCALE
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, inv_v_dx_y, inv_v_dx_z, mesh);
+#else
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, mesh);
+#endif
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*__N__; i<NB_I; i+=WI_NB*__N__) {
+ /* Compute position */
+ p = advection(i, dt, velocity_cache, mesh);
+ /* Store result */
+ vstore__N__(p, (i+line_index)/__N__, ppos);
+ }
+
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/advection_and_remeshing.cl b/hysop/old/gpu.old/cl_src/kernels/advection_and_remeshing.cl
new file mode 100644
index 0000000000000000000000000000000000000000..c9fb52ebdcd758d33088e60acefcce35d640ecf7
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/advection_and_remeshing.cl
@@ -0,0 +1,101 @@
+/**
+ * @file advection_and_remeshing.cl
+ * Advection and remeshing kernel, vectorized version.
+ */
+
+/**
+ * Performs advection and then remeshing of the particles scalar.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group. Computations of 1D problems are placed in loops over gidY and gidZ to adjust local workload and handle the work-item maximum size.
+ * Each work-item computes NB_I/WI_NB particles positions. To avoid concurrent witings, in case of strong velocity gradients, work-items computes contiguous particles.
+ * Particle are computed through OpenCL vector types of lenght 2, 4 or 8.
+ * Scalar results are stored in a local buffer as a cache and then copied to global memory buffer.
+ *
+ * @param gvelo Velocity field
+ * @param pscal Particle scalar
+ * @param gscal Grid scalar
+ * @param dt Time step
+ * @param mesh Mesh description.
+ * @param inv_v_dx_y velocity grid 1/dy
+ * @param inv_v_dx_z velocity grid 1/dz
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>NB_X</code>, <code>NB_Y</code>, <code>NB_Z</code> : points number in physical space directions.
+ * @remark <code>WI_NB</code> corresponds to the work-item number.
+ * @remark <code>ADVEC_IS_MULTISCALE</code> is a flag for multiscale.
+ * @remark <code>V_NB_I</code>, <code>V_NB_II</code>, <code>V_NB_III</code> : points number for velocity grid in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void advection_and_remeshing(__global const float* gvelo,
+ __RCOMP_P__global const float* pscal__ID__,
+ __RCOMP_P__global float* gscal__ID__,
+ float dt,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ uint i; /* Particle index in 1D problem */
+ float__N__ p; /* Particle position */
+ __RCOMP_I float__N__ s__ID__; /* Particle scalar */
+ uint line_index; /* Current 1D problem index */
+
+ __RCOMP_I__local float gscal_loc__ID__[NB_I]; /* Local buffer for result */
+ __local float velocity_cache[V_NB_I]; /* Velocity cache */
+
+ for(gidZ=get_global_id(2);
+#ifdef NB_Z
+ gidZ<NB_III;
+#else
+ gidZ<=get_global_id(2); // Single element loop
+#endif
+ gidZ+=get_global_size(2)) {
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+
+ // 1D problem computations
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+#if ADVEC_IS_MULTISCALE
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, inv_v_dx_y, inv_v_dx_z, mesh);
+#else
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, mesh);
+#endif
+
+ for(i=gidX*__N__; i<NB_I; i+=(WI_NB*__N__)) {
+ /* Initialize result buffer */
+ __RCOMP_Igscal_loc__ID__[noBC_id(i+__NN__)] = 0.0;
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*PART_NB_PER_WI; i<(gidX + 1)*PART_NB_PER_WI; i+=__N__) {
+ /* Read Particle scalar */
+ __RCOMP_Is__ID__ = vload__N__((i + line_index)/__N__, pscal__ID__);
+ /* Compute particle position */
+ p = advection(i, dt, velocity_cache, mesh);
+ /* Remesh particle */
+ remesh(i, __RCOMP_Ps__ID__, p, __RCOMP_Pgscal_loc__ID__, mesh);
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*__N__; i<NB_I; i+=(WI_NB*__N__)) {
+ /* Store result */
+ __RCOMP_Ivstore__N__((float__N__)(gscal_loc__ID__[noBC_id(i+__NN__)],
+ ), (i + line_index)/__N__, gscal__ID__);
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/advection_and_remeshing_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/advection_and_remeshing_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..5759dc6f56f201d248c1ec794598533d648aae38
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/advection_and_remeshing_noVec.cl
@@ -0,0 +1,94 @@
+/**
+ * @file advection_and_remeshing.cl
+ * Advection and remeshing kernel.
+ */
+
+/**
+ * Performs advection and then remeshing of the particles' scalar.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group.
+ * Each work-item computes NB_I/WI_NB particles positions. To avoid concurrent witings, in case of strong velocity gradients, work-items computes contiguous particles.
+ * Particle are computed through OpenCL vector types of lenght 2, 4 or 8.
+ * Scalar results are stored in a local buffer as a cache and then copied to global memory buffer.
+ *
+ * @param gvelo Velocity field
+ * @param pscal Particle scalar
+ * @param gscal Grid scalar
+ * @param dt Time step
+ * @param min_position Domain lower coordinate
+ * @param dx Space step
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ * @remark WI_NB corresponds to the work-item number.
+ * @remark \__N__ is expanded at compilation time by vector width.
+ * @remark \__NN__ is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void advection_and_remeshing(__global const float* gvelo,
+ __RCOMP_P__global const float* pscal__ID__,
+ __RCOMP_P__global float* gscal__ID__,
+ float dt,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ uint i; /* Particle index in 1D problem */
+ float p; /* Particle position */
+ __RCOMP_I float s__ID__; /* Particle scalar */
+ uint line_index; /* Current 1D problem index */
+
+ __RCOMP_I__local float gscal_loc__ID__[NB_I]; /* Local buffer for result */
+ __local float velocity_cache[V_NB_I]; /* Velocity cache */
+
+#ifdef NB_Z
+ for(gidZ=get_global_id(2); gidZ<NB_III; gidZ+=get_global_size(2)) {
+#else
+ gidZ=get_global_id(2); {
+#endif
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+#if ADVEC_IS_MULTISCALE
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, inv_v_dx_y, inv_v_dx_z, mesh);
+#else
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, mesh);
+#endif
+
+ for(i=gidX; i<NB_I; i+=(WI_NB))
+ {
+ /* Initialize result buffer */
+ __RCOMP_Igscal_loc__ID__[noBC_id(i)] = 0.0;
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*PART_NB_PER_WI; i<(gidX + 1)*PART_NB_PER_WI; i+=1)
+ {
+ /* Read Particle scalar */
+ __RCOMP_Is__ID__ = pscal__ID__[i + line_index];
+ /* Compute particle position */
+ p = advection(i, dt, velocity_cache, mesh);
+ /* Remesh particle */
+ remesh(i, __RCOMP_Ps__ID__, p, __RCOMP_Pgscal_loc__ID__, mesh);
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX; i<NB_I; i+=(WI_NB))
+ {
+ /* Store result */
+ __RCOMP_Igscal__ID__[i + line_index] = gscal_loc__ID__[noBC_id(i)];
+ }
+
+ barrier(CLK_LOCAL_MEM_FENCE);
+}
+}
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/advection_euler_and_remeshing_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/advection_euler_and_remeshing_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..99565be69e6702c197cb77d021df46636c59620f
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/advection_euler_and_remeshing_noVec.cl
@@ -0,0 +1,85 @@
+/**
+ * @file advection_and_remeshing.cl
+ * Euler advection and remeshing kernel.
+ */
+
+/**
+ * Performs advection and then remeshing of the particles scalar.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group. Computations of 1D problems are placed in loops over gidY and gidZ to adjust local workload and handle the work-item maximum size.
+ * Each work-item computes NB_I/WI_NB particles positions. To avoid concurrent witings, in case of strong velocity gradients, work-items computes contiguous particles.
+ * Particle are computed through OpenCL vector types of lenght 2, 4 or 8.
+ * Scalar results are stored in a local buffer as a cache and then copied to global memory buffer.
+ *
+ * @param gvelo Velocity field
+ * @param pscal Particle scalar
+ * @param gscal Grid scalar
+ * @param dt Time step
+ * @param min_position Domain lower coordinate
+ * @param dx Space step
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ * @remark WI_NB corresponds to the work-item number.
+ * @remark \__N__ is expanded at compilation time by vector width.
+ * @remark \__NN__ is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void advection_and_remeshing(__global const float* gvelo,
+ __RCOMP_P__global const float* pscal__ID__,
+ __RCOMP_P__global float* gscal__ID__,
+ float dt,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ uint i; /* Particle index in 1D problem */
+ float p,c; /* Particle position */
+ __RCOMP_I float s__ID__; /* Particle scalar */
+ uint line_index; /* Current 1D problem index */
+
+ __RCOMP_I__local float gscal_loc__ID__[NB_I]; /* Local buffer for result */
+
+ for(gidZ=get_global_id(2);
+#ifdef NB_Z
+ gidZ<NB_III;
+#else
+ gidZ<=get_global_id(2); // Single element loop
+#endif
+ gidZ+=get_global_size(2)) {
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+
+ // 1D computations
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+ for(i=gidX; i<NB_I; i+=(WI_NB)) {
+ /* Initialize result buffer */
+ __RCOMP_Igscal_loc__ID__[noBC_id(i)] = 0.0;
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*PART_NB_PER_WI; i<(gidX + 1)*PART_NB_PER_WI; i+=1) {
+ /* Read Particle scalar */
+ __RCOMP_Is__ID__ = pscal__ID__[i + line_index];
+ /* Compute particle position */
+ c = fma(i, mesh->dx.x, mesh->min_position);
+ p = fma(dt, gvelo[i+line_index], c);
+ /* Remesh particle */
+ remesh(i, __RCOMP_Ps__ID__, p, __RCOMP_Pgscal_loc__ID__, mesh);
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX; i<NB_I; i+=(WI_NB)) {
+ /* Store result */
+ __RCOMP_Igscal__ID__[i + line_index] = gscal_loc__ID__[noBC_id(i)];
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/advection_euler_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/advection_euler_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..df90575a224d57ebd3485bd9a8e3f9128249c0be
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/advection_euler_noVec.cl
@@ -0,0 +1,51 @@
+/**
+ * @file advection_euler_noVec.cl
+ * Advection kernel, basic version for Euler integrator for simple scale problems (no need velocity cache).
+ */
+
+/**
+ * Computes particles positions from the velocity field.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group.
+ * Each work-item computes NB_I/WI_NB particles positions.
+ *
+ * @param gvelo Velocity.
+ * @param ppos Particle position.
+ * @param dt Time step.
+ * @param min_position Domain lower coordinate.
+ * @param dx Space step.
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ * @remark WI_NB corresponds to the work-item number.
+ */
+__kernel void advection_kernel(__global const float* gvelo,
+ __global float* ppos,
+ float dt,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ uint i; /* Particle index in 1D problem */
+ uint line_index; /* Current 1D problem index */
+ float c;
+
+ for(gidZ=get_global_id(2);
+#ifdef NB_Z
+ gidZ<NB_III;
+#else
+ gidZ<=get_global_id(2); // Single element loop
+#endif
+ gidZ+=get_global_size(2)) {
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+
+ //1D computations
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+ for(i=gidX; i<NB_I; i+=WI_NB) {
+ c = fma(i, mesh->dx.x, mesh->min_position);
+ ppos[i+line_index] = fma(dt, gvelo[i+line_index], c);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/advection_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/advection_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..78ca64d6108809df5d4db707017f94a7d96d5b72
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/advection_noVec.cl
@@ -0,0 +1,63 @@
+/**
+ * @file advection_noVec.cl
+ * Advection kernel, basic version.
+ */
+
+/**
+ * Computes particles positions from the velocity field.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group.
+ * Each work-item computes NB_I/WI_NB particles positions.
+ *
+ * @param gvelo Velocity.
+ * @param ppos Particle position.
+ * @param dt Time step.
+ * @param min_position Domain lower coordinate.
+ * @param dx Space step.
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ * @remark WI_NB corresponds to the work-item number.
+ */
+__kernel void advection_kernel(__global const float* gvelo,
+ __global float* ppos,
+ float dt,
+#if ADVEC_IS_MULTISCALE
+ float inv_v_dx_y, float inv_v_dx_z,
+#endif
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ uint i; /* Particle index in 1D problem */
+ uint line_index; /* Current 1D problem index */
+
+ __local float velocity_cache[V_NB_I]; /* Velocity cache */
+
+ for(gidZ=get_global_id(2);
+#ifdef NB_Z
+ gidZ<NB_III;
+#else
+ gidZ<=get_global_id(2); // Single element loop
+#endif
+ gidZ+=get_global_size(2)) {
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+
+ // 1D computation
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+#if ADVEC_IS_MULTISCALE
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, inv_v_dx_y, inv_v_dx_z, mesh);
+#else
+ fill_velocity_cache(gvelo, gidX, gidY, gidZ, velocity_cache, mesh);
+#endif
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX; i<NB_I; i+=WI_NB) {
+ ppos[i+line_index] = advection(i, dt, velocity_cache, mesh);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/comm_MS_advection_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/comm_MS_advection_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..2f7193be4698c21f37cb2e49ebd7b9ae18c7364f
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/comm_MS_advection_noVec.cl
@@ -0,0 +1,87 @@
+
+
+
+
+__kernel void buff_advec(__global const float* gvelo,
+ __global float* ppos,
+ __global float* buffer_l,
+ __global float* buffer_r,
+ float dt,
+ float inv_v_dx_y, float inv_v_dx_z,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ int gidY = get_global_id(1); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(2); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index = gidY*NB_I+gidZ*NB_I*NB_II; /* Current 1D problem index */
+ float p,v,c;
+ float2 hY, hZ;
+ int i_ind, i_indY, i_indZ;
+
+
+ __local float velocity_cache[V_NB_I];
+ __local float buff_l_loc[V_BUFF_WIDTH];
+ __local float buff_r_loc[V_BUFF_WIDTH];
+ __local float* loc_ptr;
+
+
+ hY.s0 = (gidY * mesh->dx.y) * inv_v_dx_y;
+ hZ.s0 = (gidZ * mesh->dx.z) * inv_v_dx_z;
+ i_indY = convert_int_rtn(hY.s0);
+ i_indZ = convert_int_rtn(hZ.s0);
+ hY.s0 = hY.s0 - convert_float(i_indY);
+ hZ.s0 = hZ.s0 - convert_float(i_indZ);
+ hY.s1 = (1.0-hY.s0);
+ hZ.s1 = (1.0-hZ.s0);
+
+ i_indY = i_indY + V_GHOSTS_NB;
+ i_indZ = i_indZ + V_GHOSTS_NB;
+
+ for(i=gidX; i<V_NB_I; i+=(WI_NB)){
+ velocity_cache[noBC_id(i)] = hY.s1*hZ.s1 * gvelo[i + i_indY * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s1*hZ.s0 * gvelo[i + i_indY * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s1 * gvelo[i + (i_indY + 1) * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s0 * gvelo[i + (i_indY + 1) * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ }
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB)){
+ buff_l_loc[i] = hY.s1*hZ.s1*buffer_l[i + V_BUFF_WIDTH*(i_indY + i_indZ*V_NB_II)];
+ buff_l_loc[i] += hY.s1*hZ.s0*buffer_l[i + V_BUFF_WIDTH*(i_indY + (i_indZ+1)*V_NB_II)];
+ buff_l_loc[i] += hY.s0*hZ.s1*buffer_l[i + V_BUFF_WIDTH*(i_indY+1 + i_indZ*V_NB_II)];
+ buff_l_loc[i] += hY.s0*hZ.s0*buffer_l[i + V_BUFF_WIDTH*(i_indY+1 + (i_indZ+1)*V_NB_II)];
+ }
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB)){
+ buff_r_loc[i] = hY.s1*hZ.s1*buffer_r[i + V_BUFF_WIDTH*(i_indY + i_indZ*V_NB_II)];
+ buff_r_loc[i] += hY.s1*hZ.s0*buffer_r[i + V_BUFF_WIDTH*(i_indY + (i_indZ+1)*V_NB_II)];
+ buff_r_loc[i] += hY.s0*hZ.s1*buffer_r[i + V_BUFF_WIDTH*(i_indY+1 + i_indZ*V_NB_II)];
+ buff_r_loc[i] += hY.s0*hZ.s0*buffer_r[i + V_BUFF_WIDTH*(i_indY+1 + (i_indZ+1)*V_NB_II)];
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ {
+ c = i * mesh->dx.x + mesh->min_position;
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB) - MS_INTERPOL_SHIFT;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind+1)],p);
+ p = (c + 0.5*dt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p) - MS_INTERPOL_SHIFT;
+ p = p - convert_float(i_ind);
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB) && i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : (i_ind<(V_START_INDEX-V_GHOSTS_NB)) ? buff_l_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : buff_r_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v = (1.0-p)*(*loc_ptr);
+ i_ind = i_ind + 1;
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB) && i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : (i_ind<(V_START_INDEX-V_GHOSTS_NB)) ? buff_l_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : buff_r_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v += p*(*loc_ptr);
+ ppos[i+line_index] = c + dt * v;
+ }
+
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/comm_advection_MS_and_remeshing_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/comm_advection_MS_and_remeshing_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..8e9ea780a2aafb23ff5067028ee7dfb3d7966667
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/comm_advection_MS_and_remeshing_noVec.cl
@@ -0,0 +1,547 @@
+
+
+
+
+__kernel void buff_advec_and_remesh_l(__global const float* gvelo,
+ __global float* v_l_buff,
+ __global const float* pscal,
+ __global float* s_l_buff,
+ int used_width,
+ float dt,
+ float inv_v_dx_y, float inv_v_dx_z,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidY = get_global_id(0); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(1); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index = gidY*NB_I+gidZ*NB_I*NB_II; /* Current 1D problem index */
+ float p,v,c,s,y,w;
+ float2 hY, hZ;
+ int i_ind, i_indY, i_indZ;
+ int ind, index;
+
+
+ float velocity_cache[V_NB_I];
+ float v_l_buff_loc[V_BUFF_WIDTH];
+ float s_l_buff_loc[BUFF_WIDTH];
+ float* loc_ptr;
+
+ // Initialize buffers
+ for (i=0; i<used_width; i++)
+ s_l_buff_loc[i] = 0.0;
+
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ hY.s0 = (gidY * mesh->dx.y) * inv_v_dx_y;
+ hZ.s0 = (gidZ * mesh->dx.z) * inv_v_dx_z;
+ i_indY = convert_int_rtn(hY.s0);
+ i_indZ = convert_int_rtn(hZ.s0);
+ hY.s0 = hY.s0 - convert_float(i_indY);
+ hZ.s0 = hZ.s0 - convert_float(i_indZ);
+ hY.s1 = (1.0-hY.s0);
+ hZ.s1 = (1.0-hZ.s0);
+
+ i_indY = i_indY + V_GHOSTS_NB;
+ i_indZ = i_indZ + V_GHOSTS_NB;
+
+ for (i=0; i<V_NB_I; i++){
+ velocity_cache[noBC_id(i)] = hY.s1*hZ.s1 * gvelo[i + i_indY * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s1*hZ.s0 * gvelo[i + i_indY * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s1 * gvelo[i + (i_indY + 1) * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s0 * gvelo[i + (i_indY + 1) * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ }
+
+ for (i=0; i<V_BUFF_WIDTH; i++){
+ v_l_buff_loc[i] = hY.s1*hZ.s1*v_l_buff[i + V_BUFF_WIDTH*(i_indY + i_indZ*V_NB_II)];
+ v_l_buff_loc[i] += hY.s1*hZ.s0*v_l_buff[i + V_BUFF_WIDTH*(i_indY + (i_indZ+1)*V_NB_II)];
+ v_l_buff_loc[i] += hY.s0*hZ.s1*v_l_buff[i + V_BUFF_WIDTH*(i_indY+1 + i_indZ*V_NB_II)];
+ v_l_buff_loc[i] += hY.s0*hZ.s0*v_l_buff[i + V_BUFF_WIDTH*(i_indY+1 + (i_indZ+1)*V_NB_II)];
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=0; i<2*BUFF_WIDTH; i++)
+ {
+ c = i * mesh->dx.x + mesh->min_position;
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB) - MS_INTERPOL_SHIFT;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind+1)],p);
+ p = (c + 0.5*dt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p) - MS_INTERPOL_SHIFT;
+ p = p - convert_float(i_ind);
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : v_l_buff_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1);
+ v = (1.0-p)*(*loc_ptr);
+ i_ind = i_ind + 1;
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : v_l_buff_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1);
+ v += p*(*loc_ptr);
+ p = c + dt * v;
+
+
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+
+
+
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if (index<START_INDEX) {loc_ptr = s_l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // Store buffers
+ for (i=0; i<used_width; i++)
+ s_l_buff[i + gidY*used_width + gidZ*used_width*NB_II] = s_l_buff_loc[i];
+
+}
+
+__kernel void buff_advec_and_remesh_r(__global const float* gvelo,
+ __global float* v_r_buff,
+ __global const float* pscal,
+ __global float* s_r_buff,
+ int used_width,
+ float dt,
+ float inv_v_dx_y, float inv_v_dx_z,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidY = get_global_id(0); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(1); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index = gidY*NB_I+gidZ*NB_I*NB_II; /* Current 1D problem index */
+ float p,v,c,s,y,w;
+ float2 hY, hZ;
+ int i_ind, i_indY, i_indZ;
+ int ind, index;
+
+
+ float velocity_cache[V_NB_I];
+ float v_r_buff_loc[V_BUFF_WIDTH];
+ float s_r_buff_loc[BUFF_WIDTH];
+ float* loc_ptr;
+
+ // Initialize buffers
+ for(i=0; i<used_width; i++)
+ s_r_buff_loc[i] = 0.0;
+
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ hY.s0 = (gidY * mesh->dx.y) * inv_v_dx_y;
+ hZ.s0 = (gidZ * mesh->dx.z) * inv_v_dx_z;
+ i_indY = convert_int_rtn(hY.s0);
+ i_indZ = convert_int_rtn(hZ.s0);
+ hY.s0 = hY.s0 - convert_float(i_indY);
+ hZ.s0 = hZ.s0 - convert_float(i_indZ);
+ hY.s1 = (1.0-hY.s0);
+ hZ.s1 = (1.0-hZ.s0);
+
+ i_indY = i_indY + V_GHOSTS_NB;
+ i_indZ = i_indZ + V_GHOSTS_NB;
+
+ for(i=0;i<V_NB_I; i++){
+ velocity_cache[noBC_id(i)] = hY.s1*hZ.s1 * gvelo[i + i_indY * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s1*hZ.s0 * gvelo[i + i_indY * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s1 * gvelo[i + (i_indY + 1) * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s0 * gvelo[i + (i_indY + 1) * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ }
+
+ for(i=0;i<V_BUFF_WIDTH; i++){
+ v_r_buff_loc[i] = hY.s1*hZ.s1*v_r_buff[i + V_BUFF_WIDTH*(i_indY + i_indZ*V_NB_II)];
+ v_r_buff_loc[i] += hY.s1*hZ.s0*v_r_buff[i + V_BUFF_WIDTH*(i_indY + (i_indZ+1)*V_NB_II)];
+ v_r_buff_loc[i] += hY.s0*hZ.s1*v_r_buff[i + V_BUFF_WIDTH*(i_indY+1 + i_indZ*V_NB_II)];
+ v_r_buff_loc[i] += hY.s0*hZ.s0*v_r_buff[i + V_BUFF_WIDTH*(i_indY+1 + (i_indZ+1)*V_NB_II)];
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=NB_I-2*BUFF_WIDTH; i<NB_I; i++)
+ {
+ c = i * mesh->dx.x + mesh->min_position;
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB) - MS_INTERPOL_SHIFT;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind+1)],p);
+ p = (c + 0.5*dt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p) - MS_INTERPOL_SHIFT;
+ p = p - convert_float(i_ind);
+ loc_ptr = (i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : v_r_buff_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v = (1.0-p)*(*loc_ptr);
+ i_ind = i_ind + 1;
+ loc_ptr = (i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : v_r_buff_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v += p*(*loc_ptr);
+ p = c + dt * v;
+
+
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+
+
+
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // Store buffers
+ for(i=0;i<used_width;i++)
+ s_r_buff[i + gidY*used_width + gidZ*used_width*NB_II] = s_r_buff_loc[i];
+
+}
+
+__kernel void buff_advec_and_remesh(__global const float* gvelo,
+ __global float* v_l_buff,
+ __global float* v_r_buff,
+ __global const float* pscal,
+ __global float* gscal,
+ float dt,
+ float inv_v_dx_y, float inv_v_dx_z,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ int gidY = get_global_id(1); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(2); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index = gidY*NB_I+gidZ*NB_I*NB_II; /* Current 1D problem index */
+ float p,v,c,s,y,w;
+ float2 hY, hZ;
+ int i_ind, i_indY, i_indZ;
+ int ind, index;
+
+
+ __local float velocity_cache[V_NB_I];
+ __local float v_l_buff_loc[V_BUFF_WIDTH];
+ __local float v_r_buff_loc[V_BUFF_WIDTH];
+ __local float gscal_loc[NB_I];
+ __local float* loc_ptr;
+
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ {
+ /* Initialize result buffer */
+ gscal_loc[i] = 0.0;
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+
+
+ hY.s0 = (gidY * mesh->dx.y) * inv_v_dx_y;
+ hZ.s0 = (gidZ * mesh->dx.z) * inv_v_dx_z;
+ i_indY = convert_int_rtn(hY.s0);
+ i_indZ = convert_int_rtn(hZ.s0);
+ hY.s0 = hY.s0 - convert_float(i_indY);
+ hZ.s0 = hZ.s0 - convert_float(i_indZ);
+ hY.s1 = (1.0-hY.s0);
+ hZ.s1 = (1.0-hZ.s0);
+
+ i_indY = i_indY + V_GHOSTS_NB;
+ i_indZ = i_indZ + V_GHOSTS_NB;
+
+ for(i=gidX; i<V_NB_I; i+=(WI_NB)){
+ velocity_cache[noBC_id(i)] = hY.s1*hZ.s1 * gvelo[i + i_indY * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s1*hZ.s0 * gvelo[i + i_indY * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s1 * gvelo[i + (i_indY + 1) * V_NB_I + i_indZ * V_NB_I * V_NB_II];
+ velocity_cache[noBC_id(i)] += hY.s0*hZ.s0 * gvelo[i + (i_indY + 1) * V_NB_I + (i_indZ + 1) * V_NB_I * V_NB_II];
+ }
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB)){
+ v_l_buff_loc[i] = hY.s1*hZ.s1*v_l_buff[i + V_BUFF_WIDTH*(i_indY + i_indZ*V_NB_II)];
+ v_l_buff_loc[i] += hY.s1*hZ.s0*v_l_buff[i + V_BUFF_WIDTH*(i_indY + (i_indZ+1)*V_NB_II)];
+ v_l_buff_loc[i] += hY.s0*hZ.s1*v_l_buff[i + V_BUFF_WIDTH*(i_indY+1 + i_indZ*V_NB_II)];
+ v_l_buff_loc[i] += hY.s0*hZ.s0*v_l_buff[i + V_BUFF_WIDTH*(i_indY+1 + (i_indZ+1)*V_NB_II)];
+ }
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB)){
+ v_r_buff_loc[i] = hY.s1*hZ.s1*v_r_buff[i + V_BUFF_WIDTH*(i_indY + i_indZ*V_NB_II)];
+ v_r_buff_loc[i] += hY.s1*hZ.s0*v_r_buff[i + V_BUFF_WIDTH*(i_indY + (i_indZ+1)*V_NB_II)];
+ v_r_buff_loc[i] += hY.s0*hZ.s1*v_r_buff[i + V_BUFF_WIDTH*(i_indY+1 + i_indZ*V_NB_II)];
+ v_r_buff_loc[i] += hY.s0*hZ.s0*v_r_buff[i + V_BUFF_WIDTH*(i_indY+1 + (i_indZ+1)*V_NB_II)];
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*PART_NB_PER_WI; i<(gidX + 1)*PART_NB_PER_WI; i+=1)
+ {
+ c = i * mesh->dx.x + mesh->min_position;
+ // multi-scale : interpolate v from velocity buffer (of length V_NB_I)
+ p = c * mesh->v_invdx;
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind = i_ind - (V_START_INDEX-V_GHOSTS_NB) - MS_INTERPOL_SHIFT;
+ v = mix(velocity_cache[noBC_id(i_ind)],
+ velocity_cache[noBC_id(i_ind+1)],p);
+ p = (c + 0.5*dt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p) - MS_INTERPOL_SHIFT;
+ p = p - convert_float(i_ind);
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB) && i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : (i_ind<(V_START_INDEX-V_GHOSTS_NB)) ? v_l_buff_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : v_r_buff_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v = (1.0-p)*(*loc_ptr);
+ i_ind = i_ind + 1;
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB) && i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+noBC_id(i_ind - (V_START_INDEX-V_GHOSTS_NB)) : (i_ind<(V_START_INDEX-V_GHOSTS_NB)) ? v_l_buff_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : v_r_buff_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v += p*(*loc_ptr);
+ p = c + dt * v;
+
+
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+
+
+
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ {
+ /* Store result */
+ gscal[i + line_index] = gscal_loc[i];
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/comm_advection_and_remeshing_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/comm_advection_and_remeshing_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..1648c70e4d99e9145364ff331bfff2f13695f92c
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/comm_advection_and_remeshing_noVec.cl
@@ -0,0 +1,468 @@
+
+
+
+__kernel void buff_advec_and_remesh_l(__global const float* gvelo,
+ __global float* v_buffer_l,
+ __global const float* pscal,
+ __global float* s_buffer_l,
+ int used_width,
+ float dt, __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidY = get_global_id(0); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(1); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index ; /* Current 1D problem index */
+
+ float v,vp,p,c,s,y,w, hdt = 0.5 * dt;
+ int i_ind, i_ind_p, ind, index;
+
+ float velocity_cache[V_NB_I];
+ float v_buff_l_loc[V_BUFF_WIDTH];
+ float s_buff_l_loc[BUFF_WIDTH];
+ float* loc_ptr;
+
+ // Initialize buffers
+ for (i=0;i<used_width;i++)
+ s_buff_l_loc[i] = 0.0;
+
+ for(i=0; i<V_BUFF_WIDTH; i++)
+ v_buff_l_loc[i] = v_buffer_l[i + V_BUFF_WIDTH*(gidY + gidZ*V_NB_II)];
+
+ line_index = gidY*V_NB_I + gidZ*V_NB_I*V_NB_II;
+ /* Read velocity */
+ /* Fill velocity cache */
+ for(i=0;i<V_NB_I;i++)
+ velocity_cache[i] = gvelo[i+line_index];
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ line_index = gidY*NB_I+gidZ*NB_I*NB_II;
+ for(i=0; i<2*BUFF_WIDTH; i++)
+ {
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+
+ c = i * mesh->dx.x + mesh->min_position;
+ v = velocity_cache[i + V_GHOSTS_NB];
+ p = (c + hdt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind_p = i_ind + 1;
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB)) ? velocity_cache + i_ind - (V_START_INDEX-V_GHOSTS_NB) : v_buff_l_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1);
+ v = *loc_ptr;
+
+ loc_ptr = (i_ind_p>=(V_START_INDEX-V_GHOSTS_NB)) ? velocity_cache+i_ind_p - (V_START_INDEX-V_GHOSTS_NB) : v_buff_l_loc+i_ind_p-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1);
+ vp = *loc_ptr;
+
+ v = (p*(vp-v) + v);
+ p = c + dt * v;
+
+
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if (index<START_INDEX){ loc_ptr = s_buff_l_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // Store buffers
+ for(i=0;i<used_width;i++)
+ s_buffer_l[i + gidY*used_width + gidZ*used_width*NB_II] = s_buff_l_loc[i];
+}
+
+
+
+
+
+
+
+
+__kernel void buff_advec_and_remesh_r(__global const float* gvelo,
+ __global float* v_buffer_r,
+ __global const float* pscal,
+ __global float* s_buffer_r,
+ int used_width,
+ float dt, __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidY = get_global_id(0); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(1); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index ; /* Current 1D problem index */
+
+ float v,vp,p,c,s,y,w, hdt = 0.5 * dt;
+ int i_ind, i_ind_p, ind, index;
+
+ float velocity_cache[V_NB_I];
+ float v_buff_r_loc[V_BUFF_WIDTH];
+ float s_buff_r_loc[BUFF_WIDTH];
+ float* loc_ptr;
+
+ // Initialize buffers
+ for(i=0;i<used_width;i++)
+ s_buff_r_loc[i] = 0.0;
+
+ for(i=0;i<V_BUFF_WIDTH;i++)
+ v_buff_r_loc[i] = v_buffer_r[i + V_BUFF_WIDTH*(gidY + gidZ*V_NB_II)];
+
+ line_index = gidY*V_NB_I + gidZ*V_NB_I*V_NB_II;
+ /* Read velocity */
+ /* Fill velocity cache */
+ for(i=0;i<V_NB_I; i++)
+ velocity_cache[i] = gvelo[i+line_index];
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ line_index = gidY*NB_I+gidZ*NB_I*NB_II;
+ for(i=NB_I-2*BUFF_WIDTH; i<NB_I; i++)
+ {
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+
+ c = i * mesh->dx.x + mesh->min_position;
+ v = velocity_cache[i + V_GHOSTS_NB];
+ p = (c + hdt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind_p = i_ind + 1;
+ loc_ptr = (i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache + i_ind - (V_START_INDEX-V_GHOSTS_NB) : v_buff_r_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v = *loc_ptr;
+
+ loc_ptr = (i_ind_p <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+i_ind_p - (V_START_INDEX-V_GHOSTS_NB) : v_buff_r_loc+i_ind_p-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ vp = *loc_ptr;
+
+ v = (p*(vp-v) + v);
+ p = c + dt * v;
+
+
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if (index > STOP_INDEX){ loc_ptr = s_buff_r_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=0;i<used_width;i++)
+ s_buffer_r[i + gidY*used_width + gidZ*used_width*NB_II] = s_buff_r_loc[i];
+
+}
+
+
+__kernel void buff_advec_and_remesh(__global const float* gvelo,
+ __global float* v_buffer_l,
+ __global float* v_buffer_r,
+ __global const float* pscal,
+ __global float* gscal,
+ float dt, __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ int gidY = get_global_id(1); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(2); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index ; /* Current 1D problem index */
+
+ float v,vp,p,c,s,y,w, hdt = 0.5 * dt;
+ int i_ind, i_ind_p, ind, index;
+
+ __local float velocity_cache[V_NB_I];
+ __local float v_buff_l_loc[V_BUFF_WIDTH];
+ __local float v_buff_r_loc[V_BUFF_WIDTH];
+ __local float gscal_loc[NB_I];
+ __local float* loc_ptr;
+
+
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ /* Initialize result buffer */
+ gscal_loc[i] = 0.0;
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB))
+ v_buff_l_loc[i] = v_buffer_l[i + V_BUFF_WIDTH*(gidY + gidZ*V_NB_II)];
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB))
+ v_buff_r_loc[i] = v_buffer_r[i + V_BUFF_WIDTH*(gidY + gidZ*V_NB_II)];
+
+ line_index = gidY*V_NB_I + gidZ*V_NB_I*V_NB_II;
+ /* Read velocity */
+ /* Fill velocity cache */
+ for(i=gidX; i<V_NB_I; i+=(WI_NB))
+ velocity_cache[i] = gvelo[i+line_index];
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ line_index = gidY*NB_I+gidZ*NB_I*NB_II;
+ for(i=gidX*PART_NB_PER_WI; i<(gidX + 1)*PART_NB_PER_WI; i+=1)
+ {
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+
+ c = i * mesh->dx.x + mesh->min_position;
+ v = velocity_cache[i + V_GHOSTS_NB];
+ p = (c + hdt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind_p = i_ind + 1;
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB) && i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache + i_ind - (V_START_INDEX-V_GHOSTS_NB) : (i_ind<(V_START_INDEX-V_GHOSTS_NB)) ? v_buff_l_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : v_buff_r_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v = *loc_ptr;
+
+ loc_ptr = (i_ind_p>=(V_START_INDEX-V_GHOSTS_NB) && i_ind_p <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+i_ind_p - (V_START_INDEX-V_GHOSTS_NB) : (i_ind_p<(V_START_INDEX-V_GHOSTS_NB)) ? v_buff_l_loc+i_ind_p-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : v_buff_r_loc+i_ind_p-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ vp = *loc_ptr;
+
+ v = (p*(vp-v) + v);
+ p = c + dt * v;
+
+
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX){ loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ {
+ /* Store result */
+ gscal[i + line_index] = gscal_loc[i];
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/comm_advection_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/comm_advection_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..d10675fede5770453fa488f5472fc9b90b06f372
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/comm_advection_noVec.cl
@@ -0,0 +1,64 @@
+
+
+
+__kernel void buff_advec(__global const float* gvelo,
+ __global float* ppos,
+ __global float* buffer_l,
+ __global float* buffer_r,
+ float dt, __constant struct AdvectionMeshInfo* mesh)
+{
+ int gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ int gidY = get_global_id(1); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(2); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ int line_index ; /* Current 1D problem index */
+
+ float v,vp,p,c, hdt = 0.5 * dt;
+ int i_ind, i_ind_p;
+
+ __local float velocity_cache[V_NB_I];
+ __local float buff_l_loc[V_BUFF_WIDTH];
+ __local float buff_r_loc[V_BUFF_WIDTH];
+ __local float* loc_ptr;
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB)){
+ buff_l_loc[i] = buffer_l[i + V_BUFF_WIDTH*(gidY + gidZ*V_NB_II)];
+ }
+
+ for(i=gidX; i<V_BUFF_WIDTH; i+=(WI_NB)){
+ buff_r_loc[i] = buffer_r[i + V_BUFF_WIDTH*(gidY + gidZ*V_NB_II)];
+ }
+
+ line_index = gidY*V_NB_I + gidZ*V_NB_I*V_NB_II;
+ for(i=gidX; i<V_NB_I; i+=(WI_NB))
+ {
+ /* Read velocity */
+ /* Fill velocity cache */
+ velocity_cache[i] = gvelo[i+line_index];
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ line_index = gidY*NB_I+gidZ*NB_I*NB_II;
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ {
+ c = i * mesh->dx.x + mesh->min_position;
+ v = velocity_cache[i + V_GHOSTS_NB];
+ p = (c + hdt*v) * mesh->v_invdx;
+
+ i_ind = convert_int_rtn(p);
+ p = p - convert_float(i_ind);
+ i_ind_p = i_ind + 1;
+ loc_ptr = (i_ind>=(V_START_INDEX-V_GHOSTS_NB) && i_ind <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache + i_ind - (V_START_INDEX-V_GHOSTS_NB) : (i_ind<(V_START_INDEX-V_GHOSTS_NB)) ? buff_l_loc+i_ind-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : buff_r_loc+i_ind-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ v = *loc_ptr;
+
+ loc_ptr = (i_ind_p>=(V_START_INDEX-V_GHOSTS_NB) && i_ind_p <= (V_STOP_INDEX+V_GHOSTS_NB)) ? velocity_cache+i_ind_p - (V_START_INDEX-V_GHOSTS_NB) : (i_ind_p<(V_START_INDEX-V_GHOSTS_NB)) ? buff_l_loc+i_ind_p-(V_START_INDEX-V_GHOSTS_NB-1-V_BUFF_WIDTH+1) : buff_r_loc+i_ind_p-(V_STOP_INDEX+V_GHOSTS_NB+1) ;
+ vp = *loc_ptr;
+
+ v = (p*(vp-v) + v);
+ p = c + dt * v;
+ ppos[i+line_index] = p;
+ }
+
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/comm_remeshing_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/comm_remeshing_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..89a3dac244ff1cf5a6f72da66ccf9cc8514087ae
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/comm_remeshing_noVec.cl
@@ -0,0 +1,409 @@
+/**
+ * @file comm_remeshing_noVec.cl
+ * Remeshing kernel.
+ */
+/**
+ * Performs remeshing of the particles' scalar.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group.
+ * Each work-item computes <code>NB_I/WI_NB</code> particles positions. To avoid concurrent witings, in case of strong velocity gradients, work-items computes contiguous particles.
+ * Particle are computed through OpenCL vector types of lenght 2, 4 or 8.
+ * Scalar results are stored in a local buffer as a cache and then copied to global memory buffer.
+ *
+ * @param ppos Particle position
+ * @param pscal Particle scalar
+ * @param gscal Grid scalar
+ * @param buffer_l Buffer for storing out of domain contributions (to left)
+ * @param buffer_r Buffer for storing out of domain contributions (to right)
+ * @param min_position Domain lower coordinate
+ * @param dx Space step
+ * @param l_nb buffer_l sizes
+ * @param r_nb buffer_r sizes
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>WI_NB</code> corresponds to the work-item number.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void buff_remesh_l(__global const float* ppos,
+ __global const float* pscal,
+ __global float* buffer_l,
+ int used_width,
+ __constant struct AdvectionMeshInfo* mesh
+ )
+{
+ int gidY = get_global_id(0); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(1); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ float p; /* Particle position */
+ float s; /* Particle scalar */
+float y; /* Normalized distance to nearest left grid point */
+ int ind; /* Integer coordinate */
+ int index; /* Remeshing index */
+ float w;
+
+ uint line_index = gidY*NB_I+ gidZ*NB_I*NB_II; /* Current 1D problem index */
+
+ float l_buff_loc[BUFF_WIDTH];
+ float* loc_ptr;
+
+ // Initialize buffers
+ for(i=0; i<used_width; i++)
+ l_buff_loc[i] = 0.0;
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ //for(i=lid*PART_NB_PER_WI; i<(lid + 1)*PART_NB_PER_WI; i+=1)
+ for(i=0; i<2*BUFF_WIDTH; i++)
+ {
+ /* Read particle position */
+ p = ppos[i + line_index];
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+ /* Remesh particle */
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if(index<START_INDEX){ loc_ptr = l_buff_loc+index-(START_INDEX-1-used_width+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // Store buffers
+ for(i=0; i<used_width; i++)
+ buffer_l[i + gidY*used_width + gidZ*used_width*NB_II] = l_buff_loc[i];
+}
+
+__kernel void buff_remesh_r(__global const float* ppos,
+ __global const float* pscal,
+ __global float* buffer_r,
+ int used_width,
+ __constant struct AdvectionMeshInfo* mesh
+ )
+{
+ int gidY = get_global_id(0); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(1); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ float p; /* Particle position */
+ float s; /* Particle scalar */
+ float y; /* Normalized distance to nearest left grid point */
+ int ind; /* Integer coordinate */
+ int index; /* Remeshing index */
+ float w;
+
+ uint line_index = gidY*NB_I+ gidZ*NB_I*NB_II; /* Current 1D problem index */
+
+ float r_buff_loc[BUFF_WIDTH];
+ float* loc_ptr;
+
+ // Initialize buffers
+ for(i=0; i<used_width; i++)
+ r_buff_loc[i] = 0.0;
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=NB_I-2*BUFF_WIDTH; i<NB_I; i++)
+ {
+ /* Read particle position */
+ p = ppos[i + line_index];
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+ /* Remesh particle */
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if(index > STOP_INDEX){ loc_ptr = loc_ptr = r_buff_loc + index-(STOP_INDEX+1);
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // Store buffers
+ for(i=0; i<used_width; i++)
+ buffer_r[i + gidY*used_width + gidZ*used_width*NB_II] = r_buff_loc[i];
+
+}
+
+__kernel void remesh(__global const float* ppos,
+ __global const float* pscal,
+ __global float* gscal,
+ __constant struct AdvectionMeshInfo* mesh
+ )
+{
+ int lid = get_local_id(0); /* OpenCL work-itme global index (X) */
+ int gidY = get_global_id(1); /* OpenCL work-itme global index (Y) */
+ int gidZ = get_global_id(2); /* OpenCL work-itme global index (Z) */
+ int i; /* Particle index in 1D problem */
+ float p; /* Particle position */
+ float s; /* Particle scalar */
+float y; /* Normalized distance to nearest left grid point */
+ int ind; /* Integer coordinate */
+ int index; /* Remeshing index */
+ float w;
+
+ uint line_index = gidY*NB_I+ gidZ*NB_I*NB_II; /* Current 1D problem index */
+
+ __local float gscal_loc[NB_I];
+ __local float* loc_ptr;
+
+ /* Initialize result buffer */
+ for(i=lid; i<NB_I; i+=WI_NB)
+ gscal_loc[i] = 0.0;
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=lid*PART_NB_PER_WI; i<(lid + 1)*PART_NB_PER_WI; i+=1)
+ {
+ /* Read particle position */
+ p = ppos[i + line_index];
+ /* Read particle scalar */
+ s = pscal[i + line_index];
+ /* Remesh particle */
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ind - REMESH_SHIFT;
+
+ w = REMESH(alpha)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(beta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(gamma)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(delta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ w = REMESH(eta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(zeta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ w = REMESH(theta)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(iota)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ w = REMESH(kappa)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ w = REMESH(mu)(y);
+ if (index>=START_INDEX && index <= STOP_INDEX) {loc_ptr = gscal_loc +index-START_INDEX;
+ w = w * s;
+ (*loc_ptr) += w;}
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ /* Store result */
+ for(i=lid; i<NB_I; i+=WI_NB)
+ gscal[i + line_index] = gscal_loc[i];
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/copy.cl b/hysop/old/gpu.old/cl_src/kernels/copy.cl
new file mode 100644
index 0000000000000000000000000000000000000000..41faadc113a169365148846fad602bd8efa64961
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/copy.cl
@@ -0,0 +1,28 @@
+/**
+ * @file copy.cl
+ * Copy kernel, vectorized version.
+ */
+
+/**
+ * Performs a copy from in to out. Data are read by blocs of <code>__N__</code> contiguously.
+ *
+ * @param in Input data.
+ * @param out Output data
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ */
+__kernel void copy(__global const float* in,
+ __global float* out)
+{
+ uint xIndex = (get_group_id(0) * TILE_DIM_COPY + get_local_id(0)*__N__);
+ uint yIndex = get_group_id(1) * TILE_DIM_COPY + get_local_id(1);
+ uint zIndex = get_global_id(2);
+ uint index = xIndex + yIndex * NB_I + zIndex*NB_I*NB_II;
+ float x__NN__;
+
+ for(uint i=0; i<TILE_DIM_COPY; i+=BLOCK_ROWS_COPY)
+ {
+ x__NN__ = in[index + __NN__ + i*NB_I];
+ out[index + __NN__ + i*NB_I] = x__NN__;
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/copy_locMem.cl b/hysop/old/gpu.old/cl_src/kernels/copy_locMem.cl
new file mode 100644
index 0000000000000000000000000000000000000000..ea51b77ab13c8100dd27011bba351c76129ab43a
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/copy_locMem.cl
@@ -0,0 +1,33 @@
+/**
+ * @file copy_locMem.cl
+ * Copy kernel, use local memory.
+ */
+
+/**
+ * Performs a copy from in to out. Data are moved to local memory buffer.
+ *
+ * @param in Input data.
+ * @param out Output data
+ *
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ */
+__kernel void copy(__global const float* in,
+ __global float* out)
+{
+ uint xIndex = get_group_id(0) * TILE_DIM_COPY + get_local_id(0);
+ uint yIndex = get_group_id(1) * TILE_DIM_COPY + get_local_id(1);
+ uint zIndex = get_global_id(2);
+ uint index = xIndex + yIndex * NB_I + zIndex*NB_I*NB_II;
+
+ __local float tile[TILE_DIM_COPY][TILE_DIM_COPY];
+
+ for(uint i=0; i<TILE_DIM_COPY; i+=BLOCK_ROWS_COPY)
+ {
+ tile[get_local_id(1)+i][get_local_id(0)] = in[index + i*NB_I];
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ for(uint i=0; i<TILE_DIM_COPY; i+=BLOCK_ROWS_COPY)
+ {
+ out[index + i*NB_I] = tile[get_local_id(1)+i][get_local_id(0)];
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/copy_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/copy_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..fb4cea67ba2882f759e857234236ec9b4b5c4049
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/copy_noVec.cl
@@ -0,0 +1,25 @@
+/**
+ * @file copy.cl
+ * Copy kernel, basic version.
+ */
+
+/**
+ * Performs a copy from in to out.
+ *
+ * @param in Input data.
+ * @param out Output data
+ * @remark NB_I, NB_II, NB_III : points number in directions from 1st varying index to last.
+ */
+__kernel void copy(__global const float* in,
+ __global float* out)
+{
+ uint xIndex = get_group_id(0) * TILE_DIM_COPY + get_local_id(0);
+ uint yIndex = get_group_id(1) * TILE_DIM_COPY + get_local_id(1);
+ uint zIndex = get_global_id(2);
+ uint index = xIndex + yIndex * NB_I + zIndex*NB_I*NB_II;
+
+ for(uint i=0; i<TILE_DIM_COPY; i+=BLOCK_ROWS_COPY)
+ {
+ out[index + i*NB_I] = in[index + i*NB_I];
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/diffusion.cl b/hysop/old/gpu.old/cl_src/kernels/diffusion.cl
new file mode 100644
index 0000000000000000000000000000000000000000..edbfa572a5e09fb97d792c3860d77ba5b6e93215
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/diffusion.cl
@@ -0,0 +1,183 @@
+/**
+ * @file diffusion.cl
+ * Diffusion kernel.
+ */
+
+/**
+ * Computes diffusion operator with finite differences.
+ * Stencil computation is performed within a 2D index space of size <code>TILE_SIZE</code> by a work-group. The 3rd direction is traversed in a loop for data reuse.
+ *
+ * @param scal_in Input scalar field
+ * @param ghostsX Ghosts array if X is a communication direction
+ * @param ghostsY Ghosts array if Y is a communication direction
+ * @param ghostsZ Ghosts array if Z is a communication direction
+ * @param scal_out Output scalar field
+ * @param nudt Diffusion coefficient
+ * @param dx Mesh space step
+ *
+ * @remark <code>NB_X</code>, <code>NB_Y</code>, <code>NB_Z</code> : points number in physical space directions.
+ * @remark <code>NB_PART</code> Particles number per work-item in computing direction
+ * @remark <code>CUT_DIT_X</code>, <code>CUT_DIT_Y</code> and <code>CUT_DIT_Z</code> : flags for communication direction
+ * @remark <code>NB_GROUPS_I</code> and <code>NB_GROUPS_II</code> : tiles number in X and Y directions.
+ * @remark <code>L_WIDTH</code> : work-item number in tile.
+ */
+
+__kernel void diffusion(__global const float* scal_in,
+#if CUT_DIR_X == 1
+ __global const float* ghostsX,
+#endif
+#if CUT_DIR_Y == 1
+ __global const float* ghostsY,
+#endif
+#if CUT_DIR_Z == 1
+ __global const float* ghostsZ,
+#endif
+ __global float* scal_out,
+ float nudt,
+ float4 dx)
+{
+ int t_gidX, t_gidY;
+ int lidX, lidY;
+ int gidX, gidY, gidZ;
+ float cx, cy, cz;
+ float scal_z_m[NB_PART];
+ float scal_z[NB_PART];
+ float scal_z_p[NB_PART];
+ float s;
+ uint i;
+
+ __local float tile_XY[TILE_SIZE+2][TILE_SIZE+2];
+
+ for (t_gidX=get_group_id(0); t_gidX<NB_GROUPS_I; t_gidX+=get_num_groups(0)) {
+ for (t_gidY=get_group_id(1); t_gidY<NB_GROUPS_II; t_gidY+=get_num_groups(1)) {
+
+ // Tile computation
+ lidX = get_local_id(0);
+ lidY = get_local_id(1);
+ gidX = t_gidX*TILE_SIZE + lidX; /* OpenCL work-item global index (X) */
+ gidY = t_gidY*TILE_SIZE + lidY; /* OpenCL work-item global index (Y) */
+ cx = nudt/(dx.x*dx.x);
+ cy = nudt/(dx.y*dx.y);
+ cz = nudt/(dx.z*dx.z);
+
+ for(i=0;i<NB_PART;i++) {
+#if CUT_DIR_Z == 1
+ scal_z_m[i] = ghostsZ[gidX + (gidY+i*L_WIDTH)*NB_X + NB_X*NB_Y];
+#else
+ scal_z_m[i] = scal_in[gidX + (gidY+i*L_WIDTH)*NB_X + (NB_Z-1)*NB_X*NB_Y];
+#endif
+ scal_z[i] = scal_in[gidX + (gidY+i*L_WIDTH)*NB_X];
+ }
+
+ lidX += 1;
+ lidY += 1;
+
+ // loop over Z indices but last.
+ for (gidZ=0; gidZ<(NB_Z-1); gidZ++) {
+ for(i=0;i<NB_PART;i++) {
+ // fill the tile
+ tile_XY[lidX][lidY+i*L_WIDTH] = scal_in[gidX + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y];
+
+ /* // fill tile edges */
+#if CUT_DIR_X == 1
+ tile_XY[0][lidY+i*L_WIDTH] = (t_gidX*TILE_SIZE>=1) ? scal_in[t_gidX*TILE_SIZE-1 + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y] : ghostsX[1 + (gidY+i*L_WIDTH)*2 + gidZ*2*NB_Y];
+ tile_XY[TILE_SIZE+1][lidY+i*L_WIDTH] = ((t_gidX+1)*TILE_SIZE<NB_X) ? scal_in[(t_gidX+1)*TILE_SIZE + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y]: ghostsX[(gidY+i*L_WIDTH)*2 + gidZ*2*NB_Y];
+#else
+ tile_XY[0][lidY+i*L_WIDTH] = scal_in[((t_gidX*TILE_SIZE-1+NB_X)%NB_X) + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y];
+ tile_XY[TILE_SIZE+1][lidY+i*L_WIDTH] = scal_in[(((t_gidX+1)*TILE_SIZE+NB_X)%NB_X) + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y];
+#endif
+ }
+#if CUT_DIR_Y == 1
+ tile_XY[lidX][0] = (t_gidY*TILE_SIZE>=1)? scal_in[gidX + (t_gidY*TILE_SIZE-1)*NB_X + gidZ*NB_X*NB_Y] : ghostsY[gidX + NB_X + gidZ*NB_X*2];
+ tile_XY[lidX][TILE_SIZE+1] = ((t_gidY+1)*TILE_SIZE<NB_Y) ? scal_in[gidX + (t_gidY+1)*TILE_SIZE*NB_X + gidZ*NB_X*NB_Y] : ghostsY[gidX + gidZ*NB_X*2];
+#else
+ tile_XY[lidX][0] = scal_in[gidX + ((t_gidY*TILE_SIZE-1+NB_Y)%NB_Y)*NB_X + gidZ*NB_X*NB_Y];
+ tile_XY[lidX][TILE_SIZE+1] = scal_in[gidX + (((t_gidY+1)*TILE_SIZE+NB_Y)%NB_Y)*NB_X + gidZ*NB_X*NB_Y];
+#endif
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=0;i<NB_PART;i++) {
+ /* get scalar value in Z direction */
+ scal_z_p[i] = scal_in[gidX + (gidY+i*L_WIDTH)*NB_X + (gidZ+1)*NB_X*NB_Y];
+
+ // Compute stencil
+ // central point
+ s = scal_z[i] * (1.0 - 2.0 * (cx + cy + cz));
+
+ s += cz*(scal_z_m[i] + scal_z_p[i]);
+
+ s += cy * tile_XY[lidX][lidY+i*L_WIDTH-1];
+ s += cy * tile_XY[lidX][lidY+i*L_WIDTH+1];
+ s += cx * tile_XY[lidX-1][lidY+i*L_WIDTH];
+ s += cx * tile_XY[lidX+1][lidY+i*L_WIDTH];
+
+ // write result
+ scal_out[gidX + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y] = s;
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=0;i<NB_PART;i++) {
+ // Shift Z values
+ scal_z_m[i] = scal_z[i];
+ scal_z[i] = scal_z_p[i];
+ }
+ }
+
+ // Compute last point (from ghosts)
+ gidZ = NB_Z - 1;
+
+ for(i=0;i<NB_PART;i++) {
+ // fill the tile
+ tile_XY[lidX][lidY+i*L_WIDTH] = scal_in[gidX + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y];
+
+ /* // fill tile edges */
+#if CUT_DIR_X == 1
+ tile_XY[0][lidY+i*L_WIDTH] = (t_gidX*TILE_SIZE>=1) ? scal_in[t_gidX*TILE_SIZE-1 + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y] : ghostsX[1 + (gidY+i*L_WIDTH)*2 + gidZ*2*NB_Y];
+ tile_XY[TILE_SIZE+1][lidY+i*L_WIDTH] = ((t_gidX+1)*TILE_SIZE<NB_X) ? scal_in[(t_gidX+1)*TILE_SIZE + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y]: ghostsX[(gidY+i*L_WIDTH)*2 + gidZ*2*NB_Y];
+#else
+ tile_XY[0][lidY+i*L_WIDTH] = scal_in[((t_gidX*TILE_SIZE-1+NB_X)%NB_X) + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y];
+ tile_XY[TILE_SIZE+1][lidY+i*L_WIDTH] = scal_in[(((t_gidX+1)*TILE_SIZE+NB_X)%NB_X) + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y];
+#endif
+ }
+#if CUT_DIR_Y == 1
+ tile_XY[lidX][0] = (t_gidY*TILE_SIZE>=1)? scal_in[gidX + (t_gidY*TILE_SIZE-1)*NB_X + gidZ*NB_X*NB_Y] : ghostsY[gidX + NB_X + gidZ*NB_X*2];
+ tile_XY[lidX][TILE_SIZE+1] = ((t_gidY+1)*TILE_SIZE<NB_Y) ? scal_in[gidX + (t_gidY+1)*TILE_SIZE*NB_X + gidZ*NB_X*NB_Y] : ghostsY[gidX + gidZ*NB_X*2];
+#else
+ tile_XY[lidX][0] = scal_in[gidX + ((t_gidY*TILE_SIZE-1+NB_Y)%NB_Y)*NB_X + gidZ*NB_X*NB_Y];
+ tile_XY[lidX][TILE_SIZE+1] = scal_in[gidX + (((t_gidY+1)*TILE_SIZE+NB_Y)%NB_Y)*NB_X + gidZ*NB_X*NB_Y];
+#endif
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=0;i<NB_PART;i++) {
+ /* // get scalar value in Z direction */
+#if CUT_DIR_Z == 1
+ scal_z_p[i] = ghostsZ[gidX + (gidY+i*L_WIDTH)*NB_X];
+#else
+ scal_z_p[i] = scal_in[gidX + (gidY+i*L_WIDTH)*NB_X];
+#endif
+
+ // Compute stencil
+ /* // central point */
+ s = scal_z[i] * (1.0 - 2.0 * (cx + cy + cz));
+
+ s += cz*(scal_z_m[i] + scal_z_p[i]);
+
+ s += cy * tile_XY[lidX][lidY+i*L_WIDTH-1];
+ s += cy * tile_XY[lidX][lidY+i*L_WIDTH+1];
+ s += cx * tile_XY[lidX-1][lidY+i*L_WIDTH];
+ s += cx * tile_XY[lidX+1][lidY+i*L_WIDTH];
+
+ // write result
+ scal_out[gidX + (gidY+i*L_WIDTH)*NB_X + gidZ*NB_X*NB_Y] = s;
+ }
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/fine_to_coarse_filter.cl b/hysop/old/gpu.old/cl_src/kernels/fine_to_coarse_filter.cl
new file mode 100644
index 0000000000000000000000000000000000000000..2851c60383e2d634a729ab5cbeb0360e5c5da5a9
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/fine_to_coarse_filter.cl
@@ -0,0 +1,178 @@
+__kernel void initialize_output(__global float* scal_out) {
+ scal_out[get_global_id(0) + get_global_id(1)*NB_OUT_X + get_global_id(2)*NB_OUT_X*NB_OUT_Y] = 0.0;
+}
+
+__kernel void coarse_to_fine_filter(__global const float* scal_in,
+ __global float* scal_out,
+ float scale_factor,
+ float4 dx_in, float4 dx_out, float4 origin,
+ int offset_y, int offset_z) {
+ // Work-group is computed from coarse grid (without ghosts)
+ // globalsize(1) = (NB_OUT_Y - 2*GHOSTS_OUT_Y) / PTS_PER_CELL_Y
+ // globalsize(2) = (NB_OUT_Z - 2*GHOSTS_OUT_Z) / PTS_PER_CELL_X
+ // Resolutions are linked by: (NB_OUT - 2*GHOSTS_OUT) * PTS_PER_CELL = NB_IN
+ // A work-group is in charge of a subdomain corresponding to:
+ // - [NB_OUT_X, L_STENCIL, L_STENCIL] for the coarse grid
+ // - [NB_IN_X, PTS_PER_CELL_Y, PTS_PER_CELL] for the fine grid
+ // Data in the fine grid are read only once for the whole computation.
+ // Because of the stencil, these data are spread over multiple coarse grid cells -> we need a global memory synchronization.
+ // The global synchronization is obtained by several kernel launch with an offset
+ unsigned int lid = get_local_id(0);
+ unsigned int gid_y = get_global_id(1);
+ unsigned int gid_z = get_global_id(2);
+ unsigned int iy_c = gid_y*L_STENCIL+offset_y;
+ unsigned int iz_c = gid_z*L_STENCIL+offset_z;
+ unsigned int iy_f = iy_c*PTS_PER_CELL_Y;
+ unsigned int iz_f = iz_c*PTS_PER_CELL_Z;
+ unsigned int i, j, k, b_id, pt_x, pt_y, pt_z;
+ float4 coord_in;
+ float4 coord_out;
+ float4 d;
+#if FORMULA==L2_1
+ float4 wx, wy, wz;
+#endif
+ __local float line[WG*PTS_PER_CELL_X];
+ __local float result[NB_OUT_X][L_STENCIL][L_STENCIL];
+ __private float p_res[L_STENCIL][L_STENCIL][L_STENCIL];
+
+ // Fill local arrays
+ // Output data
+ for (k=0;k<L_STENCIL;k++)
+ for (j=0;j<L_STENCIL;j++)
+ for (i=lid;i<NB_OUT_X;i+=WG)
+ result[i][j][k] = scal_out[i + (GHOSTS_OUT_Y+iy_c-SHIFT_STENCIL+j)*NB_OUT_X +
+ (GHOSTS_OUT_Z+iz_c-SHIFT_STENCIL+k)*NB_OUT_X*NB_OUT_Y];
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for (b_id=0;b_id<NB_IN_X/(WG*PTS_PER_CELL_X);b_id++)
+ {
+ // Compute a bloc of: (b_id is the bloc number in X direction)
+ // - [WG*PTS_PER_CELL_X, PTS_PER_CELL_Y, PTS_PER_CELL_Z] points in fine grid
+ // - [WG, L_STENCIL, L_STENCIL] points in coarse grid
+ // Each work-item is computing a coarse cell (looping in 3D over PTS_PER_CELL thanks to pt_x, pt_y and pt_z indices)
+ // global fine grid data are cached line by line in the X direction
+ coord_out = ((float4)(b_id*WG+lid, iy_c, iz_c, 0.0)) * dx_out;
+ // Initialize the register corresponding to the current cell
+ for (pt_z=0;pt_z<L_STENCIL;pt_z++)
+ for (pt_y=0;pt_y<L_STENCIL;pt_y++)
+ for (pt_x=0;pt_x<L_STENCIL;pt_x++)
+ p_res[pt_x][pt_y][pt_z] = 0.0;
+
+ // Loop over PTS_PER_CELL_Z: fine grid points in the curent cell
+ for (pt_z=0;pt_z<PTS_PER_CELL_Z;pt_z++)
+ {
+ // Loop over PTS_PER_CELL_Y: fine grid points in the curent cell
+ for (pt_y=0;pt_y<PTS_PER_CELL_Y;pt_y++)
+ {
+ // Input cache
+ for (i=lid;i<WG*PTS_PER_CELL_X;i+=WG)
+ line[i] = scal_in[b_id*(WG*PTS_PER_CELL_X) + i + (iy_f+pt_y)*NB_IN_X + (iz_f+pt_z)*NB_IN_X*NB_IN_Y];
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ // Loop over PTS_PER_CELL_X: fine grid points in the curent cell
+ for (pt_x=0;pt_x<PTS_PER_CELL_X;pt_x++)
+ {
+ coord_in = ((float4)(b_id*(WG*PTS_PER_CELL_X) + lid*PTS_PER_CELL_X + pt_x, iy_f+pt_y, iz_f+pt_z, 0.0)) * dx_in;
+ d = (coord_in - coord_out) / dx_out;
+ #if FORMULA==LINEAR
+ p_res[0][0][0] += scale_factor * (1.0 - d.x) * (1.0 - d.y) * (1.0 - d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][0][1] += scale_factor * (1.0 - d.x) * (1.0 - d.y) * (d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][1][0] += scale_factor * (1.0 - d.x) * (d.y) * (1.0 - d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][1][1] += scale_factor * (1.0 - d.x) * (d.y) * (d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][0][0] += scale_factor * (d.x) * (1.0 - d.y) * (1.0 - d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][0][1] += scale_factor * (d.x) * (1.0 - d.y) * (d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][1][0] += scale_factor * (d.x) * (d.y) * (1.0 - d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][1][1] += scale_factor * (d.x) * (d.y) * (d.z) * line[lid*PTS_PER_CELL_X+pt_x];
+ #elif FORMULA==L2_1
+ wx = (float4)(alpha_l2_1(d.x), beta_l2_1(d.x), gamma_l2_1(d.x), delta_l2_1(d.x));
+ wy = (float4)(alpha_l2_1(d.y), beta_l2_1(d.y), gamma_l2_1(d.y), delta_l2_1(d.y));
+ wz = (float4)(alpha_l2_1(d.z), beta_l2_1(d.z), gamma_l2_1(d.z), delta_l2_1(d.z));
+ p_res[0][0][0] += scale_factor * wx.x * wy.x * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][0][1] += scale_factor * wx.x * wy.x * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][0][2] += scale_factor * wx.x * wy.x * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][0][3] += scale_factor * wx.x * wy.x * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][1][0] += scale_factor * wx.x * wy.y * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][1][1] += scale_factor * wx.x * wy.y * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][1][2] += scale_factor * wx.x * wy.y * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][1][3] += scale_factor * wx.x * wy.y * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][2][0] += scale_factor * wx.x * wy.z * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][2][1] += scale_factor * wx.x * wy.z * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][2][2] += scale_factor * wx.x * wy.z * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][2][3] += scale_factor * wx.x * wy.z * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][3][0] += scale_factor * wx.x * wy.w * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][3][1] += scale_factor * wx.x * wy.w * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][3][2] += scale_factor * wx.x * wy.w * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[0][3][3] += scale_factor * wx.x * wy.w * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+
+ p_res[1][0][0] += scale_factor * wx.y * wy.x * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][0][1] += scale_factor * wx.y * wy.x * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][0][2] += scale_factor * wx.y * wy.x * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][0][3] += scale_factor * wx.y * wy.x * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][1][0] += scale_factor * wx.y * wy.y * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][1][1] += scale_factor * wx.y * wy.y * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][1][2] += scale_factor * wx.y * wy.y * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][1][3] += scale_factor * wx.y * wy.y * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][2][0] += scale_factor * wx.y * wy.z * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][2][1] += scale_factor * wx.y * wy.z * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][2][2] += scale_factor * wx.y * wy.z * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][2][3] += scale_factor * wx.y * wy.z * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][3][0] += scale_factor * wx.y * wy.w * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][3][1] += scale_factor * wx.y * wy.w * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][3][2] += scale_factor * wx.y * wy.w * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[1][3][3] += scale_factor * wx.y * wy.w * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+
+ p_res[2][0][0] += scale_factor * wx.z * wy.x * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][0][1] += scale_factor * wx.z * wy.x * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][0][2] += scale_factor * wx.z * wy.x * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][0][3] += scale_factor * wx.z * wy.x * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][1][0] += scale_factor * wx.z * wy.y * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][1][1] += scale_factor * wx.z * wy.y * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][1][2] += scale_factor * wx.z * wy.y * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][1][3] += scale_factor * wx.z * wy.y * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][2][0] += scale_factor * wx.z * wy.z * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][2][1] += scale_factor * wx.z * wy.z * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][2][2] += scale_factor * wx.z * wy.z * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][2][3] += scale_factor * wx.z * wy.z * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][3][0] += scale_factor * wx.z * wy.w * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][3][1] += scale_factor * wx.z * wy.w * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][3][2] += scale_factor * wx.z * wy.w * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[2][3][3] += scale_factor * wx.z * wy.w * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+
+ p_res[3][0][0] += scale_factor * wx.w * wy.x * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][0][1] += scale_factor * wx.w * wy.x * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][0][2] += scale_factor * wx.w * wy.x * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][0][3] += scale_factor * wx.w * wy.x * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][1][0] += scale_factor * wx.w * wy.y * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][1][1] += scale_factor * wx.w * wy.y * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][1][2] += scale_factor * wx.w * wy.y * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][1][3] += scale_factor * wx.w * wy.y * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][2][0] += scale_factor * wx.w * wy.z * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][2][1] += scale_factor * wx.w * wy.z * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][2][2] += scale_factor * wx.w * wy.z * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][2][3] += scale_factor * wx.w * wy.z * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][3][0] += scale_factor * wx.w * wy.w * wz.x * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][3][1] += scale_factor * wx.w * wy.w * wz.y * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][3][2] += scale_factor * wx.w * wy.w * wz.z * line[lid*PTS_PER_CELL_X+pt_x];
+ p_res[3][3][3] += scale_factor * wx.w * wy.w * wz.w * line[lid*PTS_PER_CELL_X+pt_x];
+
+ #endif
+ }
+ }
+ }
+ // Store the registers results in local memory
+ for (pt_z=0;pt_z<L_STENCIL;pt_z++)
+ for (pt_y=0;pt_y<L_STENCIL;pt_y++)
+ for (pt_x=0;pt_x<L_STENCIL;pt_x++) {
+ result[GHOSTS_OUT_X+b_id*WG+lid-SHIFT_STENCIL+pt_x][pt_y][pt_z] += p_res[pt_x][pt_y][pt_z];
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+
+ // Write result in output array
+ for (k=0;k<L_STENCIL;k++)
+ for (j=0;j<L_STENCIL;j++)
+ for (i=lid;i<NB_OUT_X;i+=WG)
+ scal_out[i + (GHOSTS_OUT_Y+iy_c-SHIFT_STENCIL+j)*NB_OUT_X +
+ (GHOSTS_OUT_Z+iz_c-SHIFT_STENCIL+k)*NB_OUT_X*NB_OUT_Y] = result[i][j][k];
+
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/multiphase_baroclinic_rhs.cl b/hysop/old/gpu.old/cl_src/kernels/multiphase_baroclinic_rhs.cl
new file mode 100644
index 0000000000000000000000000000000000000000..d9938aa9994f0c5e1c37b8d56fe82b45db3405e0
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/multiphase_baroclinic_rhs.cl
@@ -0,0 +1,321 @@
+/** Computes the right hand side of the baroclinic term.
+ * The pressure gradient is given in input at a coarse scale.
+ * The density is given at a fine scale.
+ * Result is computed ans returned at fine scale.
+ */
+#define C_TILE_IDX(x,y) x+GHOSTS_C_X+(y+GHOSTS_C_Y)*C_TILE_WIDTH
+#if FD_ORDER == FD_C_2
+#define GRAD_GH 1
+#endif
+#if FD_ORDER == FD_C_4
+#define GRAD_GH 2
+#endif
+
+float compute_density(float x);
+float compute_density(float x){
+ return __USER_DENSITY_FUNCTION_FROM_GIVEN_INPUT__;
+}
+
+float interpolate(__local float* loc_gradp_zm, __local float* loc_gradp_zp,
+ float *h, int lidx, int lidy,
+ int cellx, int celly, int cellz);
+
+float interpolate(__local float* loc_zm,
+ __local float* loc_zp,
+ float *h,
+ int lidx,
+ int lidy,
+ int cellx,
+ int celly,
+ int cellz) {
+ float res = 0.0;
+ res += (1.0 - h[cellz]) * (1.0 - h[cellx]) * (1.0 - h[celly]) * loc_zm[C_TILE_IDX(lidx,lidy)];
+ res += (1.0 - h[cellz]) * (h[cellx]) * (1.0 - h[celly]) * loc_zm[C_TILE_IDX(lidx+1,lidy)];
+ res += (1.0 - h[cellz]) * (1.0 - h[cellx]) * (h[celly]) * loc_zm[C_TILE_IDX(lidx,lidy+1)];
+ res += (1.0 - h[cellz]) * (h[cellx]) * (h[celly]) * loc_zm[C_TILE_IDX(lidx+1,lidy+1)];
+ res += (h[cellz]) * (1.0 - h[cellx]) * (1.0 - h[celly]) * loc_zp[C_TILE_IDX(lidx,lidy)];
+ res += (h[cellz]) * (h[cellx]) * (1.0 - h[celly]) * loc_zp[C_TILE_IDX(lidx+1,lidy)];
+ res += (h[cellz]) * (1.0 - h[cellx]) * (h[celly]) * loc_zp[C_TILE_IDX(lidx,lidy+1)];
+ res += (h[cellz]) * (h[cellx]) * (h[celly]) * loc_zp[C_TILE_IDX(lidx+1,lidy+1)];
+ return res;
+}
+
+void fill_loc_rho_cache(__local float *loc_rho,
+ __global const float* rho,
+#if CUT_DIR_Y == 1
+ __global const float* rho_ghostsY,
+#endif
+ int lidx,
+ int lidy,
+ int gidx,
+ int gidy,
+ int idz);
+void fill_loc_rho_cache(__local float *loc_rho,
+ __global const float* rho,
+#if CUT_DIR_Y == 1
+ __global const float* rho_ghostsY,
+#endif
+ int lidx,
+ int lidy,
+ int gidx,
+ int gidy,
+ int idz) {
+ int celly, cellx;
+ if (gidx > 0 && gidx < ((int)get_num_groups(0))-1 && gidy > 0 && gidy < ((int)get_num_groups(1))-1) {
+ for (celly=lidy; celly<F_TILE_SIZE+2*GRAD_GH; celly+=get_local_size(1)) {
+ for (cellx=lidx; cellx<F_TILE_SIZE+2*GRAD_GH; cellx+=get_local_size(0)) {
+ loc_rho[cellx + (celly)*(F_TILE_SIZE+2*GRAD_GH)] =
+ compute_density(rho[cellx-GRAD_GH + gidx*F_TILE_SIZE +
+ (celly-GRAD_GH + gidy*F_TILE_SIZE)*NB_F_X +
+ idz*NB_F_X*NB_F_Y]);
+ }
+ }
+ } else {
+ for (celly=lidy; celly<F_TILE_SIZE+2*GRAD_GH; celly+=get_local_size(1)) {
+ for (cellx=lidx; cellx<F_TILE_SIZE+2*GRAD_GH; cellx+=get_local_size(0)) {
+#if CUT_DIR_Y == 1
+ if (celly-GRAD_GH + gidy*F_TILE_SIZE >= NB_F_Y)
+ loc_rho[cellx + (celly)*(F_TILE_SIZE+2*GRAD_GH)] =
+ compute_density(rho_ghostsY[(cellx-GRAD_GH + gidx*F_TILE_SIZE+NB_F_X)%NB_F_X +
+ (celly-GRAD_GH + gidy*F_TILE_SIZE - NB_F_Y)*NB_F_X +
+ idz*NB_F_X*2*GRAD_GH]);
+ else if (celly-GRAD_GH + gidy*F_TILE_SIZE < 0)
+ loc_rho[cellx + (celly)*(F_TILE_SIZE+2*GRAD_GH)] =
+ compute_density(rho_ghostsY[(cellx-GRAD_GH + gidx*F_TILE_SIZE+NB_F_X)%NB_F_X +
+ (2*GRAD_GH + (celly-GRAD_GH + gidy*F_TILE_SIZE))*NB_F_X +
+ idz*NB_F_X*2*GRAD_GH]);
+ else
+ loc_rho[cellx + (celly)*(F_TILE_SIZE+2*GRAD_GH)] =
+ compute_density(rho[(cellx-GRAD_GH + gidx*F_TILE_SIZE+NB_F_X)%NB_F_X +
+ (celly-GRAD_GH + gidy*F_TILE_SIZE)*NB_F_X +
+ idz*NB_F_X*NB_F_Y]);
+#else
+ loc_rho[cellx + (celly)*(F_TILE_SIZE+2*GRAD_GH)] =
+ compute_density(rho[(cellx-GRAD_GH + gidx*F_TILE_SIZE+NB_F_X)%NB_F_X +
+ ((celly-GRAD_GH + gidy*F_TILE_SIZE+NB_F_Y)%NB_F_Y)*NB_F_X +
+ idz*NB_F_X*NB_F_Y]);
+#endif
+ }
+ }
+ }
+}
+
+__kernel void baroclinic_rhs(__global float* rhs_x,
+ __global float* rhs_y,
+ __global float* rhs_z,
+ __global const float* rho,
+#if CUT_DIR_Y == 1
+ __global const float* rho_ghostsY,
+#endif
+#if CUT_DIR_Z == 1
+ __global const float* rho_ghostsZ,
+#endif
+ __global const float* gradp,
+ float4 dx_coarse,
+ float4 dx_fine)
+{
+ /* Space index refers to the coarse grid comute points */
+ int lidx = get_local_id(0);
+ int lidy = get_local_id(1);
+ int gidx = get_group_id(0);
+ int gidy = get_group_id(1);
+ int rhs_idx = lidx*N_PER_CELL + gidx*F_TILE_SIZE + (lidy*N_PER_CELL + gidy*F_TILE_SIZE)*NB_F_X;
+ float h[N_PER_CELL];
+ int i, cellx, celly, cellz;
+ int idz, c_idz;
+ float p_gradp, gradrho_x, gradrho_y, gradrho_z;
+ float rho_zm[N_PER_CELL][N_PER_CELL];
+#if FD_ORDER == FD_C_4
+ float rho_zmm[N_PER_CELL][N_PER_CELL];
+ float rho_zp[N_PER_CELL][N_PER_CELL];
+ float rho_zpp;
+#endif
+
+ __local float loc_rho[(F_TILE_SIZE+2*GRAD_GH)*(F_TILE_SIZE+2*GRAD_GH)];
+ __local float loc_gradp_zm[C_TILE_WIDTH*C_TILE_HEIGHT];
+ __local float loc_gradp_zp[C_TILE_WIDTH*C_TILE_HEIGHT];
+
+
+ // Compute distances from fine grid points to coarse left point cell.
+ for (i=0; i<N_PER_CELL; i++)
+ h[i] = i * 1.0 / (1.0 * N_PER_CELL);
+
+ idz = 0; /* Fine grid Z indice */
+ c_idz=GHOSTS_C_Z;
+ // Fill gradp z cache for first iteration
+ for (celly=lidy; celly<C_TILE_HEIGHT; celly+=get_local_size(1)) {
+ for (cellx=lidx; cellx<C_TILE_WIDTH; cellx+=get_local_size(0)) {
+ loc_gradp_zm[cellx + celly*(C_TILE_WIDTH)] =
+ gradp[cellx + gidx*C_TILE_SIZE + (celly + gidy*C_TILE_SIZE)*NB_C_X + c_idz*NB_C_X*NB_C_Y];
+ }
+ }
+
+ for (celly=0; celly<N_PER_CELL; celly++) {
+ for (cellx=0; cellx<N_PER_CELL; cellx++) {
+#if FD_ORDER == FD_C_4
+#if CUT_DIR_Z == 1
+ rho_zm[cellx][celly] = compute_density(rho_ghostsZ[rhs_idx + cellx + celly*NB_F_X + 3*NB_F_X*NB_F_Y]);
+ rho_zmm[cellx][celly] = compute_density(rho_ghostsZ[rhs_idx + cellx + celly*NB_F_X + 2*NB_F_X*NB_F_Y]);
+ rho_zp[cellx][celly] = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + NB_F_X*NB_F_Y]);
+#else
+ rho_zm[cellx][celly] = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + (NB_F_Z-1)*NB_F_X*NB_F_Y]);
+ rho_zmm[cellx][celly] = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + (NB_F_Z-2)*NB_F_X*NB_F_Y]);
+ rho_zp[cellx][celly] = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + NB_F_X*NB_F_Y]);
+#endif
+#else
+#if CUT_DIR_Z == 1
+ rho_zm[cellx][celly] = compute_density(rho_ghostsZ[rhs_idx + cellx + celly*NB_F_X + NB_F_X*NB_F_Y]);
+#else
+ rho_zm[cellx][celly] = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + (NB_F_Z-1)*NB_F_X*NB_F_Y]));
+#endif
+#endif
+ }
+ }
+
+ for (c_idz=GHOSTS_C_Z; c_idz<NB_C_Z-GHOSTS_C_Z; c_idz++) {
+
+ if((c_idz-GHOSTS_C_Z)%2 == 0)
+ for (celly=lidy; celly<C_TILE_HEIGHT; celly+=get_local_size(1)) {
+ for (cellx=lidx; cellx<C_TILE_WIDTH; cellx+=get_local_size(0)) {
+ loc_gradp_zp[cellx + celly*(C_TILE_WIDTH)] =
+ gradp[cellx + gidx*C_TILE_SIZE + (celly + gidy*C_TILE_SIZE)*NB_C_X + (c_idz+1)*NB_C_X*NB_C_Y];
+ }
+ }
+ else
+ for (celly=lidy; celly<C_TILE_HEIGHT; celly+=get_local_size(1)) {
+ for (cellx=lidx; cellx<C_TILE_WIDTH; cellx+=get_local_size(0)) {
+ loc_gradp_zm[cellx + celly*(C_TILE_WIDTH)] =
+ gradp[cellx + gidx*C_TILE_SIZE + (celly + gidy*C_TILE_SIZE)*NB_C_X + (c_idz+1)*NB_C_X*NB_C_Y];
+ }
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for (cellz=0; cellz<N_PER_CELL; cellz++) {
+ //fill rho cache
+#if CUT_DIR_Y == 1
+ fill_loc_rho_cache(loc_rho, rho, rho_ghostsY, lidx, lidy, gidx, gidy, idz);
+#else
+ fill_loc_rho_cache(loc_rho, rho, lidx, lidy, gidx, gidy, idz);
+#endif
+
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for (celly=0; celly<N_PER_CELL; celly++) {
+ for (cellx=0; cellx<N_PER_CELL; cellx++) {
+ if((c_idz-GHOSTS_C_Z)%2 == 0)
+ p_gradp = interpolate(loc_gradp_zm, loc_gradp_zp, h, lidx, lidy, cellx, celly, cellz);
+ else
+ p_gradp = interpolate(loc_gradp_zp, loc_gradp_zm, h, lidx, lidy, cellx, celly, cellz);
+
+ ///// TEMP WRITE GRADP TO RHS
+ //rhs_x[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] = p_gradp;
+ ///// END TEMP WRITE GRADP TO RHS
+
+#if FD_ORDER == FD_C_2
+ gradrho_x = loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx+1 +
+ (GRAD_GH+lidy*N_PER_CELL+celly)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_x -= loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx-1 +
+ (GRAD_GH+lidy*N_PER_CELL+celly)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_x /= (2.0*dx_fine.x);
+
+ gradrho_y = loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx +
+ (GRAD_GH+lidy*N_PER_CELL+celly+1)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_y -= loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx +
+ (GRAD_GH+lidy*N_PER_CELL+celly-1)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_y /= (2.0*dx_fine.y);
+
+#if CUT_DIR_Z == 1
+ if (idz==NB_F_Z-1)
+ gradrho_z = compute_density(rho_ghostsZ[rhs_idx + cellx + celly*NB_F_X]);
+ else
+ gradrho_z = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + ((idz+1)%NB_F_Z)*NB_F_X*NB_F_Y]);
+#else
+ gradrho_z = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + ((idz+1)%NB_F_Z)*NB_F_X*NB_F_Y]);
+#endif
+ gradrho_z -= rho_zm[cellx][celly];
+ gradrho_z /= (2.0*dx_fine.z);
+
+#endif
+#if FD_ORDER == FD_C_4
+ gradrho_x = loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx+1 +
+ (GRAD_GH+lidy*N_PER_CELL+celly)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_x -= loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx-1 +
+ (GRAD_GH+lidy*N_PER_CELL+celly)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_x *= 8.0;
+ gradrho_x += loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx-2 +
+ (GRAD_GH+lidy*N_PER_CELL+celly)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_x -= loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx+2 +
+ (GRAD_GH+lidy*N_PER_CELL+celly)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_x /= (12.0*dx_fine.x);
+
+ gradrho_y = loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx +
+ (GRAD_GH+lidy*N_PER_CELL+celly+1)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_y -= loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx +
+ (GRAD_GH+lidy*N_PER_CELL+celly-1)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_y *= 8.0;
+ gradrho_y += loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx +
+ (GRAD_GH+lidy*N_PER_CELL+celly-2)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_y -= loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx +
+ (GRAD_GH+lidy*N_PER_CELL+celly+2)*(F_TILE_SIZE+2*GRAD_GH)];
+ gradrho_y /= (12.0*dx_fine.y);
+
+#if CUT_DIR_Z == 1
+ if (idz==NB_F_Z-1)
+ rho_zpp = compute_density(rho_ghostsZ[rhs_idx + cellx + celly*NB_F_X + NB_F_X*NB_F_Y]);
+ else if (idz==NB_F_Z-2)
+ rho_zpp = compute_density(rho_ghostsZ[rhs_idx + cellx + celly*NB_F_X]);
+ else
+ rho_zpp = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + ((idz+2)%NB_F_Z)*NB_F_X*NB_F_Y]);
+#else
+ rho_zpp = compute_density(rho[rhs_idx + cellx + celly*NB_F_X + ((idz+2)%NB_F_Z)*NB_F_X*NB_F_Y]);
+#endif
+ gradrho_z = rho_zp[cellx][celly];
+ gradrho_z -= rho_zm[cellx][celly];
+ gradrho_z *= 8.0;
+ gradrho_z += rho_zmm[cellx][celly];
+ gradrho_z -= rho_zpp;
+ gradrho_z /= (12.0*dx_fine.z);
+#endif
+
+ ///// TEMP WRITE GRADrho_X TO RHS
+ //rhs_x[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] = gradrho_x;
+ ///// END TEMP WRITE GRADrho TO RHS
+ ///// TEMP WRITE GRADrho_Y TO RHS
+ //rhs_x[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] = gradrho_y;
+ ///// END TEMP WRITE GRADrho TO RHS
+ ///// TEMP WRITE GRADrho_Z TO RHS
+ //rhs_x[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] = gradrho_z;
+ ///// END TEMP WRITE GRADrho TO RHS
+
+ // Using gradp X component as gradp and assuming this kernel run first to initialise output
+#if GRADP_COMP == 0
+ rhs_x[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] = 0.0;
+ rhs_y[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] = -gradrho_z*p_gradp;
+ rhs_z[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] = gradrho_y*p_gradp;
+#endif
+ // Using gradp Y component as gradp
+#if GRADP_COMP == 1
+ rhs_x[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] += gradrho_z*p_gradp;
+ rhs_z[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] -= gradrho_x*p_gradp;
+#endif
+ // Using gradp Z component as gradp
+#if GRADP_COMP == 2
+ rhs_x[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] -= gradrho_y*p_gradp;
+ rhs_y[rhs_idx + cellx + celly*NB_F_X + idz*NB_F_X*NB_F_Y] += gradrho_x*p_gradp;
+#endif
+
+
+ // For next iteration we swap values in cache.
+#if FD_ORDER == FD_C_4
+ rho_zp[cellx][celly] = rho_zpp;
+ rho_zmm[cellx][celly] = rho_zm[cellx][celly];
+#endif
+ rho_zm[cellx][celly] = loc_rho[GRAD_GH+lidx*N_PER_CELL+cellx +
+ (GRAD_GH+lidy*N_PER_CELL+celly)*(F_TILE_SIZE+2*GRAD_GH)];
+ }
+ }
+ idz++;
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/remeshing.cl b/hysop/old/gpu.old/cl_src/kernels/remeshing.cl
new file mode 100644
index 0000000000000000000000000000000000000000..809c5ad32567ca2b91cc51773fffb480c05de721
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/remeshing.cl
@@ -0,0 +1,83 @@
+/**
+ * @file remeshing.cl
+ * Remeshing kernel.
+ */
+
+/**
+ * Performs remeshing of the particles' scalar.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group.
+ * Each work-item computes <code>NB_I/WI_NB</code> particles positions. To avoid concurrent witings, in case of strong velocity gradients, work-items computes contiguous particles.
+ * Particle are computed through OpenCL vector types of lenght 2, 4 or 8.
+ * Scalar results are stored in a local buffer as a cache and then copied to global memory buffer.
+ *
+ * @param ppos Particle position
+ * @param pscal Particle scalar
+ * @param gscal Grid scalar
+ * @param min_position Domain lower coordinate
+ * @param dx Space step
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>WI_NB</code> corresponds to the work-item number.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void remeshing_kernel(__global const float* ppos,
+ __RCOMP_P__global const float* pscal__ID__,
+ __RCOMP_P__global float* gscal__ID__,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ // float invdx = 1.0/dx; /* Space step inverse */
+ uint i; /* Particle index in 1D problem */
+ float__N__ p; /* Particle position */
+ __RCOMP_I float__N__ s__ID__; /* Particle scalar */
+ uint line_index; /* Current 1D problem index */
+
+ __RCOMP_I__local float gscal_loc__ID__[NB_I]; /* Local buffer for result */
+
+#ifdef NB_Z
+ for(gidZ=get_global_id(2); gidZ<NB_III; gidZ+=get_global_size(2)) {
+#else
+ gidZ=get_global_id(2); {
+#endif
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+ for(i=gidX*__N__; i<NB_I; i+=(WI_NB*__N__))
+ {
+ /* Initialize result buffer */
+ __RCOMP_Igscal_loc__ID__[i+__NN__] = 0.0;
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*PART_NB_PER_WI; i<(gidX + 1)*PART_NB_PER_WI; i+=__N__)
+ {
+ /* Read particle position */
+ p = vload__N__((i + line_index)/__N__, ppos);
+ /* Read particle scalar */
+ __RCOMP_Is__ID__ = vload__N__((i + line_index)/__N__, pscal__ID__);
+ /* Remesh particle */
+ remesh(i, __RCOMP_Ps__ID__, p, __RCOMP_Pgscal_loc__ID__, mesh);
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*__N__; i<NB_I; i+=(WI_NB*__N__))
+ {
+ /* Store result */
+ __RCOMP_Ivstore__N__((float__N__)(gscal_loc__ID__[noBC_id(i+__NN__)],
+ ),(i + line_index)/__N__, gscal__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+}
+}
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/remeshing_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/remeshing_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..15db5730cedc2cf8b347c831ed6dfe3b79a48985
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/remeshing_noVec.cl
@@ -0,0 +1,81 @@
+/**
+ * @file remeshing.cl
+ * Remeshing kernel.
+ */
+
+/**
+ * Performs remeshing of the particles' scalar.
+ * A work-group is handling a 1D problem. Thus, gidY and gidZ are constants among work-items of a work-group.
+ * Each work-item computes <code>NB_I/WI_NB</code> particles positions. To avoid concurrent witings, in case of strong velocity gradients, work-items computes contiguous particles.
+ * Particle are computed through OpenCL vector types of lenght 2, 4 or 8.
+ * Scalar results are stored in a local buffer as a cache and then copied to global memory buffer.
+ *
+ * @param ppos Particle position
+ * @param pscal Particle scalar
+ * @param gscal Grid scalar
+ * @param min_position Domain lower coordinate
+ * @param dx Space step
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>WI_NB</code> corresponds to the work-item number.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void remeshing_kernel(__global const float* ppos,
+ __RCOMP_P__global const float* pscal__ID__,
+ __RCOMP_P__global float* gscal__ID__,
+ __constant struct AdvectionMeshInfo* mesh)
+{
+ uint gidX = get_global_id(0); /* OpenCL work-itme global index (X) */
+ uint gidY; /* OpenCL work-itme global index (Y) */
+ uint gidZ; /* OpenCL work-itme global index (Z) */
+ uint i; /* Particle index in 1D problem */
+ float p; /* Particle position */
+ __RCOMP_I float s__ID__; /* Particle scalar */
+ uint line_index; /* Current 1D problem index */
+
+ __RCOMP_I__local float gscal_loc__ID__[NB_I]; /* Local buffer for result */
+
+#ifdef NB_Z
+ for(gidZ=get_global_id(2); gidZ<NB_III; gidZ+=get_global_size(2)) {
+#else
+ gidZ=get_global_id(2); {
+#endif
+ for(gidY=get_global_id(1); gidY<NB_II; gidY+=get_global_size(1)) {
+ line_index = gidY*NB_I+ gidZ*NB_I*NB_II;
+
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ {
+ /* Initialize result buffer */
+ __RCOMP_Igscal_loc__ID__[i] = 0.0;
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX*PART_NB_PER_WI; i<(gidX + 1)*PART_NB_PER_WI; i+=1)
+ {
+ /* Read particle position */
+ p = ppos[i + line_index];
+ /* Read particle scalar */
+ __RCOMP_Is__ID__ = pscal__ID__[i + line_index];
+ /* Remesh particle */
+ remesh(i, __RCOMP_Ps__ID__, p, __RCOMP_Pgscal_loc__ID__, mesh);
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=gidX; i<NB_I; i+=WI_NB)
+ {
+ /* Store result */
+ __RCOMP_Igscal__ID__[i + line_index] = gscal_loc__ID__[noBC_id(i)];
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+}
+}
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/rendering.cl b/hysop/old/gpu.old/cl_src/kernels/rendering.cl
new file mode 100644
index 0000000000000000000000000000000000000000..567c44d9abcb4a9a2f7a52ef9d1cda57effc7f81
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/rendering.cl
@@ -0,0 +1,57 @@
+/**
+ * @file rendering.cl
+ * Rendering kernels.
+ */
+
+/**
+ * Colorize regarding scalar values.
+ *
+ * @param scalar Scalar values used
+ * @param color Color data array that contains RGBA values for each grid point
+ */
+__kernel void colorize(__global const float* scalar,
+ __global float* color
+)
+{
+ __private uint ind;
+ __private float c;
+ __private int ix, iy;
+ ix = get_global_id(0);
+ iy = get_global_id(1);
+ ind = ix + iy*NB_X;
+
+ //plain colors
+ /* c = (scalar[ind] > 0.5f ? 1.0: 0.0); */
+ /* color[4*ind + 0] = c; //Red */
+ /* color[4*ind + 1] = 0.0; //Green */
+ /* color[4*ind + 2] = 0.0; //Blue */
+ /* color[4*ind + 3] = 1.0; //Alpha */
+
+ //shaded colors
+ c = scalar[ind];
+ color[4*ind + 0] = 2.0*c; //Red
+ color[4*ind + 1] = 2.0*c-0.5; //Green
+ color[4*ind + 2] = 2.0*c-1.0; //Blue
+ color[4*ind + 3] = 1.0; //Alpha
+}
+
+
+/**
+ * Compute grid point coordinates from OpenCL index space.
+ *
+ * @param pos Coordinates ax XY values for each grid point.
+ * @param minPos Domain origin.
+ * @param size Mesh size.
+ */
+__kernel void initPointCoordinates(__global float* pos, float4 minPos, float4 size)
+{
+ __private uint ind;
+ __private int ix, iy;
+ ix = get_global_id(0);
+ iy = get_global_id(1);
+ ind = ix + iy*NB_X;
+
+ pos[2*ind + 0] = ix*size.x;
+ pos[2*ind + 1] = iy*size.y;
+}
+
diff --git a/hysop/old/gpu.old/cl_src/kernels/transpose_xy.cl b/hysop/old/gpu.old/cl_src/kernels/transpose_xy.cl
new file mode 100644
index 0000000000000000000000000000000000000000..a8701738f17f67659f27c616cf6ad75c1f29bcec
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/transpose_xy.cl
@@ -0,0 +1,99 @@
+/**
+ * @file transpose_xy.cl
+ * Transposition in XY plane, coalesced, diagonal coordinates, vectorized version.
+ */
+
+/**
+ * Performs a transposition in xy plane.
+ * Optimizations used are:
+ * - Coalesced reads and writes by means of local memory buffer (tile),
+ * - Local memory padding to avoid banck conflicts (optional),
+ * - Work groups are mapped to diagonal coordinates in global memory,
+ * - Reads and writes are performed by OpenCL vector types.
+ *
+ * A work group handle transposition for a tile. Transposition is done when reading data in tile.
+ * Work-group layout: \code
+ * ________________________
+ * |0,0 | 1,0 | ...
+ * |N,0 | 0,1 | 1,2 | ...
+ * | . . | 0,2 | ...
+ * | . .
+ * | . .
+ * |
+ * \endcode
+ *
+ * @param in Input data
+ * @param out Output data
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last. Output layout is <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code>.
+ * @remark <code>PADDING_XY</code> : local memory padding width.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void transpose_xy(__global const float* in,
+ __global float* out)
+{
+ float__N__ temp; /* Temporary variable */
+ uint group_id_x; /* Work-group coordinate in global space index X */
+ uint group_id_y; /* Work-group coordinate in global space index Y */
+ uint lid_x = get_local_id(0);
+ uint lid_y = get_local_id(1);
+
+ uint xIndex, yIndex, zIndex;
+ uint index_in, index_out;
+ uint gidI, gidII, i;
+
+ __local float tile[TILE_DIM_XY][TILE_DIM_XY+PADDING_XY]; /* Tile with padding */
+
+#ifdef NB_III
+ for(zIndex=get_global_id(2); zIndex<NB_III; zIndex+=get_global_size(2))
+#else
+ zIndex=get_global_id(2);
+#endif
+ {
+ for(gidI=get_group_id(0); gidI<NB_GROUPS_I; gidI+=get_num_groups(0)) {
+ for(gidII=get_group_id(1); gidII<NB_GROUPS_II; gidII+=get_num_groups(1)) {
+
+ /* Use of diagonal coordinates */
+#if NB_II == NB_I
+ group_id_x = (gidI + gidII) % NB_GROUPS_I;
+ group_id_y = gidI;
+#else
+ uint bid = gidI + gidII * NB_GROUPS_I;
+ group_id_y = bid%NB_GROUPS_II;
+ group_id_x = ((bid/NB_GROUPS_II) + group_id_y)%NB_GROUPS_I;
+#endif
+
+ /* Global input index for work-item */
+ xIndex = group_id_x * TILE_DIM_XY + lid_x*__N__;
+ yIndex = group_id_y * TILE_DIM_XY + lid_y;
+ //zIndex = get_global_id(2);
+ index_in = xIndex + yIndex * NB_II + zIndex * NB_II * NB_I;
+
+ /* Global output index */
+ xIndex = group_id_y * TILE_DIM_XY + lid_x*__N__;
+ yIndex = group_id_x * TILE_DIM_XY + lid_y;
+ index_out = xIndex + yIndex * NB_I + zIndex * NB_I * NB_II;
+
+
+ for(i=0; i<TILE_DIM_XY; i+=BLOCK_ROWS_XY) {
+ /* Fill the tile */
+ temp = vload__N__((index_in + i * NB_II)/__N__, in);
+ tile[lid_y + i][lid_x*__N__+__NN__] = temp.s__NN__;
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=0; i<TILE_DIM_XY; i+=BLOCK_ROWS_XY) {
+ /* Write transposed data */
+ temp = (float__N__)(tile[lid_x*__N__+__NN__][lid_y + i],
+ );
+ vstore__N__(temp, (index_out + i*NB_I)/__N__, out);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/transpose_xy_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/transpose_xy_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..083d86eb2153e7224eab88c8c1f07ac021aa4477
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/transpose_xy_noVec.cl
@@ -0,0 +1,95 @@
+/**
+ * @file transpose_xy.cl
+ * Transposition in XY plane, coalesced, diagonal coordinates, vectorized version.
+ */
+
+/**
+ * Performs a transposition in xy plane.
+ * Optimizations used are:
+ * - Coalesced reads and writes by means of local memory buffer (tile),
+ * - Local memory padding to avoir banck conflicts (optional),
+ * - Work groups are mapped to diagonal coordinates in global memory,
+ * - Reads and writes are performed by OpenCL vector types.
+ *
+ * A work group handle transposition for a tile. Transposition is done when reading data in tile.
+ * Work-group layout: \code
+ * ________________________
+ * |0,0 | 1,0 | ...
+ * |N,0 | 0,1 | 1,2 | ...
+ * | . . | 0,2 | ...
+ * | . .
+ * | . .
+ * |
+ * \endcode
+ *
+ * @param in Input data
+ * @param out Output data
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last. Output layout is <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code>.
+ * @remark <code>PADDING_XY</code> : local memory padding width.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ */
+__kernel void transpose_xy(__global const float* in,
+ __global float* out)
+{
+ uint group_id_x; /* Work-group coordinate in global space index X */
+ uint group_id_y; /* Work-group coordinate in global space index Y */
+ uint lid_x = get_local_id(0);
+ uint lid_y = get_local_id(1);
+
+ uint xIndex, yIndex, zIndex;
+ uint index_in, index_out;
+ uint gidI, gidII, i;
+
+ __local float tile[TILE_DIM_XY][TILE_DIM_XY+PADDING_XY]; /* Tile with padding */
+
+#ifdef NB_Z
+ for(zIndex=get_global_id(2); zIndex<NB_III; zIndex+=get_global_size(2))
+#else
+ zIndex=get_global_id(2);
+#endif
+ {
+ for(gidI=get_group_id(0); gidI<NB_GROUPS_I; gidI+=get_num_groups(0)) {
+ for(gidII=get_group_id(1); gidII<NB_GROUPS_II; gidII+=get_num_groups(1)) {
+
+ /* Use of diagonal coordinates */
+#if NB_II == NB_I
+ group_id_x = (gidI + gidII) % NB_GROUPS_I;
+ group_id_y = gidI;
+#else
+ uint bid = gidI + gidII * NB_GROUPS_I;
+ group_id_y = bid%NB_GROUPS_II;
+ group_id_x = ((bid/NB_GROUPS_II) + group_id_y)%NB_GROUPS_I;
+#endif
+
+ /* Global input index for work-item */
+ xIndex = group_id_x * TILE_DIM_XY + lid_x;
+ yIndex = group_id_y * TILE_DIM_XY + lid_y;
+ index_in = xIndex + yIndex * NB_II + zIndex * NB_II * NB_I;
+
+ /* Global output index */
+ xIndex = group_id_y * TILE_DIM_XY + lid_x;
+ yIndex = group_id_x * TILE_DIM_XY + lid_y;
+ index_out = xIndex + yIndex * NB_I + zIndex * NB_I * NB_II;
+
+ for(i=0; i<TILE_DIM_XY; i+=BLOCK_ROWS_XY) {
+ /* Fill the tile */
+ tile[lid_y + i][lid_x] = in[index_in + i * NB_II];
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(i=0; i<TILE_DIM_XY; i+=BLOCK_ROWS_XY) {
+ /* Write transposed data */
+ out[index_out + i*NB_I] = tile[lid_x][lid_y + i];
+ }
+
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/transpose_xz.cl b/hysop/old/gpu.old/cl_src/kernels/transpose_xz.cl
new file mode 100644
index 0000000000000000000000000000000000000000..b2197fbb12f4643f1922ab8674a22af9a0583174
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/transpose_xz.cl
@@ -0,0 +1,90 @@
+/**
+ * @file transpose_xz.cl
+ * Transposition in XZ plane, coalesced, diagonal coordinates, 3D tiles.
+ */
+
+/**
+ * Perfoms a transposition in XZ plane. As data have to be contiguously read an write in global memory, we use a 3D tile.
+ * Optimizations used are:
+ * - Coalesced reads and writes by means of local memory buffer (tile),
+ * - Local memory padding to avoir banck conflicts (optional),
+ * - Work groups are mapped to diagonal coordinates in global memory,
+ * - Reads and writes are performed by OpenCL vector types.
+ *
+ *
+ * @param in Input data
+ * @param out Output data
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last. Output layout is <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code>.
+ * @remark <code>PADDING_XZ</code> : local memory padding width.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ * @see transpose_xy.cl
+ */
+__kernel void transpose_xz(__global const float* in,
+ __global float* out)
+{
+ float__N__ temp; /* Temporary variable */
+ uint group_id_x; /* Work-group coordinate in global space index X */
+ uint group_id_z; /* Work-group coordinate in global space index Y */
+ uint lid_x = get_local_id(0);
+ uint lid_y = get_local_id(1);
+ uint lid_z = get_local_id(2);
+
+ uint xIndex, yIndex, zIndex;
+ uint index_in, index_out, i, j;
+ uint gidI, gidII, gidIII;
+
+ __local float tile[TILE_DIM_XZ][TILE_DIM_XZ][TILE_DIM_XZ+PADDING_XZ]; /* Tile with padding */
+
+
+ for(gidI=get_group_id(0); gidI<NB_GROUPS_I; gidI+=get_num_groups(0)) {
+ for(gidII=get_group_id(1); gidII<NB_GROUPS_II; gidII+=get_num_groups(1)) {
+ for(gidIII=get_group_id(2); gidIII<NB_GROUPS_III; gidIII+=get_num_groups(2)) {
+
+ /* Use of diagonal coordinates */
+#if NB_III == NB_I
+ group_id_x = (gidI + gidIII) % NB_GROUPS_I;
+ group_id_z = gidI;
+#else
+ uint bid = gidI + gidIII * NB_GROUPS_I;
+ group_id_z = bid%NB_GROUPS_III;
+ group_id_x = ((bid/NB_GROUPS_III) + group_id_z)%NB_GROUPS_I;
+#endif
+
+ /* Global input index for work-item */
+ xIndex = group_id_x * TILE_DIM_XZ + lid_x*__N__;
+ yIndex = gidII * TILE_DIM_XZ + lid_y;
+ zIndex = group_id_z * TILE_DIM_XZ + lid_z;
+ index_in = xIndex + yIndex * NB_III + zIndex * NB_III * NB_II;
+
+ /* Global output index */
+ xIndex = group_id_z * TILE_DIM_XZ + lid_x*__N__;
+ zIndex = group_id_x * TILE_DIM_XZ + lid_z;
+ index_out = xIndex + yIndex * NB_I + zIndex * NB_I * NB_II;
+
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ for(i=0; i<TILE_DIM_XZ; i+=BLOCK_ROWS_XZ) {
+ /* Fill the tile */
+ temp = vload__N__((index_in + i*NB_III + j*NB_III*NB_II)/__N__, in);
+ tile[lid_z + j][lid_y + i][lid_x*__N__+__NN__] = temp.s__NN__;
+ }
+
+ }
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ for(i=0; i<TILE_DIM_XZ; i+=BLOCK_ROWS_XZ) {
+ /* Write transposed data */
+ temp = (float__N__)(tile[lid_x*__N__+__NN__][lid_y+i][lid_z + j],
+ );
+ vstore__N__(temp, (index_out + i*NB_I + j*NB_I*NB_II)/__N__, out);
+ }
+ }
+ }
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/transpose_xz_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/transpose_xz_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..475bc9aaebe9d5c4a2ebf2c335e08c2a6413733e
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/transpose_xz_noVec.cl
@@ -0,0 +1,84 @@
+/**
+ * @file transpose_xz.cl
+ * Transposition in XZ plane, coalesced, diagonal coordinates, 3D tiles.
+ */
+
+/**
+ * Perfoms a transposition in XZ plane. As data have to be contiguously read an write in global memory, we use a 3D tile.
+ * Optimizations used are:
+ * - Coalesced reads and writes by means of local memory buffer (tile),
+ * - Local memory padding to avoir banck conflicts (optional),
+ * - Work groups are mapped to diagonal coordinates in global memory,
+ * - Reads and writes are performed by OpenCL vector types.
+ *
+ *
+ * @param in Input data
+ * @param out Output data
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last. Output layout is <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code>.
+ * @remark <code>PADDING_XZ</code> : local memory padding width.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ * @see transpose_xy.cl
+ */
+__kernel void transpose_xz(__global const float* in,
+ __global float* out)
+{
+ uint group_id_x; /* Work-group coordinate in global space index X */
+ uint group_id_z; /* Work-group coordinate in global space index Y */
+ uint lid_x = get_local_id(0);
+ uint lid_y = get_local_id(1);
+ uint lid_z = get_local_id(2);
+
+ uint xIndex, yIndex, zIndex;
+ uint index_in, index_out, i, j;
+ uint gidI, gidII, gidIII;
+
+ __local float tile[TILE_DIM_XZ][TILE_DIM_XZ][TILE_DIM_XZ+PADDING_XZ]; /* Tile with padding */
+
+ for(gidI=get_group_id(0); gidI<NB_GROUPS_I; gidI+=get_num_groups(0)) {
+ for(gidII=get_group_id(1); gidII<NB_GROUPS_II; gidII+=get_num_groups(1)) {
+ for(gidIII=get_group_id(2); gidIII<NB_GROUPS_III; gidIII+=get_num_groups(2)) {
+
+ /* Use of diagonal coordinates */
+#if NB_III == NB_I
+ group_id_x = (gidI + gidIII) % NB_GROUPS_I;
+ group_id_z = gidI;
+#else
+ uint bid = gidI + gidIII * NB_GROUPS_I;
+ group_id_z = bid%NB_GROUPS_III;
+ group_id_x = ((bid/NB_GROUPS_III) + group_id_z)%NB_GROUPS_I;
+#endif
+
+ /* Global input index for work-item */
+ xIndex = group_id_x * TILE_DIM_XZ + lid_x;
+ yIndex = gidII * TILE_DIM_XZ + lid_y;
+ zIndex = group_id_z * TILE_DIM_XZ + lid_z;
+ index_in = xIndex + yIndex * NB_III + zIndex * NB_III * NB_II;
+
+ /* Global output index */
+ xIndex = group_id_z * TILE_DIM_XZ + lid_x;
+ zIndex = group_id_x * TILE_DIM_XZ + lid_z;
+ index_out = xIndex + yIndex * NB_I + zIndex * NB_I * NB_II;
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ for(i=0; i<TILE_DIM_XZ; i+=BLOCK_ROWS_XZ) {
+ /* Fill the tile */
+ tile[lid_z + j][lid_y + i][lid_x] = in[index_in + i*NB_III + j*NB_III*NB_II];
+ }
+ }
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ for(i=0; i<TILE_DIM_XZ; i+=BLOCK_ROWS_XZ) {
+ /* Write transposed data */
+ out[index_out + i*NB_I + j*NB_I*NB_II] = tile[lid_x][lid_y+i][lid_z + j];
+ }
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/transpose_xz_slice.cl b/hysop/old/gpu.old/cl_src/kernels/transpose_xz_slice.cl
new file mode 100644
index 0000000000000000000000000000000000000000..ec394f6cbd3690fe71ea7c3d97749077869c4f34
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/transpose_xz_slice.cl
@@ -0,0 +1,82 @@
+/**
+ * @file transpose_xz.cl
+ * Transposition in XZ plane, coalesced, diagonal coordinates, 3D tiles.
+ */
+
+/**
+ * Perfoms a transposition in XZ plane. As data have to be contiguously read an write in global memory, we use a 3D tile.
+ * Optimizations used are:
+ * - Coalesced reads and writes by means of local memory buffer (tile),
+ * - Local memory padding to avoir banck conflicts (optional),
+ * - Work groups are mapped to diagonal coordinates in global memory,
+ * - Reads and writes are performed by OpenCL vector types.
+ *
+ *
+ * @param in Input data
+ * @param out Output data
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last. Output layout is <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code>.
+ * @remark <code>PADDING_XZ</code> : local memory padding width.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ * @see transpose_xy.cl
+ */
+__kernel void transpose_xz(__global const float* in,
+ __global float* out)
+{
+ float__N__ temp; /* Temporary variable */
+ uint group_id_x; /* Work-group coordinate in global space index X */
+ uint group_id_z; /* Work-group coordinate in global space index Y */
+ uint lid_x = get_local_id(0);
+ uint lid_z = get_local_id(2);
+
+ uint xIndex, yIndex, zIndex;
+ uint index_in, index_out;
+ uint gidI, gidIII, j;
+
+ __local float tile[TILE_DIM_XZ][TILE_DIM_XZ+PADDING_XZ]; /* Tile with padding */
+
+ for(yIndex=get_global_id(1); yIndex<NB_II; yIndex+=get_global_size(1)) {
+ for(gidI=get_group_id(0); gidI<NB_GROUPS_I; gidI+=get_num_groups(0)) {
+ for(gidIII=get_group_id(2); gidIII<NB_GROUPS_III; gidIII+=get_num_groups(2)) {
+
+ /* Use of diagonal coordinates */
+#if NB_III == NB_I
+ group_id_x = (gidI + gidIII) % NB_GROUPS_I;
+ group_id_z = gidI;
+#else
+ uint bid = gidI + gidIII * NB_GROUPS_I;
+ group_id_z = bid%NB_GROUPS_III;
+ group_id_x = ((bid/NB_GROUPS_III) + group_id_z)%NB_GROUPS_I;
+#endif
+
+ /* Global input index for work-item */
+ xIndex = group_id_x * TILE_DIM_XZ + lid_x*__N__;
+ zIndex = group_id_z * TILE_DIM_XZ + lid_z;
+ index_in = xIndex + yIndex * NB_III + zIndex * NB_III * NB_II;
+
+ /* Global output index */
+ xIndex = group_id_z * TILE_DIM_XZ + lid_x*__N__;
+ zIndex = group_id_x * TILE_DIM_XZ + lid_z;
+ index_out = xIndex + yIndex * NB_I + zIndex * NB_I * NB_II;
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ /* Fill the tile */
+ temp = vload__N__((index_in + j*NB_III*NB_II)/__N__, in);
+ tile[lid_z + j][lid_x*__N__+__NN__] = temp.s__NN__;
+
+ }
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ /* Write transposed data */
+ temp = (float__N__)(tile[lid_x*__N__+__NN__][lid_z + j],
+ );
+ vstore__N__(temp, (index_out + j*NB_I*NB_II)/__N__, out);
+ }
+ }
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/kernels/transpose_xz_slice_noVec.cl b/hysop/old/gpu.old/cl_src/kernels/transpose_xz_slice_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..d97cb925e5d5b0defdb8025e8f11565f8d34048c
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/kernels/transpose_xz_slice_noVec.cl
@@ -0,0 +1,79 @@
+/**
+ * @file transpose_xz.cl
+ * Transposition in XZ plane, coalesced, diagonal coordinates, 3D tiles.
+ */
+
+/**
+ * Perfoms a transposition in XZ plane. As data have to be contiguously read an write in global memory, we use a 3D tile.
+ * Optimizations used are:
+ * - Coalesced reads and writes by means of local memory buffer (tile),
+ * - Local memory padding to avoir banck conflicts (optional),
+ * - Work groups are mapped to diagonal coordinates in global memory,
+ * - Reads and writes are performed by OpenCL vector types.
+ *
+ *
+ * @param in Input data
+ * @param out Output data
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last. Output layout is <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code>.
+ * @remark <code>PADDING_XZ</code> : local memory padding width.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @see hysop.gpu.tools.parse_file
+ * @see transpose_xy.cl
+ */
+__kernel void transpose_xz(__global const float* in,
+ __global float* out)
+{
+ uint group_id_x; /* Work-group coordinate in global space index X */
+ uint group_id_z; /* Work-group coordinate in global space index Y */
+ uint lid_x = get_local_id(0);
+ uint lid_z = get_local_id(2);
+
+ /* Global input index for work-item */
+ uint xIndex, yIndex, zIndex;
+ uint index_in, index_out;
+ uint gidI, gidIII, j;
+
+ __local float tile[TILE_DIM_XZ][TILE_DIM_XZ+PADDING_XZ]; /* Tile with padding */
+
+ for(yIndex=get_global_id(1); yIndex<NB_II; yIndex+=get_global_size(1)) {
+ for(gidI=get_group_id(0); gidI<NB_GROUPS_I; gidI+=get_num_groups(0)) {
+ for(gidIII=get_group_id(2); gidIII<NB_GROUPS_III; gidIII+=get_num_groups(2)) {
+
+ /* Use of diagonal coordinates */
+#if NB_III == NB_I
+ group_id_x = (gidI + gidIII) % NB_GROUPS_I;
+ group_id_z = gidI;
+#else
+ uint bid = gidI + gidIII * NB_GROUPS_I;
+ group_id_z = bid%NB_GROUPS_III;
+ group_id_x = ((bid/NB_GROUPS_III) + group_id_z)%NB_GROUPS_I;
+#endif
+
+ xIndex = group_id_x * TILE_DIM_XZ + lid_x;
+ zIndex = group_id_z * TILE_DIM_XZ + lid_z;
+ index_in = xIndex + yIndex * NB_III + zIndex * NB_III * NB_II;
+
+ /* Global output index */
+ xIndex = group_id_z * TILE_DIM_XZ + lid_x;
+ zIndex = group_id_x * TILE_DIM_XZ + lid_z;
+ index_out = xIndex + yIndex * NB_I + zIndex * NB_I * NB_II;
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ /* Fill the tile */
+ tile[lid_z + j][lid_x] = in[index_in + j*NB_III*NB_II];
+ }
+ /* Synchronize work-group */
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ for(j=0; j<TILE_DIM_XZ; j+=BLOCK_DEPH_XZ) {
+ /* Write transposed data */
+ out[index_out + j*NB_I*NB_II] = tile[lid_x][lid_z + j];
+ tile[lid_x][lid_z + j] = 0.0;
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ }
+ }
+}
diff --git a/hysop/old/gpu.old/cl_src/remeshing/basic.cl b/hysop/old/gpu.old/cl_src/remeshing/basic.cl
new file mode 100644
index 0000000000000000000000000000000000000000..e2fd02f4d55a0b76891dc21d5ae4be546bb00cbf
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/basic.cl
@@ -0,0 +1,106 @@
+/**
+ * @file remeshing/basic.cl
+ * Remeshing function, vectorized version.
+ */
+
+void remesh(uint i, __RCOMP_P float__N__ s__ID__, float__N__ p, __RCOMP_P__local float* gscal_loc__ID__, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Remesh particles in local buffer.
+ *
+ * Remeshing formula is given a compiling time.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ *
+ * @param i Particle index
+ * @param dx Space step
+ * @param invdx 1/dx
+ * @param s Particle scalar
+ * @param p Particle position
+ * @param gscal_loc Local buffer for result
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>FORMULA</code> : remeshing formula flag {<code>M4PRIME</code>, <code>M6PRIME</code>, <code>M8PRIME</code>, <code>L6STAR</code>}
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @remark <code>REMESH</code> is a function-like macro expanding to the proper remeshing formula (i.e.: <code>REMESH(alpha)</code> -> <code>alpha_l2_1</code>)
+ * @see hysop.gpu.tools.parse_file
+ * @see hysop.gpu.cl_src.common
+ */
+void remesh(uint i,
+ __RCOMP_P float__N__ s__ID__,
+ float__N__ p,
+ __RCOMP_P__local float* gscal_loc__ID__,
+ __constant struct AdvectionMeshInfo* mesh){
+ float__N__ y; /* Normalized distance to nearest left grid point */
+ int__N__ ind; /* Integer coordinate */
+ uint__N__ index; /* Remeshing index */
+ float w__NN__;
+
+ p = p - mesh->min_position;
+
+ ind = convert_int__N___rtn(p * mesh->invdx);
+ y = (p - convert_float__N__(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = convert_uint__N__((ind - REMESH_SHIFT + NB_I) % NB_I);
+
+ w__NN__ = REMESH(alpha)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(beta)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(gamma)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(delta)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(eta)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(zeta)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(theta)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(iota)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#endif
+
+#if REMESH_SHIFT > 3
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(kappa)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w__NN__ = REMESH(mu)(y.s__NN__);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += (w__NN__ * s__ID__.s__NN__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#endif
+}
diff --git a/hysop/old/gpu.old/cl_src/remeshing/basic_noVec.cl b/hysop/old/gpu.old/cl_src/remeshing/basic_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..a2b75e98926a6a246f1e54af288fd4ab48a7143e
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/basic_noVec.cl
@@ -0,0 +1,112 @@
+/**
+ * @file remeshing/basic_noVec.cl
+ * Remeshing function, vectorized version.
+ */
+
+void remesh(uint i, __RCOMP_P float s__ID__, float p, __RCOMP_P__local float* gscal_loc__ID__, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Remesh particles in local buffer.
+ *
+ * Remeshing formula is given a compiling time.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ *
+ * @param i Particle index
+ * @param dx Space step
+ * @param invdx 1/dx
+ * @param s Particle scalar
+ * @param p Particle position
+ * @param gscal_loc Local buffer for result
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>FORMULA</code> : remeshing formula flag {<code>M4PRIME</code>, <code>M6PRIME</code>, <code>M8PRIME</code>, <code>L6STAR</code>}
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @remark <code>REMESH</code> is a function-like macro expanding to the proper remeshing formula (i.e.: <code>REMESH(alpha)</code> -> <code>alpha_l2_1</code>)
+ * @see hysop.gpu.tools.parse_file
+ * @see hysop.gpu.cl_src.common
+ */
+void remesh(uint i,
+ __RCOMP_P float s__ID__,
+ float p,
+ __RCOMP_P__local float* gscal_loc__ID__,
+ __constant struct AdvectionMeshInfo* mesh){
+ float y; /* Normalized distance to nearest left grid point */
+ int ind; /* Integer coordinate */
+ uint index; /* Remeshing index */
+ float w;
+
+ p = p - mesh->min_position;
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = convert_uint((ind - REMESH_SHIFT + NB_I) % NB_I);
+
+ w = REMESH(alpha)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(beta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(gamma)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(delta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = (index + 1) % NB_I;
+ w = REMESH(eta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(zeta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = (index + 1) % NB_I;
+ w = REMESH(theta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(iota)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = (index + 1) % NB_I;
+ w = REMESH(kappa)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(mu)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+}
+
+
+/* Flop number
+ - distance to grid point : 5flop
+ - contributions : 2*Stencil*Nbcomponents
+ - poids (horner) : (d*fma+1)*Stencil (d=degré, +1 for the coefficient)
+
+*/
diff --git a/hysop/old/gpu.old/cl_src/remeshing/comm_basic_noVec.cl b/hysop/old/gpu.old/cl_src/remeshing/comm_basic_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..e1e886cfcb88dbaad5a237ad9c210a7d8f945568
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/comm_basic_noVec.cl
@@ -0,0 +1,124 @@
+/**
+ * @file remeshing/comm_basic_noVec.cl
+ * Remeshing function, vectorized version.
+ */
+
+void remesh(uint i, __RCOMP_P float s__ID__, float p, __RCOMP_P__local float* gscal_loc__ID__, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Remesh particles in local buffer.
+ *
+ * Remeshing formula is given a compiling time.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ *
+ * @param i Particle index
+ * @param dx Space step
+ * @param invdx 1/dx
+ * @param s Particle scalar
+ * @param p Particle position
+ * @param gscal_loc Local buffer for result
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark T_NB_I: global points number in the 1st direction (mpi cutted direction)
+ * @remark START_INDEX Global staring index for computational points
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>FORMULA</code> : remeshing formula flag {<code>M4PRIME</code>, <code>M6PRIME</code>, <code>M8PRIME</code>, <code>L6STAR</code>}
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @remark <code>REMESH</code> is a function-like macro expanding to the proper remeshing formula (i.e.: <code>REMESH(alpha)</code> -> <code>alpha_l2_1</code>)
+ * @see hysop.gpu.tools.parse_file
+ * @see hysop.gpu.cl_src.common
+ */
+void remesh(uint i,
+ __RCOMP_P float s__ID__,
+ float p,
+ __RCOMP_P__local float* gscal_loc__ID__,
+ __constant struct AdvectionMeshInfo* mesh){
+ float y; /* Normalized distance to nearest left grid point */
+ int ind; /* Integer coordinate */
+ int index; /* Remeshing index */
+ float w;
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = ((ind - REMESH_SHIFT + T_NB_I) % T_NB_I) - START_INDEX;
+
+ if (index>=0 && index < NB_I){
+ w = REMESH(alpha)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(beta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(gamma)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(delta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(eta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(zeta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(theta)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(iota)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(kappa)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = index + 1;
+ if (index>=0 && index < NB_I){
+ w = REMESH(mu)(y);
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += (w * s__ID__);
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+}
diff --git a/hysop/old/gpu.old/cl_src/remeshing/private.cl b/hysop/old/gpu.old/cl_src/remeshing/private.cl
new file mode 100644
index 0000000000000000000000000000000000000000..18943652bf3885a13dc77e77babc7280c28c319c
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/private.cl
@@ -0,0 +1,116 @@
+/**
+ * @file private.cl
+ * Remeshing function, vectorized, private variable.
+ */
+
+void remesh(uint i, __RCOMP_P float__N__ s__ID__, float__N__ p, __RCOMP_P__local float* gscal_loc__ID__, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Remesh particles in local buffer.
+ *
+ * Remeshing formula is given a compiling time.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ * Use of a private temporary variable for remeshing weights.
+ *
+ * @param i Particle index
+ * @param dx Space step
+ * @param invdx 1/dx
+ * @param s Particle scalar
+ * @param p Particle position
+ * @param gscal_loc Local buffer for result
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>FORMULA</code> : remeshing formula flag {<code>M4PRIME</code>, <code>M6PRIME</code>, <code>M8PRIME</code>, <code>L6STAR</code>}
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @remark <code>REMESH</code> is a function-like macro expanding to the proper remeshing formula (i.e.: <code>REMESH(alpha)</code> -> <code>alpha_l2_1</code>)
+ * @see hysop.gpu.tools.parse_file
+ * @see hysop.gpu.cl_src.common
+ */
+void remesh(uint i,
+ __RCOMP_P float__N__ s__ID__,
+ float__N__ p,
+ __RCOMP_P__local float* gscal_loc__ID__,
+ __constant struct AdvectionMeshInfo* mesh){
+ float__N__ y, /* Normalized distance to nearest left grid point */
+ w;
+ __RCOMP_I float__N__ temp__ID__; /* Temporary remeshing weights */
+ int__N__ ind; /* Integer coordinate */
+ uint__N__ index; /* Remeshing index */
+
+ p = p - mesh->min_position;
+
+ ind = convert_int__N___rtn(p * mesh->invdx);
+ y = (p - convert_float__N__(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = convert_uint__N__((ind - REMESH_SHIFT + NB_I) % NB_I);
+
+ w = REMESH(alpha)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(beta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(gamma)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(delta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = (index + 1) % NB_I;
+ w = REMESH(eta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(zeta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = (index + 1) % NB_I;
+ w = REMESH(theta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(iota)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = (index + 1) % NB_I;
+ w = REMESH(kappa)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(mu)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index.s__NN__)] += temp__ID__.s__NN__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+}
diff --git a/hysop/old/gpu.old/cl_src/remeshing/private_noVec.cl b/hysop/old/gpu.old/cl_src/remeshing/private_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..7bafbe37de8e4a92fa839336045d4566374f167c
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/private_noVec.cl
@@ -0,0 +1,116 @@
+/**
+ * @file private.cl
+ * Remeshing function, vectorized, private variable.
+ */
+
+void remesh(uint i, __RCOMP_P float s__ID__, float p, __RCOMP_P__local float* gscal_loc__ID__, __constant struct AdvectionMeshInfo* mesh);
+
+
+/**
+ * Remesh particles in local buffer.
+ *
+ * Remeshing formula is given a compiling time.
+ * Use of builtin OpenCL functions fma and mix. Computations through OpenCL vector types.
+ * Use of a private temporary variable for remeshing weights.
+ *
+ * @param i Particle index
+ * @param dx Space step
+ * @param invdx 1/dx
+ * @param s Particle scalar
+ * @param p Particle position
+ * @param gscal_loc Local buffer for result
+ *
+ * @remark <code>NB_I</code>, <code>NB_II</code>, <code>NB_III</code> : points number in directions from 1st varying index to last.
+ * @remark <code>__N__</code> is expanded at compilation time by vector width.
+ * @remark <code>__NN__</code> is expanded at compilation time by a sequence of integer for each vector component.
+ * @remark <code>FORMULA</code> : remeshing formula flag {<code>M4PRIME</code>, <code>M6PRIME</code>, <code>M8PRIME</code>, <code>L6STAR</code>}
+ * @remark <code>__RCOMP_I</code> flag is for instruction expansion for the different remeshed components.
+ * @remark <code>__RCOMP_P</code> flag is for function parameter expansion for the different remeshed components.
+ * @remark <code>__ID__</code> is replaced by the remeshed component id in an expansion.
+ * @remark <code>REMESH</code> is a function-like macro expanding to the proper remeshing formula (i.e.: <code>REMESH(alpha)</code> -> <code>alpha_l2_1</code>)
+ * @see hysop.gpu.tools.parse_file
+ * @see hysop.gpu.cl_src.common
+ */
+void remesh(uint i,
+ __RCOMP_P float s__ID__,
+ float p,
+ __RCOMP_P__local float* gscal_loc__ID__,
+ __constant struct AdvectionMeshInfo* mesh){
+ float y, /* Normalized distance to nearest left grid point */
+ w; /* Temporary remeshing weights */
+ __RCOMP_I float temp__ID__;
+ int ind; /* Integer coordinate */
+ uint index; /* Remeshing index */
+
+ p = p - mesh->min_position;
+
+ ind = convert_int_rtn(p * mesh->invdx);
+ y = (p - convert_float(ind) * mesh->dx.x) * mesh->invdx;
+
+ index = convert_uint((ind - REMESH_SHIFT + NB_I) % NB_I);
+
+ w = REMESH(alpha)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(beta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(gamma)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(delta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+#if REMESH_SHIFT > 1
+ index = (index + 1) % NB_I;
+ w = REMESH(eta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(zeta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 2
+ index = (index + 1) % NB_I;
+ w = REMESH(theta)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(iota)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+#endif
+
+#if REMESH_SHIFT > 3
+ index = (index + 1) % NB_I;
+ w = REMESH(kappa)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+
+ index = (index + 1) % NB_I;
+ w = REMESH(mu)(y);
+ __RCOMP_Itemp__ID__ = w * s__ID__;
+ __RCOMP_Igscal_loc__ID__[noBC_id(index)] += temp__ID__;
+ barrier(CLK_LOCAL_MEM_FENCE);
+ #endif
+}
diff --git a/hysop/old/gpu.old/cl_src/remeshing/weights.cl b/hysop/old/gpu.old/cl_src/remeshing/weights.cl
new file mode 100644
index 0000000000000000000000000000000000000000..d101fffed4fac3f0a97327d1c1186f3d0682d486
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/weights.cl
@@ -0,0 +1,202 @@
+/**
+ * @file weights.cl
+ * Remeshing formulas, vectorized version.
+ * Polynomials under Horner form.
+ */
+
+inline float__N__ alpha_l2_1(float__N__ y){
+ return ((y * (y * (-y + 2.0) - 1.0)) * 0.5);}
+inline float__N__ beta_l2_1(float__N__ y){
+ return ((y * y * (3.0 * y - 5.0) + 2.0) * 0.5);}
+inline float__N__ gamma_l2_1(float__N__ y){
+ return ((y * (y * (-3.0 * y + 4.0) + 1.0)) * 0.5);}
+inline float__N__ delta_l2_1(float__N__ y){
+ return ((y * y * (y - 1.0)) * 0.5);}
+
+
+inline float__N__ alpha_l2_2(float__N__ y){
+ return ((y * (y * (y * (y * (2.0 * y - 5.0) + 3.0) + 1.0) - 1.0)) * 0.5);}
+inline float__N__ beta_l2_2(float__N__ y){
+ return ((y * y * (y * (y * (-6.0 * y + 15.0) - 9.0) - 2.0) + 2.0) * 0.5);}
+inline float__N__ gamma_l2_2(float__N__ y){
+ return ((y * (y * (y * (y * (6.0 * y - 15.0) + 9.0) + 1.0) + 1.0)) * 0.5);}
+inline float__N__ delta_l2_2(float__N__ y){
+ return ((y * y * y * (y * (-2.0 * y + 5.0) - 3.0)) * 0.5);}
+
+
+inline float__N__ alpha_l2_3(float__N__ y){
+ return ((y * (y * (y * y * (y * (y * (-6.0 * y + 21.0) - 25.0) + 10.0) + 1.0) - 1.0)) * 0.5);}
+inline float__N__ beta_l2_3(float__N__ y){
+ return ((y * y * (y * y * (y * (y * (18.0 * y - 63.0) + 75.0) - 30.0) - 2.0) + 2.0) * 0.5);}
+inline float__N__ gamma_l2_3(float__N__ y){
+ return ((y * (y * (y * y * (y * (y * (-18.0 * y + 63.0) - 75.0) + 30.0) + 1.0) + 1.0)) * 0.5);}
+inline float__N__ delta_l2_3(float__N__ y){
+ return ((y * y * y * y * (y * (y * (6.0 * y - 21.0) + 25.0) - 10.0)) * 0.5);}
+
+
+inline float__N__ alpha_l2_4(float__N__ y){
+ return ((y * (y * (y * y * y * (y * (y * (y * (20.0 * y - 90.0) + 154.0) - 119.0) + 35.0) + 1.0) - 1.0)) * 0.5);}
+inline float__N__ beta_l2_4(float__N__ y){
+ return ((y * y * (y * y * y * (y * (y * (y * (-60.0 * y + 270.0) - 462.0) + 357.0) - 105.0) - 2.0) + 2.0) * 0.5);}
+inline float__N__ gamma_l2_4(float__N__ y){
+ return ((y * (y * (y * y * y * (y * (y * (y * (60.0 * y - 270.0) + 462.0) - 357.0) + 105.0) + 1.0) + 1.0)) * 0.5);}
+inline float__N__ delta_l2_4(float__N__ y){
+ return ((y * y * y * y * y * (y * (y * (y * (-20.0 * y + 90.0) - 154.0) + 119.0) - 35.0)) * 0.5);}
+
+
+inline float__N__ alpha_l4_2(float__N__ y){
+ return ((y * (y * (y * (y * (-5.0 * y + 13.0) - 9.0) - 1.0) + 2.0)) * 0.041666666666666664);}
+inline float__N__ beta_l4_2(float__N__ y){
+ return ((y * (y * (y * (y * (25.0 * y - 64.0) + 39.0) + 16.0) - 16.0)) * 0.041666666666666664);}
+inline float__N__ gamma_l4_2(float__N__ y){
+ return ((y * y * (y * (y * (-50.0 * y + 126.0) - 70.0) - 30.0) + 24.0) * 0.041666666666666664);}
+inline float__N__ delta_l4_2(float__N__ y){
+ return ((y * (y * (y * (y * (50.0 * y - 124.0) + 66.0) + 16.0) + 16.0)) * 0.041666666666666664);}
+inline float__N__ eta_l4_2(float__N__ y){
+ return ((y * (y * (y * (y * (-25.0 * y + 61.0) - 33.0) - 1.0) - 2.0)) * 0.041666666666666664);}
+inline float__N__ zeta_l4_2(float__N__ y){
+ return ((y * y * y * (y * (5.0 * y - 12.0) + 7.0)) * 0.041666666666666664);}
+
+
+inline float__N__ alpha_l4_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (14.0 * y - 49.0) + 58.0) - 22.0) - 2.0) - 1.0) + 2.0)) * 0.041666666666666664);}
+inline float__N__ beta_l4_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (-70.0 * y + 245.0) - 290.0) + 111.0) + 4.0) + 16.0) - 16.0)) * 0.041666666666666664);}
+inline float__N__ gamma_l4_3(float__N__ y){
+ return ((y * y * (y * y * (y * (y * (140.0 * y - 490.0) + 580.0) - 224.0) - 30.0) + 24.0) * 0.041666666666666664);}
+inline float__N__ delta_l4_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (-140.0 * y + 490.0) - 580.0) + 226.0) - 4.0) + 16.0) + 16.0)) * 0.041666666666666664);}
+inline float__N__ eta_l4_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (70.0 * y - 245.0) + 290.0) - 114.0) + 2.0) - 1.0) - 2.0)) * 0.041666666666666664);}
+inline float__N__ zeta_l4_3(float__N__ y){
+ return ((y * y * y * y * (y * (y * (-14.0 * y + 49.0) - 58.0) + 23.0)) * 0.041666666666666664);}
+
+
+inline float__N__ alpha_l4_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-46.0 * y + 207.0) - 354.0) + 273.0) - 80.0) + 1.0) - 2.0) - 1.0) + 2.0)) * 0.041666666666666664);}
+inline float__N__ beta_l4_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (230.0 * y - 1035.0) + 1770.0) - 1365.0) + 400.0) - 4.0) + 4.0) + 16.0) - 16.0)) * 0.041666666666666664);}
+inline float__N__ gamma_l4_4(float__N__ y){
+ return ((y * y * (y * y * (y * (y * (y * (y * (-460.0 * y + 2070.0) - 3540.0) + 2730.0) - 800.0) + 6.0) - 30.0) + 24.0) * 0.041666666666666664);}
+inline float__N__ delta_l4_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (460.0 * y - 2070.0) + 3540.0) - 2730.0) + 800.0) - 4.0) - 4.0) + 16.0) + 16.0)) * 0.041666666666666664);}
+inline float__N__ eta_l4_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-230.0 * y + 1035.0) - 1770.0) + 1365.0) - 400.0) + 1.0) + 2.0) - 1.0) - 2.0)) * 0.041666666666666664);}
+inline float__N__ zeta_l4_4(float__N__ y){
+ return ((y * y * y * y * y * (y * (y * (y * (46.0 * y - 207.0) + 354.0) - 273.0) + 80.0)) * 0.041666666666666664);}
+
+
+inline float__N__ alpha_M8p(float__N__ y){
+ return ((y*(y*(y*(y*(y*(y*(-10.0*y + 21.0) + 28.0) - 105.0) + 70.0) + 35.0) - 56.0) + 17.0) * 0.00029761904761904765);}
+inline float__N__ beta_M8p(float__N__ y){
+ return ((y*(y*(y*(y*(y*(y*(70.0*y - 175.0) - 140.0) + 770.0) - 560.0) - 350.0) + 504.0) - 102.0) * 0.00029761904761904765);}
+inline float__N__ gamma_M8p(float__N__ y){
+ return ((y*(y*(y*(y*(y*(y*(-210.0*y + 609.0) + 224.0) - 2135.0) + 910.0) + 2765.0) - 2520.0) + 255.0) * 0.00029761904761904765);}
+inline float__N__ delta_M8p(float__N__ y){
+ return ((y*y* (y*y* (y*y* (70.0*y - 231.0) + 588.0) - 980.0) + 604.0) * 0.001488095238095238);}
+inline float__N__ eta_M8p(float__N__ y){
+ return ((y*(y*(y*(y*(y*(y*(-70.0*y+ 259.0) - 84.0) - 427.0) - 182.0)+ 553.0) + 504.0)+ 51.0) * 0.001488095238095238);}
+inline float__N__ zeta_M8p(float__N__ y){
+ return ((y*(y*(y*(y*(y*(y*(210.0*y- 861.0) + 532.0) + 770.0) + 560.0) - 350.0) - 504.0) - 102.0) * 0.00029761904761904765);}
+inline float__N__ theta_M8p(float__N__ y){
+ return ((y* (y* (y* (y* (y* (y* (-70.0* y+ 315.0) -280.0) -105.0) -70.0) +35.0)+ 56.0) +17.0) * 0.00029761904761904765);}
+inline float__N__ iota_M8p(float__N__ y){
+ return ((y * y * y * y * y * (y * (10.0 * y - 49.0) + 56.0)) * 0.00029761904761904765);}
+
+
+inline float__N__ alpha_l6_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (-89.0 * y + 312.0) - 370.0) + 140.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (623.0 * y - 2183.0) + 2581.0) - 955.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (-1869.0 * y + 6546.0) - 7722.0) + 2850.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_3(float__N__ y){
+ return ((y * y * (y * y * (y * (y * (3115.0 * y - 10905.0) + 12845.0) - 4795.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (-3115.0 * y + 10900.0) - 12830.0) + 4880.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (1869.0 * y - 6537.0) + 7695.0) - 2985.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_3(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (-623.0 * y + 2178.0) - 2566.0) + 1010.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_3(float__N__ y){
+ return ((y * y * y * y * (y * (y * (89.0 * y - 311.0) + 367.0) - 145.0)) * 0.001388888888888889);}
+
+
+inline float__N__ alpha_l6_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (290.0 * y - 1305.0) + 2231.0) - 1718.0) + 500.0) - 5.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-2030.0 * y + 9135.0) - 15617.0) + 12027.0) - 3509.0) + 60.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (6090.0 * y - 27405.0) + 46851.0) - 36084.0) + 10548.0) - 195.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_4(float__N__ y){
+ return ((y * y * (y * y * (y * (y * (y * (y * (-10150.0 * y + 45675.0) - 78085.0) + 60145.0) - 17605.0) + 280.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (10150.0 * y - 45675.0) + 78085.0) - 60150.0) + 17620.0) - 195.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-6090.0 * y + 27405.0) - 46851.0) + 36093.0) - 10575.0) + 60.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (2030.0 * y - 9135.0) + 15617.0) - 12032.0) + 3524.0) - 5.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_4(float__N__ y){
+ return ((y * y * y * y * y * (y * (y * (y * (-290.0 * y + 1305.0) - 2231.0) + 1719.0) - 503.0)) * 0.001388888888888889);}
+
+
+inline float__N__ alpha_l6_5(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-1006.0 * y + 5533.0) - 12285.0) + 13785.0) - 7829.0) + 1803.0) - 3.0) - 5.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_5(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (7042.0 * y - 38731.0) + 85995.0) - 96495.0) + 54803.0) - 12620.0) + 12.0) + 60.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_5(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-21126.0 * y + 116193.0) - 257985.0) + 289485.0) - 164409.0) + 37857.0) - 15.0) - 195.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_5(float__N__ y){
+ return ((y * y * (y * y * (y * y * (y * (y * (y * (y * (35210.0 * y - 193655.0) + 429975.0) - 482475.0) + 274015.0) - 63090.0) + 280.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_5(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-35210.0 * y + 193655.0) - 429975.0) + 482475.0) - 274015.0) + 63085.0) + 15.0) - 195.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_5(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (21126.0 * y - 116193.0) + 257985.0) - 289485.0) + 164409.0) - 37848.0) - 12.0) + 60.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_5(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-7042.0 * y + 38731.0) - 85995.0) + 96495.0) - 54803.0) + 12615.0) + 3.0) - 5.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_5(float__N__ y){
+ return ((y * y * y * y * y * y * (y * (y * (y * (y * (1006.0 * y - 5533.0) + 12285.0) - 13785.0) + 7829.0) - 1802.0)) * 0.001388888888888889);}
+
+
+inline float__N__ alpha_l6_6(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (3604.0 * y - 23426.0) + 63866.0) - 93577.0) + 77815.0) - 34869.0) + 6587.0) + 1.0) - 3.0) - 5.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_6(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-25228.0 * y + 163982.0) - 447062.0) + 655039.0) - 544705.0) + 244083.0) - 46109.0) - 6.0) + 12.0) + 60.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_6(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (75684.0 * y - 491946.0) + 1341186.0) - 1965117.0) + 1634115.0) - 732249.0) + 138327.0) + 15.0) - 15.0) - 195.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_6(float__N__ y){
+ return ((y * y * (y * y * (y * y * (y * (y * (y * (y * (y * (y * (-126140.0 * y + 819910.0) - 2235310.0) + 3275195.0) - 2723525.0) + 1220415.0) - 230545.0) - 20.0) + 280.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_6(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (126140.0 * y - 819910.0) + 2235310.0) - 3275195.0) + 2723525.0) - 1220415.0) + 230545.0) + 15.0) + 15.0) - 195.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_6(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-75684.0 * y + 491946.0) - 1341186.0) + 1965117.0) - 1634115.0) + 732249.0) - 138327.0) - 6.0) - 12.0) + 60.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_6(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (25228.0 * y - 163982.0) + 447062.0) - 655039.0) + 544705.0) - 244083.0) + 46109.0) + 1.0) + 3.0) - 5.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_6(float__N__ y){
+ return ((y * y * y * y * y * y * y * (y * (y * (y * (y * (y * (-3604.0 * y + 23426.0) - 63866.0) + 93577.0) - 77815.0) + 34869.0) - 6587.0)) * 0.001388888888888889);}
+
+
+inline float__N__ alpha_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-3569.0 * y + 16061.0) - 27454.0) + 21126.0) - 6125.0) + 49.0) - 196.0) - 36.0) + 144.0)) * 2.48015873015873e-05);}
+inline float__N__ beta_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (32121.0 * y - 144548.0) + 247074.0) - 190092.0) + 55125.0) - 672.0) + 2016.0) + 512.0) - 1536.0)) * 2.48015873015873e-05);}
+inline float__N__ gamma_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-128484.0 * y + 578188.0) - 988256.0) + 760312.0) - 221060.0) + 4732.0) - 9464.0) - 4032.0) + 8064.0)) * 2.48015873015873e-05);}
+inline float__N__ delta_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (299796.0 * y - 1349096.0) + 2305856.0) - 1774136.0) + 517580.0) - 13664.0) + 13664.0) + 32256.0) - 32256.0)) * 2.48015873015873e-05);}
+inline float__N__ eta_l8_4(float__N__ y){
+ return ((y * y * (y * y * (y * (y * (y * (y * (-449694.0 * y + 2023630.0) - 3458700.0) + 2661540.0) - 778806.0) + 19110.0) - 57400.0) + 40320.0) * 2.48015873015873e-05);}
+inline float__N__ zeta_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (449694.0 * y - 2023616.0) + 3458644.0) - 2662016.0) + 780430.0) - 13664.0) - 13664.0) + 32256.0) + 32256.0)) * 2.48015873015873e-05);}
+inline float__N__ theta_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-299796.0 * y + 1349068.0) - 2305744.0) + 1775032.0) - 520660.0) + 4732.0) + 9464.0) - 4032.0) - 8064.0)) * 2.48015873015873e-05);}
+inline float__N__ iota_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (128484.0 * y - 578168.0) + 988176.0) - 760872.0) + 223020.0) - 672.0) - 2016.0) + 512.0) + 1536.0)) * 2.48015873015873e-05);}
+inline float__N__ kappa_l8_4(float__N__ y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-32121.0 * y + 144541.0) - 247046.0) + 190246.0) - 55685.0) + 49.0) + 196.0) - 36.0) - 144.0)) * 2.48015873015873e-05);}
+inline float__N__ mu_l8_4(float__N__ y){
+ return ((y * y * y * y * y * (y * (y * (y * (3569.0 * y - 16060.0) + 27450.0) - 21140.0) + 6181.0)) * 2.48015873015873e-05);}
+
+
+
+#endif
diff --git a/hysop/old/gpu.old/cl_src/remeshing/weights_builtin.cl b/hysop/old/gpu.old/cl_src/remeshing/weights_builtin.cl
new file mode 100644
index 0000000000000000000000000000000000000000..cd1827937456989bf6eb51b36bf5025c5d4bbd55
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/weights_builtin.cl
@@ -0,0 +1,199 @@
+/**
+ * @file weights_builtin.cl
+ * Remeshing formulas, vectorized version, use of builtin OpenCL fma.
+ * Polynomials under Horner form.
+ */
+
+inline float__N__ alpha_l2_1(float__N__ y){
+ return (y*fma(y,fma(y,-1.0, 2.0), - 1.0) * 0.5);}
+inline float__N__ beta_l2_1(float__N__ y){
+ return (fma(y*y, fma(y, 3.0, -5.0), 2.0) * 0.5);}
+inline float__N__ gamma_l2_1(float__N__ y){
+ return ((y * fma(y , fma(-3.0, y, 4.0), 1.0)) * 0.5);}
+inline float__N__ delta_l2_1(float__N__ y){
+ return ((y * y * fma(1.0, y, - 1.0)) * 0.5);}
+
+
+inline float__N__ alpha_l2_2(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 2.0, -5.0), 3.0), 1.0), -1.0)) * 0.5);}
+inline float__N__ beta_l2_2(float__N__ y){
+ return (fma(y * y, fma(y, fma(y, fma(y, -6.0, 15.0), -9.0), -2.0), 2.0) * 0.5);}
+inline float__N__ gamma_l2_2(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 6.0, -15.0), 9.0), 1.0), 1.0)) * 0.5);}
+inline float__N__ delta_l2_2(float__N__ y){
+ return ((y * y * y * fma(y, fma(y, -2.0, 5.0), -3.0)) * 0.5);}
+
+
+inline float__N__ alpha_l2_3(float__N__ y){
+ return ((y * fma(y, fma(y * y, fma(y, fma(y, fma(y, -6.0, 21.0), -25.0), 10.0), 1.0), -1.0)) * 0.5);}
+inline float__N__ beta_l2_3(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, 18.0, -63.0), 75.0), -30.0), -2.0), 2.0) * 0.5);}
+inline float__N__ gamma_l2_3(float__N__ y){
+ return ((y * fma(y, fma(y * y, fma(y, fma(y, fma(y, -18.0, 63.0), -75.0), 30.0), 1.0), 1.0)) * 0.5);}
+inline float__N__ delta_l2_3(float__N__ y){
+ return ((y * y * y * y * fma(y, fma(y, fma(y, 6.0, -21.0), 25.0), -10.0)) * 0.5);}
+
+
+inline float__N__ alpha_l2_4(float__N__ y){
+ return ((y * fma(y, fma(y * y * y, fma(y, fma(y, fma(y, fma(y, 20.0, -90.0), 154.0), -119.0), 35.0), 1.0), -1.0)) * 0.5);}
+inline float__N__ beta_l2_4(float__N__ y){
+ return (fma(y * y, fma(y * y * y, fma(y, fma(y, fma(y, fma(y, -60.0, 270.0), -462.0), 357.0), -105.0), -2.0), 2.0) * 0.5);}
+inline float__N__ gamma_l2_4(float__N__ y){
+ return ((y * fma(y, fma(y * y * y, fma(y, fma(y, fma(y, fma(y, 60.0, -270.0), 462.0), -357.0), 105.0), 1.0), 1.0)) * 0.5);}
+inline float__N__ delta_l2_4(float__N__ y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, -20.0, 90.0), -154.0), 119.0), -35.0)) * 0.5);}
+
+
+inline float__N__ alpha_l4_2(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, -5.0, 13.0), -9.0), -1.0), 2.0)) * 0.041666666666666664);}
+inline float__N__ beta_l4_2(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 25.0, -64.0), 39.0), 16.0), -16.0)) * 0.041666666666666664);}
+inline float__N__ gamma_l4_2(float__N__ y){
+ return (fma(y * y, fma(y, fma(y, fma(y, -50.0, 126.0), -70.0), -30.0), 24.0) * 0.041666666666666664);}
+inline float__N__ delta_l4_2(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 50.0, -124.0), 66.0), 16.0), 16.0)) * 0.041666666666666664);}
+inline float__N__ eta_l4_2(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, -25.0, 61.0), -33.0), -1.0), -2.0)) * 0.041666666666666664);}
+inline float__N__ zeta_l4_2(float__N__ y){
+ return ((y * y * y * fma(y, fma(y, 5.0, -12.0), 7.0)) * 0.041666666666666664);}
+
+
+inline float__N__ alpha_l4_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 14.0, -49.0), 58.0), -22.0), -2.0), -1.0), 2.0)) * 0.041666666666666664);}
+inline float__N__ beta_l4_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -70.0, 245.0), -290.0), 111.0), 4.0), 16.0), -16.0)) * 0.041666666666666664);}
+inline float__N__ gamma_l4_3(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, 140.0, -490.0), 580.0), -224.0), -30.0), 24.0) * 0.041666666666666664);}
+inline float__N__ delta_l4_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -140.0, 490.0), -580.0), 226.0), -4.0), 16.0), 16.0)) * 0.041666666666666664);}
+inline float__N__ eta_l4_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 70.0, -245.0), 290.0), -114.0), 2.0), -1.0), -2.0)) * 0.041666666666666664);}
+inline float__N__ zeta_l4_3(float__N__ y){
+ return ((y * y * y * y * fma(y, fma(y, fma(y, -14.0, 49.0), -58.0), 23.0)) * 0.041666666666666664);}
+
+
+inline float__N__ alpha_l4_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -46.0, 207.0), -354.0), 273.0), -80.0), 1.0), -2.0), -1.0), 2.0)) * 0.041666666666666664);}
+inline float__N__ beta_l4_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 230.0, -1035.0), 1770.0), -1365.0), 400.0), -4.0), 4.0), 16.0), -16.0)) * 0.041666666666666664);}
+inline float__N__ gamma_l4_4(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, -460.0, 2070.0), -3540.0), 2730.0), -800.0), 6.0), -30.0), 24.0) * 0.041666666666666664);}
+inline float__N__ delta_l4_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 460.0, -2070.0), 3540.0), -2730.0), 800.0), -4.0), -4.0), 16.0), 16.0)) * 0.041666666666666664);}
+inline float__N__ eta_l4_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -230.0, 1035.0), -1770.0), 1365.0), -400.0), 1.0), 2.0), -1.0), -2.0)) * 0.041666666666666664);}
+inline float__N__ zeta_l4_4(float__N__ y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, 46.0, -207.0), 354.0), -273.0), 80.0)) * 0.041666666666666664);}
+
+
+inline float__N__ alpha_M8p(float__N__ y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(-10.0,y, + 21.0), + 28.0), - 105.0), + 70.0), + 35.0), - 56.0), + 17.0) * 0.00029761904761904765);}
+inline float__N__ beta_M8p(float__N__ y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(70.0,y, - 175.0), - 140.0), + 770.0), - 560.0), - 350.0), + 504.0), - 102.0) * 0.00029761904761904765);}
+inline float__N__ gamma_M8p(float__N__ y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(-210.0,y, + 609.0), + 224.0), - 2135.0), + 910.0), + 2765.0), - 2520.0), + 255.0) * 0.00029761904761904765);}
+inline float__N__ delta_M8p(float__N__ y){
+ return (fma(y*y, fma(y*y, fma(y*y, fma(70.0,y, - 231.0), + 588.0), - 980.0), + 604.0) * 0.001488095238095238);}
+inline float__N__ eta_M8p(float__N__ y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(-70.0,y, 259.0), - 84.0), - 427.0), - 182.0), + 553.0), + 504.0), + 51.0) * 0.001488095238095238);}
+inline float__N__ zeta_M8p(float__N__ y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(210.0,y,- 861.0), + 532.0), + 770.0), + 560.0), - 350.0), - 504.0), - 102.0) * 0.00029761904761904765);}
+inline float__N__ theta_M8p(float__N__ y){
+ return (fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(-70.0, y, 315.0), -280.0), -105.0), -70.0), 35.0), 56.0), 17.0) * 0.00029761904761904765);}
+inline float__N__ iota_M8p(float__N__ y){
+ return ((y * y * y * y * y * fma(y , fma(10.0 , y ,- 49.0) , 56.0)) * 0.00029761904761904765);}
+
+
+inline float__N__ alpha_l6_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -89.0, 312.0), -370.0), 140.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 623.0, -2183.0), 2581.0), -955.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -1869.0, 6546.0), -7722.0), 2850.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_3(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, 3115.0, -10905.0), 12845.0), -4795.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -3115.0, 10900.0), -12830.0), 4880.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 1869.0, -6537.0), 7695.0), -2985.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_3(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -623.0, 2178.0), -2566.0), 1010.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_3(float__N__ y){
+ return ((y * y * y * y * fma(y, fma(y, fma(y, 89.0, -311.0), 367.0), -145.0)) * 0.001388888888888889);}
+
+
+inline float__N__ alpha_l6_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 290.0, -1305.0), 2231.0), -1718.0), 500.0), -5.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -2030.0, 9135.0), -15617.0), 12027.0), -3509.0), 60.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 6090.0, -27405.0), 46851.0), -36084.0), 10548.0), -195.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_4(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, -10150.0, 45675.0), -78085.0), 60145.0), -17605.0), 280.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 10150.0, -45675.0), 78085.0), -60150.0), 17620.0), -195.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -6090.0, 27405.0), -46851.0), 36093.0), -10575.0), 60.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 2030.0, -9135.0), 15617.0), -12032.0), 3524.0), -5.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_4(float__N__ y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, -290.0, 1305.0), -2231.0), 1719.0), -503.0)) * 0.001388888888888889);}
+
+
+inline float__N__ alpha_l6_5(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -1006.0, 5533.0), -12285.0), 13785.0), -7829.0), 1803.0), -3.0), -5.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_5(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 7042.0, -38731.0), 85995.0), -96495.0), 54803.0), -12620.0), 12.0), 60.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_5(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -21126.0, 116193.0), -257985.0), 289485.0), -164409.0), 37857.0), -15.0), -195.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_5(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, 35210.0, -193655.0), 429975.0), -482475.0), 274015.0), -63090.0), 280.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_5(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -35210.0, 193655.0), -429975.0), 482475.0), -274015.0), 63085.0), 15.0), -195.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_5(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 21126.0, -116193.0), 257985.0), -289485.0), 164409.0), -37848.0), -12.0), 60.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_5(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -7042.0, 38731.0), -85995.0), 96495.0), -54803.0), 12615.0), 3.0), -5.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_5(float__N__ y){
+ return ((y * y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, fma(y, 1006.0, -5533.0), 12285.0), -13785.0), 7829.0), -1802.0)) * 0.001388888888888889);}
+
+
+inline float__N__ alpha_l6_6(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 3604.0, -23426.0), 63866.0), -93577.0), 77815.0), -34869.0), 6587.0), 1.0), -3.0), -5.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float__N__ beta_l6_6(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -25228.0, 163982.0), -447062.0), 655039.0), -544705.0), 244083.0), -46109.0), -6.0), 12.0), 60.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float__N__ gamma_l6_6(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 75684.0, -491946.0), 1341186.0), -1965117.0), 1634115.0), -732249.0), 138327.0), 15.0), -15.0), -195.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float__N__ delta_l6_6(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -126140.0, 819910.0), -2235310.0), 3275195.0), -2723525.0), 1220415.0), -230545.0), -20.0), 280.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float__N__ eta_l6_6(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 126140.0, -819910.0), 2235310.0), -3275195.0), 2723525.0), -1220415.0), 230545.0), 15.0), 15.0), -195.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float__N__ zeta_l6_6(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -75684.0, 491946.0), -1341186.0), 1965117.0), -1634115.0), 732249.0), -138327.0), -6.0), -12.0), 60.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float__N__ theta_l6_6(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 25228.0, -163982.0), 447062.0), -655039.0), 544705.0), -244083.0), 46109.0), 1.0), 3.0), -5.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float__N__ iota_l6_6(float__N__ y){
+ return ((y * y * y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -3604.0, 23426.0), -63866.0), 93577.0), -77815.0), 34869.0), -6587.0)) * 0.001388888888888889);}
+
+
+
+inline float__N__ alpha_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -3569.0, 16061.0), -27454.0), 21126.0), -6125.0), 49.0), -196.0), -36.0), 144.0)) * 2.48015873015873e-05);}
+inline float__N__ beta_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 32121.0, -144548.0), 247074.0), -190092.0), 55125.0), -672.0), 2016.0), 512.0), -1536.0)) * 2.48015873015873e-05);}
+inline float__N__ gamma_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -128484.0, 578188.0), -988256.0), 760312.0), -221060.0), 4732.0), -9464.0), -4032.0), 8064.0)) * 2.48015873015873e-05);}
+inline float__N__ delta_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 299796.0, -1349096.0), 2305856.0), -1774136.0), 517580.0), -13664.0), 13664.0), 32256.0), -32256.0)) * 2.48015873015873e-05);}
+inline float__N__ eta_l8_4(float__N__ y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, -449694.0, 2023630.0), -3458700.0), 2661540.0), -778806.0), 19110.0), -57400.0), 40320.0) * 2.48015873015873e-05);}
+inline float__N__ zeta_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 449694.0, -2023616.0), 3458644.0), -2662016.0), 780430.0), -13664.0), -13664.0), 32256.0), 32256.0)) * 2.48015873015873e-05);}
+inline float__N__ theta_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -299796.0, 1349068.0), -2305744.0), 1775032.0), -520660.0), 4732.0), 9464.0), -4032.0), -8064.0)) * 2.48015873015873e-05);}
+inline float__N__ iota_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 128484.0, -578168.0), 988176.0), -760872.0), 223020.0), -672.0), -2016.0), 512.0), 1536.0)) * 2.48015873015873e-05);}
+inline float__N__ kappa_l8_4(float__N__ y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -32121.0, 144541.0), -247046.0), 190246.0), -55685.0), 49.0), 196.0), -36.0), -144.0)) * 2.48015873015873e-05);}
+inline float__N__ mu_l8_4(float__N__ y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, 3569.0, -16060.0), 27450.0), -21140.0), 6181.0)) * 2.48015873015873e-05);}
diff --git a/hysop/old/gpu.old/cl_src/remeshing/weights_noVec.cl b/hysop/old/gpu.old/cl_src/remeshing/weights_noVec.cl
new file mode 100644
index 0000000000000000000000000000000000000000..a46f89e31324df10b568c2ca10d0923bc428ecbc
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/weights_noVec.cl
@@ -0,0 +1,198 @@
+/**
+ * @file weights_noVec.cl
+ * Remeshing formulas, basic version.
+ * Polynomials under Horner form.
+ */
+
+inline float alpha_l2_1(float y){
+ return ((y * (y * (-y + 2.0) - 1.0)) * 0.5);}
+inline float beta_l2_1(float y){
+ return ((y * y * (3.0 * y - 5.0) + 2.0) * 0.5);}
+inline float gamma_l2_1(float y){
+ return ((y * (y * (-3.0 * y + 4.0) + 1.0)) * 0.5);}
+inline float delta_l2_1(float y){
+ return ((y * y * (y - 1.0)) * 0.5);}
+
+
+inline float alpha_l2_2(float y){
+ return ((y * (y * (y * (y * (2.0 * y - 5.0) + 3.0) + 1.0) - 1.0)) * 0.5);}
+inline float beta_l2_2(float y){
+ return ((y * y * (y * (y * (-6.0 * y + 15.0) - 9.0) - 2.0) + 2.0) * 0.5);}
+inline float gamma_l2_2(float y){
+ return ((y * (y * (y * (y * (6.0 * y - 15.0) + 9.0) + 1.0) + 1.0)) * 0.5);}
+inline float delta_l2_2(float y){
+ return ((y * y * y * (y * (-2.0 * y + 5.0) - 3.0)) * 0.5);}
+
+
+inline float alpha_l2_3(float y){
+ return ((y * (y * (y * y * (y * (y * (-6.0 * y + 21.0) - 25.0) + 10.0) + 1.0) - 1.0)) * 0.5);}
+inline float beta_l2_3(float y){
+ return ((y * y * (y * y * (y * (y * (18.0 * y - 63.0) + 75.0) - 30.0) - 2.0) + 2.0) * 0.5);}
+inline float gamma_l2_3(float y){
+ return ((y * (y * (y * y * (y * (y * (-18.0 * y + 63.0) - 75.0) + 30.0) + 1.0) + 1.0)) * 0.5);}
+inline float delta_l2_3(float y){
+ return ((y * y * y * y * (y * (y * (6.0 * y - 21.0) + 25.0) - 10.0)) * 0.5);}
+
+
+inline float alpha_l2_4(float y){
+ return ((y * (y * (y * y * y * (y * (y * (y * (20.0 * y - 90.0) + 154.0) - 119.0) + 35.0) + 1.0) - 1.0)) * 0.5);}
+inline float beta_l2_4(float y){
+ return ((y * y * (y * y * y * (y * (y * (y * (-60.0 * y + 270.0) - 462.0) + 357.0) - 105.0) - 2.0) + 2.0) * 0.5);}
+inline float gamma_l2_4(float y){
+ return ((y * (y * (y * y * y * (y * (y * (y * (60.0 * y - 270.0) + 462.0) - 357.0) + 105.0) + 1.0) + 1.0)) * 0.5);}
+inline float delta_l2_4(float y){
+ return ((y * y * y * y * y * (y * (y * (y * (-20.0 * y + 90.0) - 154.0) + 119.0) - 35.0)) * 0.5);}
+
+
+inline float alpha_l4_2(float y){
+ return ((y * (y * (y * (y * (-5.0 * y + 13.0) - 9.0) - 1.0) + 2.0)) * 0.041666666666666664);}
+inline float beta_l4_2(float y){
+ return ((y * (y * (y * (y * (25.0 * y - 64.0) + 39.0) + 16.0) - 16.0)) * 0.041666666666666664);}
+inline float gamma_l4_2(float y){
+ return ((y * y * (y * (y * (-50.0 * y + 126.0) - 70.0) - 30.0) + 24.0) * 0.041666666666666664);}
+inline float delta_l4_2(float y){
+ return ((y * (y * (y * (y * (50.0 * y - 124.0) + 66.0) + 16.0) + 16.0)) * 0.041666666666666664);}
+inline float eta_l4_2(float y){
+ return ((y * (y * (y * (y * (-25.0 * y + 61.0) - 33.0) - 1.0) - 2.0)) * 0.041666666666666664);}
+inline float zeta_l4_2(float y){
+ return ((y * y * y * (y * (5.0 * y - 12.0) + 7.0)) * 0.041666666666666664);}
+
+
+inline float alpha_l4_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (14.0 * y - 49.0) + 58.0) - 22.0) - 2.0) - 1.0) + 2.0)) * 0.041666666666666664);}
+inline float beta_l4_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (-70.0 * y + 245.0) - 290.0) + 111.0) + 4.0) + 16.0) - 16.0)) * 0.041666666666666664);}
+inline float gamma_l4_3(float y){
+ return ((y * y * (y * y * (y * (y * (140.0 * y - 490.0) + 580.0) - 224.0) - 30.0) + 24.0) * 0.041666666666666664);}
+inline float delta_l4_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (-140.0 * y + 490.0) - 580.0) + 226.0) - 4.0) + 16.0) + 16.0)) * 0.041666666666666664);}
+inline float eta_l4_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (70.0 * y - 245.0) + 290.0) - 114.0) + 2.0) - 1.0) - 2.0)) * 0.041666666666666664);}
+inline float zeta_l4_3(float y){
+ return ((y * y * y * y * (y * (y * (-14.0 * y + 49.0) - 58.0) + 23.0)) * 0.041666666666666664);}
+
+
+inline float alpha_l4_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-46.0 * y + 207.0) - 354.0) + 273.0) - 80.0) + 1.0) - 2.0) - 1.0) + 2.0)) * 0.041666666666666664);}
+inline float beta_l4_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (230.0 * y - 1035.0) + 1770.0) - 1365.0) + 400.0) - 4.0) + 4.0) + 16.0) - 16.0)) * 0.041666666666666664);}
+inline float gamma_l4_4(float y){
+ return ((y * y * (y * y * (y * (y * (y * (y * (-460.0 * y + 2070.0) - 3540.0) + 2730.0) - 800.0) + 6.0) - 30.0) + 24.0) * 0.041666666666666664);}
+inline float delta_l4_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (460.0 * y - 2070.0) + 3540.0) - 2730.0) + 800.0) - 4.0) - 4.0) + 16.0) + 16.0)) * 0.041666666666666664);}
+inline float eta_l4_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-230.0 * y + 1035.0) - 1770.0) + 1365.0) - 400.0) + 1.0) + 2.0) - 1.0) - 2.0)) * 0.041666666666666664);}
+inline float zeta_l4_4(float y){
+ return ((y * y * y * y * y * (y * (y * (y * (46.0 * y - 207.0) + 354.0) - 273.0) + 80.0)) * 0.041666666666666664);}
+
+
+inline float alpha_M8p(float y){
+ return ((y*(y*(y*(y*(y*(y*(-10.0*y + 21.0) + 28.0) - 105.0) + 70.0) + 35.0) - 56.0) + 17.0) * 0.00029761904761904765);}
+inline float beta_M8p(float y){
+ return ((y*(y*(y*(y*(y*(y*(70.0*y - 175.0) - 140.0) + 770.0) - 560.0) - 350.0) + 504.0) - 102.0) * 0.00029761904761904765);}
+inline float gamma_M8p(float y){
+ return ((y*(y*(y*(y*(y*(y*(-210.0*y + 609.0) + 224.0) - 2135.0) + 910.0) + 2765.0) - 2520.0) + 255.0) * 0.00029761904761904765);}
+inline float delta_M8p(float y){
+ return ((y*y* (y*y* (y*y* (70.0*y - 231.0) + 588.0) - 980.0) + 604.0) * 0.001488095238095238);}
+inline float eta_M8p(float y){
+ return ((y*(y*(y*(y*(y*(y*(-70.0*y+ 259.0) - 84.0) - 427.0) - 182.0)+ 553.0) + 504.0)+ 51.0) * 0.001488095238095238);}
+inline float zeta_M8p(float y){
+ return ((y*(y*(y*(y*(y*(y*(210.0*y- 861.0) + 532.0) + 770.0) + 560.0) - 350.0) - 504.0) - 102.0) * 0.00029761904761904765);}
+inline float theta_M8p(float y){
+ return ((y* (y* (y* (y* (y* (y* (-70.0* y+ 315.0) -280.0) -105.0) -70.0) +35.0)+ 56.0) +17.0) * 0.00029761904761904765);}
+inline float iota_M8p(float y){
+ return ((y * y * y * y * y * (y * (10.0 * y - 49.0) + 56.0)) * 0.00029761904761904765);}
+
+
+inline float alpha_l6_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (-89.0 * y + 312.0) - 370.0) + 140.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float beta_l6_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (623.0 * y - 2183.0) + 2581.0) - 955.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (-1869.0 * y + 6546.0) - 7722.0) + 2850.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float delta_l6_3(float y){
+ return ((y * y * (y * y * (y * (y * (3115.0 * y - 10905.0) + 12845.0) - 4795.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float eta_l6_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (-3115.0 * y + 10900.0) - 12830.0) + 4880.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (1869.0 * y - 6537.0) + 7695.0) - 2985.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float theta_l6_3(float y){
+ return ((y * (y * (y * (y * (y * (y * (-623.0 * y + 2178.0) - 2566.0) + 1010.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float iota_l6_3(float y){
+ return ((y * y * y * y * (y * (y * (89.0 * y - 311.0) + 367.0) - 145.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l6_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (290.0 * y - 1305.0) + 2231.0) - 1718.0) + 500.0) - 5.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float beta_l6_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-2030.0 * y + 9135.0) - 15617.0) + 12027.0) - 3509.0) + 60.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (6090.0 * y - 27405.0) + 46851.0) - 36084.0) + 10548.0) - 195.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float delta_l6_4(float y){
+ return ((y * y * (y * y * (y * (y * (y * (y * (-10150.0 * y + 45675.0) - 78085.0) + 60145.0) - 17605.0) + 280.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float eta_l6_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (10150.0 * y - 45675.0) + 78085.0) - 60150.0) + 17620.0) - 195.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-6090.0 * y + 27405.0) - 46851.0) + 36093.0) - 10575.0) + 60.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float theta_l6_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (2030.0 * y - 9135.0) + 15617.0) - 12032.0) + 3524.0) - 5.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float iota_l6_4(float y){
+ return ((y * y * y * y * y * (y * (y * (y * (-290.0 * y + 1305.0) - 2231.0) + 1719.0) - 503.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l6_5(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-1006.0 * y + 5533.0) - 12285.0) + 13785.0) - 7829.0) + 1803.0) - 3.0) - 5.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float beta_l6_5(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (7042.0 * y - 38731.0) + 85995.0) - 96495.0) + 54803.0) - 12620.0) + 12.0) + 60.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_5(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-21126.0 * y + 116193.0) - 257985.0) + 289485.0) - 164409.0) + 37857.0) - 15.0) - 195.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float delta_l6_5(float y){
+ return ((y * y * (y * y * (y * y * (y * (y * (y * (y * (35210.0 * y - 193655.0) + 429975.0) - 482475.0) + 274015.0) - 63090.0) + 280.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float eta_l6_5(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-35210.0 * y + 193655.0) - 429975.0) + 482475.0) - 274015.0) + 63085.0) + 15.0) - 195.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_5(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (21126.0 * y - 116193.0) + 257985.0) - 289485.0) + 164409.0) - 37848.0) - 12.0) + 60.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float theta_l6_5(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-7042.0 * y + 38731.0) - 85995.0) + 96495.0) - 54803.0) + 12615.0) + 3.0) - 5.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float iota_l6_5(float y){
+ return ((y * y * y * y * y * y * (y * (y * (y * (y * (1006.0 * y - 5533.0) + 12285.0) - 13785.0) + 7829.0) - 1802.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l6_6(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (3604.0 * y - 23426.0) + 63866.0) - 93577.0) + 77815.0) - 34869.0) + 6587.0) + 1.0) - 3.0) - 5.0) + 15.0) + 4.0) - 12.0)) * 0.001388888888888889);}
+inline float beta_l6_6(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-25228.0 * y + 163982.0) - 447062.0) + 655039.0) - 544705.0) + 244083.0) - 46109.0) - 6.0) + 12.0) + 60.0) - 120.0) - 54.0) + 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_6(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (75684.0 * y - 491946.0) + 1341186.0) - 1965117.0) + 1634115.0) - 732249.0) + 138327.0) + 15.0) - 15.0) - 195.0) + 195.0) + 540.0) - 540.0)) * 0.001388888888888889);}
+inline float delta_l6_6(float y){
+ return ((y * y * (y * y * (y * y * (y * (y * (y * (y * (y * (y * (-126140.0 * y + 819910.0) - 2235310.0) + 3275195.0) - 2723525.0) + 1220415.0) - 230545.0) - 20.0) + 280.0) - 980.0) + 720.0) * 0.001388888888888889);}
+inline float eta_l6_6(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (126140.0 * y - 819910.0) + 2235310.0) - 3275195.0) + 2723525.0) - 1220415.0) + 230545.0) + 15.0) + 15.0) - 195.0) - 195.0) + 540.0) + 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_6(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (-75684.0 * y + 491946.0) - 1341186.0) + 1965117.0) - 1634115.0) + 732249.0) - 138327.0) - 6.0) - 12.0) + 60.0) + 120.0) - 54.0) - 108.0)) * 0.001388888888888889);}
+inline float theta_l6_6(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (y * (25228.0 * y - 163982.0) + 447062.0) - 655039.0) + 544705.0) - 244083.0) + 46109.0) + 1.0) + 3.0) - 5.0) - 15.0) + 4.0) + 12.0)) * 0.001388888888888889);}
+inline float iota_l6_6(float y){
+ return ((y * y * y * y * y * y * y * (y * (y * (y * (y * (y * (-3604.0 * y + 23426.0) - 63866.0) + 93577.0) - 77815.0) + 34869.0) - 6587.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-3569.0 * y + 16061.0) - 27454.0) + 21126.0) - 6125.0) + 49.0) - 196.0) - 36.0) + 144.0)) * 2.48015873015873e-05);}
+inline float beta_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (32121.0 * y - 144548.0) + 247074.0) - 190092.0) + 55125.0) - 672.0) + 2016.0) + 512.0) - 1536.0)) * 2.48015873015873e-05);}
+inline float gamma_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-128484.0 * y + 578188.0) - 988256.0) + 760312.0) - 221060.0) + 4732.0) - 9464.0) - 4032.0) + 8064.0)) * 2.48015873015873e-05);}
+inline float delta_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (299796.0 * y - 1349096.0) + 2305856.0) - 1774136.0) + 517580.0) - 13664.0) + 13664.0) + 32256.0) - 32256.0)) * 2.48015873015873e-05);}
+inline float eta_l8_4(float y){
+ return ((y * y * (y * y * (y * (y * (y * (y * (-449694.0 * y + 2023630.0) - 3458700.0) + 2661540.0) - 778806.0) + 19110.0) - 57400.0) + 40320.0) * 2.48015873015873e-05);}
+inline float zeta_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (449694.0 * y - 2023616.0) + 3458644.0) - 2662016.0) + 780430.0) - 13664.0) - 13664.0) + 32256.0) + 32256.0)) * 2.48015873015873e-05);}
+inline float theta_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-299796.0 * y + 1349068.0) - 2305744.0) + 1775032.0) - 520660.0) + 4732.0) + 9464.0) - 4032.0) - 8064.0)) * 2.48015873015873e-05);}
+inline float iota_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (128484.0 * y - 578168.0) + 988176.0) - 760872.0) + 223020.0) - 672.0) - 2016.0) + 512.0) + 1536.0)) * 2.48015873015873e-05);}
+inline float kappa_l8_4(float y){
+ return ((y * (y * (y * (y * (y * (y * (y * (y * (-32121.0 * y + 144541.0) - 247046.0) + 190246.0) - 55685.0) + 49.0) + 196.0) - 36.0) - 144.0)) * 2.48015873015873e-05);}
+inline float mu_l8_4(float y){
+ return ((y * y * y * y * y * (y * (y * (y * (3569.0 * y - 16060.0) + 27450.0) - 21140.0) + 6181.0)) * 2.48015873015873e-05);}
diff --git a/hysop/old/gpu.old/cl_src/remeshing/weights_noVec_builtin.cl b/hysop/old/gpu.old/cl_src/remeshing/weights_noVec_builtin.cl
new file mode 100644
index 0000000000000000000000000000000000000000..4c0e124803bf7a58c73fa796ccda0f0c18e919ba
--- /dev/null
+++ b/hysop/old/gpu.old/cl_src/remeshing/weights_noVec_builtin.cl
@@ -0,0 +1,198 @@
+/**
+ * @file weights_noVec_builtin.cl
+ * Remeshing formulas, vectorized version, use of builtin OpenCL fma.
+ * Polynomials under Horner form.
+ */
+
+inline float alpha_l2_1(float y){
+ return (y*fma(y,fma(y,-1.0, 2.0), - 1.0) * 0.5);}
+inline float beta_l2_1(float y){
+ return (fma(y*y, fma(y, 3.0, -5.0), 2.0) * 0.5);}
+inline float gamma_l2_1(float y){
+ return ((y * fma(y , fma(-3.0, y, 4.0), 1.0)) * 0.5);}
+inline float delta_l2_1(float y){
+ return ((y * y * fma(1.0, y, - 1.0)) * 0.5);}
+
+
+inline float alpha_l2_2(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 2.0, -5.0), 3.0), 1.0), -1.0)) * 0.5);}
+inline float beta_l2_2(float y){
+ return (fma(y * y, fma(y, fma(y, fma(y, -6.0, 15.0), -9.0), -2.0), 2.0) * 0.5);}
+inline float gamma_l2_2(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 6.0, -15.0), 9.0), 1.0), 1.0)) * 0.5);}
+inline float delta_l2_2(float y){
+ return ((y * y * y * fma(y, fma(y, -2.0, 5.0), -3.0)) * 0.5);}
+
+
+inline float alpha_l2_3(float y){
+ return ((y * fma(y, fma(y * y, fma(y, fma(y, fma(y, -6.0, 21.0), -25.0), 10.0), 1.0), -1.0)) * 0.5);}
+inline float beta_l2_3(float y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, 18.0, -63.0), 75.0), -30.0), -2.0), 2.0) * 0.5);}
+inline float gamma_l2_3(float y){
+ return ((y * fma(y, fma(y * y, fma(y, fma(y, fma(y, -18.0, 63.0), -75.0), 30.0), 1.0), 1.0)) * 0.5);}
+inline float delta_l2_3(float y){
+ return ((y * y * y * y * fma(y, fma(y, fma(y, 6.0, -21.0), 25.0), -10.0)) * 0.5);}
+
+
+inline float alpha_l2_4(float y){
+ return ((y * fma(y, fma(y * y * y, fma(y, fma(y, fma(y, fma(y, 20.0, -90.0), 154.0), -119.0), 35.0), 1.0), -1.0)) * 0.5);}
+inline float beta_l2_4(float y){
+ return (fma(y * y, fma(y * y * y, fma(y, fma(y, fma(y, fma(y, -60.0, 270.0), -462.0), 357.0), -105.0), -2.0), 2.0) * 0.5);}
+inline float gamma_l2_4(float y){
+ return ((y * fma(y, fma(y * y * y, fma(y, fma(y, fma(y, fma(y, 60.0, -270.0), 462.0), -357.0), 105.0), 1.0), 1.0)) * 0.5);}
+inline float delta_l2_4(float y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, -20.0, 90.0), -154.0), 119.0), -35.0)) * 0.5);}
+
+
+inline float alpha_l4_2(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, -5.0, 13.0), -9.0), -1.0), 2.0)) * 0.041666666666666664);}
+inline float beta_l4_2(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 25.0, -64.0), 39.0), 16.0), -16.0)) * 0.041666666666666664);}
+inline float gamma_l4_2(float y){
+ return (fma(y * y, fma(y, fma(y, fma(y, -50.0, 126.0), -70.0), -30.0), 24.0) * 0.041666666666666664);}
+inline float delta_l4_2(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, 50.0, -124.0), 66.0), 16.0), 16.0)) * 0.041666666666666664);}
+inline float eta_l4_2(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, -25.0, 61.0), -33.0), -1.0), -2.0)) * 0.041666666666666664);}
+inline float zeta_l4_2(float y){
+ return ((y * y * y * fma(y, fma(y, 5.0, -12.0), 7.0)) * 0.041666666666666664);}
+
+
+inline float alpha_l4_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 14.0, -49.0), 58.0), -22.0), -2.0), -1.0), 2.0)) * 0.041666666666666664);}
+inline float beta_l4_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -70.0, 245.0), -290.0), 111.0), 4.0), 16.0), -16.0)) * 0.041666666666666664);}
+inline float gamma_l4_3(float y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, 140.0, -490.0), 580.0), -224.0), -30.0), 24.0) * 0.041666666666666664);}
+inline float delta_l4_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -140.0, 490.0), -580.0), 226.0), -4.0), 16.0), 16.0)) * 0.041666666666666664);}
+inline float eta_l4_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 70.0, -245.0), 290.0), -114.0), 2.0), -1.0), -2.0)) * 0.041666666666666664);}
+inline float zeta_l4_3(float y){
+ return ((y * y * y * y * fma(y, fma(y, fma(y, -14.0, 49.0), -58.0), 23.0)) * 0.041666666666666664);}
+
+
+inline float alpha_l4_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -46.0, 207.0), -354.0), 273.0), -80.0), 1.0), -2.0), -1.0), 2.0)) * 0.041666666666666664);}
+inline float beta_l4_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 230.0, -1035.0), 1770.0), -1365.0), 400.0), -4.0), 4.0), 16.0), -16.0)) * 0.041666666666666664);}
+inline float gamma_l4_4(float y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, -460.0, 2070.0), -3540.0), 2730.0), -800.0), 6.0), -30.0), 24.0) * 0.041666666666666664);}
+inline float delta_l4_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 460.0, -2070.0), 3540.0), -2730.0), 800.0), -4.0), -4.0), 16.0), 16.0)) * 0.041666666666666664);}
+inline float eta_l4_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -230.0, 1035.0), -1770.0), 1365.0), -400.0), 1.0), 2.0), -1.0), -2.0)) * 0.041666666666666664);}
+inline float zeta_l4_4(float y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, 46.0, -207.0), 354.0), -273.0), 80.0)) * 0.041666666666666664);}
+
+
+inline float alpha_M8p(float y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(-10.0,y, + 21.0), + 28.0), - 105.0), + 70.0), + 35.0), - 56.0), + 17.0) * 0.00029761904761904765);}
+inline float beta_M8p(float y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(70.0,y, - 175.0), - 140.0), + 770.0), - 560.0), - 350.0), + 504.0), - 102.0) * 0.00029761904761904765);}
+inline float gamma_M8p(float y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(-210.0,y, + 609.0), + 224.0), - 2135.0), + 910.0), + 2765.0), - 2520.0), + 255.0) * 0.00029761904761904765);}
+inline float delta_M8p(float y){
+ return (fma(y*y, fma(y*y, fma(y*y, fma(70.0,y, - 231.0), + 588.0), - 980.0), + 604.0) * 0.001488095238095238);}
+inline float eta_M8p(float y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(-70.0,y, 259.0), - 84.0), - 427.0), - 182.0), + 553.0), + 504.0), + 51.0) * 0.001488095238095238);}
+inline float zeta_M8p(float y){
+ return (fma(y,fma(y,fma(y,fma(y,fma(y,fma(y,fma(210.0,y,- 861.0), + 532.0), + 770.0), + 560.0), - 350.0), - 504.0), - 102.0) * 0.00029761904761904765);}
+inline float theta_M8p(float y){
+ return (fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(-70.0, y, 315.0), -280.0), -105.0), -70.0), 35.0), 56.0), 17.0) * 0.00029761904761904765);}
+inline float iota_M8p(float y){
+ return ((y * y * y * y * y * fma(y , fma(10.0 , y ,- 49.0) , 56.0)) * 0.00029761904761904765);}
+
+
+inline float alpha_l6_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -89.0, 312.0), -370.0), 140.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float beta_l6_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 623.0, -2183.0), 2581.0), -955.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -1869.0, 6546.0), -7722.0), 2850.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float delta_l6_3(float y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, 3115.0, -10905.0), 12845.0), -4795.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float eta_l6_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -3115.0, 10900.0), -12830.0), 4880.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 1869.0, -6537.0), 7695.0), -2985.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float theta_l6_3(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -623.0, 2178.0), -2566.0), 1010.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float iota_l6_3(float y){
+ return ((y * y * y * y * fma(y, fma(y, fma(y, 89.0, -311.0), 367.0), -145.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l6_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 290.0, -1305.0), 2231.0), -1718.0), 500.0), -5.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float beta_l6_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -2030.0, 9135.0), -15617.0), 12027.0), -3509.0), 60.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 6090.0, -27405.0), 46851.0), -36084.0), 10548.0), -195.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float delta_l6_4(float y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, -10150.0, 45675.0), -78085.0), 60145.0), -17605.0), 280.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float eta_l6_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 10150.0, -45675.0), 78085.0), -60150.0), 17620.0), -195.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -6090.0, 27405.0), -46851.0), 36093.0), -10575.0), 60.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float theta_l6_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 2030.0, -9135.0), 15617.0), -12032.0), 3524.0), -5.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float iota_l6_4(float y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, -290.0, 1305.0), -2231.0), 1719.0), -503.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l6_5(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -1006.0, 5533.0), -12285.0), 13785.0), -7829.0), 1803.0), -3.0), -5.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float beta_l6_5(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 7042.0, -38731.0), 85995.0), -96495.0), 54803.0), -12620.0), 12.0), 60.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_5(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -21126.0, 116193.0), -257985.0), 289485.0), -164409.0), 37857.0), -15.0), -195.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float delta_l6_5(float y){
+ return (fma(y * y, fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, 35210.0, -193655.0), 429975.0), -482475.0), 274015.0), -63090.0), 280.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float eta_l6_5(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -35210.0, 193655.0), -429975.0), 482475.0), -274015.0), 63085.0), 15.0), -195.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_5(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 21126.0, -116193.0), 257985.0), -289485.0), 164409.0), -37848.0), -12.0), 60.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float theta_l6_5(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -7042.0, 38731.0), -85995.0), 96495.0), -54803.0), 12615.0), 3.0), -5.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float iota_l6_5(float y){
+ return ((y * y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, fma(y, 1006.0, -5533.0), 12285.0), -13785.0), 7829.0), -1802.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l6_6(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 3604.0, -23426.0), 63866.0), -93577.0), 77815.0), -34869.0), 6587.0), 1.0), -3.0), -5.0), 15.0), 4.0), -12.0)) * 0.001388888888888889);}
+inline float beta_l6_6(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -25228.0, 163982.0), -447062.0), 655039.0), -544705.0), 244083.0), -46109.0), -6.0), 12.0), 60.0), -120.0), -54.0), 108.0)) * 0.001388888888888889);}
+inline float gamma_l6_6(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 75684.0, -491946.0), 1341186.0), -1965117.0), 1634115.0), -732249.0), 138327.0), 15.0), -15.0), -195.0), 195.0), 540.0), -540.0)) * 0.001388888888888889);}
+inline float delta_l6_6(float y){
+ return (fma(y * y, fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -126140.0, 819910.0), -2235310.0), 3275195.0), -2723525.0), 1220415.0), -230545.0), -20.0), 280.0), -980.0), 720.0) * 0.001388888888888889);}
+inline float eta_l6_6(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 126140.0, -819910.0), 2235310.0), -3275195.0), 2723525.0), -1220415.0), 230545.0), 15.0), 15.0), -195.0), -195.0), 540.0), 540.0)) * 0.001388888888888889);}
+inline float zeta_l6_6(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -75684.0, 491946.0), -1341186.0), 1965117.0), -1634115.0), 732249.0), -138327.0), -6.0), -12.0), 60.0), 120.0), -54.0), -108.0)) * 0.001388888888888889);}
+inline float theta_l6_6(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 25228.0, -163982.0), 447062.0), -655039.0), 544705.0), -244083.0), 46109.0), 1.0), 3.0), -5.0), -15.0), 4.0), 12.0)) * 0.001388888888888889);}
+inline float iota_l6_6(float y){
+ return ((y * y * y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -3604.0, 23426.0), -63866.0), 93577.0), -77815.0), 34869.0), -6587.0)) * 0.001388888888888889);}
+
+
+inline float alpha_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -3569.0, 16061.0), -27454.0), 21126.0), -6125.0), 49.0), -196.0), -36.0), 144.0)) * 2.48015873015873e-05);}
+inline float beta_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 32121.0, -144548.0), 247074.0), -190092.0), 55125.0), -672.0), 2016.0), 512.0), -1536.0)) * 2.48015873015873e-05);}
+inline float gamma_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -128484.0, 578188.0), -988256.0), 760312.0), -221060.0), 4732.0), -9464.0), -4032.0), 8064.0)) * 2.48015873015873e-05);}
+inline float delta_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 299796.0, -1349096.0), 2305856.0), -1774136.0), 517580.0), -13664.0), 13664.0), 32256.0), -32256.0)) * 2.48015873015873e-05);}
+inline float eta_l8_4(float y){
+ return (fma(y * y, fma(y * y, fma(y, fma(y, fma(y, fma(y, fma(y, -449694.0, 2023630.0), -3458700.0), 2661540.0), -778806.0), 19110.0), -57400.0), 40320.0) * 2.48015873015873e-05);}
+inline float zeta_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 449694.0, -2023616.0), 3458644.0), -2662016.0), 780430.0), -13664.0), -13664.0), 32256.0), 32256.0)) * 2.48015873015873e-05);}
+inline float theta_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -299796.0, 1349068.0), -2305744.0), 1775032.0), -520660.0), 4732.0), 9464.0), -4032.0), -8064.0)) * 2.48015873015873e-05);}
+inline float iota_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, 128484.0, -578168.0), 988176.0), -760872.0), 223020.0), -672.0), -2016.0), 512.0), 1536.0)) * 2.48015873015873e-05);}
+inline float kappa_l8_4(float y){
+ return ((y * fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, fma(y, -32121.0, 144541.0), -247046.0), 190246.0), -55685.0), 49.0), 196.0), -36.0), -144.0)) * 2.48015873015873e-05);}
+inline float mu_l8_4(float y){
+ return ((y * y * y * y * y * fma(y, fma(y, fma(y, fma(y, 3569.0, -16060.0), 27450.0), -21140.0), 6181.0)) * 2.48015873015873e-05);}
diff --git a/hysop/gpu/config_cayman.py b/hysop/old/gpu.old/config_cayman.py
similarity index 100%
rename from hysop/gpu/config_cayman.py
rename to hysop/old/gpu.old/config_cayman.py
diff --git a/hysop/gpu/config_default.py b/hysop/old/gpu.old/config_default.py
similarity index 100%
rename from hysop/gpu/config_default.py
rename to hysop/old/gpu.old/config_default.py
diff --git a/hysop/gpu/config_k20m.py b/hysop/old/gpu.old/config_k20m.py
similarity index 100%
rename from hysop/gpu/config_k20m.py
rename to hysop/old/gpu.old/config_k20m.py
diff --git a/hysop/old/gpu.old/directional/__init__.py b/hysop/old/gpu.old/directional/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/old/gpu.old/directional/advection_dir.py b/hysop/old/gpu.old/directional/advection_dir.py
new file mode 100644
index 0000000000000000000000000000000000000000..e9802729dd45cbbb4b9b3801d9fe1b6edbf32c3f
--- /dev/null
+++ b/hysop/old/gpu.old/directional/advection_dir.py
@@ -0,0 +1,136 @@
+
+from hysop.constants import np
+
+from hysop.backend.device.kernel_config import KernelConfig
+from hysop.backend.device.opencl.directional.directional_codegen import OpenClCodegenDirectionalOperator
+
+from hysop.tools.types import InstanceOf
+from hysop.methods import TimeIntegrator, ExtraArgs, Interpolation, Precision, \
+ ExplicitRungeKutta, Remesh
+
+from hysop.constants import HYSOP_REAL
+from hysop.numerics.odesolvers import Euler, RK2, RK3, RK4
+from hysop.numerics.interpolation.interpolation import Linear
+
+from hysop.numerics.remeshing import L2_1, L2_2, L2_3, L2_4
+from hysop.numerics.remeshing import L4_2, L4_3, L4_4
+from hysop.numerics.remeshing import L6_3, L6_4, L6_5, L6_6
+from hysop.numerics.remeshing import L8_4
+
+class OpenClCodegenDirectionalAdvection(OpenClCodegenDirectionalOperator):
+
+ __default_method = {
+ TimeIntegrator: RK2,
+ Interpolation: Linear,
+ Remesh: L2_1,
+ Precision: HYSOP_REAL,
+ KernelConfig: KernelConfig()
+ }
+
+ __available_methods = {
+ TimeIntegrator: [Euler,RK2,RK3,RK4,InstanceOf(ExplicitRungeKutta)],
+ Interpolation: [Linear],
+ Remesh: [L2_1,L2_2,L2_3,L2_4,L4_2,L4_3,L4_4,L6_3,L6_4,L6_5,L6_6,L8_4],
+ Precision: [np.float32,np.float64],
+ KernelConfig: InstanceOf(KernelConfig)
+ }
+
+ def __init__(self, velocity, advected_fields_in, advected_fields_out,
+ is_multi_scale, is_multi_topo,
+ **kargs):
+ """Particular advection of field(s) in a given direction,
+ on GPU, without remeshing.
+
+ OpenCL kernels are build once per dimension in order to handle
+ directional splitting with resolution non uniform in directions.
+
+ Parameters
+ ----------
+ dimension: The number of dimensions used for directional splitting.
+ direction: The direction of discretisation, should be less than dimension.
+ velocity: Velocity used for advection, as a continuous variable.
+ advected_fields: List of advected continuous variables.
+ variables: Dictionary containing all continuous fields as keys and their
+ corresponding topology as values.
+ method: Dictionary containing valid method keys and values.
+ Valid methods can be retrieved by using the class function available_methods().
+ """
+
+
+ super(OpenClCodegenDirectionalAdvection,self).__init__(**kargs)
+
+ self.velocity = velocity
+ self.advected_fields_in = advected_fields_in
+ self.advected_fields_out = advected_fields_out
+
+ # point _do_compute_impl function to the right implementation
+ if self._is_distributed:
+ if is_multi_scale:
+ impl = self._do_compute_multiscale_comm
+ else:
+ impl = self._do_compute_monoscale_comm
+ else:
+ if is_multi_scale:
+ impl = self._do_compute_multiscale
+ else:
+ impl = self._do_compute_monoscale
+ self._do_compute_impl = impl
+
+ def initialize(self):
+ pass
+ def discretize(self):
+ pass
+ def get_work_properties(self):
+ return None
+ def setup(self,work):
+ pass
+ def apply(self):
+ pass
+
+ def _generate_kernels(self):
+ self._generate_advection_kernel()
+
+ def _generate_advection_kernel():
+ self._advec = None
+ raise NotImplementedError()
+
+ def _do_compute_monoscale(self, dt):
+ raise NotImplementedError()
+ def _do_compute_multiscale(self, dt):
+ raise NotImplementedError()
+ def _do_compute_monoscale_comm(self, dt):
+ raise NotImplementedError()
+ def _do_compute_multiscale_comm(self, dt):
+ raise NotImplementedError()
+
+
+ ## Backend methods
+ # ComputationalNode
+ @classmethod
+ def default_method(cls):
+ return cls.__default_method
+
+ @classmethod
+ def available_methods(cls):
+ return cls.__available_methods
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return False
+
+ @classmethod
+ def supports_mpi(cls):
+ return False
+
+ # DirectionalOperator
+ @classmethod
+ def supported_dimensions(cls):
+ return [1,2,3]
+
+ # ComputationalGraphNode
+ @classmethod
+ def supports_multiscale(cls):
+ return False
+ @classmethod
+ def supports_multiple_advected_topologies(cls):
+ return False
diff --git a/hysop/old/gpu.old/directional/directional_codegen.py b/hysop/old/gpu.old/directional/directional_codegen.py
new file mode 100644
index 0000000000000000000000000000000000000000..0d6fc0831a49a5173eea8ff64b42bd1afd02e81d
--- /dev/null
+++ b/hysop/old/gpu.old/directional/directional_codegen.py
@@ -0,0 +1,11 @@
+
+from hysop.backend.device.opencl.gpu_codegen import OpenClCodegenOperator
+
+class OpenClCodegenDirectionalOperator(OpenClCodegenOperator):
+
+ def __init__(self,direction,splitting_dim,**kargs):
+ super(OpenClCodegenDirectionalOperator,self).__init__(direction=direction,**kargs)
+ assert direction<splitting_dim
+ self.direction = direction
+ self.splitting_dim = splitting_dim
+
diff --git a/hysop/old/gpu.old/gpu_codegen.py b/hysop/old/gpu.old/gpu_codegen.py
new file mode 100644
index 0000000000000000000000000000000000000000..5d9e587a48312fface40e9fff4d326e220cd7eb5
--- /dev/null
+++ b/hysop/old/gpu.old/gpu_codegen.py
@@ -0,0 +1,9 @@
+
+from hysop.backend.device.opencl.gpu_operator import GPUOperator
+from hysop.core.graph.computational_operator import ComputationalGraphOperator
+from hysop.backend.device.kernel_config import KernelConfig
+
+class OpenClCodegenOperator(ComputationalGraphOperator):
+
+ def __init__(self, **kargs):
+ super(OpenClCodegenOperator,self).__init__(**kargs)
diff --git a/hysop/gpu/gpu_diffusion.py b/hysop/old/gpu.old/gpu_diffusion.py
similarity index 92%
rename from hysop/gpu/gpu_diffusion.py
rename to hysop/old/gpu.old/gpu_diffusion.py
index 0f2084b76c7d0b8a39663ac5bb858b5aefe9be37..b4496e0f24431858d36abd6dbf7c8f7425386329 100644
--- a/hysop/gpu/gpu_diffusion.py
+++ b/hysop/old/gpu.old/gpu_diffusion.py
@@ -3,17 +3,17 @@
Diffusion on GPU
"""
-from hysop.constants import debug, np, S_DIR, HYSOP_MPI_REAL, ORDERMPI, \
+from hysop.constants import debug, np, DirectionLabels, hysop.core.mpi_REAL, ORDERMPI, \
HYSOP_REAL, ORDER
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.operator.discrete.discrete import get_extra_args_from_method
-from hysop.gpu import cl
-from hysop.gpu.gpu_operator import GPUOperator
-from hysop.gpu.gpu_kernel import KernelLauncher
-from hysop.gpu.gpu_discrete import GPUDiscreteField
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.gpu_operator import GPUOperator
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
from hysop.tools.profiler import FProfiler
-from hysop.mpi import Wtime
+from hysop.core.mpi import Wtime
class GPUDiffusion(DiscreteOperator, GPUOperator):
@@ -21,7 +21,7 @@ class GPUDiffusion(DiscreteOperator, GPUOperator):
@debug
def __init__(self, field, viscosity, **kwds):
super(GPUDiffusion, self).__init__(variables=[field], **kwds)
- ## Discretisation of the solution field
+ ## Discretization of the solution field
self.field = self.variables[0]
## Viscosity.
self.viscosity = viscosity
@@ -38,8 +38,8 @@ class GPUDiffusion(DiscreteOperator, GPUOperator):
**kwds)
## GPU allocation.
- alloc = not isinstance(self.field, GPUDiscreteField)
- GPUDiscreteField.fromField(self.cl_env, self.field,
+ alloc = not isinstance(self.field, OpenClDiscreteField)
+ OpenClDiscreteField.fromField(self.cl_env, self.field,
self.gpu_precision, simple_layout=False)
if not self.field.gpu_allocated:
self.field.allocate()
@@ -79,10 +79,10 @@ class GPUDiffusion(DiscreteOperator, GPUOperator):
# _to_recv[..., 1] contains [..., -1] data (left ghosts)
self._to_send[d] = npw.zeros(tuple(shape))
_to_recv = npw.zeros(tuple(shape))
- self.mpi_type_diff_l[d] = HYSOP_MPI_REAL.Create_subarray(
+ self.mpi_type_diff_l[d] = hysop.core.mpi_REAL.Create_subarray(
shape, shape_b, start_l, order=ORDERMPI)
self.mpi_type_diff_l[d].Commit()
- self.mpi_type_diff_r[d] = HYSOP_MPI_REAL.Create_subarray(
+ self.mpi_type_diff_r[d] = hysop.core.mpi_REAL.Create_subarray(
shape, shape_b, start_r, order=ORDERMPI)
self.mpi_type_diff_r[d].Commit()
self._to_recv_buf[d] = self.cl_env.global_allocation(_to_recv)
@@ -136,11 +136,11 @@ class GPUDiffusion(DiscreteOperator, GPUOperator):
self._compute = self._compute_diffusion
self._mesh_size = npw.ones(4, dtype=self.gpu_precision)
- self._mesh_size[:self.dim] = self._reorderVect(topo.mesh.space_step)
+ self._mesh_size[:self.dim] = topo.mesh.space_step
shape = topo.mesh.resolution
resol = shape.copy()
self.resol_dir = npw.dim_ones((self.dim,))
- self.resol_dir[:self.dim] = self._reorderVect(shape)
+ self.resol_dir[:self.dim] = shape
self._append_size_constants(resol)
src, tile_size, nb_part_per_wi, vec, f_space = \
@@ -151,7 +151,7 @@ class GPUDiffusion(DiscreteOperator, GPUOperator):
build_options += " -D NB_PART=" + str(nb_part_per_wi)
build_options += " -D L_WIDTH=" + str(tile_size / nb_part_per_wi)
for d in xrange(self.dim):
- build_options += " -D CUT_DIR" + S_DIR[d] + "="
+ build_options += " -D CUT_DIR" + DirectionLabels[d] + "="
build_options += str(1 if topo.shape[d] > 1 else 0)
gwi, lwi, blocs_nb = f_space(self.field.data[0].shape,
@@ -159,9 +159,9 @@ class GPUDiffusion(DiscreteOperator, GPUOperator):
build_options += " -D NB_GROUPS_I={0}".format(blocs_nb[0])
build_options += " -D NB_GROUPS_II={0}".format(blocs_nb[1])
prg = self.cl_env.build_src(src, build_options, vec)
- self.num_diffusion = KernelLauncher(
+ self.num_diffusion = OpenClKernelLauncher(
prg.diffusion, self.cl_env.queue, gwi, lwi)
- self.copy = KernelLauncher(cl.enqueue_copy,
+ self.copy = OpenClKernelLauncher(cl.enqueue_copy,
self.cl_env.queue)
def _compute_diffusion(self, simulation):
diff --git a/hysop/gpu/gpu_discrete.py b/hysop/old/gpu.old/gpu_discrete.py
similarity index 83%
rename from hysop/gpu/gpu_discrete.py
rename to hysop/old/gpu.old/gpu_discrete.py
index 16d11c6a8c1f9e400209b36fa8e19c30298e0aec..ab7d58b68996a1fd706addba29e4de4e2d75d065 100644
--- a/hysop/gpu/gpu_discrete.py
+++ b/hysop/old/gpu.old/gpu_discrete.py
@@ -1,14 +1,11 @@
-"""
-@file gpu_discrete.py
-
-Contains class for discrete fields on GPU.
+"""Discrete field defined on device (GPU)
"""
from hysop import __VERBOSE__
from hysop.constants import ORDER, np,\
- debug, HYSOP_REAL, S_DIR
+ debug, HYSOP_REAL, DirectionLabels
from hysop.fields.discrete import DiscreteField
-from hysop.gpu import cl, CL_PROFILE
-from hysop.gpu.gpu_kernel import KernelLauncher, KernelListLauncher
+from hysop.backend.device.opencl import cl, CL_PROFILE
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher, KernelListLauncher
from hysop.tools.profiler import FProfiler
fromLayoutMgrFunc_3D_seq = [
@@ -68,57 +65,66 @@ toLayoutMgrFunc_1D = [
]
-class GPUDiscreteField(DiscreteField):
- """
- GPU Discrete vector field implementation.
+class OpenClDiscreteField(DiscreteField):
+ """GPU Discrete vector field implementation.
Allocates OpenCL device memory for the field.
"""
def __init__(self, cl_env, topology=None, is_vector=False, name="?",
precision=HYSOP_REAL, layout=True, simple_layout=False):
+ """GPU Discrete vector field implementation.
+ Allocates OpenCL device memory for the field.
+
+ Parameters
+ ----------
+
+ queue : OpenCL queue
+ topology : :class:`~hysop.core.mpi.topology.Cartesian`, optional
+ mpi topology and local meshes info
+ precision : np type, optional
+ Floating point precision,
+ default=:data:`~hysop.constants.HYSOP_REAL`
+ is_vector: boolean, optional
+ true if parent field is a vector field, default=False
+ name : string, optional
+ Field name
+ layour : boolean, optional
+ indicates if components are arranged in memory, default=True
+ i.e. all components are considered in the same way.
+ simple_layout : boolean, optional
+ indicates if in the Z direction, layout is ZYX (simple) or ZXY.
"""
- Constructor.
- @param queue : OpenCL queue
- @param precision : Floating point precision
- @param parent : Continuous field.
- @param topology : Topology informations
- @param name : Field name
- @param idFromParent : Index in the parent's discrete fields
- @param layout : Boolean indicating if components are rearranged in memory
- Default : all components are considered in the same way.
- @param simple_layout : Boolean indicating if in the Z direction,
- layout is ZYX (simple) or ZXY.
- @see hysop.fields.vector.VectorField.__init__
- """
- super(GPUDiscreteField, self).__init__(topology, is_vector, name)
- ## OpenCL environment
+ # init base class
+ super(OpenClDiscreteField, self).__init__(topology, is_vector, name)
+ # OpenCL environment
self.cl_env = cl_env
- ## Precision for the field
+ # Precision for the field
self.precision = precision
- ## Memory used
+ # Memory used
self.mem_size = 0
- ## Initialization OpenCL kernel as KernelLauncher
+ ## Initialization OpenCL kernel as OpenClKernelLauncher
self.init_kernel = None
self._isReleased = False
## OpenCL Buffer pointer
self.gpu_data = [None] * self.nb_components
- ## Is the device allocations are performed
+ # True if device allocations have been done,
+ # (self.allocate call)
self.gpu_allocated = False
## OpenCL Events list modifying this field
self.events = []
- # Get the process number involved in this field discretisation
- # By default, all mpi process are take, otherwise, user create and
- # gives his own topologies.
+ # Get the ids of processes involved in the field discretisation.
+ # Default = all, otherwise, get info from input topology if given.
if topology is None:
- from hysop.mpi import main_rank
+ from hysop.core.mpi import main_rank
self._rank = main_rank
else:
self._rank = topology.rank
- ## Data layout is direction dependant
+ # Data layout is direction dependant
self.layout = layout
- ## Layout for the Z direction
+ # Layout for the Z direction
self.simple_layout = simple_layout
+
## Layout and shape managers
dim = self.domain.dimension
if dim == 3:
@@ -144,12 +150,13 @@ class GPUDiscreteField(DiscreteField):
self.profiler += FProfiler("Transfer_to_host")
self.profiler += FProfiler("Transfer_to_device")
- ## Transfer size counter (to device)
+
+ # Transfer size counter (to device)
self.to_dev_size = 0.
- ## Transfer size counter (to host)
+ # Transfer size counter (to host)
self.to_host_size = 0.
- ## Temporary cpu buffer to change data layout between cpu ang gpu
+ # Temporary cpu buffer to change data layout between cpu ang gpu
self.host_data_pinned = [None, ] * self.nb_components
def allocate(self):
@@ -157,9 +164,12 @@ class GPUDiscreteField(DiscreteField):
if not self.gpu_allocated:
evt = [None, ] * self.nb_components
for d in xrange(self.nb_components):
+ # convert data to required precision
self.data[d] = np.asarray(self.data[d],
dtype=self.precision, order=ORDER)
+ # create on-device buffer
self.gpu_data[d] = self.cl_env.global_allocation(self.data[d])
+ # update memory counter
self.mem_size += self.gpu_data[d].size
self.host_data_pinned[d], evt[d] = cl.enqueue_map_buffer(
self.cl_env.queue,
@@ -190,9 +200,9 @@ class GPUDiscreteField(DiscreteField):
@param layout : Boolean indicating if components are arranged in memory
@param simple_layout : Boolean indicating if in the Z direction,
"""
- if not isinstance(vfield, GPUDiscreteField):
+ if not isinstance(vfield, OpenClDiscreteField):
vfield.__class__ = cls
- GPUDiscreteField.__init__(
+ OpenClDiscreteField.__init__(
vfield, cl_env,
vfield.topology, vfield.nb_components > 1, vfield.name,
precision, layout, simple_layout)
@@ -200,7 +210,7 @@ class GPUDiscreteField(DiscreteField):
def setInitializationKernel(self, kernel):
"""
Set the initialization kernel
- @param kernel : KernelLauncher to use for initialize field.
+ @param kernel : OpenClKernelLauncher to use for initialize field.
"""
self.init_kernel = kernel
@@ -237,7 +247,7 @@ class GPUDiscreteField(DiscreteField):
t = self.precision(time)
if __VERBOSE__:
print "{" + str(self._rank) + "}", "Initialize", self.name
- isGPUKernel = isinstance(formula, KernelLauncher) \
+ isGPUKernel = isinstance(formula, OpenClKernelLauncher) \
or isinstance(formula, KernelListLauncher)
if not isGPUKernel and self.init_kernel is None:
DiscreteField.initialize(self, formula, False, time, *args)
@@ -329,7 +339,7 @@ class GPUDiscreteField(DiscreteField):
layoutDir = 0
if __VERBOSE__:
print "{" + str(self._rank) + "}", "host->device :", \
- self.name, S_DIR[d], layoutDir
+ self.name, DirectionLabels[d], layoutDir
self.host_data_pinned[d][...] = \
self._toLayoutMgrFunc[layoutDir](self.data[d])
evt[d_id] = cl.enqueue_copy(
@@ -345,11 +355,12 @@ class GPUDiscreteField(DiscreteField):
if e is not None:
e.wait()
time += (e.profile.end - e.profile.start) * 1e-9
- self.profiler['Transfer_to_device'] += time
- if __VERBOSE__ and CL_PROFILE:
- print self.mem_size, "Bytes transfered at ",
- print "{0:.3f} GBytes/sec".format(
- mem_transfered / (time * 1024 ** 3))
+ self.profiler['Transfer_to_device'] += time
+
+ if __VERBOSE__ and time!=0:
+ print self.mem_size/(1024**2), "MBytes transfered at ",
+ print "{0:.3f} GBytes/sec".format(
+ mem_transfered / (time * 1024 ** 3))
def to_host(self, component=None, layoutDir=None):
"""
@@ -381,7 +392,7 @@ class GPUDiscreteField(DiscreteField):
layoutDir = 0
if __VERBOSE__:
print "{" + str(self._rank) + "}", "device->host :", \
- self.name, S_DIR[d], layoutDir
+ self.name, DirectionLabels[d], layoutDir
evt[d_id] = cl.enqueue_copy(self.cl_env.queue,
self.host_data_pinned[d],
self.gpu_data[d],
@@ -403,9 +414,8 @@ class GPUDiscreteField(DiscreteField):
e.wait()
time += (e.profile.end - e.profile.start) * 1e-9
self.profiler['Transfer_to_host'] += time
- if __VERBOSE__:
- if CL_PROFILE:
- print self.mem_size, "Bytes transfered at ",
+ if __VERBOSE__ and time!=0:
+ print self.mem_size/(1024**2), "MBytes transfered at ",
print "{0:.3f} GBytes/sec".format(
mem_transfered / (time * 1024 ** 3))
diff --git a/hysop/gpu/gpu_kernel.py b/hysop/old/gpu.old/gpu_kernel.py
similarity index 87%
rename from hysop/gpu/gpu_kernel.py
rename to hysop/old/gpu.old/gpu_kernel.py
index c2ab202340ca684c9d8e1937f7743ff8c2afc087..7107623728ff2193154637f5bd6c6d8fafed219f 100644
--- a/hysop/gpu/gpu_kernel.py
+++ b/hysop/old/gpu.old/gpu_kernel.py
@@ -1,25 +1,29 @@
"""
-@file gpu_kernel.py
"""
-from hysop.constants import debug, S_DIR
+from hysop.constants import debug, DirectionLabels
from hysop import __VERBOSE__, __DEBUG__
-from hysop.gpu import cl, CL_PROFILE
+from hysop.backend.device.opencl import cl, CL_PROFILE
from hysop.tools.profiler import FProfiler
+
class KernelListLauncher(object):
- """
- OpenCL kernel list launcher.
+ """OpenCL kernel list launcher.
Manage launching of OpenCL kernels as a list.
"""
@debug
def __init__(self, kernel, queue, gsize, lsize=None):
- """
- Create a kernel list launcher.
- @param kernel : kernel list.
- @param queue : OpenCL command queue.
- @param gsize : OpenCL global size index.
- @param lsize : OpenCL local size index.
+ """Create a kernel list launcher.
+
+ Parameters
+ ----------
+
+ kernel : list
+ queue : OpenCL command queue
+ gsize : int
+ OpenCL global size index.
+ lsize : int, optional
+ OpenCL local size index.
"""
## OpenCL Kernel list
self.kernel = kernel
@@ -40,7 +44,7 @@ class KernelListLauncher(object):
for k in self.kernel]
else:
self.profile = [
- FProfiler("OpenCL_" + k.function_name + S_DIR[d])
+ FProfiler("OpenCL_" + k.function_name + DirectionLabels[d])
for d, k in enumerate(self.kernel)]
else:
self.profile = []
@@ -81,11 +85,11 @@ class KernelListLauncher(object):
"""
if __VERBOSE__:
try:
- print "OpenCL kernel:", self.kernel[d].function_name, d, args[0], args[1]
+ print ' ',self.kernel[d].function_name, d, args[0], args[1]
# print "\targs: ",args[2:]
# print "\tkwargs: ", kwargs
except AttributeError:
- print "OpenCL kernel:", self.kernel[d].__name__
+ print ' ', self.kernel[d].__name__
evt = self.kernel[d](self.queue, *args, **kwargs)
if CL_PROFILE:
evt.wait()
@@ -119,7 +123,7 @@ class KernelListLauncher(object):
for d in xrange(len(self.kernel))]
-class KernelLauncher(KernelListLauncher):
+class OpenClKernelLauncher(KernelListLauncher):
"""
OpenCL kernel launcher.
@@ -129,7 +133,7 @@ class KernelLauncher(KernelListLauncher):
@debug
def __init__(self, kernel, queue, gsize=None, lsize=None):
"""
- Create a KernelLauncher.
+ Create a OpenClKernelLauncher.
Create a KernelListLauncher with a list of one kernel.
diff --git a/hysop/gpu/gpu_multiphase_baroclinic_rhs.py b/hysop/old/gpu.old/gpu_multiphase_baroclinic_rhs.py
similarity index 94%
rename from hysop/gpu/gpu_multiphase_baroclinic_rhs.py
rename to hysop/old/gpu.old/gpu_multiphase_baroclinic_rhs.py
index 32ce524cb79d6d3d97db0945f2bc04d5495a1ed4..ac9924b80f04e257194ae485e030bb9be2d57d48 100644
--- a/hysop/gpu/gpu_multiphase_baroclinic_rhs.py
+++ b/hysop/old/gpu.old/gpu_multiphase_baroclinic_rhs.py
@@ -3,18 +3,18 @@
Multiscale baroclinic term on GPU
"""
-from hysop.constants import debug, np, S_DIR, HYSOP_MPI_REAL, ORDERMPI, \
+from hysop.constants import debug, np, DirectionLabels, hysop.core.mpi_REAL, ORDERMPI, \
HYSOP_REAL, ORDER
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.operator.discrete.discrete import get_extra_args_from_method
-from hysop.gpu import cl
-from hysop.gpu.gpu_operator import GPUOperator
-from hysop.gpu.gpu_kernel import KernelListLauncher
-from hysop.gpu.gpu_discrete import GPUDiscreteField
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.gpu_operator import GPUOperator
+from hysop.backend.device.opencl.opencl_kernel import KernelListLauncher
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
from hysop.tools.profiler import FProfiler
-from hysop.mpi import Wtime
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.core.mpi import Wtime
+from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4
@@ -74,8 +74,8 @@ class BaroclinicRHS(DiscreteOperator, GPUOperator):
# GPU allocation.
for field in self.variables:
- alloc = not isinstance(field, GPUDiscreteField)
- GPUDiscreteField.fromField(self.cl_env, field,
+ alloc = not isinstance(field, OpenClDiscreteField)
+ OpenClDiscreteField.fromField(self.cl_env, field,
self.gpu_precision, layout=False)
if not field.gpu_allocated:
field.allocate()
@@ -103,7 +103,7 @@ class BaroclinicRHS(DiscreteOperator, GPUOperator):
if 0 in self._cutdir_list:
raise ValueError("Not yet implemented with comm in X dir")
for d in self._cutdir_list:
- if self.method[SpaceDiscretisation] == FDC4:
+ if self.method[SpaceDiscretization] == FDC4:
gh = 2
else:
gh = 1
@@ -120,10 +120,10 @@ class BaroclinicRHS(DiscreteOperator, GPUOperator):
# _to_recv[..., 1] contains [..., -1] data (left ghosts)
self._to_send[d] = npw.zeros(tuple(shape))
_to_recv = npw.zeros(tuple(shape))
- self.mpi_type_diff_l[d] = HYSOP_MPI_REAL.Create_subarray(
+ self.mpi_type_diff_l[d] = hysop.core.mpi_REAL.Create_subarray(
shape, shape_b, start_l, order=ORDERMPI)
self.mpi_type_diff_l[d].Commit()
- self.mpi_type_diff_r[d] = HYSOP_MPI_REAL.Create_subarray(
+ self.mpi_type_diff_r[d] = hysop.core.mpi_REAL.Create_subarray(
shape, shape_b, start_r, order=ORDERMPI)
self.mpi_type_diff_r[d].Commit()
self._to_recv_buf[d] = self.cl_env.global_allocation(_to_recv)
@@ -219,10 +219,10 @@ class BaroclinicRHS(DiscreteOperator, GPUOperator):
build_options += " -D F_TILE_SIZE=" + str(tile_size_f)
build_options += " -D N_PER_CELL=" + str(pts_per_cell)
for d in xrange(self.dim):
- build_options += " -D CUT_DIR" + S_DIR[d] + "="
+ build_options += " -D CUT_DIR" + DirectionLabels[d] + "="
build_options += str(1 if topo_coarse.shape[d] > 1 else 0)
build_options += " -D FD_ORDER=" + \
- str(self.method[SpaceDiscretisation].__name__)
+ str(self.method[SpaceDiscretization].__name__)
build_options += " -D GRADP_COMP=__GRADP_COMPONENT__"
macros = {'__USER_DENSITY_FUNCTION_FROM_GIVEN_INPUT__':
get_extra_args_from_method(self, 'density_func', 'x')}
diff --git a/hysop/gpu/gpu_multiresolution_filter.py b/hysop/old/gpu.old/gpu_multiresolution_filter.py
similarity index 95%
rename from hysop/gpu/gpu_multiresolution_filter.py
rename to hysop/old/gpu.old/gpu_multiresolution_filter.py
index c2f77984fb1ba43e43408179f8590c3bd6d7412d..3597822cdd2dae38fb99ff2175224924a0cdad08 100644
--- a/hysop/gpu/gpu_multiresolution_filter.py
+++ b/hysop/old/gpu.old/gpu_multiresolution_filter.py
@@ -4,13 +4,13 @@ Filter values from a fine grid to a coarse grid.
GPU version.
"""
from hysop.constants import debug, np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.operator.discrete.multiresolution_filter import FilterFineToCoarse
-from hysop.gpu.gpu_operator import GPUOperator
+from hysop.backend.device.opencl.gpu_operator import GPUOperator
from hysop.operator.discrete.discrete import get_extra_args_from_method
-from hysop.gpu.gpu_discrete import GPUDiscreteField
-from hysop.gpu.gpu_kernel import KernelLauncher
-from hysop.methods_keys import Remesh
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.methods import Remesh
class GPUFilterFineToCoarse(FilterFineToCoarse, GPUOperator):
@@ -38,16 +38,16 @@ class GPUFilterFineToCoarse(FilterFineToCoarse, GPUOperator):
**kwds)
#GPU allocations
- alloc = not isinstance(self.field_in[0], GPUDiscreteField)
- GPUDiscreteField.fromField(self.cl_env, self.field_in[0],
+ alloc = not isinstance(self.field_in[0], OpenClDiscreteField)
+ OpenClDiscreteField.fromField(self.cl_env, self.field_in[0],
self.gpu_precision, layout=False)
if not self.field_in[0].gpu_allocated:
self.field_in[0].allocate()
if alloc:
self.size_global_alloc += self.field_in[0].mem_size
- alloc = not isinstance(self.field_out[0], GPUDiscreteField)
- GPUDiscreteField.fromField(self.cl_env, self.field_out[0],
+ alloc = not isinstance(self.field_out[0], OpenClDiscreteField)
+ OpenClDiscreteField.fromField(self.cl_env, self.field_out[0],
self.gpu_precision, layout=False)
if not self.field_out[0].gpu_allocated:
self.field_out[0].allocate()
@@ -122,9 +122,9 @@ class GPUFilterFineToCoarse(FilterFineToCoarse, GPUOperator):
build_options += " -D WG=" + str(lwi[0])
build_options += " -D FORMULA=" + self.method[Remesh].__name__.upper()
prg = self.cl_env.build_src(src, build_options, vec)
- self.fine_to_coarse = KernelLauncher(
+ self.fine_to_coarse = OpenClKernelLauncher(
prg.coarse_to_fine_filter, self.cl_env.queue, gwi, lwi)
- self.initialize = KernelLauncher(
+ self.initialize = OpenClKernelLauncher(
prg.initialize_output, self.cl_env.queue,
self.field_out[0].data[0].shape, None)
self._evts = [None, ] * self.field_in[0].dimension
diff --git a/hysop/gpu/gpu_operator.py b/hysop/old/gpu.old/gpu_operator.py
similarity index 50%
rename from hysop/gpu/gpu_operator.py
rename to hysop/old/gpu.old/gpu_operator.py
index 35287a45da42313c5f8525ae8d6c3cb6cad70bcc..1acb420418f12abf7af2d6aa7afada1b677c13d1 100644
--- a/hysop/gpu/gpu_operator.py
+++ b/hysop/old/gpu.old/gpu_operator.py
@@ -1,39 +1,66 @@
-"""
-@file gpu_operator.py
+"""Abstract class providing a common interface to all
+discrete operators working on GPU.
+
+* :class:`~hysop.gpu_operator.GPUOperator` is an abstract class
+ used to provide a common interface to all discrete operators
+ working on GPU.
+ See for example :class:`~hysop.gpu.gpu_diffusion.GPUDiffusion` or
+ :class:`~hysop.gpu.gpu_particle_advection.GPUParticleAdvection`.
-Discrete operator for GPU architecture.
"""
from abc import ABCMeta
-from hysop.constants import HYSOP_REAL, S_DIR
-from hysop.methods_keys import Precision
-from hysop.gpu.tools import get_opencl_environment
-
+from hysop.constants import HYSOP_REAL, DirectionLabels
+from hysop.backend.device.opencl.opencl_tools import get_opencl_environment
+from hysop.methods import ExtraArgs
+from hysop.operator.discrete.discrete import get_extra_args_from_method
+from hysop.backend.device.kernel_config import KernelConfig
+from hysop.methods import Precision
class GPUOperator(object):
- """
- Abstract class for GPU operators.
-
- In practice, discrete operators must inherit from the classic
- version and this abstract layer.
+ """Abstract class for discrete operators working on GPU.
"""
__metaclass__ = ABCMeta
def __init__(self, platform_id=None, device_id=None, device_type=None,
- direction=None, **kwds):
-
+ direction=None, gpu_precision=HYSOP_REAL, **kwds):
"""
Create the common attributes of all GPU discrete operators.
All in this interface is independant of a discrete operator.
- @param platform_id : OpenCL platform id (default = 0).
- @param device_id : OpenCL device id (default = 0).
- @param device_type : OpenCL device type (default = 'gpu').
+ Parameters
+ ----------
+ direction : int
+ leading direction of work (for example advection dir)
+ platform_id : int, optional
+ OpenCL id, default = 0.
+ device_id : int, optional
+ OpenCL id, default = 0.
+ device_type : string, optional.
+ OpenCL selected device, default = 'gpu'.
+ gpu_precision : numpy.dtype, optional
+ floating precision for gpu, default=HYSOP_REAL
"""
+
+ super(GPUOperator, self).__init__(**kwds)
## real type precision on GPU
- self.gpu_precision = HYSOP_REAL
- if 'method' in kwds and Precision in kwds['method'].keys():
- self.gpu_precision = kwds['method'][Precision]
+ self.gpu_precision = gpu_precision
+ if 'method' in kwds:
+ method = kwds['method']
+ assert (method is not None)
+
+ if Precision in method:
+ self.gpu_precision = method[Precision]
+
+ if KernelConfig in method:
+ config = method[KernelConfig]
+ platform_id = config.platform_id
+ device_id = config.device_id
+ device_type = config.device_type
+ elif ExtraArgs in method:
+ platform_id = get_extra_args_from_method(self,'platform_id',platform_id)
+ device_id = get_extra_args_from_method(self,'device_id',device_id)
+ device_type = get_extra_args_from_method(self,'device_type',device_type)
# Initialize opencl environment
comm_ref = self.variables[0].topology.comm
@@ -69,38 +96,42 @@ class GPUOperator(object):
else:
msg = 'Dimension {} not implemented yet!'.format(dim)
raise NotImplementedError(msg)
-
- self._reorder_vect = _reorder_vect
+ self._reorder_vect = _reorder_vect
+
self.dim = dim
self.direction = direction
# Size constants for local mesh size
self._size_constants = ''
- # Try to load kernel condfigurations
+ # Try to load kernel configurations
try:
self._kernel_cfg = \
self.cl_env.kernels_config[self.dim][self.gpu_precision]
except:
self._kernel_cfg = None
- self._num_locMem = None
-
- ## Global memory allocated on gpu by this operator
+ # Global memory allocated on gpu by this operator
self.size_global_alloc = 0
- ## Local memory allocated on gpu by this operator
+ # Local memory allocated on gpu by this operator
self.size_local_alloc = 0
+
+ self._num_locMem = None
def _append_size_constants(self, values, prefix='NB', suffix=None):
- """
- Append to the string containing the constants for building kernels.
- @param values : values to add
- @param prefix : prefix of variables names
- @param suffix : suffix of variables names
+ """Append to the string containing the constants for building kernels.
+
+ Parameters
+ ----------
+ values : list
+ prefix : string, optional
+ suffix : list of strings, optional
+ directions, default = `hysop.constants.DirectionLabels`.
"""
if suffix is None:
- suffix = S_DIR
+ suffix = DirectionLabels
assert len(values) <= len(suffix), str(values) + str(suffix)
for v, s in zip(values, suffix):
self._size_constants += " -D " + prefix + s + "=" + str(v)
+
diff --git a/hysop/old/gpu.old/gpu_particle_advection.py b/hysop/old/gpu.old/gpu_particle_advection.py
new file mode 100644
index 0000000000000000000000000000000000000000..da69ab227e56238b4ce6ce57b7687c3944f9758a
--- /dev/null
+++ b/hysop/old/gpu.old/gpu_particle_advection.py
@@ -0,0 +1,781 @@
+"""Discrete advection for GPU
+"""
+from abc import abstractmethod, ABCMeta
+from hysop import __VERBOSE__
+from hysop.constants import np, debug, DirectionLabels, HYSOP_REAL
+from hysop.methods import TimeIntegrator, Remesh, \
+ Support, Splitting, MultiScale, Precision
+from hysop.numerics.odesolvers import Euler
+from hysop.operator.discrete.particle_advection import ParticleAdvection
+from hysop.operator.discrete.discrete import get_extra_args_from_method
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+import hysop.default_methods as default
+from hysop.tools.numpywrappers import npw
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
+from hysop.backend.device.opencl.gpu_operator import GPUOperator
+from hysop.tools.profiler import profile
+from hysop.numerics.update_ghosts import UpdateGhostsFull
+from hysop.tools.misc import WorkSpaceTools
+
+
+class GPUParticleAdvection(ParticleAdvection, GPUOperator):
+ """Particle advection solver on GPU
+
+ """
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, **kwds):
+ """Particular advection of field(s) in a given direction,
+ on GPU.
+
+ OpenCL kernels are build once per dimension in order to handle
+ directional splitting with resolution non uniform in directions.
+
+ Parameters
+ ----------
+ kwds : base classes parameters
+
+ Note
+ ----
+ * warning : this operator is derived from ParticleAdvection AND
+ GPUOperator. kwds must then handle argument of both classes.
+ """
+ # Set default method if unknown
+ if 'method' not in kwds:
+ kwds['method'] = default.ADVECTION
+ kwds['method'][Support] = 'gpu_2k'
+
+ # init base class (i.e. ParticleAdvection)
+ super(GPUParticleAdvection, self).__init__(**kwds)
+
+ # mpi comm is set to advected field topology communicator.
+ self.fields_topo = self.fields_on_grid[0].topology
+ self._comm = self.fields_topo.comm
+ self._comm_size = self._comm.Get_size()
+ self._comm_rank = self._comm.Get_rank()
+ assert self._comm == self.velocity.topology.comm
+
+ # init second base class (i.e GPUOperator)
+ if Precision in self.method:
+ gpu_precision = self.method[Precision]
+ else:
+ gpu_precision = None
+ GPUOperator.__init__(
+ self, topology=self.velocity.topology,
+ direction=self.direction,
+ platform_id=get_extra_args_from_method(self, 'platform_id', None),
+ device_id=get_extra_args_from_method(self, 'device_id', None),
+ device_type=get_extra_args_from_method(self, 'device_type', None),
+ gpu_precision=gpu_precision)
+
+ # Choose between one kernel for all operations (default) ...
+ self._use_2_kernels = False
+ if self.method[Support].find('gpu_2k') >= 0:
+ # ... or two different kernels for advection and remesh
+ self._use_2_kernels = True
+
+ self._synchronize = None
+ self._isMultiScale = False
+ if MultiScale in self.method and self.method[MultiScale] is not None:
+ self._isMultiScale = True
+ self._synchronize = UpdateGhostsFull(
+ self.velocity.topology, self.velocity.nb_components)
+
+ # Compute resolutions for kernels for each direction.
+ # Resolution of the local mesh but reoganized regarding
+ # splitting direction:
+ # direction X : XYZ
+ # direction Y : YXZ
+ # direction Z : ZYX in parallel, ZXY in sequentiel.
+ self.resol_dir = npw.dim_ones((self._dim,))
+ self.v_resol_dir = npw.dim_ones((self._dim,))
+ shape = self.fields_topo.mesh.resolution
+ v_shape = self.velocity.topology.mesh.resolution
+ # Local mesh resolution
+ self.resol_dir[:self._dim] = self._reorderVect(shape)
+ self.v_resol_dir[:self._dim] = self._reorderVect(v_shape)
+ self._init_size_constants()
+
+ # Init mesh info
+ self._cl_mesh_info = None
+ self._init_cl_mesh_info()
+
+ # user defined opencl sources
+ self.prg = None
+ # get extra (opencl kernels) files from method, if any
+ self._collect_usr_cl_src()
+
+ # Set copy kernel
+ self.copy = self._collect_kernels_cl_src_copy()
+
+ # Set transposition kernels
+ self.transpose_xy, self.transpose_xy_r = None, None
+ self.transpose_xz, self.transpose_xz_r = None, None
+ self._collect_kernels_cl_src_transpositions_xy()
+ if self._dim == 3:
+ self._collect_kernels_cl_src_transpositions_xz()
+
+ # Set advection and remesh kernels
+ self.num_advec, self.num_remesh = None, None
+ self.num_advec_and_remesh = None
+ if self._use_2_kernels:
+ self._collect_kernels_cl_src_2k()
+ self._compute = self._compute_2k
+ else:
+ self._collect_kernels_cl_src_1k()
+ if self._isMultiScale:
+ self._compute = self._compute_1k_multiechelle
+ else:
+ if self.method[TimeIntegrator] is Euler:
+ self._compute = self._compute_1k_euler_simpleechelle
+ else:
+ self._compute = self._compute_1k_simpleechelle
+
+ self._buffer_allocations()
+ if self.direction == 0:
+ self._buffer_initialisations()
+
+ # List of executions
+ self.exec_list = None
+ self._build_exec_list()
+
+ # Particle initialisation OpenCL events for each field:
+ self._init_events = {self.fields_on_grid[0]: []}
+
+ def _init_size_constants(self):
+ """Fill size_constants attribute in
+ (_size_constant belongs to gpu_operator)
+ """
+ v_shape = self.velocity.topology.mesh.resolution
+ f_shape = self.fields_topo.mesh.resolution
+ self._append_size_constants(f_shape)
+ self._append_size_constants(v_shape, prefix='V_NB')
+ self._append_size_constants(
+ [self.velocity.topology.ghosts()[self.direction]],
+ prefix='V_GHOSTS_NB', suffix=[''])
+ enum = ['I', 'II', 'III']
+ self._append_size_constants(
+ self._reorderVect(['NB' + d for d in DirectionLabels[:self._dim]]),
+ prefix='NB_', suffix=enum[:self._dim])
+ self._append_size_constants(
+ self._reorderVect(['V_NB' + d for d in DirectionLabels[:self._dim]]),
+ prefix='V_NB_', suffix=enum[:self._dim])
+
+ def _init_cl_mesh_info(self):
+ """Collect mesh info from fields and velocity,
+ set and send opencl buffer (self._cl_mesh_info) to device.
+ """
+ # Space step for fields
+ mesh_size = npw.ones(4, dtype=self.gpu_precision)
+ mesh_size[:self._dim] = self._reorderVect(
+ self.fields_topo.mesh.space_step)
+
+ # Space step for velocity
+ self._v_mesh_size = npw.ones(4, dtype=self.gpu_precision)
+ self._v_mesh_size[:self._dim] = self._reorderVect(
+ self.velocity.topology.mesh.space_step)
+
+ mesh_info = npw.ones((12, ), dtype=self.gpu_precision)
+ mesh_info[:4] = mesh_size
+ mesh_info[4:8] = self._v_mesh_size
+ # Coordinate of the local origin in advection dir.
+ mesh_info[8] = self.fields_topo.mesh.origin[self.direction]
+ mesh_info[9] = 1. / mesh_size[0]
+ mesh_info[10] = 1. / self._v_mesh_size[0]
+ assert mesh_size.dtype == self.gpu_precision
+ # returns an opencl buffer
+ self._cl_mesh_info = cl.Buffer(self.cl_env.ctx, cl.mem_flags.READ_ONLY,
+ size=mesh_info.nbytes)
+ cl.enqueue_write_buffer(self.cl_env.queue,
+ self._cl_mesh_info, mesh_info).wait()
+
+ def _set_work_arrays(self, rwork=None, iwork=None):
+
+ topo = self.fields_on_grid[0].topology
+ # Find number and shape of required work arrays
+ # For GPU version, no need of numerics works
+ # Shape of reference comes from fields, not from velocity
+ rwork_length = np.sum([f.nb_components for f in self.fields_on_grid])
+ if self.method[Support].find('gpu_2k') >= 0:
+ rwork_length += 1 # work array for positions
+
+ # check and/or allocate work arrays according to properties above
+ subshape = tuple(topo.mesh.resolution)
+ self._rwork = WorkSpaceTools.check_work_array(rwork_length, subshape,
+ rwork, HYSOP_REAL)
+
+ @abstractmethod
+ def global_memory_usage(self, v_shape, shape):
+ """Returns an estimation of memory usage
+
+ Parameters
+ ----------
+ v_shape, shape : tuples
+ shapes of the velocity and advected fields
+ """
+ pass
+
+ def _build_exec_list(self):
+ """Prepare GPU kernels sequence
+ """
+ # Build execution list regarding splitting:
+ # Splitting Strang 2nd order:
+ # 3D: X(dt/2), Y(dt/2), Z(dt), Y(dt/2), X(dt/2)
+ # 2D: X(dt/2), Y(dt), X(dt/2)
+ if self.method[Splitting] == 'o2':
+ if self._dim == 2:
+ self.exec_list = [
+ [self._init_copy, self._compute], # X(dt/2)
+ [self._init_transpose_xy, self._compute], # Y(dt)
+ [self._init_transpose_xy, self._compute] # X(dt/2)
+ ]
+ elif self._dim == 3:
+ self.exec_list = [
+ [self._init_copy, self._compute], # X(dt/2)
+ [self._init_transpose_xy, self._compute], # Y(dt/2)
+ [self._init_transpose_xz, self._compute], # Z(dt)
+ [self._init_transpose_xz, self._compute], # Y(dt/2)
+ [self._init_transpose_xy, self._compute] # X(dt/2)
+ ]
+
+ # Splitting Strang 2nd order (fullHalf):
+ # X(dt/2), Y(dt/2), Z(dt/2), Z(dt/2), Y(dt/2), X(dt/2)
+ elif self.method[Splitting] == 'o2_FullHalf':
+ if self._dim == 2:
+ self.exec_list = [
+ [self._init_copy, self._compute], # X(dt/2)
+ [self._init_transpose_xy, self._compute], # Y(dt)
+ [self._init_copy, self._compute], # Y(dt)
+ [self._init_transpose_xy, self._compute] # X(dt/2)
+ ]
+ elif self._dim == 3:
+ self.exec_list = [
+ [self._init_copy, self._compute], # X(dt/2)
+ [self._init_transpose_xy, self._compute], # Y(dt/2)
+ [self._init_transpose_xz, self._compute], # Z(dt/2)
+ [self._init_copy, self._compute], # Z(dt/2)
+ [self._init_transpose_xz, self._compute], # Y(dt/2)
+ [self._init_transpose_xy, self._compute] # X(dt/2)
+ ]
+ elif self.method[Splitting] == 'x_only':
+ self.exec_list = [
+ [self._init_copy, self._compute], # X(dt)
+ #[self._init_copy, self._init_copy_r], # X(dt)
+ ]
+ else:
+ raise ValueError('Splitting type not yet implemeted on GPU: ' +
+ self.method[Splitting])
+
+ def global_memory_usage(self, v_shape, shape):
+ if self._use_2_kernels:
+ r = (self.velocity.nb_components * v_shape.prod() +
+ (2 * self.fields_on_grid[0].nb_components + 1) * shape.prod())
+ else:
+ r = (self.velocity.nb_components * v_shape.prod() +
+ 2 * self.fields_on_grid[0].nb_components * shape.prod())
+ return r * self.cl_env.prec_size
+
+ def _configure_numerical_methods(self):
+ pass
+
+ def _buffer_allocations(self):
+ """Allocate OpenCL buffers for velocity and advected field.
+ """
+ # Velocity.
+ alloc = not isinstance(self.velocity, OpenClDiscreteField)
+ OpenClDiscreteField.fromField(self.cl_env, self.velocity,
+ self.gpu_precision, simple_layout=False)
+ if alloc:
+ self.size_global_alloc += self.velocity.mem_size
+
+ # Transported field.
+ alloc = not isinstance(self.fields_on_grid[0], OpenClDiscreteField)
+ OpenClDiscreteField.fromField(self.cl_env,
+ self.fields_on_grid[0],
+ self.gpu_precision,
+ layout=False)
+ if alloc:
+ self.size_global_alloc += self.fields_on_grid[0].mem_size
+
+ # Fields on particles
+ start = 0
+ for f in self.fields_on_grid:
+ for i in xrange(start, start + f.nb_components):
+ if isinstance(self._rwork[i], np.ndarray):
+ self._rwork[i] = \
+ self.cl_env.global_allocation(self._rwork[i])
+ self.fields_on_part[f] = self._rwork[start: start + f.nb_components]
+ start += f.nb_components
+
+ if self._use_2_kernels:
+ # Particles position
+ if isinstance(self._rwork[start], np.ndarray):
+ self._rwork[start] = \
+ self.cl_env.global_allocation(self._rwork[start])
+ self.part_position = self._rwork[start:start + 1]
+
+ self._work = self.fields_on_part.values()
+
+ def _buffer_initialisations(self):
+ """
+ OpenCL buffer initializations from user OpenCL kernels.
+ Looking for kernels named <code>init<FieldName></code>.
+ """
+ for gpudf in self.variables:
+ match = 'init' + '_'.join(gpudf.name.split('_')[:-1])
+ # Looking for initKernel
+ if self.prg is not None:
+ for k in self.prg.all_kernels():
+ k_name = k.get_info(cl.kernel_info.FUNCTION_NAME)
+ if match.find(k_name) >= 0:
+ if __VERBOSE__:
+ print gpudf.name, '-> OpenCL Kernel', k_name
+ if gpudf == self.velocity:
+ workItemNumber, gwi, lwi = \
+ self.cl_env.get_work_items(self.v_resol_dir)
+ else:
+ workItemNumber, gwi, lwi = \
+ self.cl_env.get_work_items(self.resol_dir)
+ gpudf.setInitializationKernel(OpenClKernelLauncher(
+ cl.Kernel(self.prg, k_name), self.cl_env.queue,
+ gwi, lwi))
+
+ def _collect_kernels_cl_src_copy(self):
+ """
+ Compile OpenCL sources for copy kernel.
+ """
+ # # copy settings
+ # src, t_dim, b_rows, vec, f_space = self._kernel_cfg['copy']
+ # while t_dim > self.resol_dir[0] or (self.resol_dir[0] % t_dim) > 0:
+ # t_dim /= 2
+ # gwi, lwi = f_space(self.resol_dir, t_dim, b_rows, vec)
+
+ # # Build code
+ # build_options += " -D TILE_DIM_COPY={0}".format(t_dim)
+ # build_options += " -D BLOCK_ROWS_COPY={0}".format(b_rows)
+ # build_options += self._size_constants
+ # prg = self.cl_env.build_src(
+ # src,
+ # build_options,
+ # vec)
+ # self.copy = OpenClKernelLauncher(prg.copy,
+ # self.cl_env.queue, gwi, lwi)
+ return OpenClKernelLauncher(cl.enqueue_copy, self.cl_env.queue)
+
+ def _collect_kernels_cl_src_transpositions_xy(self):
+ """Compile OpenCL sources for transpositions kernel.
+
+ Notes
+ -----
+
+ * Transpositions kernels are launched at initialization.
+
+ This routine sets transpose_xy and transpose_xy_r.
+ """
+ resol = self.fields_topo.mesh.resolution
+
+ # XY transposition settings
+ is_XY_needed = self.direction == 1 or self.direction == 0
+ if is_XY_needed:
+ resol_tmp = resol.copy()
+ if self.direction == 1: # (XY -> YX)
+ resol_tmp[0] = resol[1]
+ resol_tmp[1] = resol[0]
+ ocl_cte = " -D NB_I=NB_Y -D NB_II=NB_X -D NB_III=NB_Z"
+ else:
+ # self.direction == 0: # (YX -> XY) only for sequential
+ ocl_cte = " -D NB_I=NB_X -D NB_II=NB_Y -D NB_III=NB_Z"
+
+ self.transpose_xy = self._make_transpose_xy(resol_tmp, ocl_cte)
+
+ def _make_transpose_xy(self, resolution, ocl_cte):
+ """Perform xy transposition
+
+ Parameters
+ ----------
+ resolution : numpy array
+ required shape for?
+ ocl_cte: string
+ compilation options
+ """
+ build_options = self._size_constants
+ src, t_dim, b_rows, is_padding, vec, f_space = \
+ self._kernel_cfg['transpose_xy']
+ while t_dim > resolution[0] or t_dim > resolution[1] or \
+ (resolution[0] % t_dim) > 0 or (resolution[1] % t_dim) > 0:
+ t_dim /= 2
+ gwi, lwi, blocs_nb = f_space(resolution, t_dim, b_rows, vec)
+
+ if is_padding:
+ build_options += " -D PADDING_XY=1"
+ else:
+ build_options += " -D PADDING_XY=0"
+ build_options += " -D TILE_DIM_XY={0}".format(t_dim)
+ build_options += " -D BLOCK_ROWS_XY={0}".format(b_rows)
+ build_options += " -D NB_GROUPS_I={0}".format(blocs_nb[0])
+ build_options += " -D NB_GROUPS_II={0}".format(blocs_nb[1])
+ build_options += ocl_cte
+ prg = self.cl_env.build_src(src, build_options, vec)
+ return OpenClKernelLauncher(prg.transpose_xy, self.cl_env.queue, gwi, lwi)
+
+ def _collect_kernels_cl_src_transpositions_xz(self):
+ resol = self.fields_topo.mesh.resolution
+ resol_tmp = npw.zeros_like(resol)
+
+ is_XZ_needed = self.direction == 2 or self.direction == 1
+ # XZ transposition settings
+ if is_XZ_needed:
+ resol_tmp[...] = resol[...]
+ if self.direction == 1: # ZXY -> YXZ (only for seqential)
+ resol_tmp[0] = resol[1]
+ resol_tmp[1] = resol[0]
+ resol_tmp[2] = resol[2]
+ ocl_cte = " -D NB_I=NB_Y -D NB_II=NB_X -D NB_III=NB_Z"
+ elif self.direction == 2:
+ # YXZ -> ZXY
+ resol_tmp[0] = resol[2]
+ resol_tmp[1] = resol[0]
+ resol_tmp[2] = resol[1]
+ ocl_cte = " -D NB_I=NB_Z -D NB_II=NB_X -D NB_III=NB_Y"
+ # else: # XYZ -> ZYX
+ # resol_tmp[0] = resol[2]
+ # resol_tmp[1] = resol[1]
+ # resol_tmp[2] = resol[0]
+ # ocl_cte = " -D NB_I=NB_Z -D NB_II=NB_Y -D NB_III=NB_X"
+ self.transpose_xz = self._make_transpose_xz(resol_tmp, ocl_cte)
+
+ # is_XZ_r_needed = self.direction == 2 and self._comm_size > 1
+ # if is_XZ_r_needed:
+ # # Reversed XZ transposition settings (ZYX -> XYZ)
+ # resol_tmp[...] = resol[...]
+ # ocl_cte = " -D NB_I=NB_X -D NB_II=NB_Y -D NB_III=NB_Z"
+ # self.transpose_xz_r = self._make_transpose_xz(resol_tmp, ocl_cte)
+
+ def _make_transpose_xz(self, resol_tmp, ocl_cte):
+
+ build_options = self._size_constants
+ src, t_dim, b_rows, b_deph, is_padding, vec, f_space = \
+ self._kernel_cfg['transpose_xz']
+
+ while t_dim > resol_tmp[0] or t_dim > resol_tmp[2] or \
+ (resol_tmp[0] % t_dim) > 0 or (resol_tmp[2] % t_dim) > 0:
+ t_dim /= 2
+ gwi, lwi, blocs_nb = f_space(resol_tmp, t_dim, b_rows, b_deph, vec)
+ if is_padding:
+ build_options += " -D PADDING_XZ=1"
+ else:
+ build_options += " -D PADDING_XZ=0"
+ build_options += " -D TILE_DIM_XZ={0}".format(t_dim)
+ build_options += " -D BLOCK_ROWS_XZ={0}".format(b_rows)
+ build_options += " -D BLOCK_DEPH_XZ={0}".format(b_deph)
+ build_options += " -D NB_GROUPS_I={0}".format(blocs_nb[0])
+ build_options += " -D NB_GROUPS_III={0}".format(blocs_nb[2])
+ build_options += ocl_cte
+ prg = self.cl_env.build_src(
+ src,
+ build_options,
+ vec)
+ return OpenClKernelLauncher(prg.transpose_xz, self.cl_env.queue, gwi, lwi)
+
+ def _collect_usr_cl_src(self):
+ """Build user sources.
+
+ """
+ # get extra (opencl kernels) files from method, if any
+ user_src = get_extra_args_from_method(self, 'user_src', None)
+ if user_src is not None:
+ build_options = self._size_constants
+ workItemNb, gwi, lwi = self.cl_env.get_work_items(self.resol_dir)
+ v_workItemNb, gwi, lwi = self.cl_env.get_work_items(self.v_resol_dir)
+ build_options += " -D WI_NB=" + str(workItemNb)
+ build_options += " -D V_WI_NB=" + str(v_workItemNb)
+ self.prg = self.cl_env.build_src(user_src, build_options, 1)
+
+
+ def _collect_kernels_cl_src_1k(self):
+ """
+ Compile OpenCL sources for advection and remeshing kernel.
+ """
+ build_options = self._size_constants
+ src, is_noBC, vec, f_space = self._kernel_cfg['advec_and_remesh']
+ gwi, lwi = f_space(self.resol_dir, vec)
+ WINb = lwi[0]
+ build_options += " -D FORMULA=" + self.method[Remesh].__name__.upper()
+ if self._isMultiScale:
+ build_options += " -D MS_FORMULA="
+ build_options += self.method[MultiScale].__name__.upper()
+ if is_noBC:
+ build_options += " -D WITH_NOBC=1"
+ build_options += " -D WI_NB=" + str(WINb)
+ build_options += " -D PART_NB_PER_WI="
+ build_options += str(self.resol_dir[0] / WINb)
+ # Build code
+ src = [s.replace('RKN', self.method[TimeIntegrator].__name__.lower())
+ for s in src]
+ # Euler integrator
+ if self.method[TimeIntegrator] is Euler:
+ if not self._isMultiScale:
+ src = [s for s in src if s.find(Euler.__name__.lower()) < 0]
+ src[-1] = src[-1].replace('advection', 'advection_euler')
+ prg = self.cl_env.build_src(
+ src, build_options, vec,
+ nb_remesh_components=self.fields_on_grid[0].nb_components)
+
+ self.num_advec_and_remesh = OpenClKernelLauncher(
+ prg.advection_and_remeshing, self.cl_env.queue, gwi, lwi)
+
+ def _collect_kernels_cl_src_2k(self):
+ """
+ Compile OpenCL sources for advection and remeshing kernel.
+ """
+ # Advection
+ build_options = self._size_constants
+ src, is_noBC, vec, f_space = self._kernel_cfg['advec']
+ gwi, lwi = f_space(self.resol_dir, vec)
+ WINb = lwi[0]
+ if self._isMultiScale:
+ build_options += " -D MS_FORMULA="
+ build_options += self.method[MultiScale].__name__.upper()
+ self._compute_advec = self._compute_advec_multiechelle
+ else:
+ self._compute_advec = self._compute_advec_simpleechelle
+
+ if is_noBC:
+ build_options += " -D WITH_NOBC=1"
+ build_options += " -D WI_NB=" + str(WINb)
+ build_options += " -D PART_NB_PER_WI="
+ build_options += str(self.resol_dir[0] / WINb)
+ # Build code
+ src = [s.replace('RKN', self.method[TimeIntegrator].__name__.lower())
+ for s in src]
+ # Adding remeshing weights for the multiscale advection
+ if self._isMultiScale:
+ src.insert(1, self._kernel_cfg['remesh'][0][1])
+ # Euler integrator
+ if self.method[TimeIntegrator] is Euler:
+ if not self._isMultiScale:
+ src = [s for s in src if s.find(Euler.__name__.lower()) < 0]
+ src[-1] = src[-1].replace('advection', 'advection_euler')
+ self._compute_advec = self._compute_advec_euler_simpleechelle
+ prg = self.cl_env.build_src(
+ src,
+ build_options,
+ vec,
+ nb_remesh_components=self.fields_on_grid[0].nb_components)
+
+ self.num_advec = OpenClKernelLauncher(
+ prg.advection_kernel, self.cl_env.queue, gwi, lwi)
+
+ # remeshing
+ build_options = self._size_constants
+ src, is_noBC, vec, f_space = self._kernel_cfg['remesh']
+ gwi, lwi = f_space(self.resol_dir, vec)
+ WINb = lwi[0]
+
+ build_options += " -D FORMULA=" + self.method[Remesh].__name__.upper()
+ if is_noBC:
+ build_options += " -D WITH_NOBC=1"
+ build_options += " -D WI_NB=" + str(WINb)
+ build_options += " -D PART_NB_PER_WI="
+ build_options += str(self.resol_dir[0] / WINb)
+ # Build code
+ prg = self.cl_env.build_src(
+ src, build_options, vec,
+ nb_remesh_components=self.fields_on_grid[0].nb_components)
+ self.num_remesh = OpenClKernelLauncher(
+ prg.remeshing_kernel, self.cl_env.queue, gwi, lwi)
+
+ @debug
+ @profile
+ def apply(self, simulation, dt_coeff, split_id, old_dir):
+ """
+ Apply operator along specified splitting direction.
+ @param t : Current time
+ @param dt : Time step
+ @param d : Splitting direction
+ @param split_id : Splitting step id
+ """
+ # If first direction of advection, wait for work gpu fields
+ # It avoid wait_for lists to increase indefinitely
+ # In practice, all events are terminated so wait() resets events list
+ if split_id == 0:
+ for v in self.fields_on_grid + [self.velocity]:
+ v.clean_events()
+ for exe in self.exec_list[split_id]:
+ exe(simulation, dt_coeff, split_id, old_dir)
+
+ def _init_copy(self, simulation, dt_coeff, split_id, old_dir):
+ wait_evt = self.fields_on_grid[0].events
+ for g, p in zip(self.fields_on_grid[0].gpu_data,
+ self.fields_on_part[self.fields_on_grid[0]]):
+ evt = self.copy.launch_sizes_in_args(p, g, wait_for=wait_evt)
+ #evt = self.copy(g, p, wait_for=wait_evt)
+ self._init_events[self.fields_on_grid[0]].append(evt)
+
+ # def _init_copy_r(self, simulation, dt_coeff, split_id, old_dir):
+ # wait_evt = self.fields_on_grid[0].events
+ # for g, p in zip(self.fields_on_grid[0].gpu_data,
+ # self.fields_on_part[self.fields_on_grid[0]]):
+ # evt = self.copy.launch_sizes_in_args(g, p, wait_for=wait_evt)
+ # #evt = self.copy(p, g, wait_for=wait_evt)
+ # self._init_events[self.fields_on_grid[0]].append(evt)
+
+ def _init_transpose_xy(self, simulation, dt_coeff, split_id, old_dir):
+ wait_evt = self.fields_on_grid[0].events
+ for g, p in zip(self.fields_on_grid[0].gpu_data,
+ self.fields_on_part[self.fields_on_grid[0]]):
+ evt = self.transpose_xy(g, p, wait_for=wait_evt)
+ self._init_events[self.fields_on_grid[0]].append(evt)
+
+ # def _init_transpose_xy_r(self, simulation, dt_coeff, split_id, old_dir):
+ # wait_evt = self.fields_on_grid[0].events
+ # for g, p in zip(self.fields_on_grid[0].gpu_data,
+ # self.fields_on_part[self.fields_on_grid[0]]):
+ # evt = self.transpose_xy_r(p, g, wait_for=wait_evt)
+ # self._init_events[self.fields_on_grid[0]].append(evt)
+
+ def _init_transpose_xz(self, simulation, dt_coeff, split_id, old_dir):
+ wait_evt = self.fields_on_grid[0].events
+ for g, p in zip(self.fields_on_grid[0].gpu_data,
+ self.fields_on_part[self.fields_on_grid[0]]):
+ evt = self.transpose_xz(g, p, wait_for=wait_evt)
+ self._init_events[self.fields_on_grid[0]].append(evt)
+
+ # def _init_transpose_xz_r(self, simulation, dt_coeff, split_id, old_dir):
+ # wait_evt = self.fields_on_grid[0].events
+ # for g, p in zip(self.fields_on_grid[0].gpu_data,
+ # self.fields_on_part[self.fields_on_grid[0]]):
+ # evt = self.transpose_xz_r(p, g, wait_for=wait_evt)
+ # self._init_events[self.fields_on_grid[0]].append(evt)
+
+ def _compute_advec_euler_simpleechelle(self, simulation, dt_coeff, split_id, old_dir):
+ dt = simulation.time_step * dt_coeff
+ wait_evts = self.velocity.events + \
+ self._init_events[self.fields_on_grid[0]]
+ # Advection
+ evt = self.num_advec(
+ self.velocity.gpu_data[self.direction],
+ self.part_position[0],
+ self.gpu_precision(dt),
+ self._cl_mesh_info,
+ wait_for=wait_evts)
+ self._init_events[self.fields_on_grid[0]].append(evt)
+
+ def _compute_advec_simpleechelle(self, simulation, dt_coeff, split_id, old_dir):
+ dt = simulation.time_step * dt_coeff
+ wait_evts = self.velocity.events + \
+ self._init_events[self.fields_on_grid[0]]
+ # Advection
+ evt = self.num_advec(
+ self.velocity.gpu_data[self.direction],
+ self.part_position[0],
+ self.gpu_precision(dt),
+ self._cl_mesh_info,
+ wait_for=wait_evts)
+ self._init_events[self.fields_on_grid[0]].append(evt)
+
+ def _compute_advec_multiechelle(self, simulation, dt_coeff, split_id, old_dir):
+ dt = simulation.time_step * dt_coeff
+ wait_evts = self.velocity.events + \
+ self._init_events[self.fields_on_grid[0]]
+ # Advection
+ evt = self.num_advec(
+ self.velocity.gpu_data[self.direction],
+ self.part_position[0],
+ self.gpu_precision(dt),
+ self.gpu_precision(1. / self._v_mesh_size[1]),
+ self.gpu_precision(1. / self._v_mesh_size[2]),
+ self._cl_mesh_info,
+ wait_for=wait_evts)
+ self._init_events[self.fields_on_grid[0]].append(evt)
+
+ def _compute_2k(self, simulation, dt_coeff, split_id, old_dir):
+ self._compute_advec(simulation, dt_coeff, split_id, old_dir)
+ wait_evts = self._init_events[self.fields_on_grid[0]] + \
+ self.fields_on_grid[0].events
+ nbc = self.fields_on_grid[0].nb_components
+ evt = self.num_remesh(*tuple(
+ [self.part_position[0], ] +
+ [self.fields_on_part[self.fields_on_grid[0]][i]
+ for i in xrange(nbc)] +
+ [self.fields_on_grid[0].gpu_data[i] for i in xrange(nbc)] +
+ [self._cl_mesh_info, ]),
+ wait_for=wait_evts)
+ self.fields_on_grid[0].events.append(evt)
+ self._init_events[self.fields_on_grid[0]] = []
+
+ def _compute_1k_multiechelle(self, simulation, dt_coeff, split_id, old_dir):
+ if split_id==0 and self._synchronize is not None:
+ self._synchronize(self.velocity.data)
+ self.velocity.toDevice()
+ dt = simulation.time_step * dt_coeff
+ wait_evts = self.velocity.events + \
+ self._init_events[self.fields_on_grid[0]] + \
+ self.fields_on_grid[0].events
+ nbc = self.fields_on_grid[0].nb_components
+ evt = self.num_advec_and_remesh(*tuple(
+ [self.velocity.gpu_data[self.direction], ] +
+ [self.fields_on_part[self.fields_on_grid[0]][i]
+ for i in xrange(nbc)] +
+ [self.fields_on_grid[0].gpu_data[i] for i in xrange(nbc)] +
+ [self.gpu_precision(dt),
+ self.gpu_precision(1. / self._v_mesh_size[1]),
+ self.gpu_precision(1. / self._v_mesh_size[2]),
+ self._cl_mesh_info]),
+ wait_for=wait_evts)
+ self.fields_on_grid[0].events.append(evt)
+ self._init_events[self.fields_on_grid[0]] = []
+
+ def _compute_1k_simpleechelle(self, simulation, dt_coeff, split_id, old_dir):
+ dt = simulation.time_step * dt_coeff
+ wait_evts = self.velocity.events + \
+ self._init_events[self.fields_on_grid[0]] + \
+ self.fields_on_grid[0].events
+ nbc = self.fields_on_grid[0].nb_components
+ evt = self.num_advec_and_remesh(*tuple(
+ [self.velocity.gpu_data[self.direction], ] +
+ [self.fields_on_part[self.fields_on_grid[0]][i]
+ for i in xrange(nbc)] +
+ [self.fields_on_grid[0].gpu_data[i] for i in xrange(nbc)] +
+ [self.gpu_precision(dt), self._cl_mesh_info]),
+ wait_for=wait_evts)
+ self.fields_on_grid[0].events.append(evt)
+ self._init_events[self.fields_on_grid[0]] = []
+
+
+ def _compute_1k_euler_simpleechelle(self, simulation, dt_coeff, split_id, old_dir):
+ dt = simulation.time_step * dt_coeff
+ wait_evts = self.velocity.events + \
+ self._init_events[self.fields_on_grid[0]] + \
+ self.fields_on_grid[0].events
+ nbc = self.fields_on_grid[0].nb_components
+ evt = self.num_advec_and_remesh(*tuple(
+ [self.velocity.gpu_data[self.direction], ] +
+ [self.fields_on_part[self.fields_on_grid[0]][i]
+ for i in xrange(nbc)] +
+ [self.fields_on_grid[0].gpu_data[i] for i in xrange(nbc)] +
+ [self.gpu_precision(dt), self._cl_mesh_info]),
+ wait_for=wait_evts)
+ self.fields_on_grid[0].events.append(evt)
+ self._init_events[self.fields_on_grid[0]] = []
+
+ def get_profiling_info(self):
+ for k in [self.copy, self.transpose_xy, self.transpose_xy_r,
+ self.transpose_xz, self.transpose_xz_r,
+ self.num_advec_and_remesh,
+ self.num_advec, self.num_remesh]:
+ if k is not None:
+ for p in k.profile:
+ self.profiler += p
+
+ @debug
+ def finalize(self):
+ """
+ Cleaning, if required.
+ """
+ pass
+ # for w in self._rwork:
+ # self.cl_env.global_deallocation(w)
+ # self.cl_env.global_deallocation(self._cl_mesh_info)
diff --git a/hysop/gpu/gpu_particle_advection_dir.py b/hysop/old/gpu.old/gpu_particle_advection_dir.py
similarity index 64%
rename from hysop/gpu/gpu_particle_advection_dir.py
rename to hysop/old/gpu.old/gpu_particle_advection_dir.py
index 0bd1829b7b2c5ccc53847409d6c30ec72ffb5277..e9855cd52905f7cdd357e67ffab27f370988ced2 100644
--- a/hysop/gpu/gpu_particle_advection_dir.py
+++ b/hysop/old/gpu.old/gpu_particle_advection_dir.py
@@ -1,35 +1,43 @@
"""Discrete advection for GPU
"""
from hysop import __VERBOSE__, __DEBUG__, __PROFILE__
-from hysop.constants import HYSOP_REAL, HYSOP_INTEGER, ORDER, debug
-from hysop.constants import StretchingFormulation
+from hysop.constants import HYSOP_REAL, debug
from hysop.tools.profiler import profile
from hysop.tools.misc import WorkSpaceTools
from hysop.operator.discrete.particle_advection_dir import ParticleAdvectionDir
from hysop.numerics.update_ghosts import UpdateGhostsFull
-from hysop.gpu import cl
-from hysop.gpu.gpu_discrete import GPUDiscreteField
-from hysop.gpu.gpu_operator import GPUOperator
-from hysop.gpu.gpu_kernel import KernelLauncher
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
+from hysop.backend.device.opencl.gpu_operator import GPUOperator
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.kernel_autotuner import AutotunerConfig
-from hysop.codegen.structs.mesh_info import MeshInfoStruct, MeshState, MeshDir
+from hysop.backend.device.codegen.structs.mesh_info import MeshInfoStruct, TranspositionState, MeshDirection
-from hysop.methods_keys import TimeIntegrator, Remesh, ExtraArgs, \
- Support, Splitting, MultiScale, Interpolation, Precision, \
- Formulation
+from hysop.methods import TimeIntegrator, Remesh, ExtraArgs, \
+ DeviceSupport, Splitting, MultiScale, Interpolation, Precision, \
+ StretchingFormulation, DirectionalSplitting, Backend, ExplicitRungeKutta
from hysop.numerics.odesolvers import Euler, RK2, RK3, RK4
-from hysop.numerics.interpolation import Linear
+from hysop.numerics.interpolation.interpolation import Linear
from hysop.numerics.remeshing import L2_1, L2_2, L2_3, L2_4
from hysop.numerics.remeshing import L4_2, L4_3, L4_4
from hysop.numerics.remeshing import L6_3, L6_4, L6_5, L6_6
from hysop.numerics.remeshing import L8_4
+from hysop.constants import callback_profiler
+
from hysop.constants import np
+class InstanceOf(object):
+ def __init__(self, cls):
+ self.cls = cls
+ def match_instance(self, obj):
+ return isinstance(obj,self.cls)
+
class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
"""
@@ -42,8 +50,9 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
_default_method = {
TimeIntegrator: RK2,
Interpolation: Linear,
- Support: 'gpu',
- Splitting: 'o2',
+ Backend: Backend.OPENCL,
+ DeviceSupport: DeviceSupport.DEVICE_GPU,
+ Splitting: DirectionalSplitting.STRANG_FIRST_ORDER,
Remesh: L2_1,
MultiScale: L2_1,
Precision: HYSOP_REAL,
@@ -55,17 +64,21 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
'device_type':None,
'stretching':None,
'diffusion':None,
- 'split_kernels':False
+ 'split_kernels':True,
+ 'use_builtin_copy':True,
+ 'autotuner_config':AutotunerConfig()
}
}
_valid_method_values = {
- TimeIntegrator: [Euler,RK2,RK3,RK4],
+ TimeIntegrator: [Euler,RK2,RK3,RK4,InstanceOf(ExplicitRungeKutta)],
Interpolation: [Linear],
Remesh: [L2_1,L2_2,L2_3,L2_4,L4_2,L4_3,L4_4,L6_3,L6_4,L6_5,L6_6,L8_4],
- Support: ['gpu'],
- Splitting: ['o2'],
- Precision: [HYSOP_REAL,np.float32,np.float64]
+ DeviceSupport: [DeviceSupport.DEVICE_GPU],
+ Backend: [Backend.OPENCL],
+ Splitting: [DirectionalSplitting.STRANG_FIRST_ORDER,
+ DirectionalSplitting.STRANG_SECOND_ORDER],
+ Precision: [np.float32,np.float64]
}
@staticmethod
@@ -86,16 +99,20 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
msg="WARNING: Unknown extra arg '{}', ' \
+ 'valid values are:\n\t{}".format(ke,vke)
print msg
- elif (valid_method_values[k] is not None) and \
- (user_method[k] not in valid_method_values[k]):
- msg = "Unknown method value '{}', valid values for key '{}' are:\n\t{}"
- raise ValueError(msg.format(user_method[k],k,valid_method_values[k]))
+ elif (valid_method_values[k] is not None):
+ valid_vals = [v for v in valid_method_values[k] if not isinstance(v,InstanceOf)]
+ valid_cls = [v.cls for v in valid_method_values[k] if isinstance(v,InstanceOf)]
+ if (user_method[k] not in valid_vals \
+ and user_method[k].__class__ not in valid_cls):
+ pass
+ msg = "Unknown method value '{}', valid values for key '{}' are:\n\t{}"
+ raise ValueError(msg.format(user_method[k],k,valid_method_values[k]))
method = default_method.copy()
method.update(user_method)
+ method[ExtraArgs] = default_method[ExtraArgs].copy()
if ExtraArgs in user_method.keys():
- method[ExtraArgs] = default_method[ExtraArgs].copy()
method[ExtraArgs].update(user_method[ExtraArgs])
if __DEBUG__:
@@ -134,9 +151,11 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
# Kernel configuration
extra_args = method[ExtraArgs]
- self._split_kernels = extra_args.pop('split_kernels')
- self._user_src = extra_args.pop('user_src')
- self._build_options = extra_args.pop('build_options')
+ self._split_kernels = extra_args.pop('split_kernels')
+ self._user_src = extra_args.pop('user_src')
+ self._build_options = extra_args.pop('build_options')
+ self._use_builtin_copy = extra_args.pop('use_builtin_copy')
+ self._autotuner_config = extra_args.pop('autotuner_config')
stretching = extra_args.pop('stretching')
if (stretching is not None):
@@ -166,6 +185,9 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
device_id = extra_args.pop('device_id'),
device_type = extra_args.pop('device_type'),
**kwds)
+
+ if extra_args:
+ raise ValueError('Some extra arguments were not used:\n\t{}\n'.format(extra_args))
def _check(self):
@@ -216,13 +238,13 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
direction=self.direction
- mesh_dir = MeshDir[direction]
- if direction==MeshDir.X:
- mesh_state = MeshState.XYZ
- elif direction==MeshDir.Y:
- mesh_state = MeshState.YXZ
- elif direction==MeshDir.Z:
- mesh_state = MeshState.ZYX if (self._is_distributed) else MeshState.ZXY
+ mesh_dir = MeshDirection[direction]
+ if direction==MeshDirection.X:
+ mesh_state = TranspositionState.XYZ
+ elif direction==MeshDirection.Y:
+ mesh_state = TranspositionState.YXZ
+ elif direction==MeshDirection.Z:
+ mesh_state = TranspositionState.ZYX if (self._is_distributed) else TranspositionState.ZXY
else:
raise ValueError()
@@ -240,7 +262,7 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
self.v_resol_dir = v_resol_dir
def _collect_copy_kernels(self):
- self.copy = KernelLauncher(cl.enqueue_copy,
+ self.copy = OpenClKernelLauncher(cl.enqueue_copy,
self.cl_env.queue)
def _collect_transposition_kernels(self):
@@ -253,33 +275,58 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
Kernels are only collected if the dimension and direction match.
"""
- self._transpose_xy, self._transpose_yx = None, None
- self._transpose_xz, self._transpose_zx = None, None
-
dim = self.dim
direction = self.direction
- is_XY_needed = (dim>1) and (direction == MeshDir.Y)
- is_YX_needed = (dim>1) and (direction == MeshDir.X)
+ smethod = self.method[Splitting]
- is_XZ_needed = (dim>2) and (direction == MeshDir.Z) \
- and (not self._is_distributed)
- is_ZX_needed = (dim>2) and (direction == MeshDir.Y) \
- and (not self._is_distributed)
+ is_XY_needed, is_YX_needed = False, False
+ is_XZ_needed, is_ZX_needed = False, False
+ if dim==1:
+ pass
+ elif dim==2:
+ if smethod==DirectionalSplitting.STRANG_FIRST_ORDER:
+ is_XY_needed = (dim>1) and (direction == MeshDirection.X)
+ is_YX_needed = (dim>1) and (direction == MeshDirection.Y)
+ elif smethod==DirectionalSplitting.STRANG_SECOND_ORDEVR:
+ is_XY_needed = (dim>1) and (direction == MeshDirection.X)
+ is_YX_needed = (dim>1) and (direction == MeshDirection.Y)
+ elif dim==3:
+ if smethod==DirectionalSplitting.STRANG_FIRST_ORDER:
+ is_XY_needed = (dim>1) and (direction == MeshDirection.X)
+ is_YX_needed = (dim>1) and (direction == MeshDirection.Z)
+ is_XZ_needed = (dim>2) and (direction == MeshDirection.Y) \
+ and (not self._is_distributed)
+ is_ZX_needed = (dim>2) and (direction == MeshDirection.Z) \
+ and (not self._is_distributed)
+ elif smethod==DirectionalSplitting.STRANG_SECOND_ORDER:
+ is_XY_needed = (dim>1) and (direction == MeshDirection.X)
+ is_YX_needed = (dim>1) and (direction == MeshDirection.Y)
+
+ is_XZ_needed = (dim>2) and (direction == MeshDirection.Y) \
+ and (not self._is_distributed)
+ is_ZX_needed = (dim>2) and (direction == MeshDirection.Z) \
+ and (not self._is_distributed)
+ else:
+ msg = 'Dimension {} not implemented yet!'.format(dim)
+ raise NotImplementedError(msg)
+
+
+ transpose_xy, transpose_yx = None, None
+ transpose_zx, transpose_xz = None, None
+
if is_XY_needed:
- self._collect_transposition_kernel_xy()
+ transpose_xy = self._collect_transposition_kernel_xy()
if is_YX_needed:
- self._collect_transposition_kernel_yx()
+ transpose_yx = self._collect_transposition_kernel_yx()
if is_XZ_needed:
- self._collect_transposition_kernel_xz()
+ transpose_xz = self._collect_transposition_kernel_xz()
if is_ZX_needed:
- self._collect_transposition_kernel_zx()
- if dim>3:
- msg = 'Dimension {} not implemented yet!'.format(dim)
- raise NotImplementedError(msg)
-
-
+ transpose_zx = self._collect_transposition_kernel_zx()
+
+ self._build_tranpose_funcs(transpose_xy, transpose_yx, transpose_xz, transpose_zx)
+
def _collect_advection_remesh_kernels(self):
self._advec, self._remesh = None, None
self._advec_and_remesh = None
@@ -337,14 +384,14 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
raise RuntimeError('_set_work_arrays has not been implemented properly.')
# Velocity
- GPUDiscreteField.fromField(self.cl_env, self.velocity,
+ OpenClDiscreteField.fromField(self.cl_env, self.velocity,
self.gpu_precision, simple_layout=False)
if self.velocity.allocate():
self.size_global_alloc += self.velocity.mem_size
# Fields on grids
for fg in self.fields_on_grid:
- GPUDiscreteField.fromField(self.cl_env,
+ OpenClDiscreteField.fromField(self.cl_env,
fg,
self.gpu_precision,
layout=False)
@@ -378,7 +425,7 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
OpenCL buffer initializations from user OpenCL kernels.
Looking for kernels named init<FieldName>.
"""
- if (self._user_prg is None) or (self.direction != MeshDir.X):
+ if (self._user_prg is None) or (self.direction != MeshDirection.X):
return
f_resolution = self.f_resolution
@@ -401,7 +448,7 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
init_field_kernel = cl.Kernel(self.prg, k_name)
gpudf.setInitializationKernel(
- KernelLauncher(init_field_kernel,self.cl_env.queue,gwi,lwi)
+ OpenClKernelLauncher(init_field_kernel,self.cl_env.queue,gwi,lwi)
)
@@ -409,6 +456,11 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
def _build_exec_list(self):
"""Prepare GPU kernels sequence
Build execution list regarding splitting:
+
+ **Splitting Strang 1st order**
+ 1D: X(dt)
+ 2D: X(dt), Y(dt)
+ 3D: X(dt), Y(dt), Z(dt)
**Splitting Strang 2nd order**
1D: X(dt)
@@ -427,39 +479,70 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
param_list,exec_list = None,None
- if smethod == 'o2':
+ if smethod == DirectionalSplitting.STRANG_FIRST_ORDER:
+ if self.dim == 1:
+ param_list = [
+ {'dir':MeshDirection.X, 'dt_coeff':1.0},
+ ]
+ exec_list = [
+ [self._do_sync, self._do_copy, self._do_compute], # X(dt)
+ ]
+ elif dim == 2:
+ param_list = [
+ {'dir':MeshDirection.X, 'dt_coeff':1.0},
+ {'dir':MeshDirection.Y, 'dt_coeff':1.0},
+ ]
+ exec_list = [
+ [self._do_sync, self._do_copy, self._do_compute, self._do_transpose_xy_g2p], # X(dt)
+ [ self._do_compute, self._do_transpose_yx_g2g], # Y(dt)
+ ]
+ elif dim == 3:
+ param_list = [
+ {'dir':MeshDirection.X, 'dt_coeff':1.0},
+ {'dir':MeshDirection.Y, 'dt_coeff':1.0},
+ {'dir':MeshDirection.Z, 'dt_coeff':1.0},
+ ]
+ exec_list = [
+ [self._do_sync, self._do_copy, self._do_compute, self._do_transpose_xy_g2p], # X(dt)
+ [ self._do_compute, self._do_transpose_xz_g2p], # Y(dt)
+ [ self._do_compute, self._do_transpose_zx_g2p, \
+ self._do_transpose_yx_p2g] # Z(dt)
+ ]
+ else:
+ raise ValueError(dim_msg)
+ elif smethod == DirectionalSplitting.STRANG_SECOND_ORDER:
if self.dim == 1:
param_list = [
- {'dir':MeshDir.X, 'dt_coeff':1.0},
+ {'dir':MeshDirection.X, 'dt_coeff':1.0},
]
exec_list = [
[self._do_sync, self._do_copy, self._do_compute], # X(dt)
]
elif dim == 2:
param_list = [
- {'dir':MeshDir.X, 'dt_coeff':0.5},
- {'dir':MeshDir.Y, 'dt_coeff':1.0},
- {'dir':MeshDir.X, 'dt_coeff':0.5},
+ {'dir':MeshDirection.X, 'dt_coeff':0.5},
+ {'dir':MeshDirection.Y, 'dt_coeff':1.0},
+ {'dir':MeshDirection.X, 'dt_coeff':0.5},
]
exec_list = [
- [self._do_sync, self._do_copy, self._do_compute], # X(dt/2)
- [self._do_transpose_xy, self._do_compute], # Y(dt)
- [self._do_transpose_yx, self._do_compute] # X(dt/2)
+ [self._do_sync, self._do_copy, self._do_compute, self._do_transpose_xy_g2p], # X(dt/2)
+ [ self._do_compute, self._do_transpose_yx_g2p], # Y(dt)
+ [ self._do_compute] # X(dt/2)
]
elif dim == 3:
param_list = [
- {'dir':MeshDir.X, 'dt_coeff':0.5},
- {'dir':MeshDir.Y, 'dt_coeff':0.5},
- {'dir':MeshDir.Z, 'dt_coeff':1.0},
- {'dir':MeshDir.Y, 'dt_coeff':0.5},
- {'dir':MeshDir.X, 'dt_coeff':0.5},
+ {'dir':MeshDirection.X, 'dt_coeff':0.5},
+ {'dir':MeshDirection.Y, 'dt_coeff':0.5},
+ {'dir':MeshDirection.Z, 'dt_coeff':1.0},
+ {'dir':MeshDirection.Y, 'dt_coeff':0.5},
+ {'dir':MeshDirection.X, 'dt_coeff':0.5},
]
exec_list = [
- [self._do_sync, self._do_copy, self._do_compute], # X(dt/2)
- [self._do_transpose_xy, self._do_compute], # Y(dt/2)
- [self._do_transpose_xz, self._do_compute], # Z(dt)
- [self._do_transpose_zx, self._do_compute], # Y(dt/2)
- [self._do_transpose_yx, self._do_compute] # X(dt/2)
+ [self._do_sync, self._do_copy, self._do_compute, self._do_transpose_xy_g2p], # X(dt/2)
+ [ self._do_compute, self._do_transpose_xz_g2p], # Y(dt/2)
+ [ self._do_compute, self._do_transpose_zx_g2p], # Z(dt)
+ [ self._do_compute, self._do_transpose_yx_g2p], # Y(dt/2)
+ [ self._do_compute] # X(dt/2)
]
else:
raise ValueError(dim_msg)
@@ -516,7 +599,7 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
@param extra_params: Extra kernel parameters that complete or override
step parameters param_list[step_id].
"""
-
+
if (simulation is None):
raise ValueError('simulation is None.')
if (step_id<0) or (step_id>=len(self._exec_list)):
@@ -526,6 +609,8 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
if step_id == 0:
for v in self.variables:
v.clean_events()
+
+ self._pre_apply()
import copy
parameters = copy.deepcopy(self._param_list[step_id])
@@ -536,7 +621,7 @@ class GPUParticleAdvectionDir(ParticleAdvectionDir, GPUOperator):
if my_dir != req_dir:
msg = 'Discrete splitting operator called for wrong direction, \
splitting step id {} requires direction {} but currently applied operator \
-direction is {}!'.format(step_id,MeshDir[req_dir],MeshDir[my_dir])
+direction is {}!'.format(step_id,MeshDirection[req_dir],MeshDirection[my_dir])
raise RuntimeError(msg)
exec_list = self._exec_list[step_id]
@@ -569,7 +654,7 @@ direction is {}!'.format(step_id,MeshDir[req_dir],MeshDir[my_dir])
##
-## OpenCL kernel backend interface
+## OpenCL kernel interface
##
@abstractmethod
def _initialize_cl_env(self):
@@ -606,15 +691,6 @@ direction is {}!'.format(step_id,MeshDir[req_dir],MeshDir[my_dir])
def _do_copy(self,**kargs):
raise NotImplementedError()
- def _do_transpose_xy(self,**kargs):
- raise NotImplementedError()
- def _do_transpose_yx(self,**kargs):
- raise NotImplementedError()
- def _do_transpose_xz(self,**kargs):
- raise NotImplementedError()
- def _do_transpose_zx(self,**kargs):
- raise NotImplementedError()
-
def _do_compute_1k_monoscale(self, dt):
raise NotImplementedError()
def _do_compute_1k_multiscale(self, dt):
@@ -632,6 +708,9 @@ direction is {}!'.format(step_id,MeshDir[req_dir],MeshDir[my_dir])
raise NotImplementedError()
def _do_compute_2k_multiscale_comm(self, dt):
raise NotImplementedError()
+
+ def _pre_apply(self):
+ pass
@staticmethod
def supports_kernel_splitting():
@@ -647,3 +726,63 @@ direction is {}!'.format(step_id,MeshDir[req_dir],MeshDir[my_dir])
return False
+ def _exec_transpose(self,kernel,mode):
+ velocity = self.velocity
+ all_evts = []
+ evts = []
+ for Vi in velocity.gpu_data:
+ evt = kernel(Vi,Vi,wait_for=velocity.events)
+ evts.append(evt)
+ velocity.events += evts
+ all_evts+=evts
+
+ for (fg,fp) in self.fields_on_part.iteritems():
+ evts = []
+ for (g,p) in zip(fg.gpu_data,fp):
+ if mode=='g2g':
+ evt = kernel(g,g,wait_for=fg.events)
+ elif mode=='g2p':
+ evt = kernel(g,p,wait_for=fg.events)
+ elif mode=='p2g':
+ evt = kernel(p,g,wait_for=fg.events)
+ else:
+ raise ValueError('Unknown mode \'{}\'.'.format(mode))
+ evts.append(evt)
+ fg.events += evts
+ all_evts += evts
+ return all_evts
+
+ def _build_tranpose_funcs(self,Txy,Tyx,Txz,Tzx):
+
+ def build_none(fname):
+ def transposition_kernel(**kargs):
+ msg='The transposition kernel {} has not been collected.'
+ raise RuntimeError(msg.format(fname))
+ return transposition_kernel
+
+ def build_func(fprefix,fname,src2dst,kernel):
+ def transposition_kernel(**kargs):
+ if __VERBOSE__:
+ print fname
+ callback_profiler.tic(fprefix)
+ evts = self._exec_transpose(kernel,src2dst)
+ callback_profiler.tac(fprefix,evt=evts)
+ return evts
+ return transposition_kernel
+
+ axes = ['xy','yx','xz','zx']
+ kernels = [Txy,Tyx,Txz,Tzx]
+ for axe,kernel in zip(axes,kernels):
+ fprefix = 'do_transpose_{}'.format(axe)
+ for src2dst in ['g2g','g2p','p2g']:
+ fname = '_{}_{}'.format(fprefix,src2dst)
+ if kernel is None:
+ func = build_none(fname)
+ else:
+ func = build_func(fprefix,fname,src2dst,kernel)
+ callback_profiler.register_tasks(fprefix)
+ setattr(self,fname,func)
+
+
+
+
diff --git a/hysop/gpu/gpu_stretching.py b/hysop/old/gpu.old/gpu_stretching.py
similarity index 88%
rename from hysop/gpu/gpu_stretching.py
rename to hysop/old/gpu.old/gpu_stretching.py
index 4efd80dae257dcd5e037873854f4b6af3c39fffb..c536b09d5be977532396274ccd08efece4af47f1 100644
--- a/hysop/gpu/gpu_stretching.py
+++ b/hysop/old/gpu.old/gpu_stretching.py
@@ -4,26 +4,26 @@
Stretching on GPU
"""
from hysop import __VERBOSE__, __DEBUG__
-from hysop.constants import debug, np, S_DIR, HYSOP_MPI_REAL, ORDERMPI, \
+from hysop.constants import debug, np, DirectionLabels, hysop.core.mpi_REAL, ORDERMPI, \
HYSOP_REAL, ORDER
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.tools.io_utils import IO
from hysop.operator.discrete.discrete import DiscreteOperator, get_extra_args_from_method
-from hysop.mpi import Wtime
-from hysop.gpu import cl
-from hysop.gpu.gpu_operator import GPUOperator
-from hysop.gpu.gpu_kernel import KernelLauncher
-from hysop.gpu.gpu_discrete import GPUDiscreteField
+from hysop.core.mpi import Wtime
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.gpu_operator import GPUOperator
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.opencl.opencl_discrete import OpenClDiscreteField
from hysop.tools.profiler import FProfiler
-from hysop.methods_keys import TimeIntegrator, SpaceDiscretisation, Formulation, Support
+from hysop.methods import TimeIntegrator, SpaceDiscretization, Formulation, Support
from hysop.numerics.odesolvers import Euler, RK2, RK3, RK4
from hysop.numerics.finite_differences import FDC2, FDC4
from hysop.operator.discrete.stretching import Conservative, GradUW
-from hysop.codegen.kernels.stretching import CachedStretchingKernel
-from hysop.gpu.tools import KernelAutotuner
+from hysop.backend.device.codegen.kernels.stretching import CachedStretchingKernel
+from hysop.backend.device.opencl.opencl_tools import KernelAutotuner
class GPUStretching(DiscreteOperator, GPUOperator):
@@ -66,14 +66,14 @@ class GPUStretching(DiscreteOperator, GPUOperator):
self.velocity = velocity
# order of spatial scheme
- self.order = 2 if self.method[SpaceDiscretisation] is FDC2 else 4
+ self.order = 2 if self.method[SpaceDiscretization] is FDC2 else 4
# Worksize handling
self._cl_work_size = 0
## GPU allocations
for field in variables:
- GPUDiscreteField.fromField(self.cl_env, field,
+ OpenClDiscreteField.fromField(self.cl_env, field,
self.gpu_precision, simple_layout=False)
if field.allocate():
self.size_global_alloc += field.mem_size
@@ -105,11 +105,11 @@ class GPUStretching(DiscreteOperator, GPUOperator):
msg += 'but only {} time integrators have been implemented in the GPU Stretching Operator!'.format(self._supported_time_integrators)
raise NotImplementedError(msg)
- if SpaceDiscretisation not in method.keys():
+ if SpaceDiscretization not in method.keys():
msg = 'No space discretization specified for the GPU Stretching Operator!'
raise ValueError(msg)
- elif method[SpaceDiscretisation] not in self._supported_space_discretizations:
- msg = 'Asked for a \'{}\' space discretization '.format(method[SpaceDiscretisation])
+ elif method[SpaceDiscretization] not in self._supported_space_discretizations:
+ msg = 'Asked for a \'{}\' space discretization '.format(method[SpaceDiscretization])
msg += 'but only {} space discretizations have been implemented in the GPU Stretching Operator!'.format(self._supported_space_discretizations)
raise NotImplementedError(msg)
@@ -139,7 +139,7 @@ class GPUStretching(DiscreteOperator, GPUOperator):
dt = typegen.make_floatn([0.01],1)
- from hysop.codegen.structs.mesh_info import MeshInfoStruct
+ from hysop.backend.device.codegen.structs.mesh_info import MeshInfoStruct
mesh_info = MeshInfoStruct.build_instance_from_mesh(typegen, mesh)
mesh_info_buffer = cl.Buffer(context, cl.mem_flags.READ_ONLY | cl.mem_flags.COPY_HOST_PTR,
hostbuf=mesh_info)
@@ -168,7 +168,7 @@ class GPUStretching(DiscreteOperator, GPUOperator):
self.size_local_alloc += cached_bytes
kernels = {}
- kernels['stretching'] = KernelLauncher(kernel, cl_env.queue, gwi, lwi)
+ kernels['stretching'] = OpenClKernelLauncher(kernel, cl_env.queue, gwi, lwi)
self.kernels = kernels
def _gen_and_build_kernel(self, local_size, global_size, kernel_args,
diff --git a/hysop/gpu/gpu_transfer.py b/hysop/old/gpu.old/gpu_transfer.py
similarity index 95%
rename from hysop/gpu/gpu_transfer.py
rename to hysop/old/gpu.old/gpu_transfer.py
index b915bff1812b328f658d9aa67b2e7371145b1171..4694b63da6063679091f834501919d96c5b033c1 100644
--- a/hysop/gpu/gpu_transfer.py
+++ b/hysop/old/gpu.old/gpu_transfer.py
@@ -1,5 +1,5 @@
from hysop.operator.computational import Computational
-from hysop.methods_keys import Support
+from hysop.methods import Support
from hysop.operator.continuous import opsetup, opapply
from hysop.numerics.update_ghosts import UpdateGhostsFull
@@ -47,7 +47,7 @@ class DataTransfer(Computational):
assert isinstance(run_till, list)
self._run_till = run_till
- from hysop.mpi.topology import Cartesian
+ from hysop.core.mpi.topology import Cartesian
if not isinstance(self._target, Cartesian):
# target operator must wait for
# the end of this operator to apply.
@@ -61,9 +61,9 @@ class DataTransfer(Computational):
for op in self._run_till:
op.wait_for(self)
topo = self.variables.values()[0]
- self._d_var = [v.discreteFields[topo] for v in self.variables]
+ self._d_var = [v.discrete_fields[topo] for v in self.variables]
- from hysop.mpi.topology import Cartesian
+ from hysop.core.mpi.topology import Cartesian
source_is_topo = isinstance(self._source, Cartesian)
target_is_topo = isinstance(self._target, Cartesian)
diff --git a/hysop/old/gpu.old/kernel_autotuner.py b/hysop/old/gpu.old/kernel_autotuner.py
new file mode 100644
index 0000000000000000000000000000000000000000..95bd0340994b64271113a207806ca596ca42d652
--- /dev/null
+++ b/hysop/old/gpu.old/kernel_autotuner.py
@@ -0,0 +1,598 @@
+
+from hysop.constants import __DEBUG__, __VERBOSE__, __KERNEL_DEBUG__, \
+ DEFAULT_AUTOTUNER_FLAG, DEFAULT_AUTOTUNER_PRUNE_THRESHOLD
+from hysop.tools.io_utils import IO
+from hysop.tools.misc import Utils
+
+from hysop.constants import np, AutotunerFlags
+from hysop.backend.device.opencl import cl, KERNEL_DUMP_FOLDER
+
+import os, itertools, hashlib, gzip, pickle
+
+class KernelGenerationError(RuntimeError):
+ pass
+
+class OpenClKernelStatistics(object):
+ """Execution statistics from kernel events.
+ """
+ def __init__(self,nruns=0,events=None):
+ if events is not None:
+ p0 = events[0].profile
+ t0 = p0.end - p0.start
+ total = 0
+ maxi = t0
+ mini = t0
+ for evt in events:
+ dt = evt.profile.end - evt.profile.start
+ total += dt
+ if dt<mini:
+ mini = dt
+ if dt>maxi:
+ maxi = dt
+
+ self.tot = total
+ self.min = mini
+ self.max = maxi
+ self.mean = total/len(events)
+ else:
+ self.tot = None
+ self.min = None
+ self.max = None
+ self.mean = None
+ self.nruns = nruns
+
+ def __str__(self):
+ mini = self.min * 1e-6
+ maxi = self.max * 1e-6
+ total = self.tot * 1e-6
+ mean = self.mean * 1e-6
+ return 'min={:.2f}ms, max={:.2f}ms, mean={:.2f}ms (nruns={})'.format(mini,maxi,mean,self.nruns)
+
+ @staticmethod
+ def cmp(lhs,rhs):
+ if lhs.mean==rhs.mean:
+ if lhs.max==rhs.max:
+ if lhs.min==rhs.min:
+ return 0
+ elif lhs.min>rhs.min:
+ return 1
+ else:
+ return -1
+ elif lhs.max > rhs.max:
+ return 1
+ else:
+ return -1
+ elif lhs.mean>rhs.mean:
+ return 1
+ else:
+ return -1
+ def __lt__(self, other):
+ return self.cmp(self, other) < 0
+ def __gt__(self, other):
+ return self.cmp(self, other) > 0
+ def __eq__(self, other):
+ return self.cmp(self, other) == 0
+ def __le__(self, other):
+ return self.cmp(self, other) <= 0
+ def __ge__(self, other):
+ return self.cmp(self, other) >= 0
+ def __ne__(self, other):
+ return self.cmp(self, other) != 0
+
+class AutotunerConfig(object):
+
+ _default_initial_runs = {
+ AutotunerFlags.ESTIMATE: 1,
+ AutotunerFlags.MEASURE: 2,
+ AutotunerFlags.PATIENT: 4,
+ AutotunerFlags.EXHAUSTIVE: 8
+ }
+
+ def __init__(self,
+ autotuner_flag=DEFAULT_AUTOTUNER_FLAG,
+ prune_threshold=DEFAULT_AUTOTUNER_PRUNE_THRESHOLD,
+ verbose=__VERBOSE__,
+ debug=__KERNEL_DEBUG__,
+ dump_folder=KERNEL_DUMP_FOLDER,
+ override_cache=False,
+ nruns=None):
+
+ self.autotuner_flag = autotuner_flag
+ self.prune_threshold = prune_threshold
+ self.verbose = verbose
+ self.debug = debug
+ self.override_cache = override_cache
+ if (nruns is None):
+ self.nruns = AutotunerConfig._default_initial_runs[autotuner_flag]
+ else:
+ if (nruns<1):
+ raise ValueError('nruns<1.')
+ self.nruns = nruns
+
+class KernelAutotuner(object):
+ cache_dir = IO.cache_path() + '/autotune'
+ config_file = cache_dir+'/configs.pklz'
+ if not os.path.exists(cache_dir):
+ os.makedirs(cache_dir)
+
+ """OpenCl kernel work group size autotuner.
+ """
+ def __init__(self,name,work_dim,build_opts,autotuner_config,local_work_dim=None):
+ """Initialize a KernelAutotuner.
+
+ Parameters
+ ----------
+ work_dim: int
+ Work dimension used in targetted OpenCL kernels.
+ local_work_dim: int
+ Work dimension used in workgroup sizes.
+ """
+
+ if not isinstance(autotuner_config, AutotunerConfig):
+ raise ValueError('autotuner_config is not an AutotunerConfig.')
+
+ self.name = name
+ self.work_dim = work_dim
+ self.local_work_dim = work_dim if (local_work_dim is None) else local_work_dim
+ self.build_opts = build_opts
+ self.autotuner_config = autotuner_config
+
+ self.enable_variable_workload = False
+ self.workloads = [(1,1,1)]
+
+ self.extra_parameters = None
+
+ self._init_and_load_cache()
+ self._load_default_filters()
+
+ @staticmethod
+ def _hash_func():
+ return hashlib.new('sha256')
+
+ @staticmethod
+ def _load_configs():
+ configs = {}
+ if os.path.isfile(KernelAutotuner.config_file):
+ with gzip.open(KernelAutotuner.config_file, 'rb') as f:
+ configs.update(pickle.loads(f.read()))
+ return configs
+
+ @staticmethod
+ def _make_config_key(work_dim, typegen, build_opts):
+ concat_unique_list = lambda L: '['+'_'.join([str(val) for val in frozenset(L)])+']'
+ hasher = KernelAutotuner._hash_func()
+ hasher.update('{}_{}_{}'.format(work_dim, concat_unique_list(build_opts),
+ typegen.__repr__()))
+ return hasher.hexdigest()
+
+ def _update_configs(self):
+ configs = KernelAutotuner._load_configs()
+ if configs.keys() != self.configs.keys():
+ configs.update(self.configs)
+ with gzip.open(KernelAutotuner.config_file, 'wb') as f:
+ pickle.dump(configs,f)
+ self.configs = configs
+
+ def _init_and_load_cache(self):
+ cache_file = '{}/{}.pklz'.format(KernelAutotuner.cache_dir,self.name.replace(' ','_'))
+ if os.path.isfile(cache_file):
+ with gzip.open(cache_file, 'rb') as f:
+ self.results = pickle.loads(f.read())
+ else:
+ self.results = {}
+ self.configs = KernelAutotuner._load_configs()
+ self.cache_file = cache_file
+
+ def _dump_cache(self):
+ with gzip.open(self.cache_file, 'wb') as f:
+ pickle.dump(self.results,f)
+
+
+ def enable_variable_workitem_workload(self, max_workitem_workload):
+ max_workitem_workload = np.asarray(max_workitem_workload)
+ assert (max_workitem_workload>0).all()
+
+ def _compute_pows(max_workload):
+ pows = [1]
+ workload = 1
+ while(workload<max_workload):
+ workload <<= 1
+ pows.append(workload)
+ return pows
+
+ self.enable_variable_workload = True
+ if np.isscalar(max_workitem_workload):
+ workloads = _compute_pows(max_workitem_workload)
+ workloads = itertools.product(workloads, repeat=3)
+ else:
+ workloads = [_compute_pows(mww) for mww in max_workitem_workload]
+ workloads = itertools.product(*workloads)
+ self.workloads = [w for w in workloads]
+
+ def register_extra_parameter(self,name, values):
+ if self.extra_parameters is None:
+ self.extra_parameters = {}
+ self.extra_parameters[name] = values
+
+ def add_filter(self,fname, f):
+ self.filters[fname] = f
+ return self
+
+ def get_candidates(self,**kargs):
+ return np.asarray([c for c in self._get_wi_candidates(**kargs)])
+
+ def get_workloads(self,global_size):
+ def F(wl):
+ return (wl[0]<=global_size[0]) and (wl[1]<=global_size[1]) and (wl[2]<=global_size[2])
+ candidates = itertools.ifilter(F, self.workloads)
+ return np.asarray([c for c in candidates])
+
+ def get_extra_parameters(self):
+ if self.extra_parameters is None:
+ return [None]
+ else:
+ return itertools.product(*self.extra_parameters.values())
+
+ def bench(self,typegen,work_size,kernel_args,
+ kernel_generator = None,
+ get_max_global_size = None,
+ **kargs):
+
+ assert 'global_size' not in kargs, \
+ 'global_size has been replaced by work_size, due to the variable work per workitem option.'
+
+ if np.isscalar(work_size):
+ work_size = [work_size]
+ else:
+ work_size = list(work_size)
+ work_size += [1]*(3-len(work_size))
+ work_size = np.asarray(work_size)
+ ws = tuple(work_size,)
+
+ if not isinstance(kernel_args, list):
+ msg='kernel_args should be a list.'
+ raise ValueError(msg)
+
+ if (get_max_global_size is None):
+ get_max_global_size = lambda work_size, work_load, **kargs: \
+ (work_size+workload-1)/workload
+
+ platform = typegen.platform
+ device = typegen.device
+ ctx = typegen.context
+
+ verbose = self.autotuner_config.verbose
+ if verbose:
+ print '== Kernel {} Autotuning =='.format(self.name)
+ print 'platform: {}'.format(platform.name)
+ print 'device: {}'.format(device.name)
+ print 'ctx: {}'.format(ctx)
+ print 'work_size: {}'.format(work_size)
+ print 'fbtype: {}'.format(typegen.fbtype)
+ print 'build_opts: {}'.format(self.build_opts)
+
+ config = KernelAutotuner._make_config_key(self.work_dim, typegen, self.build_opts)
+ if config not in self.configs.keys():
+ self.configs[config] = {'work_dim':self.work_dim,
+ 'build_opts':self.build_opts,
+ 'typegen':typegen.__repr__()}
+ self._update_configs()
+ if config not in self.results.keys():
+ self.results[config] = {}
+ results = self.results[config]
+
+ best_workload = None
+ best_global_size = None
+ best_local_size = None
+ best_stats = None
+ best_extra_params = None
+
+ dump_cache = False
+
+ separator = '_'*100
+ indent = lambda i: ' '*i
+
+ for extra_parameters in self.get_extra_parameters():
+ if self.extra_parameters is None:
+ extra_parameters = {}
+ else:
+ extra_parameters = dict(zip(self.extra_parameters.keys(), extra_parameters))
+
+ params_hash = hashlib.sha256(str(hash(frozenset(sorted(extra_parameters.items()))))).hexdigest()
+ params_hash = params_hash[:8]
+
+ best_params_workload = None
+ best_params_global_size = None
+ best_params_local_size = None
+ best_params_stats = None
+
+ if verbose:
+ print separator
+ print '::Current tuning parameters:: {}'.format(extra_parameters)
+
+ workloads = self.get_workloads(work_size)
+ for workload in workloads:
+ workload=np.asarray(workload)
+ max_global_size = get_max_global_size(work_size, workload, **extra_parameters)
+
+ best_workload_global_size = None
+ best_workload_local_size = None
+ best_workload_stats = None
+ best_workload_candidate = None
+ best_workload_ids = None
+
+ if verbose:
+ print separator
+ print indent(1)+'::Current workload {}::'.format(workload)
+ print indent(2)+'-> global_size is set to {}'.format(max_global_size)
+
+ candidates = self.get_candidates(ctx=ctx,device=device,
+ max_global_size=max_global_size,**kargs)
+ unpruned_candidates = np.zeros_like(candidates)
+ nruns=self.autotuner_config.nruns
+
+ step=0
+ all_pruned=False
+ while step==0 or candidates.shape[0]>1:
+ stats = []
+ pruned_count = 0
+ unpruned_count = 0
+
+ if verbose and candidates.shape[0]>0:
+ msg='\n'+indent(2)+'Step {} :: running {} candidates over {} runs:'
+ print msg.format(step,candidates.shape[0],nruns)
+
+ for local_work_size in candidates:
+ local_work_size = np.asarray(local_work_size)
+ lwi = tuple(local_work_size)
+
+ try:
+ (_kernel,_kernel_args,src_hash, global_size) = kernel_generator(
+ ctx=ctx,device=device,
+ work_size=work_size,work_load=workload,local_work_size=lwi,
+ build_opts=self.build_opts,
+ kernel_args=kernel_args,
+ extra_parameters=extra_parameters,
+ **kargs)
+ except KernelGenerationError:
+ pruned_count += 1
+ continue
+
+ global_size = np.asarray(global_size)
+ gwi = tuple(global_size)
+
+ update=False
+ pms = params_hash
+
+ if (not self.autotuner_config.override_cache) \
+ and src_hash in results.keys() \
+ and pms in results[src_hash].keys() \
+ and ws in results[src_hash][pms].keys() \
+ and gwi in results[src_hash][pms][ws].keys() \
+ and lwi in results[src_hash][pms][ws][gwi].keys():
+
+ stat = self.results[config][src_hash][pms][ws][gwi][lwi]
+ if stat.nruns >= nruns:
+ if self.autotuner_config.verbose:
+ print indent(3)+'{} {} => {} (cached)'.format(gwi, lwi, stat)
+ unpruned_candidates[unpruned_count,:] = local_work_size
+ unpruned_count+=1
+ stats.append(stat)
+ continue
+ else:
+ update=True
+
+ if (best_stats is not None):
+ current_best_stats = best_stats
+ elif (best_params_stats is not None):
+ current_best_stats = best_params_stats
+ elif (best_workload_stats is not None):
+ current_best_stats = best_workload_stats
+ else:
+ current_best_stats = None
+
+ (stat,pruned) = self._bench_one(ctx,device,gwi,lwi,_kernel,_kernel_args,nruns,
+ current_best_stats)
+
+ if not pruned:
+ unpruned_candidates[unpruned_count,:] = local_work_size
+ unpruned_count+=1
+ status='update' if update else 'new'
+ stats.append(stat)
+ else:
+ pruned_count+=1
+ status='pruned'
+
+ if verbose:
+ print indent(3)+'{} {} => {} ({})'.format(gwi, lwi, stat, status)
+
+ if not pruned:
+ if src_hash not in results.keys():
+ results[src_hash] = {}
+ if pms not in results[src_hash].keys():
+ results[src_hash][pms] = {}
+ if ws not in results[src_hash][pms].keys():
+ results[src_hash][pms][ws] = {}
+ if gwi not in results[src_hash][pms][ws].keys():
+ results[src_hash][pms][ws][gwi] = {}
+ results[src_hash][pms][ws][gwi][lwi] = stat
+ dump_cache = True
+
+ all_pruned = (pruned_count==candidates.shape[0])
+ if unpruned_count+pruned_count!=candidates.shape[0]:
+ raise RuntimeError()
+ if all_pruned:
+ break
+
+ keep = max(1,unpruned_count//2)
+ best_workload_ids=Utils.argsort(stats)[:keep]
+ candidates=unpruned_candidates[best_workload_ids,:]
+
+ nruns *= 2
+ step += 1
+
+ if all_pruned:
+ if verbose:
+ print separator
+ print indent(1)+' Workload {} winner for kernel {}:'.format(workload, self.name)
+ print indent(2)+'no winner (all candidates were pruned)'
+ continue
+
+ if (candidates.shape[0]!=1 or len(best_workload_ids)!=1):
+ raise RuntimeError()
+
+ if dump_cache:
+ self.results[config] = results
+ self._dump_cache()
+ dump_cache=False
+
+ best_workload_id = best_workload_ids[0]
+ best_workload_stats = stats[best_workload_id]
+ best_workload_candidate = candidates[0]
+
+ best_workload_local_size = best_workload_candidate
+ (_,_,_,best_workload_global_size) = kernel_generator(
+ ctx=ctx,device=device,
+ work_size=work_size,work_load=workload,
+ local_work_size=best_workload_local_size,
+ build_opts=self.build_opts,
+ kernel_args=kernel_args,
+ extra_parameters=extra_parameters,
+ **kargs)
+
+ if verbose:
+ print separator
+ print indent(1)+' Workload {} winner for kernel {}:'.format(workload, self.name)
+ print indent(2)+'{} {} => {}'.format(best_workload_global_size,
+ best_workload_local_size, best_workload_stats)
+
+ if (best_params_stats is None) or (best_workload_stats<best_workload_stats):
+ best_params_workload = workload
+ best_params_stats = best_workload_stats
+ best_params_global_size = best_workload_global_size
+ best_params_local_size = best_workload_local_size
+
+ if verbose:
+ print separator
+ print ' Current parameters winner for kernel {}:'.format(self.name)
+ if (best_params_stats is None):
+ print indent(1)+'no winner (all candidates were pruned)'
+ else:
+ print indent(1)+'{} {} => {}'.format(best_params_global_size,
+ best_params_local_size, best_params_stats)
+
+ if (best_params_stats is not None) and \
+ ((best_stats is None) or (best_params_stats<best_stats)):
+ best_workload = best_params_workload
+ best_stats = best_params_stats
+ best_global_size = best_params_global_size
+ best_local_size = best_params_local_size
+ best_extra_params = extra_parameters
+
+ if verbose:
+ print separator
+ print ' BEST OVERALL RESULT for kernel {}:'.format(self.name)
+ print ' => Extra params: {}'.format(best_extra_params)
+ print ' => WL={} G={} L={} => {}'.format(best_workload, best_global_size, best_local_size,
+ best_stats)
+ print separator
+ print
+
+ return (best_global_size, best_local_size, best_stats, best_workload, best_extra_params)
+
+
+ def _bench_one(self,ctx,device,global_size,local_work_size,kernel,kernel_args,nruns,
+ best_stat):
+
+ assert(nruns>=1)
+ profiling_enable=cl.command_queue_properties.PROFILING_ENABLE
+ kernel.set_args(*kernel_args)
+
+
+ evts = []
+ with cl.CommandQueue(ctx,device,profiling_enable) as queue:
+ evt = cl.enqueue_nd_range_kernel(queue, kernel, global_size, local_work_size)
+ evts.append(evt)
+ stats = OpenClKernelStatistics(events=evts, nruns=1)
+ if (best_stat is None):
+ pruned = False
+ else:
+ pruned = (stats.min > self.autotuner_config.prune_threshold*best_stat.max)
+
+ if not pruned and nruns>1:
+ with cl.CommandQueue(ctx,device,profiling_enable) as queue:
+ for i in xrange(nruns-1):
+ evt = cl.enqueue_nd_range_kernel(queue, kernel, global_size, local_work_size)
+ evts.append(evt)
+ stats = OpenClKernelStatistics(events=evts,nruns=nruns)
+ return (stats, pruned)
+
+ def _get_wi_candidates(self,ctx,device,max_global_size,**kargs):
+ pows = []
+ size = 1
+
+ max_size = device.max_work_group_size
+ while(size<=max_size):
+ pows.append(size)
+ size <<= 1
+ pows = np.asarray(pows)
+
+ product = []
+ for i in xrange(self.work_dim):
+ good = (pows<=max_global_size[i])
+ product.append(pows[good])
+ for i in xrange(3-self.work_dim):
+ product.append([1])
+ candidates = itertools.product(*product)
+
+ for fname,f in self.filters.iteritems():
+ F = f(ctx=ctx,device=device,max_global_size=max_global_size,**kargs)
+ candidates = itertools.ifilter(F, candidates)
+ return candidates
+
+ def _load_default_filters(self):
+ self.filters = {}
+ self.add_filter('dim_reqs',self._dim_filter)
+ self.add_filter('minmax_wi',self._minmax_workitems_filter)
+
+ #default filters
+ def _dim_filter(self,device,**kargs):
+ work_dim = self.local_work_dim
+ max_wi_dim = device.max_work_item_dimensions
+ return lambda local_work_size: (work_dim<=max_wi_dim) and \
+ (work_dim==3
+ or (work_dim==2 and local_work_size[2]==1)
+ or (work_dim==1 and local_work_size[1]==1 and local_work_size[2]==1))
+ def _minmax_workitems_filter(self, device, min_load_factor=None, **kargs):
+ def filter(local_work_size, **kargs):
+ max_wg_size = device.max_work_group_size
+ wi=1
+ for i in xrange(3):
+ wi*=local_work_size[i]
+ if min_load_factor is None:
+ return (wi<=max_wg_size)
+ else:
+ return (wi>=max_wg_size/min_load_factor) and (wi<=max_wg_size)
+ return filter
+
+ #user available filters
+ def ordering_filter(self, **kargs):
+ return lambda local_work_size: (local_work_size[2]<=local_work_size[1]) \
+ and (local_work_size[1]<=local_work_size[0])
+ def min_workitems_per_direction(self, min_local_size, **kargs):
+ if np.isscalar(min_local_size):
+ min_local_size = [min_local_size]
+ else:
+ min_local_size = list(min_local_size)
+ min_local_size = np.asarray(min_local_size)
+ wd = self.work_dim
+ return lambda local_work_size,**kargs: (local_work_size[:wd]>=min_local_size).all()
+ def max_workitems_per_direction(self, max_local_size, **kargs):
+ if np.isscalar(max_local_size):
+ max_local_size = [max_local_size]
+ else:
+ max_local_size = list(max_local_size)
+ max_local_size = np.asarray(max_local_size)
+ wd = self.work_dim
+ return lambda local_work_size,**kargs: (local_work_size[:wd]<=max_local_size).all()
+
diff --git a/hysop/gpu/kernel_benchmark.py b/hysop/old/gpu.old/kernel_benchmark.py
similarity index 99%
rename from hysop/gpu/kernel_benchmark.py
rename to hysop/old/gpu.old/kernel_benchmark.py
index 1eeebf8e6be84eb2d43634795d61bf2add5fc71e..c7d739937404a17067800e800475738f1e65f266 100644
--- a/hysop/gpu/kernel_benchmark.py
+++ b/hysop/old/gpu.old/kernel_benchmark.py
@@ -3,7 +3,7 @@
Package for benchmarking OpenCL kernels.
"""
-from hysop.gpu import cl
+from hysop.backend.device.opencl import cl
from hysop.constants import np, HYSOP_REAL
import pickle
diff --git a/hysop/gpu/multi_gpu_particle_advection.py b/hysop/old/gpu.old/multi_gpu_particle_advection.py
similarity index 96%
rename from hysop/gpu/multi_gpu_particle_advection.py
rename to hysop/old/gpu.old/multi_gpu_particle_advection.py
index c66e0501e3de598d48dcd9ce3283990a8192d350..dc80317eb37fc2a386efbfbad428402b7408683f 100644
--- a/hysop/gpu/multi_gpu_particle_advection.py
+++ b/hysop/old/gpu.old/multi_gpu_particle_advection.py
@@ -5,17 +5,17 @@ Discrete advection representation for Multi-GPU architecture.
"""
from abc import ABCMeta
from hysop.constants import np, debug, HYSOP_INTEGER, HYSOP_REAL, ORDER,\
- HYSOP_MPI_REAL, SIZEOF_HYSOP_REAL
-from hysop.gpu.gpu_particle_advection import GPUParticleAdvection
+ hysop.core.mpi_REAL, SIZEOF_HYSOP_REAL
+from hysop.backend.device.opencl.gpu_particle_advection import GPUParticleAdvection
from hysop.operator.discrete.discrete import get_extra_args_from_method
-from hysop.methods_keys import Support, TimeIntegrator, MultiScale, Remesh
-from hysop.numerics.integrators.runge_kutta2 import RK2
+from hysop.methods import TimeIntegrator, MultiScale, Remesh
+from hysop.numerics.odesolvers import RK2
from hysop.numerics.remeshing import Linear as Linear_rmsh
-from hysop.gpu.gpu_kernel import KernelLauncher
-from hysop.tools.profiler import FProfiler, profile
-from hysop.gpu import cl, CL_PROFILE
-from hysop.mpi import Wtime
-import hysop.tools.numpywrappers as npw
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.tools.profiler import FProfiler
+from hysop.backend.device.opencl import cl, CL_PROFILE
+from hysop.core.mpi import Wtime
+from hysop.tools.numpywrappers import npw
class MultiGPUParticleAdvection(GPUParticleAdvection):
@@ -375,13 +375,13 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
build_options += " -D BUFF_WIDTH=" + str(self._s_buff_width)
prg = self.cl_env.build_src(
src, build_options, 1)
- self.num_advec_and_remesh_comm_l = KernelLauncher(
+ self.num_advec_and_remesh_comm_l = OpenClKernelLauncher(
prg.buff_advec_and_remesh_l, self.cl_env.queue,
(gwi[1], gwi[2]), (32, 1))
- self.num_advec_and_remesh_comm_r = KernelLauncher(
+ self.num_advec_and_remesh_comm_r = OpenClKernelLauncher(
prg.buff_advec_and_remesh_r, self.cl_env.queue,
(gwi[1], gwi[2]), (32, 1))
- self.num_advec_and_remesh = KernelLauncher(
+ self.num_advec_and_remesh = OpenClKernelLauncher(
prg.buff_advec_and_remesh, self.cl_env.queue,
gwi, lwi)
@@ -409,7 +409,7 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
build_options += " -D V_BUFF_WIDTH=" + str(self._v_buff_width)
prg = self.cl_env.build_src(
src, build_options, 1)
- self.num_advec = KernelLauncher(
+ self.num_advec = OpenClKernelLauncher(
prg.buff_advec, self.cl_env.queue,
gwi, lwi)
@@ -429,13 +429,13 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
build_options += " -D BUFF_WIDTH=" + str(self._s_buff_width)
prg = self.cl_env.build_src(
src, build_options, 1)
- self.num_remesh_comm_l = KernelLauncher(
+ self.num_remesh_comm_l = OpenClKernelLauncher(
prg.buff_remesh_l, self._queue_comm_m,
(gwi[1], gwi[2]), (32, 1))
- self.num_remesh_comm_r = KernelLauncher(
+ self.num_remesh_comm_r = OpenClKernelLauncher(
prg.buff_remesh_r, self._queue_comm_p,
(gwi[1], gwi[2]), (32, 1))
- self.num_remesh = KernelLauncher(
+ self.num_remesh = OpenClKernelLauncher(
prg.remesh, self.cl_env.queue,
gwi, lwi)
@@ -629,20 +629,20 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
for b in xrange(self._v_n_blocks):
self._l_recv_v[b] = self._comm.Irecv(
[self._v_l_buff_flat[self._v_block_slice[b]],
- self._v_elem_block, HYSOP_MPI_REAL],
+ self._v_elem_block, hysop.core.mpi_REAL],
source=self._L_rk, tag=17 + 19 * self._L_rk + 59 * b)
self._r_recv_v[b] = self._comm.Irecv(
[self._v_r_buff_flat[self._v_block_slice[b]],
- self._v_elem_block, HYSOP_MPI_REAL],
+ self._v_elem_block, hysop.core.mpi_REAL],
source=self._R_rk, tag=29 + 23 * self._R_rk + 57 * b)
for b in xrange(self._v_n_blocks):
self._send_to_r_v[b] = self._comm.Issend(
[self._v_r_buff_loc_flat[self._v_block_slice[b]],
- self._v_elem_block, HYSOP_MPI_REAL],
+ self._v_elem_block, hysop.core.mpi_REAL],
dest=self._R_rk, tag=17 + 19 * self._comm_rank + 59 * b)
self._send_to_l_v[b] = self._comm.Issend(
[self._v_l_buff_loc_flat[self._v_block_slice[b]],
- self._v_elem_block, HYSOP_MPI_REAL],
+ self._v_elem_block, hysop.core.mpi_REAL],
dest=self._L_rk, tag=29 + 23 * self._comm_rank + 57 * b)
if CL_PROFILE:
for b in xrange(self._v_n_blocks):
@@ -681,8 +681,8 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
advec_gpu_time += (evt.profile.end - evt.profile.start) * 1e-9
self.profiler['comm_gpu_advec_set'] += advec_gpu_time
- def _init_copy(self, simulation, dtCoeff, split_id, old_dir):
- self._exchange_velocity_buffers(simulation.time_step * dtCoeff)
+ def _init_copy(self, simulation, dt_coeff, split_id, old_dir):
+ self._exchange_velocity_buffers(simulation.time_step * dt_coeff)
wait_evt = self.fields_on_grid[0].events
for g, p in zip(self.fields_on_grid[0].gpu_data,
self.fields_on_part[self.fields_on_grid[0]]):
@@ -690,24 +690,25 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
#evt = self.copy(g, p, wait_for=wait_evt)
self._init_events[self.fields_on_grid[0]].append(evt)
- def _init_transpose_xy(self, simulation, dtCoeff, split_id, old_dir):
- self._exchange_velocity_buffers(simulation.time_step * dtCoeff)
+ def _init_transpose_xy(self, simulation, dt_coeff, split_id, old_dir):
+ self._exchange_velocity_buffers(simulation.time_step * dt_coeff)
wait_evt = self.fields_on_grid[0].events
for g, p in zip(self.fields_on_grid[0].gpu_data,
self.fields_on_part[self.fields_on_grid[0]]):
evt = self.transpose_xy(g, p, wait_for=wait_evt)
self._init_events[self.fields_on_grid[0]].append(evt)
- def _init_transpose_xz(self, simulation, dtCoeff, split_id, old_dir):
- self._exchange_velocity_buffers(simulation.time_step * dtCoeff)
+ def _init_transpose_xz(self, simulation, dt_coeff, split_id, old_dir):
+ self._exchange_velocity_buffers(simulation.time_step * dt_coeff)
wait_evt = self.fields_on_grid[0].events
for g, p in zip(self.fields_on_grid[0].gpu_data,
self.fields_on_part[self.fields_on_grid[0]]):
evt = self.transpose_xz(g, p, wait_for=wait_evt)
self._init_events[self.fields_on_grid[0]].append(evt)
- def _compute_advec_comm(self, simulation, dtCoeff, split_id, old_dir):
- dt = simulation.time_step * dtCoeff
+ def _compute_advec_comm(self, simulation, dt_coeff, split_id, old_dir):
+ dt = simulation.time_step * dt_coeff
+
self._todevice_velocity_buffers()
wait_evts = self.velocity.events + self._evt_l_v + self._evt_r_v + \
self._init_events[self.fields_on_grid[0]]
@@ -831,10 +832,10 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
self._cl_mesh_info,
wait_for=wait_list)
- def _compute_1c_comm(self, simulation, dtCoeff, split_id, old_dir):
- dt = simulation.time_step * dtCoeff
+ def _compute_1c_comm(self, simulation, dt_coeff, split_id, old_dir):
+ dt = simulation.time_step * dt_coeff
if self._is2kernel:
- self._compute_advec_comm(simulation, dtCoeff, split_id, old_dir)
+ self._compute_advec_comm(simulation, dt_coeff, split_id, old_dir)
else:
self._todevice_velocity_buffers()
wait_evts = self.velocity.events + \
@@ -847,12 +848,12 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
for b in xrange(self._s_n_blocks_from_l):
self._l_recv[b] = self._comm.Irecv(
[self._s_froml_buff_flat[self._s_block_slice_from_l[b]],
- self._s_elem_block_from_l, HYSOP_MPI_REAL],
+ self._s_elem_block_from_l, hysop.core.mpi_REAL],
source=self._L_rk, tag=888 + self._L_rk + 19 * b)
for b in xrange(self._s_n_blocks_from_r):
self._r_recv[b] = self._comm.Irecv(
[self._s_fromr_buff_flat[self._s_block_slice_from_r[b]],
- self._s_elem_block_from_r, HYSOP_MPI_REAL],
+ self._s_elem_block_from_r, hysop.core.mpi_REAL],
source=self._R_rk, tag=333 + self._R_rk + 17 * b)
# Fill and get the left buffer
@@ -877,7 +878,7 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
self._evt_get_l[b].wait()
self._l_send[b] = self._comm.Issend(
[self._s_l_buff[self._s_block_slice_to_l[b]],
- self._s_elem_block_to_l, HYSOP_MPI_REAL],
+ self._s_elem_block_to_l, hysop.core.mpi_REAL],
dest=self._L_rk, tag=333 + self._comm_rank + 17 * b)
ctime_send_l = Wtime() - ctime
@@ -902,7 +903,7 @@ class MultiGPUParticleAdvection(GPUParticleAdvection):
self._evt_get_r[b].wait()
self._r_send[b] = self._comm.Issend(
[self._s_r_buff[self._s_block_slice_to_r[b]],
- self._s_elem_block_to_r, HYSOP_MPI_REAL],
+ self._s_elem_block_to_r, hysop.core.mpi_REAL],
dest=self._R_rk, tag=888 + self._comm_rank + 19 * b)
ctime_send_r = Wtime() - ctime
diff --git a/hysop/gpu/static_gpu_particle_advection_dir.py b/hysop/old/gpu.old/static_gpu_particle_advection_dir.py
similarity index 59%
rename from hysop/gpu/static_gpu_particle_advection_dir.py
rename to hysop/old/gpu.old/static_gpu_particle_advection_dir.py
index d14e76332eb0064d65da3ecbce0abdbecb7dc665..28faac124cc76b051bbb7acbb4db5bff610190e1 100644
--- a/hysop/gpu/static_gpu_particle_advection_dir.py
+++ b/hysop/old/gpu.old/static_gpu_particle_advection_dir.py
@@ -1,26 +1,32 @@
from hysop import __VERBOSE__
-from hysop.gpu import cl
-from hysop.gpu.gpu_kernel import KernelLauncher
-from hysop.gpu.gpu_particle_advection_dir import GPUParticleAdvectionDir, MeshDir
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.backend.device.opencl.gpu_particle_advection_dir import GPUParticleAdvectionDir, MeshDirection
-from hysop.methods_keys import TimeIntegrator, Remesh, ExtraArgs, \
- Support, Splitting, MultiScale, Interpolation, Precision
+from hysop.methods import TimeIntegrator, Remesh, ExtraArgs, \
+ Support, Splitting, MultiScale, Interpolation, Precision,\
+ StretchingFormulation, BoundaryCondition
from hysop.numerics.odesolvers import Euler, RK2, RK3, RK4
-from hysop.numerics.interpolation import Linear
+from hysop.numerics.interpolation.interpolation import Linear
from hysop.numerics.remeshing import L2_1, L2_2, L2_3, L2_4
from hysop.numerics.remeshing import L4_2, L4_3, L4_4
from hysop.numerics.remeshing import L6_3, L6_4, L6_5, L6_6
from hysop.numerics.remeshing import L8_4
-from hysop.constants import np, S_DIR, StretchingFormulation
-import hysop.tools.numpywrappers as npw
+from hysop.constants import np, DirectionLabels
+from hysop.tools.numpywrappers import npw
-from hysop.codegen.structs.mesh_info import MeshInfoStruct
-from hysop.codegen.kernels.directional_stretching import DirectionalStretchingKernel
+from hysop.backend.device.codegen.structs.mesh_info import MeshInfoStruct
+from hysop.backend.device.codegen.kernels.copy_kernel import CopyKernel
+
+from hysop.backend.device.codegen.kernels.directional_advection import DirectionalAdvectionKernel
+from hysop.backend.device.codegen.kernels.directional_stretching import DirectionalStretchingKernel
+
+from hysop.constants import callback_profiler
class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
##
@@ -35,17 +41,6 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
def __init__(self,**kargs):
super(self.__class__, self).__init__(**kargs)
- #TODO REMOVE
- self.cl_env.queue = cl.CommandQueue(self.cl_env.ctx,self.cl_env.device,cl.command_queue_properties.PROFILING_ENABLE)
- self.bench = {
- 'enqueue_copy': [],
- 'transpose_xy':[],
- 'transpose_yx':[],
- 'transpose_xz':[],
- 'transpose_zx':[],
- 'stretching':[],
- }
-
# Additional method and configuration checks
self._check()
@@ -94,8 +89,8 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
if order<0:
msg='Stretching order < 0'
raise ValueError(msg)
- if formulation not in StretchingFormulation.entries():
- msg='Stretching formulation is not one of {}.'.format(StretchingFormulation.fields().keys())
+ if not isinstance(formulation,StretchingFormulation):
+ msg='Stretching formulation is not one of {}.'.format(StretchingFormulation.svalues())
raise ValueError(msg)
def _initialize_cl_env(self):
@@ -121,13 +116,6 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
self._append_size_constants(
[self.velocity_topo.ghosts()[self.direction]],
prefix='V_GHOSTS_NB', suffix=[''])
- enum = ['I', 'II', 'III']
- self._append_size_constants(
- self._reorder_vect(['NB' + d for d in S_DIR[:self.dim]]),
- prefix='NB_', suffix=enum[:self.dim])
- self._append_size_constants(
- self._reorder_vect(['V_NB' + d for d in S_DIR[:self.dim]]),
- prefix='V_NB_', suffix=enum[:self.dim])
self._append_size_constants([self._is_multi_scale*1],
prefix='ADVEC_IS_MULTISCALE', suffix=[''])
@@ -166,64 +154,42 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
#TODO remove
fields_mesh = self.fields_topo.mesh
- (fields_mesh_info,fields_mesh_info_var) = MeshInfoStruct.create_from_mesh('mesh_info',self.cl_env, \
- self.fields_topo.mesh, self.mesh_dir, self.mesh_state)
+ (fields_mesh_info,fields_mesh_info_var) = MeshInfoStruct.create_from_mesh('field_mesh_info',
+ self.cl_env, self.fields_topo.mesh, self.mesh_dir, self.mesh_state)
self._fields_mesh_info = fields_mesh_info
self._fields_mesh_info_var = fields_mesh_info_var
-
- # elif self._kernel_backend == KernelBackend.CODEGEN:
- # tg = self.cl_env.typegen
- # dim = self.dim
-
- # fields_mesh = self.fields_topo.mesh
- # fields_mesh_info = MeshInfoStruct.create_from_mesh(tg, \
- # fields_mesh, mesh_dir, mesh_state)
- # cl_fields_mesh_info = cl.Buffer(self.cl_env.ctx, cl.mem_flags.READ_ONLY,
- # size=fields_mesh_info.nbytes)
- # cl.enqueue_write_buffer(self.cl_env.queue, cl_fields_mesh_info,\
- # fields_mesh_info).wait()
-
- # velocity_mesh = self.velocity_topo.mesh
- # velocity_mesh_info = MeshInfoStruct.create_from_mesh(tg, \
- # velocity_mesh, mesh_dir, mesh_state)
- # cl_velocity_mesh_info = cl.Buffer(self.cl_env.ctx, cl.mem_flags.READ_ONLY,
- # size=velocity_mesh_info.nbytes)
- # cl.enqueue_write_buffer(self.cl_env.queue, cl_velocity_mesh_info,\
- # velocity_mesh_info).wait()
-
- # if (not self._is_multi_scale) and (fields_mesh_info != velocity_mesh_info):
- # raise RuntimeError()
- # self._fields_mesh_info = fields_mesh_info
- # self._velocity_mesh_info = velocity_mesh_info
- # self._cl_fields_mesh_info = cl_fields_mesh_info
- # self._cl_velocity_mesh_info = cl_velocity_mesh_info
+ velocity_mesh = self.velocity_topo.mesh
+ (velocity_mesh_info,velocity_mesh_info_var) = MeshInfoStruct.create_from_mesh('velocity_mesh_info',
+ self.cl_env, self.velocity_topo.mesh, self.mesh_dir, self.mesh_state)
+
+ self._velocity_mesh_info = velocity_mesh_info
+ self._velocity_mesh_info_var = velocity_mesh_info_var
-
def _collect_transposition_kernel_xy(self):
# Only collected for direction Y (XYZ -> YXZ)
resolution = self.f_resol_dir
defines = ' -D NB_I=NB_Y -D NB_II=NB_X -D NB_III=NB_Z'
- self.transpose_xy = self._build_transpose_kernel_xy(resolution, defines)
+ return self._build_transpose_kernel_xy(resolution, defines)
def _collect_transposition_kernel_xz(self):
# Only collected for direction Z (YXZ -> ZXY)
resolution = self.f_resol_dir
defines = ' -D NB_I=NB_Z -D NB_II=NB_X -D NB_III=NB_Y'
- self.transpose_xz = self._build_transpose_kernel_xz(resolution, defines)
+ return self._build_transpose_kernel_xz(resolution, defines)
def _collect_transposition_kernel_zx(self):
# Only collected for direction Y (ZXY -> YXZ) in sequential
resolution = self.f_resol_dir
defines = ' -D NB_I=NB_Y -D NB_II=NB_X -D NB_III=NB_Z'
- self.transpose_zx = self._build_transpose_kernel_xz(resolution, defines)
+ return self._build_transpose_kernel_xz(resolution, defines)
def _collect_transposition_kernel_yx(self):
# Only collected for direction X (YXZ -> XYZ)
resolution = self.f_resol_dir
defines = ' -D NB_I=NB_X -D NB_II=NB_Y -D NB_III=NB_Z'
- self.transpose_yx = self._build_transpose_kernel_xy(resolution, defines)
+ return self._build_transpose_kernel_xy(resolution, defines)
def _build_transpose_kernel_xy(self, resolution, defines):
build_options = self._build_options + self._size_constants
@@ -247,8 +213,7 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
build_options += defines
prg = self.cl_env.build_src(src, build_options, vec)
-
- return KernelLauncher(prg.transpose_xy, self.cl_env.queue, gwi, lwi)
+ return OpenClKernelLauncher(prg.transpose_xy, self.cl_env.queue, gwi, lwi)
def _build_transpose_kernel_xz(self, resolution, defines):
build_options = self._build_options + self._size_constants
@@ -272,50 +237,51 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
build_options += defines
prg = self.cl_env.build_src(src,build_options,vec)
- return KernelLauncher(prg.transpose_xz, self.cl_env.queue, gwi, lwi)
+ return OpenClKernelLauncher(prg.transpose_xz, self.cl_env.queue, gwi, lwi)
- def _collect_advec_kernel(self):
- """
- Compile OpenCL sources for advection and remeshing kernel.
- """
+ # def _collect_advec_kernel(self):
+ # """
+ # Compile OpenCL sources for advection and remeshing kernel.
+ # """
# Advection
- build_options = self._build_options + self._size_constants
- src, is_noBC, vec, f_space = self._kernel_cfg['advec']
- gwi, lwi = f_space(self.f_resol_dir, vec)
- WINb = lwi[0]
-
- if self._is_multi_scale:
- build_options += " -D MS_FORMULA="
- build_options += self.method[MultiScale].__name__.upper()
-
- if is_noBC:
- build_options += " -D WITH_NOBC=1"
- build_options += " -D WI_NB=" + str(WINb)
- build_options += " -D PART_NB_PER_WI="
- build_options += str(self.f_resol_dir[0] / WINb)
+ # build_options = self._build_options + self._size_constants
+ # src, is_noBC, vec, f_space = self._kernel_cfg['advec']
+ # gwi, lwi = f_space(self.f_resol_dir, vec)
+ # WINb = lwi[0]
+
+ # if self._is_multi_scale:
+ # build_options += " -D MS_FORMULA="
+ # build_options += self.method[MultiScale].__name__.upper()
+
+ # if is_noBC:
+ # build_options += " -D WITH_NOBC=1"
+ # build_options += " -D WI_NB=" + str(WINb)
+ # build_options += " -D PART_NB_PER_WI="
+ # build_options += str(self.f_resol_dir[0] / WINb)
# Build code
- src = [s.replace('RKN', self.method[TimeIntegrator].__name__.lower())
- for s in src]
+ # src = [s.replace('RKN', self.method[TimeIntegrator].__name__.lower())
+ # for s in src]
# Adding remeshing weights for the multiscale advection
- if self._is_multi_scale:
- src.insert(1, self._kernel_cfg['remesh'][0][1])
+ # if self._is_multi_scale:
+ # src.insert(1, self._kernel_cfg['remesh'][0][1])
# Euler integrator
- if self.method[TimeIntegrator] is Euler:
- if not self._is_multi_scale:
- src = [s for s in src if s.find(Euler.__name__.lower()) < 0]
- src[-1] = src[-1].replace('advection', 'advection_euler')
+ # if self.method[TimeIntegrator] is Euler:
+ # if not self._is_multi_scale:
+ # src = [s for s in src if s.find(Euler.__name__.lower()) < 0]
+ # src[-1] = src[-1].replace('advection', 'advection_euler')
- prg = self.cl_env.build_src(
- src,
- build_options,
- vec,
- nb_remesh_components=self.velocity.nb_components)
+ # prg = self.cl_env.build_src(
+ # src,
+ # build_options,
+ # vec,
+ # nb_remesh_components=self.velocity.nb_components)
- self._advec = KernelLauncher(
- prg.advection_kernel, self.cl_env.queue, gwi, lwi)
+ # callback_profiler.register_tasks('advection')
+ # self._advec = OpenClKernelLauncher(
+ # prg.advection_kernel, self.cl_env.queue, gwi, lwi)
def _collect_remesh_kernel(self):
# remeshing
@@ -330,14 +296,31 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
build_options += " -D WI_NB=" + str(WINb)
build_options += " -D PART_NB_PER_WI="
build_options += str(self.f_resol_dir[0] / WINb)
+
+ enum = ['I', 'II', 'III']
+ comp = self._reorder_vect(['NB' + d for d in DirectionLabels[:self.dim]])
+ vcomp = self._reorder_vect(['V_NB' + d for d in DirectionLabels[:self.dim]])
+ for i,suffix in enumerate(enum[:self.dim]):
+ build_options += ' -D NB_{}={}'.format(suffix,comp[i])
+ for i,suffix in enumerate(enum[:self.dim]):
+ build_options += ' -D V_NB_{}={}'.format(suffix,vcomp[i])
self._remesh = {}
+ cnames = []
for rc in self.required_components:
prg = self.cl_env.build_src(
src, build_options, vec,
nb_remesh_components=rc)
- self._remesh[rc] = KernelLauncher(
+ self._remesh[rc] = OpenClKernelLauncher(
prg.remeshing_kernel, self.cl_env.queue, gwi, lwi)
+
+ cname = 'remesh' if len(self.required_components)==1 \
+ else 'remesh_{}'.format(rc)
+ cnames.append(cname)
+ callback_profiler.register_tasks(cname)
+
+ if len(cnames)>1:
+ callback_profiler.register_group('remesh',cnames)
def _collect_advec_remesh_kernel(self):
"""
@@ -371,12 +354,22 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
src[-1] = src[-1].replace('advection', 'advection_euler')
self._advec_and_remesh = {}
+ cnames = []
for rc in self.required_components:
prg = self.cl_env.build_src(
src, build_options, vec,
nb_remesh_components=rc)
- self._advec_and_remesh[rc] = KernelLauncher(
+ self._advec_and_remesh[rc] = OpenClKernelLauncher(
prg.advection_and_remeshing, self.cl_env.queue, gwi, lwi)
+
+ cname = 'advec_remesh' if len(self.required_components)==1 \
+ else 'advec_remesh_{}'.format(rc)
+ callback_profiler.register_tasks(cname)
+ cnames.append(cname)
+
+ if len(cnames)>1:
+ callback_profiler.register_group('remesh',cnames)
+
def _collect_user_kernels(self):
"""
@@ -406,73 +399,134 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
self._collect_stretching_kernels()
if self._has_diffusion:
self._collect_diffusion_kernels()
+
+
+ def _collect_copy_kernels(self):
+
+ if self._use_builtin_copy:
+ super(StaticGPUParticleAdvectionDir,self)._collect_copy_kernels()
+ else:
+ tg = self.cl_env.typegen
+ (fg,fp) = self.fields_on_part.items()[0]
+ src = fp[0]
+ dst = fg.gpu_data[0]
+ vtype = tg.fbtype
+ size = fg.mem_size // (3*tg.FLT_BYTES[vtype])
+
+ (kernel_launcher, kernel_args, kernel_args_mapping, cached_bytes) = \
+ CopyKernel.autotune(self.cl_env,
+ src, dst, vtype, size,
+ restrict=True,
+ build_opts=self._build_options,
+ autotuner_config=self._autotuner_config)
+ self.copy = kernel_launcher
+
+ def _collect_advec_kernel(self):
+
+ ftype = self.cl_env.typegen.fbtype
+ compute_resolution = self.fields_topo.mesh.compute_resolution
+ boundary = BoundaryCondition.PERIODIC
+ rk_scheme = self.method[TimeIntegrator]
+
+ velocity = self.velocity
+ position = self._particle_position
+
+ field_mesh_info = self._fields_mesh_info_var
+ velo_mesh_info = self._velocity_mesh_info_var
+
+ max_dt=0.01
+ max_velocity=1
+ velocity_dx = velo_mesh_info.value['dx'][0]
+
+ (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistic, cached_bytes) = \
+ DirectionalAdvectionKernel.autotune(self.cl_env, ftype,
+ self.dim,self.direction,
+ velocity, position,
+ compute_resolution, field_mesh_info,
+ boundary, rk_scheme,
+ max_dt, max_velocity, velocity_dx,
+ build_opts=self._build_options,
+ autotuner_config=self._autotuner_config)
+
+ callback_profiler.register_tasks('advection')
+ # ftype=ftype,
+ # total_work=total_work,
+ # per_work_statistic=per_work_statistic)
+
+ def do_advec(dt,**kargs):
+ callback_profiler.tic('advection')
+ kernel_args[kernel_args_mapping['dt']] = self.cl_env.precision(dt)
+ evt = kernel_launcher(*kernel_args)
+ callback_profiler.tac('advection',evt=evt)
+ return evt
+
+ self._do_advec = do_advec
+
def _collect_stretching_kernels(self):
self.vorticity = self.fields_on_grid[0]
+ ftype = self.cl_env.typegen.fbtype
compute_resolution = self.fields_topo.mesh.compute_resolution
- boundary='periodic'
+ boundary=self._stretching['boundary']
order=self._stretching['order']
+ formulation=self._stretching['formulation']
+ rk_scheme=self._stretching['rk_scheme']
mesh_info = self._fields_mesh_info_var
dt=0.1
- nruns=16
- force_renew_cache=True
-
- (kernel_launcher, kernel_args, kernel_args_mapping, cached_bytes) = \
- DirectionalStretchingKernel.autotune(self.cl_env,
+ (kernel_launcher, kernel_args, kernel_args_mapping,
+ total_work, per_work_statistic, cached_bytes) = \
+ DirectionalStretchingKernel.autotune(self.cl_env, ftype,
self.dim,self.direction,
- compute_resolution,boundary,order,
+ compute_resolution,
+ boundary,order,
+ formulation, rk_scheme,
self.velocity, self.vorticity,
mesh_info, dt,
- nruns, force_renew_cache,
- self._build_options)
+ build_opts=self._build_options,
+ autotuner_config=self._autotuner_config)
+
+ callback_profiler.register_tasks('stretching',
+ ftype=ftype,
+ total_work=total_work,
+ per_work_statistic=per_work_statistic)
def do_stretch(dt,**kargs):
+ callback_profiler.tic('stretching')
kernel_args[kernel_args_mapping['dt']] = self.cl_env.precision(dt)
evt = kernel_launcher(*kernel_args)
- self.bench['stretching'].append(evt)
+ callback_profiler.tac('stretching',evt=evt)
+ return evt
self._do_stretch = do_stretch
def _collect_diffusion_kernels(self):
self._diffuse = None
-
+ #callback_profiler.register_tasks('diffusion')
+
+
def _exec_kernel(self,kernel):
- name = kernel.function_name()
for (fg,fp) in self.fields_on_part.iteritems():
evts = []
for (g,p) in zip(fg.gpu_data,fp):
- if kernel is self.copy:
- evt = kernel.launch_sizes_in_args(p,g,wait_for=fg.events)
+ if kernel is self.copy and self._use_builtin_copy:
+ evt = kernel.launch_sizes_in_args(g,p,wait_for=fg.events)
else:
- evt = kernel(g,p,wait_for=fg.events)
+ evt = kernel(p,g,wait_for=fg.events)
evts.append(evt)
fg.events += evts
- self.bench[name]+= evts
+ return evts
def _do_copy(self,**kargs):
if __VERBOSE__:
print '_do_copy'
- self._exec_kernel(self.copy)
- def _do_transpose_xy(self,**kargs):
- if __VERBOSE__:
- print '_do_transpose_xy'
- self._exec_kernel(self.transpose_xy)
- def _do_transpose_yx(self,**kargs):
- if __VERBOSE__:
- print '_do_transpose_yx'
- self._exec_kernel(self.transpose_yx)
- def _do_transpose_xz(self,**kargs):
- if __VERBOSE__:
- print '_do_transpose_xz'
- self._exec_kernel(self.transpose_xz)
- def _do_transpose_zx(self,**kargs):
- if __VERBOSE__:
- print '_do_transpose_zx'
- self._exec_kernel(self.transpose_zx)
+ callback_profiler.tic('cpu2gpu')
+ evts = self._exec_kernel(self.copy)
+ callback_profiler.tac('cpu2gpu',evts=evts)
def _do_compute_1k_monoscale(self, dt, **kargs):
@@ -488,8 +542,13 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
+ [self.gpu_precision(dt)]
+ [self._cl_mesh_info]
)
-
+
+ cname = 'advec_remesh' if len(self.required_components)==1 \
+ else 'advec_remesh_{}'.format(nbc)
+ callback_profiler.tic(cname)
evt = self._advec_and_remesh[nbc](*args, wait_for=wait_evts)
+ callback_profiler.tac(cname)
+
fg.events.append(evt)
velocity.events.append(evt)
@@ -499,18 +558,15 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
nbc = velocity.nb_components
# Advection
- args = tuple([
- velocity.gpu_data[self.direction],
- self._particle_position,
- self.gpu_precision(dt),
- self._cl_mesh_info
- ])
- advec_evt = self._advec(*args,wait_for=velocity.events)
+ advec_evt = self._do_advec(dt=dt,wait_for=velocity.events)
velocity.events.append(advec_evt)
-
+
+ # Remesh
for (fg,fp) in self.fields_on_part.iteritems():
- # Remesh
nbc = fg.nb_components
+ cname = 'remesh' if len(self.required_components)==1 \
+ else 'remesh_{}'.format(nbc)
+ callback_profiler.tic(cname)
args = tuple(
[self._particle_position]
+ [fp[i] for i in xrange(nbc)]
@@ -519,9 +575,10 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
)
remesh_evt = self._remesh[nbc](*args, wait_for=[advec_evt])
fg.events.append(remesh_evt)
+ callback_profiler.tac(cname)
if self._has_stretching:
- self._do_stretch(dt)
+ evt=self._do_stretch(dt)
def _do_compute_1k_multiscale(self, dt, **kargs):
@@ -579,7 +636,19 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
)
remesh_evt = self._remesh[nbc](*args, wait_for=[advec_evt])
fg.events.append(remesh_evt)
-
+
+ def _pre_apply(self):
+ super(StaticGPUParticleAdvectionDir,self)._pre_apply()
+ if 'cpu2gpu' not in callback_profiler.tasks:
+ membytes=0
+ for fg in self.fields_on_part.keys():
+ membytes += fg.mem_size
+ callback_profiler.register_tasks('cpu2gpu',membytes=membytes)
+
+ #callback_profiler.register_group('transpose',
+ #['transpose_xy','transpose_yx','transpose_zx','transpose_xz'])
+
+
@staticmethod
def supports_multiscale():
return True
@@ -595,159 +664,3 @@ class StaticGPUParticleAdvectionDir(GPUParticleAdvectionDir):
@staticmethod
def supports_mpi():
return False
-
-
-if __name__=='__main__':
- from hysop.domain.box import Box
- from hysop.fields.continuous import Field
- from hysop.problem.simulation import Simulation
- from hysop.mpi.topology import Cartesian
- from hysop.tools.parameters import Discretization
- from hysop.operator.advection import Advection
-
- dim = 3
- GHOSTS = 0
- NSCALARS = 0
- f_resolution = (65,65,65)[:dim]
- v_resolution = f_resolution
- #v_resolution = (33,33,33)[:dim]
- ghosts = (GHOSTS,)*dim
-
- def initVel(res, *args):
- res[0][...] = 0.
- if dim>1:
- res[1][...] = 0.
- if dim>2:
- res[2][...] = 0.
- return res
- def initVort(res, *args):
- res[0][...] = args[0]
- if dim>1:
- res[1][...] = args[0]*args[0]
- if dim>2:
- res[2][...] = args[0]*args[0]*args[0]
- return res
-
- def initScalar(i):
- def init(res,*args):
- res[0][...] = i+1
- return res
- return init
-
-
- d3d = Discretization(resolution=f_resolution, ghosts=ghosts)
- d3dv = Discretization(resolution=v_resolution, ghosts=ghosts)
-
- box = Box(length=[1.0]*dim, origin=[0.0]*dim)
-
- velo = Field(domain=box, formula=initVel,
- name='Velocity', is_vector=True)
- vorti = Field(domain=box, formula=initVort,
- name='Vorticity', is_vector=True)
- scalars = [ Field(domain=box, formula=initScalar(i),
- name='Scalar_{}'.format(i),
- is_vector=False)
- for i in xrange(NSCALARS) ]
-
- f_topo = Cartesian(box,d3d,dim)
- v_topo = Cartesian(box,d3dv,dim)
-
- dvelo = velo.discretize(v_topo)
- dvorti = vorti.discretize(f_topo)
- dscalars = []
- for s in scalars:
- dscalars.append(s.discretize(f_topo))
-
- def check_values(it=-1):
- tol=0
- failed=False
- print '\nChecking iteration {} -> '.format(it),
-
- suffix=['x','y','z']
- for d in dvelo.data:
- if not np.allclose(d,0.0,rtol=tol):
- print 'Velocity has been altered!'
- failed=True
- for i in xrange(dim):
- delta=dvorti[i] - dvorti[0]**(i+1)
- if not np.allclose(delta,0.0,rtol=tol):
- print 'Checking W{}:'.format(suffix[i])
- if np.isnan(delta).any():
- print '\tContains NaNs!'
- if np.isinf(delta).any():
- print '\tContains inf!'
- delta[~np.isfinite(delta)]=0.0
- vdelta = np.abs(delta)
- L1 = np.sum(vdelta)/vdelta.size
- L2 = np.sqrt(np.sum(vdelta*vdelta))/vdelta.size
- Linf = np.max(vdelta)
- argmax = np.asarray(np.unravel_index(np.argmax(vdelta), vdelta.shape))
- pos = argmax / (np.asarray(vdelta.shape, dtype=float)-1)
- print '\tL1 distance: {}'.format(L1)
- print '\tL2 distance: {}'.format(L2)
- print '\tLinf distance: {} at id {} {}'.format(Linf,argmax,pos)
- failed=True
- for i,s in enumerate(dscalars):
- delta=s[0]-i-1
- if not np.allclose(delta,0.0,rtol=tol):
- print 'Checking rho_{}:'.format(i)
- if np.isnan(delta).any():
- print '\tContains NaNs!'
- if np.isinf(delta).any():
- print '\tContains inf!'
- delta=delta[np.isfinite(delta)]
- L1 = np.sum(np.abs(delta))
- L2 = np.sqrt(np.sum(delta*delta))
- Linf = np.max(np.abs(delta))
- print '\tL1 distance: {}'.format(L1)
- print '\tL2 distance: {}'.format(L2)
- print '\tLinf distance: {}'.format(Linf)
- failed=True
- if failed:
- print 'KO'
- raise RuntimeError('Test failed!')
- else:
- print 'OK'
-
-
- method = {
- Support: 'gpu',
- ExtraArgs: {
- 'stretching': {
- 'formulation': StretchingFormulation.GRADUW,
- 'order':6
- },
- 'split_kernels':True}
- }
-
- advected_fields = [vorti]+scalars
- variables = dict(zip(advected_fields, [f_topo]*len(advected_fields)))
-
- A = Advection(velo, v_topo, variables=variables, method=method)
- A.discretize()
- A.setup()
-
- velo.initialize()
- vorti.initialize()
- for s in scalars:
- s.initialize()
- check_values()
-
- simu = Simulation(start=0.0, end=1.0, time_step=0.2)
- simu.initialize()
-
- i=0
- while not simu.is_over:
- print
- simu.print_state()
-
- A.apply(simu)
-
- A._advec_dir[0]._do_sync(simu)
- for v in A.discrete_fields.values():
- v.to_host()
- #check_values(i)
-
- simu.advance()
- i+=1
-
diff --git a/hysop/old/gpu.old/tests/__init__.py b/hysop/old/gpu.old/tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/gpu/tests/test_advection_nullVelocity.py b/hysop/old/gpu.old/tests/test_advection_nullVelocity.py
similarity index 97%
rename from hysop/gpu/tests/test_advection_nullVelocity.py
rename to hysop/old/gpu.old/tests/test_advection_nullVelocity.py
index 5a26b98c2a6c57a56161730c74b51f25f1aef94e..476c877df1a5a0b0069c9a15a740cc920262c57f 100644
--- a/hysop/gpu/tests/test_advection_nullVelocity.py
+++ b/hysop/old/gpu.old/tests/test_advection_nullVelocity.py
@@ -7,13 +7,13 @@ from hysop.fields.continuous import Field
from hysop.operator.advection import Advection
from hysop.constants import np, HYSOP_REAL
from hysop.problem.simulation import Simulation
-from hysop.methods_keys import TimeIntegrator, Interpolation, Remesh, \
+from hysop.methods import TimeIntegrator, Interpolation, Remesh, \
Support, Splitting, Precision
from hysop.numerics.integrators.runge_kutta2 import RK2
-from hysop.numerics.interpolation import Linear
+from hysop.numerics.interpolation.interpolation import Linear
from hysop.numerics.remeshing import L2_1, L4_2, L6_3, M8Prime
from hysop.tools.parameters import Discretization
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
def setup_2D():
@@ -34,8 +34,8 @@ def assertion_2D(scal, velo, advec):
advec.discretize()
advec.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros_like(scal_d.data[0])
velo_d.data[1][...] = npw.zeros_like(scal_d.data[0])
@@ -59,8 +59,8 @@ def assertion_2D_withPython(scal, velo, advec, advec_py):
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(
np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros(scal_d.data[0].shape)
@@ -87,8 +87,8 @@ def assertion_3D(scal, velo, advec):
advec.discretize()
advec.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros_like(scal_d.data[0])
velo_d.data[1][...] = npw.zeros_like(scal_d.data[0])
@@ -114,8 +114,8 @@ def assertion_3D_withPython(scal, velo, advec, advec_py):
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros_like(scal_d.data[0])
velo_d.data[1][...] = npw.zeros_like(scal_d.data[0])
@@ -823,8 +823,8 @@ def test_rectangular_domain2D():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros_like(scal_d.data[0])
velo_d.data[1][...] = npw.zeros_like(scal_d.data[0])
@@ -867,8 +867,8 @@ def test_rectangular_domain3D():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros_like(scal_d.data[0])
velo_d.data[1][...] = npw.zeros_like(scal_d.data[0])
@@ -912,8 +912,8 @@ def test_2D_vector():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
scal_d.data[1][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros_like(scal_d.data[0])
@@ -961,8 +961,8 @@ def test_3D_vector():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
scal_d.data[1][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
scal_d.data[2][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
diff --git a/hysop/gpu/tests/test_copy.py b/hysop/old/gpu.old/tests/test_copy.py
similarity index 91%
rename from hysop/gpu/tests/test_copy.py
rename to hysop/old/gpu.old/tests/test_copy.py
index e38cd8c6b1fc4d6f76825f4f5d012a7b77aa9e4c..754551f211b9bbb5c220a5122a2e312f90fab499 100644
--- a/hysop/gpu/tests/test_copy.py
+++ b/hysop/old/gpu.old/tests/test_copy.py
@@ -2,11 +2,11 @@
@file hysop.gpu.tests.test_copy
Testing copy kernels.
"""
-from hysop.gpu import cl
+from hysop.backend.device.opencl import cl
from hysop.constants import np
-from hysop.gpu.tools import get_opencl_environment
-from hysop.gpu.gpu_kernel import KernelLauncher
-import hysop.tools.numpywrappers as npw
+from hysop.backend.device.opencl.opencl_tools import get_opencl_environment
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.tools.numpywrappers import npw
def test_copy2D():
@@ -22,7 +22,7 @@ def test_copy2D():
int(resolution[1] / 2))
lwi = (8, 8)
prg = cl_env.build_src(src_copy, build_options, vec)
- copy = KernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
+ copy = OpenClKernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
data_in = npw.asrealarray(np.random.random(resolution))
data_out = npw.empty_like(data_in)
@@ -59,7 +59,7 @@ def test_copy2D_rect():
int(resolution[1] / 2))
lwi = (8, 8)
prg = cl_env.build_src(src_copy, build_options, vec)
- copy_x = KernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
+ copy_x = OpenClKernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
build_options = ""
build_options += " -D NB_I=512 -D NB_II=256"
@@ -69,7 +69,7 @@ def test_copy2D_rect():
int(resolution[0] / 2))
lwi = (8, 8)
prg = cl_env.build_src(src_copy, build_options, vec)
- copy_y = KernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
+ copy_y = OpenClKernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
data_in = npw.asrealarray(np.random.random(resolution))
data_out = npw.empty_like(data_in)
@@ -121,7 +121,7 @@ def test_copy3D():
# Build code
prg = cl_env.build_src(src_copy, build_options, vec)
- init_copy = KernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
+ init_copy = OpenClKernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
data_in = npw.asrealarray(np.random.random(resolution))
data_out = npw.empty_like(data_in)
@@ -161,7 +161,7 @@ def test_copy3D_rect():
int(resolution_x[2]))
lwi = (4, 8, 1)
prg = cl_env.build_src(src_copy, build_options, vec)
- init_copy_x = KernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
+ init_copy_x = OpenClKernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
build_options = ""
build_options += " -D NB_I=32 -D NB_II=16 -D NB_III=64"
@@ -172,7 +172,7 @@ def test_copy3D_rect():
int(resolution_x[2]))
lwi = (4, 8, 1)
prg = cl_env.build_src(src_copy, build_options, vec)
- init_copy_y = KernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
+ init_copy_y = OpenClKernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
build_options = ""
build_options += " -D NB_I=64 -D NB_II=16 -D NB_III=32"
@@ -183,7 +183,7 @@ def test_copy3D_rect():
int(resolution_x[1]))
lwi = (4, 8, 1)
prg = cl_env.build_src(src_copy, build_options, vec)
- init_copy_z = KernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
+ init_copy_z = OpenClKernelLauncher(prg.copy, cl_env.queue, gwi, lwi)
data_in = npw.asrealarray(np.random.random(resolution_x))
data_out = np.empty_like(data_in)
diff --git a/hysop/old/gpu.old/tests/test_gpu_advection_null_velocity.py b/hysop/old/gpu.old/tests/test_gpu_advection_null_velocity.py
new file mode 100644
index 0000000000000000000000000000000000000000..2644fc2237f7700310251c7bdd1e0bce5813a3de
--- /dev/null
+++ b/hysop/old/gpu.old/tests/test_gpu_advection_null_velocity.py
@@ -0,0 +1,436 @@
+"""Testing advection kernels with null velocity.
+"""
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.operator.advection import Advection
+from hysop.constants import np, HYSOP_REAL
+from hysop.problem.simulation import Simulation
+from hysop.methods import TimeIntegrator, Interpolation, Remesh, \
+ Support, Splitting, Precision
+from hysop.numerics.odesolvers import RK2
+from hysop.numerics.interpolation.interpolation import Linear
+from hysop.numerics.remeshing import L2_1, L4_2, L6_3, M8Prime
+from hysop.tools.parameters import Discretization
+from hysop.tools.numpywrappers import npw
+from hysop.problem.simulation import O2, O2FULLHALF
+
+
+d2d = Discretization([33, 33])
+d3d = Discretization([17, 17, 17])
+m1k = {TimeIntegrator: RK2, Interpolation: Linear,
+ Remesh: L4_2, Support: 'gpu_1k', Splitting: O2,
+ Precision: HYSOP_REAL}
+m2k = {TimeIntegrator: RK2, Interpolation: Linear,
+ Remesh: L4_2, Support: 'gpu_2k', Splitting: O2,
+ Precision: HYSOP_REAL}
+
+
+def run_advection(discr, vector_field, method=None):
+ """Create advection operator, ref operator
+ and fields, run scales and python advection,
+ compare results.
+
+ Parameters
+ ----------
+ dicr : :class:`~hysop.tools.parameters.Discretization`
+ chosen discretization for operator --> set domain dimension
+ vector_field: bool
+ True to advect a vector field, else scalar field.
+ method : dictionnary
+ Set scales remeshing type.
+ """
+ dimension = len(discr.resolution)
+ box = Box(length=[1., ] * dimension, origin=[0., ] * dimension)
+ scal = Field(domain=box, name='Scalar', is_vector=vector_field)
+ scal_ref = Field(domain=box, name='Scalar_ref', is_vector=vector_field)
+ velo = Field(domain=box, name='Velocity',
+ formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
+ vectorize_formula=True)
+ # build gpu advection
+ if method is None:
+ method = m1k
+
+ advec = Advection(velocity=velo,
+ advected_fields=scal,
+ discretization=discr,
+ method=method)
+ advec.discretize()
+ advec.setup()
+
+ # Get and randomize discrete fields
+ topo = advec.advected_fields_topology()
+ scal_d = scal.randomize(topo)
+ assert (velo.norm(topo) == 0).all()
+ ic = topo.mesh.compute_index
+ # copy data for reference
+ scal_ref.copy(scal, topo)
+ scal_ref_d = scal_ref.discretize(topo)
+ topo_velo = advec.velocity_topology()
+ velo_d = velo.discretize(topo_velo)
+ # transfer data to gpu
+ scal_d.toDevice()
+ velo_d.toDevice()
+ scal_d.wait()
+ velo_d.wait()
+
+ advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
+ # Get data back
+ scal_d.toHost()
+ scal_d.wait()
+ advec.finalize()
+ for d in xrange(len(scal_d.data)):
+ assert np.allclose(scal_ref_d.data[d][ic], scal_d.data[d][ic])
+
+
+def test_2D_m6_1k():
+ """Test M6 remeshing formula in 2D, 1 kernel,
+ o2 splitting.
+ """
+ run_advection(d2d, False, m1k)
+
+
+# def test_2D_m6_2k():
+# """Test M6 remeshing formula in 2D, 2 kernels,
+# o2 splitting.
+# """
+# run_advection(d2d, False, m2k)
+
+
+# def test_2D_m6_1k_sFH():
+# """Test M6 remeshing formula in 2D, 1 kernel,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_m6_2k_sFH():
+# """Test M6 remeshing formula in 2D, 2 kernels,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_3D_m6_1k():
+# """Test M6 remeshing formula in 3D, 1 kernel,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m6_2k():
+# """Test M6 remeshing formula in 3D, 2 kernels,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_2k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m6_1k_sFH():
+# """Test M6 remeshing formula in 3D, 1 kernel,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m6_2k_sFH():
+# """Test M6 remeshing formula in 3D, 2 kernels,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_2D_m4_1k():
+# """Test M4 remeshing formula in 2D, 1 kernel,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_m4_2k():
+# """Test M4 remeshing formula in 2D, 2 kernels,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_2k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_m4_1k_sFH():
+# """Test M4 remeshing formula in 2D, 1 kernel,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_m4_2k_sFH():
+# """Test M4 remeshing formula in 2D, 2 kernels,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_3D_m4_1k():
+# """Test M4 remeshing formula in 3D, 1 kernel,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m4_2k():
+# """Test M4 remeshing formula in 3D, 2 kernels,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_2k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m4_1k_sFH():
+# """Test M4 remeshing formula in 3D, 1 kernel,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m4_2k_sFH():
+# """Test M4 remeshing formula in 3D, 2 kernels,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L2_1, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_2D_m8_1k():
+# """Test M8 remeshing formula in 2D, 1 kernel,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_m8_2k():
+# """Test M8 remeshing formula in 2D, 2 kernels,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_2k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_m8_1k_sFH():
+# """Test M8 remeshing formula in 2D, 1 kernel,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_m8_2k_sFH():
+# """Test M8 remeshing formula in 2D, 2 kernels,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_3D_m8_1k():
+# """Test M8 remeshing formula in 3D, 1 kernel,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m8_2k():
+# """Test M8 remeshing formula in 3D, 2 kernels,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_2k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m8_1k_sFH():
+# """Test M8 remeshing formula in 3D, 1 kernel,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_m8_2k_sFH():
+# """Test M8 remeshing formula in 3D, 2 kernels,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: M8Prime, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_2D_l6_1k():
+# """Test L6 remeshing formula in 2D, 1 kernel,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_l6_2k():
+# """Test L6 remeshing formula in 2D, 2 kernels,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_2k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_l6_1k_sFH():
+# """Test L6 remeshing formula in 2D, 1 kernel,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_2D_l6_2k_sFH():
+# """Test L6 remeshing formula in 2D, 2 kernels,
+# o2 full-half splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d2d, False, meth)
+
+
+# def test_3D_l6_1k():
+# """Test L6 remeshing formula in 3D, 1 kernel,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_l6_2k():
+# """Test L6 remeshing formula in 3D, 2 kernels,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_2k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_l6_1k_sFH():
+# """Test L6 remeshing formula in 3D, 1 kernel,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_1k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_3D_l6_2k_sFH():
+# """Test L6 remeshing formula in 3D, 2 kernels,
+# o2 fh splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L6_3, Support: 'gpu_2k', Splitting: O2FULLHALF,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
+
+
+# def test_rectangular_domain2D():
+# """Test remeshing formula in 2D, with different resolutions in each dir,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(Discretization([65, 33]), False, meth)
+
+
+# def test_rectangular_domain3D():
+# """Test remeshing formula in 3D, with different resolutions in each dir,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(Discretization([65, 33, 17]), False, meth)
+
+
+# def test_vector_2D():
+# """Test remeshing formula in 2D, advection of a vector field,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(Discretization([129, 129]), True, meth)
+
+
+# def test_vector_3D():
+# """Test remeshing formula in 3D, advection of a vector field,
+# o2 splitting.
+# """
+# meth = {TimeIntegrator: RK2, Interpolation: Linear,
+# Remesh: L4_2, Support: 'gpu_1k', Splitting: O2,
+# Precision: HYSOP_REAL}
+# run_advection(d3d, False, meth)
diff --git a/hysop/gpu/tests/test_advection_randomVelocity.py b/hysop/old/gpu.old/tests/test_gpu_advection_random_velocity.py
similarity index 97%
rename from hysop/gpu/tests/test_advection_randomVelocity.py
rename to hysop/old/gpu.old/tests/test_gpu_advection_random_velocity.py
index 64f0e274004b63ca6d88c1760af61d39323b1497..27adf57db68335923e0ed858fe882eee2cbd4516 100644
--- a/hysop/gpu/tests/test_advection_randomVelocity.py
+++ b/hysop/old/gpu.old/tests/test_gpu_advection_random_velocity.py
@@ -7,13 +7,13 @@ from hysop.fields.continuous import Field
from hysop.operator.advection import Advection
from hysop.constants import np
from hysop.problem.simulation import Simulation
-from hysop.methods_keys import TimeIntegrator, Interpolation, Remesh, \
+from hysop.methods import TimeIntegrator, Interpolation, Remesh, \
Support, Splitting
from hysop.numerics.integrators.runge_kutta2 import RK2
-from hysop.numerics.interpolation import Linear
+from hysop.numerics.interpolation.interpolation import Linear
from hysop.numerics.remeshing import L2_1, L4_2, M8Prime
from hysop.tools.parameters import Discretization
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
def setup_2D():
@@ -36,8 +36,8 @@ def assertion_2D_withPython(scal, velo, advec, advec_py):
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(
np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = np.asarray(
@@ -64,8 +64,8 @@ def assertion_3D_withPython(scal, velo, advec, advec_py):
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(
np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.zeros_like(
@@ -693,8 +693,8 @@ def test_rectangular_domain2D():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = np.asarray(
np.random.random(velo_d.data[0].shape)) / (2. * scal_d.resolution[0])
@@ -738,8 +738,8 @@ def test_rectangular_domain3D():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
velo_d.data[0][...] = npw.asrealarray(
np.random.random(velo_d.data[0].shape)) / (2. * scal_d.resolution[0])
@@ -786,8 +786,8 @@ def test_vector_2D():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(np.random.random(scal_d.data[0].shape))
scal_d.data[1][...] = npw.asrealarray(np.random.random(scal_d.data[1].shape))
velo_d.data[0][...] = npw.asarray(
@@ -837,8 +837,8 @@ def test_vector_3D():
advec.setup()
advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
+ velo_d = velo.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(
np.random.random(scal_d.data[0].shape))
scal_d.data[1][...] = npw.asrealarray(
diff --git a/hysop/gpu/tests/test_gpu_multiresolution_filter.py b/hysop/old/gpu.old/tests/test_gpu_multiresolution_filter.py
similarity index 90%
rename from hysop/gpu/tests/test_gpu_multiresolution_filter.py
rename to hysop/old/gpu.old/tests/test_gpu_multiresolution_filter.py
index 814d2c85be00c008044ea0895bc82ed7f8a030e8..8acd71bb538e0a3ce1b7e4e90b84110765be0b14 100755
--- a/hysop/gpu/tests/test_gpu_multiresolution_filter.py
+++ b/hysop/old/gpu.old/tests/test_gpu_multiresolution_filter.py
@@ -3,12 +3,12 @@ from hysop.tools.parameters import Discretization, MPIParams
from hysop.domain.box import Box
from hysop.fields.continuous import Field
from hysop.operator.multiresolution_filter import MultiresolutionFilter
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
-from hysop.methods_keys import Remesh, Support, ExtraArgs
+from hysop.methods import Remesh, Support, ExtraArgs
from hysop.methods import Rmsh_Linear, L2_1
# In parallel we need to use as many threads as gpu
-from hysop.mpi import main_size, main_rank
+from hysop.core.mpi import main_size, main_rank
import pyopencl as cl
n_gpu = len(cl.get_platforms()[0].get_devices(
device_type=cl.device_type.GPU))
@@ -44,11 +44,11 @@ def test_filter_linear():
if box.is_on_task(1):
op.discretize()
op.setup()
- topo_coarse = op.discreteFields[f].topology
- topo_fine = [t for t in f.discreteFields.keys()
+ topo_coarse = op.discrete_fields[f].topology
+ topo_fine = [t for t in f.discrete_fields.keys()
if not t is topo_coarse][0]
f.initialize(topo=topo_fine)
- f_out = f.discreteFields[topo_coarse]
+ f_out = f.discrete_fields[topo_coarse]
f_out.toDevice()
op.apply(simu)
f_out.toHost()
@@ -70,7 +70,7 @@ def test_filter_linear():
op_py.setup()
f_py.initialize(topo=topo_fine)
op_py.apply(simu)
- valid = f_py.discreteFields[topo_coarse]
+ valid = f_py.discrete_fields[topo_coarse]
assert np.allclose(valid[0][topo_coarse.mesh.compute_index],
f_out[0][topo_coarse.mesh.compute_index]), \
np.max(np.abs(valid[0][topo_coarse.mesh.compute_index] -
@@ -96,11 +96,11 @@ def test_filter_L2_1():
mpi_params=mpi_p)
op.discretize()
op.setup()
- topo_coarse = op.discreteFields[f].topology
- topo_fine = [t for t in f.discreteFields.keys()
+ topo_coarse = op.discrete_fields[f].topology
+ topo_fine = [t for t in f.discrete_fields.keys()
if not t is topo_coarse][0]
f.initialize(topo=topo_fine)
- f_out = f.discreteFields[topo_coarse]
+ f_out = f.discrete_fields[topo_coarse]
f_out.toDevice()
op.apply(simu)
f_out.toHost()
@@ -120,7 +120,7 @@ def test_filter_L2_1():
op_py.setup()
f_py.initialize(topo=topo_fine)
op_py.apply(simu)
- valid = f_py.discreteFields[topo_coarse]
+ valid = f_py.discrete_fields[topo_coarse]
assert np.allclose(valid[0][topo_coarse.mesh.compute_index],
f_out[0][topo_coarse.mesh.compute_index]), \
np.max(np.abs(valid[0][topo_coarse.mesh.compute_index] -
diff --git a/hysop/gpu/tests/test_multiphase_baroclinic.py b/hysop/old/gpu.old/tests/test_multiphase_baroclinic.py
similarity index 90%
rename from hysop/gpu/tests/test_multiphase_baroclinic.py
rename to hysop/old/gpu.old/tests/test_multiphase_baroclinic.py
index 5c3aa47f847fb130ee077a32f1ee62a7efb58941..7582990cdf0c41400720d14687076349f976e377 100755
--- a/hysop/gpu/tests/test_multiphase_baroclinic.py
+++ b/hysop/old/gpu.old/tests/test_multiphase_baroclinic.py
@@ -6,9 +6,9 @@ from hysop.domain.box import Box
from hysop.fields.continuous import Field
from hysop.operator.multiphase_baroclinic_rhs import MultiphaseBaroclinicRHS
from hysop.numerics.finite_differences import FDC4, FDC2
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
-from hysop.methods_keys import Support, SpaceDiscretisation, ExtraArgs
+from hysop.methods import Support, SpaceDiscretization, ExtraArgs
from hysop.constants import HYSOP_REAL
def test_baroclinic_rhs():
@@ -91,15 +91,15 @@ def call_operator(func, grad_func, vfunc):
gradp: d_coarse,
rho: d_fine},
method={Support: 'gpu',
- SpaceDiscretisation: FDC4,
+ SpaceDiscretization: FDC4,
ExtraArgs: {'density_func': 'x', }})
op.discretize()
op.setup()
- topo_coarse = op.discreteFields[gradp].topology
- topo_fine = op.discreteFields[rho].topology
- d_rhs = rhs.discreteFields[topo_fine]
- d_gradp = gradp.discreteFields[topo_coarse]
- d_rho = rho.discreteFields[topo_fine]
+ topo_coarse = op.discrete_fields[gradp].topology
+ topo_fine = op.discrete_fields[rho].topology
+ d_rhs = rhs.discrete_fields[topo_fine]
+ d_gradp = gradp.discrete_fields[topo_coarse]
+ d_rho = rho.discrete_fields[topo_fine]
rhs.initialize(topo=topo_fine)
gradp.initialize(topo=topo_coarse)
rho.initialize(topo=topo_fine)
@@ -108,11 +108,11 @@ def call_operator(func, grad_func, vfunc):
d_rhs.wait()
gradrho.initialize(topo=topo_fine)
- d_gradrho = gradrho.discreteFields[topo_fine]
+ d_gradrho = gradrho.discrete_fields[topo_fine]
gradp_fine.initialize(topo=topo_fine)
- d_gradp_fine = gradp_fine.discreteFields[topo_fine]
+ d_gradp_fine = gradp_fine.discrete_fields[topo_fine]
true_rhs.initialize(topo=topo_fine)
- d_true_rhs = true_rhs.discreteFields[topo_fine]
+ d_true_rhs = true_rhs.discrete_fields[topo_fine]
d_true_rhs[0] = d_gradrho[2] * d_gradp_fine[1] - \
d_gradrho[1] * d_gradp_fine[2]
d_true_rhs[1] = d_gradrho[0] * d_gradp_fine[2] - \
diff --git a/hysop/gpu/tests/test_opencl_environment.py b/hysop/old/gpu.old/tests/test_opencl_environment.py
similarity index 76%
rename from hysop/gpu/tests/test_opencl_environment.py
rename to hysop/old/gpu.old/tests/test_opencl_environment.py
index 0d7d0d6d720b779e3507b85ede1c20d0a2ebfe51..995239ac2bbbd7174c255690120c396824805535 100644
--- a/hysop/gpu/tests/test_opencl_environment.py
+++ b/hysop/old/gpu.old/tests/test_opencl_environment.py
@@ -1,6 +1,46 @@
-from hysop.constants import np
-from hysop.gpu.tools import get_opencl_environment
+"""Test hysop implementation of OpenCL basic functionnalities"""
+import numpy as np
+from hysop.backend.device.opencl.opencl_tools import get_opencl_environment, explore, OpenClEnvironment
+from hysop.constants import HYSOP_REAL
FLOAT_GPU = np.float32
+from hysop.core.mpi import main_comm
+import pyopencl as cl
+
+
+def test_opencl_env_default():
+ """Test gpu tools. Just call get_opencl_environment and explore functions.
+ """
+ # Display devices info.
+ explore()
+ # Create default opencl env.
+ cl_env = get_opencl_environment()
+ assert isinstance(cl_env, OpenClEnvironment)
+ assert cl_env.device is not None
+ assert cl_env.ctx is not None
+ assert cl_env.queue is not None
+ assert cl_env.precision == HYSOP_REAL
+
+
+def test_opencl_env():
+ """Test gpu tools. Just call get_opencl_environment and explore functions.
+ """
+ # Display devices info.
+ explore()
+ # Create default opencl env.
+ comm = main_comm.Dup()
+ plt = cl.get_platforms()[-1]
+ device = plt.get_devices()[-1]
+ nb_platforms = len(cl.get_platforms())
+ nb_devices = len(plt.get_devices())
+ cl_env = get_opencl_environment(platform_id=nb_platforms - 1,
+ device_id=nb_devices - 1,
+ precision=FLOAT_GPU, comm=comm)
+ assert isinstance(cl_env, OpenClEnvironment)
+ assert cl_env.platform == plt
+ assert cl_env.device == device
+ assert cl_env.ctx is not None
+ assert cl_env.queue is not None
+ assert cl_env.precision == FLOAT_GPU
def test_queue_unique_creation():
diff --git a/hysop/gpu/tests/test_transposition.py b/hysop/old/gpu.old/tests/test_transposition.py
similarity index 93%
rename from hysop/gpu/tests/test_transposition.py
rename to hysop/old/gpu.old/tests/test_transposition.py
index 65128e713d5f255d91f05e8796bd0db4a262a2e7..34c7a39938265ede3e8caa5c5da8c2e56bc8b97d 100644
--- a/hysop/gpu/tests/test_transposition.py
+++ b/hysop/old/gpu.old/tests/test_transposition.py
@@ -2,11 +2,11 @@
@file hysop.gpu.tests.test_transposition
Testing copy kernels.
"""
-from hysop.gpu import cl
+from hysop.backend.device.opencl import cl
from hysop.constants import np
-from hysop.gpu.tools import get_opencl_environment
-from hysop.gpu.gpu_kernel import KernelLauncher
-import hysop.tools.numpywrappers as npw
+from hysop.backend.device.opencl.opencl_tools import get_opencl_environment
+from hysop.backend.device.opencl.opencl_kernel import OpenClKernelLauncher
+from hysop.tools.numpywrappers import npw
def _comparison(resolution, resolutionT,
@@ -65,7 +65,7 @@ def test_transposition_xy2D():
# Build code
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy = KernelLauncher(
+ init_transpose_xy = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xy, init_transpose_xy,
@@ -87,7 +87,7 @@ def test_transposition_xy2D_noVec():
# Build code
prg = cl_env.build_src(src_transpose_xy, build_options)
- init_transpose_xy = KernelLauncher(
+ init_transpose_xy = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xy, init_transpose_xy,
@@ -111,7 +111,7 @@ def test_transposition_xy2D_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[0] / 4) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_x = KernelLauncher(prg.transpose_xy,
+ init_transpose_xy_x = OpenClKernelLauncher(prg.transpose_xy,
cl_env.queue,
gwi, lwi)
@@ -124,7 +124,7 @@ def test_transposition_xy2D_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[1] / 4) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[0] / 4) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_y = KernelLauncher(prg.transpose_xy,
+ init_transpose_xy_y = OpenClKernelLauncher(prg.transpose_xy,
cl_env.queue,
gwi, lwi)
_comparison(resolution, resolutionT,
@@ -149,7 +149,7 @@ def test_transposition_xy2D_noVec_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[0]) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_x = KernelLauncher(prg.transpose_xy,
+ init_transpose_xy_x = OpenClKernelLauncher(prg.transpose_xy,
cl_env.queue,
gwi, lwi)
@@ -162,7 +162,7 @@ def test_transposition_xy2D_noVec_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[1]) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[0] / 4) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_y = KernelLauncher(prg.transpose_xy,
+ init_transpose_xy_y = OpenClKernelLauncher(prg.transpose_xy,
cl_env.queue,
gwi, lwi)
_comparison(resolution, resolutionT,
@@ -185,7 +185,7 @@ def test_transposition_xy3D():
build_options += " -D NB_GROUPS_I=" + str((resolution[0] / 2) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 2) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy = KernelLauncher(
+ init_transpose_xy = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xy, init_transpose_xy,
@@ -207,7 +207,7 @@ def test_transposition_xy3D_noVec():
build_options += " -D NB_GROUPS_I=" + str((resolution[0]) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 2) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy = KernelLauncher(
+ init_transpose_xy = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xy, init_transpose_xy,
@@ -232,7 +232,7 @@ def test_transposition_xy3D_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[0] / 2) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 2) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_x = KernelLauncher(
+ init_transpose_xy_x = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
build_options = ""
@@ -245,7 +245,7 @@ def test_transposition_xy3D_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[1] / 2) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[0] / 2) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_y = KernelLauncher(
+ init_transpose_xy_y = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
_comparison(resolution, resolutionT,
init_transpose_xy_x, init_transpose_xy_y,
@@ -270,7 +270,7 @@ def test_transposition_xy3D_noVec_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[0]) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 2) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_x = KernelLauncher(
+ init_transpose_xy_x = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
build_options = ""
@@ -283,7 +283,7 @@ def test_transposition_xy3D_noVec_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[1]) / lwi[0])
build_options += " -D NB_GROUPS_II=" + str((resolution[0] / 2) / lwi[1])
prg = cl_env.build_src(src_transpose_xy, build_options, vec)
- init_transpose_xy_y = KernelLauncher(
+ init_transpose_xy_y = OpenClKernelLauncher(
prg.transpose_xy, cl_env.queue, gwi, lwi)
_comparison(resolution, resolutionT,
init_transpose_xy_x, init_transpose_xy_y,
@@ -307,7 +307,7 @@ def test_transposition_xz3D():
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz = KernelLauncher(
+ init_transpose_xz = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xz, init_transpose_xz,
@@ -331,7 +331,7 @@ def test_transposition_xz3D_noVec():
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz = KernelLauncher(
+ init_transpose_xz = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xz, init_transpose_xz,
@@ -358,7 +358,7 @@ def test_transposition_xz3D_rect():
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_x = KernelLauncher(
+ init_transpose_xz_x = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
build_options = ""
@@ -373,7 +373,7 @@ def test_transposition_xz3D_rect():
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
build_options += " -D NB_GROUPS_III=" + str((resolution[0] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_z = KernelLauncher(
+ init_transpose_xz_z = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolutionT,
init_transpose_xz_x, init_transpose_xz_z,
@@ -400,7 +400,7 @@ def test_transposition_xz3D_noVec_rect():
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_x = KernelLauncher(
+ init_transpose_xz_x = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
build_options = ""
@@ -415,7 +415,7 @@ def test_transposition_xz3D_noVec_rect():
build_options += " -D NB_GROUPS_II=" + str((resolution[1] / 4) / lwi[1])
build_options += " -D NB_GROUPS_III=" + str((resolution[0] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_z = KernelLauncher(
+ init_transpose_xz_z = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolutionT,
init_transpose_xz_x, init_transpose_xz_z,
@@ -439,7 +439,7 @@ def test_transposition_xz3Dslice():
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz = KernelLauncher(
+ init_transpose_xz = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xz, init_transpose_xz,
@@ -462,7 +462,7 @@ def test_transposition_xz3Dslice_noVec():
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz = KernelLauncher(
+ init_transpose_xz = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolution,
init_transpose_xz, init_transpose_xz,
@@ -488,7 +488,7 @@ def test_transposition_xz3Dslice_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[0] / 2) / lwi[0])
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_x = KernelLauncher(
+ init_transpose_xz_x = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
build_options = ""
@@ -502,7 +502,7 @@ def test_transposition_xz3Dslice_rect():
build_options += " -D NB_GROUPS_I=" + str((resolution[2] / 2) / lwi[0])
build_options += " -D NB_GROUPS_III=" + str((resolution[0] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_z = KernelLauncher(
+ init_transpose_xz_z = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolutionT,
init_transpose_xz_x, init_transpose_xz_z,
@@ -527,7 +527,7 @@ def test_transposition_xz3Dslice_noVec_rect():
build_options += " -D NB_GROUPS_I=" + str(resolution[0] / lwi[0])
build_options += " -D NB_GROUPS_III=" + str((resolution[2] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_x = KernelLauncher(
+ init_transpose_xz_x = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
build_options = ""
@@ -541,7 +541,7 @@ def test_transposition_xz3Dslice_noVec_rect():
build_options += " -D NB_GROUPS_I=" + str(resolution[2] / lwi[0])
build_options += " -D NB_GROUPS_III=" + str((resolution[0] / 4) / lwi[2])
prg = cl_env.build_src(src_transpose_xz, build_options, vec)
- init_transpose_xz_z = KernelLauncher(
+ init_transpose_xz_z = OpenClKernelLauncher(
prg.transpose_xz, cl_env.queue, gwi, lwi)
_comparison(resolution, resolutionT,
init_transpose_xz_x, init_transpose_xz_z,
diff --git a/hysop/gpu/tools.py b/hysop/old/gpu.old/tools.py
similarity index 64%
rename from hysop/gpu/tools.py
rename to hysop/old/gpu.old/tools.py
index 84e8ea1dfa93fc3b6b97c05911271157b06e6290..d03fe95bdc57c8f296f3045c4a420ada2072a3b8 100644
--- a/hysop/gpu/tools.py
+++ b/hysop/old/gpu.old/tools.py
@@ -1,18 +1,35 @@
-"""Misc. tools for gpu/OpenCL management.
+"""Classes and tools used to handle openCL interface.
+
+
+* :class:`~hysop.gpu.tools.OpenClEnvironment`:
+ object handling opencl platform, device ... info.
+* :func:`~hysop.gpu.tools.get_opengl_shared_environment`:
+ build or get an OpenCL environment with openGL properties.
+* :func:`~hysop.gpu.tools.get_opencl_environment`:
+ build or get an OpenCL environment.
+* :func:`~hysop.gpu.tools.explore`
+ explore system and display platform, devices, memory ... info.
+
+
"""
import os, re, itertools, hashlib, pickle, gzip
-from hysop import __DEBUG__, __VERBOSE__, __DEFAULT_PLATFORM_ID__, __DEFAULT_DEVICE_ID__
+# from __future__ import print_function
+
+from hysop import __VERBOSE__, __KERNEL_DEBUG__, \
+ __DEFAULT_PLATFORM_ID__, __DEFAULT_DEVICE_ID__
from hysop.tools.io_utils import IO
from hysop.constants import np, HYSOP_REAL
-from hysop.gpu import cl, GPU_SRC, CL_PROFILE
-from hysop.mpi import MPI
-FLOAT_GPU, DOUBLE_GPU = np.float32, np.float64
+from hysop.backend.device.opencl import cl, GPU_SRC, CL_PROFILE, KERNEL_DUMP_FOLDER
+from hysop.core.mpi import MPI
+
+
+FLOAT_GPU, DOUBLE_GPU = np.float32, np.float64
-# Global variable handling the OpenCL Environment instance
__cl_env = None
+"""Global variable handling the OpenCL Environment instance """
class KernelError(Exception):
"""Custom exception for kernel errors.
@@ -26,7 +43,7 @@ class KernelError(Exception):
return self.err + ': ' + self.msg
-class OpenCLEnvironment(object):
+class OpenClEnvironment(object):
"""OpenCL environment informations and useful functions.
"""
@@ -50,7 +67,7 @@ class OpenCLEnvironment(object):
Default=False.
comm : mpi communicator, optional
Communicator which handles the OpenCL env.
- Default = hysop.mpi.main_comm
+ Default = :data:`~hysop.core.mpi.main_comm`
"""
self._platform_id = platform_id
@@ -70,7 +87,7 @@ class OpenCLEnvironment(object):
# MPI sub-communicator for all processes attached to the same device
if comm is None:
- from hysop.mpi import main_comm
+ from hysop.core.mpi import main_comm
else:
main_comm = comm
@@ -86,19 +103,22 @@ class OpenCLEnvironment(object):
key=main_comm.Get_rank())
# Floating point codegeneration mode
- from hysop.codegen.base.types import OpenClTypeGen
- if __VERBOSE__ or __DEBUG__:
- float_dump_mode='dec'
+ from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+ _kargs = {'device':self.device, 'context':self.ctx, 'platform':self.platform }
+ if __KERNEL_DEBUG__:
+ _kargs['float_dump_mode'] = 'dec'
else:
- float_dump_mode='hex'
+ _kargs['float_dump_mode'] = 'hex'
# Floating point precision
if precision is FLOAT_GPU:
- typegen = OpenClTypeGen('float', float_dump_mode)
+ _kargs['fbtype'] = 'float'
elif precision is DOUBLE_GPU:
- typegen = OpenClTypeGen('double', float_dump_mode)
+ _kargs['fbtype'] = 'double'
else:
raise ValueError('Unknown floating point precision {}!'.format(precision))
+
+ typegen = OpenClTypeGen(**_kargs)
self.typegen = typegen
self.prec_size = typegen.FLT_BYTES[typegen.fbtype]
@@ -108,17 +128,18 @@ class OpenCLEnvironment(object):
self.default_build_opts = ""
if CL_PROFILE and self.device.vendor.find('NVIDIA') >= 0:
self.default_build_opts += " -cl-nv-verbose"
- self.default_build_opts += " -Werror" + self._get_precision_opts()
+ #self.default_build_opts += "-Werror" + self._get_precision_opts()
+ self.default_build_opts += self._get_precision_opts()
# Kernels configuration dictionary
if self.device.name == "Cayman":
- from hysop.gpu.config_cayman import kernels_config as kernel_cfg
+ from hysop.backend.device.opencl.config_cayman import kernels_config as kernel_cfg
elif self.device.name == "Tesla K20m" or \
self.device.name == "Tesla K20Xm":
- from hysop.gpu.config_k20m import kernels_config as kernel_cfg
+ from hysop.backend.device.opencl.config_k20m import kernels_config as kernel_cfg
else:
- print "/!\\ Get a defautl kernels config for", self.device.name
- from hysop.gpu.config_default import kernels_config as kernel_cfg
+ print("/!\\ Get a defautl kernels config for", self.device.name)
+ from hysop.backend.device.opencl.config_default import kernels_config as kernel_cfg
self.kernels_config = kernel_cfg
self._locMem_Buffers = {}
@@ -143,13 +164,13 @@ class OpenCLEnvironment(object):
"""
platform_changed, device_changed = False, False
if not platform_id == self._platform_id:
- print ("platform changed")
+ print("platform changed")
self._platform_id = platform_id
self.platform = self._get_platform(platform_id)
platform_changed = True
- if platform_changed or not (device_id is self._device_id
- and device_type == self._device_type):
- print ("device changed")
+ if platform_changed or not (device_id is self._device_id and
+ device_type == self._device_type):
+ print("device changed")
self._device_id = device_id
self._device_type = device_type
self.device = self._get_device(self.platform,
@@ -159,21 +180,44 @@ class OpenCLEnvironment(object):
if platform_changed or device_changed or \
(not self._gl_sharing and gl_sharing is not self._gl_sharing):
if self._gl_sharing and not gl_sharing:
- print ("Warning: Loosing Gl shared context.")
+ print("Warning: Loosing Gl shared context.")
self._gl_sharing = gl_sharing
self.ctx = self._get_context(self.device, gl_sharing)
self.queue = self._get_queue(self.ctx)
if self.precision is not precision and precision is not None:
if self.precision is not None:
- print ("Warning, GPU precision is overrided from",)
- print (self.precision, 'to', precision)
+ print("Warning, GPU precision is overrided from",)
+ print(self.precision, 'to', precision)
self.precision = precision
self.default_build_opts = ""
if CL_PROFILE and self.device.vendor.find('NVIDIA') >= 0:
self.default_build_opts += " -cl-nv-verbose"
self.default_build_opts += "-Werror" + self._get_precision_opts()
+
+ ## update opencl typegen
+ # Floating point codegeneration mode
+ from hysop.backend.device.opencl.opencl_types import OpenClTypeGen
+ _kargs = {'device':self.device, 'context':self.ctx, 'platform':self.platform }
+ if __KERNEL_DEBUG__:
+ _kargs['float_dump_mode'] = 'dec'
+ else:
+ _kargs['float_dump_mode'] = 'hex'
+
+ # Floating point precision
+ if precision is FLOAT_GPU:
+ _kargs['fbtype'] = 'float'
+ elif precision is DOUBLE_GPU:
+ _kargs['fbtype'] = 'double'
+ else:
+ raise ValueError('Unknown floating point precision {}!'.format(precision))
+
+ typegen = OpenClTypeGen(**_kargs)
+
+ self.typegen = typegen
+ self.prec_size = typegen.FLT_BYTES[typegen.fbtype]
- def _get_platform(self, platform_id):
+ @staticmethod
+ def _get_platform(platform_id):
"""Returns an OpenCL platform
:param platform_id : OpenCL platform id
@@ -182,17 +226,19 @@ class OpenCLEnvironment(object):
# OpenCL platform
platform = cl.get_platforms()[platform_id]
except IndexError:
- print (" Incorrect platform_id :", platform_id, ".",)
- print (" Only ", len(cl.get_platforms()), " available.",)
- print (" Getting default platform. ")
- platform = cl.get_platforms()[0]
+ plist = cl.get_platforms()
+ platform = plist[0]
+ print(" Incorrect platform_id :", platform_id, ".",)
+ print(" Only ", len(plist), " available.",)
+ print(" --> getting default platform ", platform.name)
if __VERBOSE__:
- print (" Platform ")
- print (" - Name :", platform.name)
- print (" - Version :", platform.version)
+ print(" Platform ")
+ print(" - Name :", platform.name)
+ print(" - Version :", platform.version)
return platform
- def _get_device(self, platform, device_id, device_type):
+ @staticmethod
+ def _get_device(platform, device_id, device_type):
"""Returns an OpenCL device
Parameters
@@ -210,42 +256,42 @@ class OpenCLEnvironment(object):
display = False
try:
if device_type is not None:
- device = platform.get_devices(
- eval("cl.device_type." + str(device_type.upper()))
- )[device_id]
+ device_type_id = cl.device_type.__getattribute__(
+ cl.device_type, str(device_type.upper()))
+ device = platform.get_devices(device_type_id)[device_id]
else:
device = platform.get_devices()[device_id]
except cl.RuntimeError as e:
- print ("RuntimeError:", e)
+ print("RuntimeError:", e)
device = cl.create_some_context().devices[0]
display = True
except AttributeError as e:
- print ("AttributeError:", e)
+ print("AttributeError:", e)
device = cl.create_some_context().devices[0]
display = True
except IndexError:
- print (" Incorrect device_id :", device_id, ".",)
- print (" Only ", len(platform.get_devices()), " available.",)
+ print(" Incorrect device_id :", device_id, ".",)
+ print(" Only ", len(platform.get_devices()), " available.",)
if device_type is not None:
- print (" Getting first device of type " +
- str(device_type.upper()))
+ device_type = str(device_type.upper())
+ print(" Getting first device of type " + device_type)
else:
- print (" Getting first device of the platform")
+ print(" Getting first device of the platform")
device = platform.get_devices()[0]
display = True
if device_type is not None:
assert device_type.upper() == cl.device_type.to_string(device.type)
if display or __VERBOSE__:
- print (" Device")
- print (" - id :", device_id)
- print (" - Name :",)
- print (device.name)
- print (" - Type :",)
- print cl.device_type.to_string(device.type)
+ print(" Device")
+ print(" - id :", device_id)
+ print(" - Name :",)
+ print(device.name)
+ print(" - Type :",)
+ print(cl.device_type.to_string(device.type))
print (" - C Version :",)
print (device.opencl_c_version)
print (" - Global mem size :",)
- print device.global_mem_size / (1024 ** 3), "GB"
+ print(device.global_mem_size / (1024 ** 3), "GB")
return device
def _get_context(self, device, gl_sharing):
@@ -276,12 +322,13 @@ class OpenCLEnvironment(object):
else:
ctx = cl.Context([device])
if __VERBOSE__:
- print " Context:"
+ print(" Context:")
if props is not None:
- print " - properties :", props
+ print(" - properties :", props)
return ctx
- def _get_queue(self, ctx):
+ @staticmethod
+ def _get_queue(ctx):
"""Returns OpenCL queue from context
:param ctx : OpenCL context
@@ -294,10 +341,10 @@ class OpenCLEnvironment(object):
else:
queue = cl.CommandQueue(ctx)
if __VERBOSE__:
- print " Queue"
+ print(" Queue")
if props is not None:
- print " - properties :", props
- print "==="
+ print(" - properties :", props)
+ print("===")
return queue
def create_other_queue(self):
@@ -305,7 +352,8 @@ class OpenCLEnvironment(object):
"""
return self._get_queue(self.ctx)
- def get_work_items(self, resolution, vector_width=1):
+ @staticmethod
+ def get_work_items(resolution, vector_width=1):
"""Set the optimal work-item number and OpenCL space index.
Parameters
@@ -336,12 +384,12 @@ class OpenCLEnvironment(object):
# Change work-item regarding problem size
if resolution[0] % workItemNumber > 0:
if len(resolution) == 3:
- print "Warning : GPU best performances obtained for",
- print "problem sizes multiples of 64"
+ print("Warning : GPU best performances obtained for",)
+ print("problem sizes multiples of 64")
else:
- print "Warning : GPU best performances obtained for",
- print "problem sizes multiples of 256"
- while(resolution[0] % workItemNumber > 0):
+ print("Warning : GPU best performances obtained for",)
+ print("problem sizes multiples of 256")
+ while resolution[0] % workItemNumber > 0:
workItemNumber = workItemNumber / 2
# Change work-item regarding vector_width
if workItemNumber * vector_width > resolution[0]:
@@ -361,13 +409,11 @@ class OpenCLEnvironment(object):
return workItemNumber, gwi, lwi
def _get_precision_opts(self):
- """Check if device is capable regarding given precision
- and returns build options regarding the required precision.
+ """Check if device is capable to work with given precision
+ and returns build options considering this precision
"""
opts = ""
# Precision supported
- if __VERBOSE__:
- print " Precision capability ",
fp32_rounding_flag = True
if self.precision is FLOAT_GPU:
opts += " -cl-single-precision-constant"
@@ -377,7 +423,8 @@ class OpenCLEnvironment(object):
raise ValueError("Double Precision is not supported by device")
prec = "double"
if __VERBOSE__:
- print "for " + prec + " Precision: "
+ print(" Precision capability ",)
+ print("for " + prec + " Precision: ")
for v in ['DENORM', 'INF_NAN',
'ROUND_TO_NEAREST', 'ROUND_TO_ZERO', 'ROUND_TO_INF',
'FMA', 'CORRECTLY_ROUNDED_DIVIDE_SQRT', 'SOFT_FLOAT']:
@@ -386,7 +433,7 @@ class OpenCLEnvironment(object):
' cl.device_fp_config.' +
v + ') == cl.device_fp_config.' + v):
if __VERBOSE__:
- print v
+ print(v)
else:
if v is 'CORRECTLY_ROUNDED_DIVIDE_SQRT':
fp32_rounding_flag = False
@@ -394,57 +441,74 @@ class OpenCLEnvironment(object):
if v is 'CORRECTLY_ROUNDED_DIVIDE_SQRT':
fp32_rounding_flag = False
if __VERBOSE__:
- print v, 'is not supported in OpenCL C 1.2.\n',
- print ' Exception catched : ', ae
+ print(v, 'is not supported in OpenCL C 1.2.\n',)
+ print(' Exception catched : ', ae)
if fp32_rounding_flag:
opts += " -cl-fp32-correctly-rounded-divide-sqrt"
return opts
- def build_src(self, files, options="", vector_width=4,
- nb_remesh_components=1, dump_src=True):
+ def _create_cl_program(self, file_list,
+ vector_width=4,
+ nb_remesh_components=1,
+ options="",
+ force_verbose=None, force_debug=None):
"""Build OpenCL sources
Parameters
----------
- files : file or list of files
- sources
- options : string
- Compiler options to use for buildind
- vector_width : int
- OpenCL vector type width
- nb_remesh_components : int
- number of remeshed components
-
- Returns OpenCL binaries
-
+ files : string or list of strings
+ user defined files names
+ vector_width : int, optional
+ OpenCL vector type width, default=4
+ nb_remesh_components : int, optional
+ number of remeshed components, default=1
+ options: string
+ additional OpenCL compile flags
+ force_verbose: bool, optional, default=None
+ force verbose mode
+ force_debug: bool, optional, default=None
+ force debug mode (kernel source dumping and preprocessing)
+
+ Returns OpenCL kernel
Parse the sources to handle single and double precision.
"""
+ VERBOSE = __VERBOSE__ if (force_verbose is None) else force_verbose
+ DEBUG = __KERNEL_DEBUG__ if (force_debug is None) else force_debug
+
gpu_src = ""
if cl.device_type.to_string(self.device.type) == 'GPU' and \
self.precision is DOUBLE_GPU:
- gpu_src += "#pragma OPENCL EXTENSION cl_khr_fp64: enable \n"
+ gpu_src += '#pragma OPENCL EXTENSION cl_khr_fp64: enable \n'
+
if isinstance(files, list):
file_list = files
else:
file_list = [files]
- if __VERBOSE__:
- print "=== Kernel sources compiling ==="
- for sf in file_list:
- print " - ", sf
+
+ if VERBOSE:
+ print '=== Kernel sources compiling ==='
+ for sd in file_list:
+ print ' - ', sf
+
for sf in file_list:
+ # search and open cl file.
try:
f = open(sf, 'r')
except IOError as ioe:
if ioe.errno == 2:
+ # path to cl files inside hysop.gpu package
f = open(GPU_SRC + sf, 'r')
else:
raise ioe
gpu_src += "".join(
self.parse_file(f, vector_width, nb_remesh_components))
f.close()
- # print gpu_src
- for k in self.macros:
- gpu_src = gpu_src.replace(k, str(self.macros[k]))
+
+ # print gpu_src
+ if self.macros is not None:
+ for k in self.macros:
+ gpu_src = gpu_src.replace(k, str(self.macros[k]))
+
if self.precision is FLOAT_GPU:
# Rexexp to add 'f' suffix to float constants
# Match 1.2, 1.234, 1.2e3, 1.2E-05
@@ -454,8 +518,7 @@ class OpenCLEnvironment(object):
gpu_src = gpu_src.replace('float', 'double')
# Log final opencl generated code for debug purposes
- dump_src = dump_src or __DEBUG__
- if dump_src:
+ if DEBUG:
kernel_name = (file_list[-1].split('/')[-1]).replace('.cl','_parsed')
def listformat(L):
if isinstance(L,str):
@@ -481,10 +544,11 @@ Dumped OpenCL Kernel '{}'
listformat(file_list),
listformat(self.default_build_opts),
listformat(options))
-
- dumped_src = dump_prefix + gpu_src
+
- dump_folder=IO.default_path()+'/generated_kernels'
+ dumped_src = dump_prefix + gpu_src
+
+ dump_folder=IO.default_path()+'/'+KERNEL_DUMP_FOLDER
dump_file_prefix=dump_folder+'/'+kernel_name
tmp_dump_file=dump_file_prefix+'.c'
dump_file=dump_file_prefix+'.cl'
@@ -492,27 +556,81 @@ Dumped OpenCL Kernel '{}'
os.makedirs(dump_folder)
with open(tmp_dump_file, 'w+') as f:
f.write(dumped_src)
+
try:
#try to preprocess sources
import subprocess
- cmd = ['gcc',self.default_build_opts,options,'-E','-c',tmp_dump_file,'-o',dump_file_prefix+'_preprocessed.cl']
+ opts = self.default_build_opts + options
+ opts = re.sub('-cl-([a-z0-9]+-?)+ ','',opts)
+ cmd = ['gcc',opts,'-E','-c',tmp_dump_file,'-o',dump_file_prefix+'_preprocessed.cl']
subprocess.check_call(' '.join(cmd), shell=True);
finally:
os.rename(tmp_dump_file,dump_file)
- if __VERBOSE__ or __DEBUG__:
- print 'OpenCL kernel {} source dumped to {}.'.format(kernel_name, dump_file)
+
+ if VERBOSE:
+ msg = 'OpenCL kernel {} source dumped to {}.'.format(kernel_name, dump_file)
+ print msg
# OpenCL program
prg = cl.Program(self.ctx, gpu_src)
+ return prg
+
+ def build_src(self, files,
+ options="",
+ vector_width=4,
+ nb_remesh_components=1):
+ """Build OpenCL sources
+
+ Parameters
+ ----------
+ files : string or list of strings
+ user defined file names
+ options : string, optional
+ Compiler options, default=""
+ vector_width : int, optional
+ OpenCL vector type width, default=4
+ nb_remesh_components : int, optional
+ number of remeshed components, default=1
+ force_verbose: bool, optional
+ force verbose mode
+ force_debug: bool, optional
+ force debug mode (kernel dumping)
+
+ Returns OpenCL binaries
+
+ Parse the sources to handle single and double precision.
+ """
+
+ if isinstance(files, list):
+ file_list = files
+ else:
+ file_list = [files]
+
+ if __VERBOSE__:
+ print("=== Kernel sources compiling ===")
+ for sf in file_list:
+ print(" - ", sf)
+
+ # --- create kernel from cl files ---
+ prg = self._create_cl_program(files=file_list,
+ options=options,
+ vector_width=vector_width,
+ nb_remesh_components=nb_remesh_components,
+ force_verbose=force_verbose,
+ force_debug=force_debug)
+
+ # --- Build kernel ---
try:
build = prg.build(self.default_build_opts + options)
except Exception, e:
- print "Build files : "
+ print("Build files : ")
for sf in file_list:
- print " - ", sf
- print "Build options : ", self.default_build_opts + options
- print "Vectorization : ", vector_width
+ print(" - ", sf)
+ print("Build options : ", self.default_build_opts + options)
+ print("Vectorization : ", vector_width)
raise e
+
+ # display post-build info
if __VERBOSE__:
# print options
print "Build options : ",
@@ -523,16 +641,13 @@ Dumped OpenCL Kernel '{}'
self.device, cl.program_build_info.STATUS)
print "Compiler log : ",
print build.get_build_info(self.device,
- cl.program_build_info.LOG)
+ cl.program_build_info.LOG)
print "===\n"
- elif CL_PROFILE:
- print "Build files: " + str(file_list)
- print "With build options: " + self.default_build_opts + options
- print "Compiler output : " + build.get_build_info(
- self.device, cl.program_build_info.LOG)
return build
- def build_raw_src(self, src, options="", force_verbose=None):
+ def build_raw_src(self, src, options="",
+ kernel_name=None,
+ force_verbose=None, force_debug=None):
"""Build raw OpenCL sources
Parameters
@@ -543,20 +658,39 @@ Dumped OpenCL Kernel '{}'
Compiler options to use for buildind
Returns OpenCL binaries
"""
- VERBOSE = __VERBOSE__ if (force_verbose is None) else force_verbose
+ VERBOSE = __VERBOSE__ if (force_verbose is None) else force_verbose
+ DEBUG = __KERNEL_DEBUG__ if (force_debug is None) else force_debug
gpu_src = src
+
+ src_hash = hashlib.sha1(gpu_src).hexdigest()
+ if (kernel_name is None):
+ kernel_name = src_hash
+ else:
+ kernel_name += '_{}'.format(src_hash[:4])
+
soptions = ' '.join(options)
if VERBOSE:
print "=== Kernel raw source compiling ==="
prg = cl.Program(self.ctx, gpu_src)
+
+
+ dump_folder=IO.default_path()+'/'+KERNEL_DUMP_FOLDER
+ if not os.path.exists(dump_folder):
+ os.makedirs(dump_folder)
- # OpenCL program
+ # Build OpenCL program
try:
build = prg.build(self.default_build_opts + soptions)
except Exception, e:
+ # always dump source when build fails
+ dump_file=dump_folder+'/'+'{}_build_fail.cl'.format(kernel_name)
+ with open(dump_file, 'w+') as f:
+ f.write(gpu_src)
print "Build options : ", self.default_build_opts + soptions
+ print 'Build Failed: dumped source to {}.'.format(dump_file)
raise e
+
if VERBOSE:
#print options
print "Build options : ",
@@ -568,19 +702,26 @@ Dumped OpenCL Kernel '{}'
print "Compiler log : ",
print build.get_build_info(self.device,
cl.program_build_info.LOG)
+ if DEBUG:
+ # dump kernel source while in debug mode
+ dump_file=dump_folder+'/'+'{}_dump.cl'.format(kernel_name)
+ print 'Dumping kernel src at \'{}\'.'.format(dump_file)
+ with open(dump_file, 'w+') as f:
+ f.write(gpu_src)
+
+ if VERBOSE:
print "===\n"
- elif CL_PROFILE:
- print "With build options: " + self.default_build_opts + soptions
- print "Compiler output : " + build.get_build_info(
- self.device, cl.program_build_info.LOG)
+
return build
- def parse_file(self, f, n=8, nb_remesh_components=1):
+ @staticmethod
+ def parse_file(f, n=8, nb_remesh_components=1):
"""Parse a file containing OpenCL sources.
Parameters
----------
- f : file
+ f : string
+ file name
n : int, optional
vector width, default=8
nb_remesh_components : int
@@ -590,49 +731,51 @@ Dumped OpenCL Kernel '{}'
-------
string, the parsed sources.
- - <code>__N__</code> is expanded as an integer corresponding to a
- vector with
- - <code>__NN__</code>, instruction is duplicated to operate on each
- vector component:
- - if line ends with '<code>;</code>', the whole instruciton is
- duplicated.
- - if line ends with '<code>,</code>' and contains
- '<code>(float__N__)(</code>', the float element is duplicated
- - Remeshing fields components are expanded as follows :
- All code between '<code>__RCOMPONENT_S__</code>' and
- '<code>__RCOMPONENT_E__</code>' flags are duplicated n times with n
+ Notes
+ -----
+ * __N__ is expanded as an integer corresponding to vector width.
+ * __NN__ instruction is duplicated to operate on each vector component:
+
+ * if line ends with ';', the whole instruciton is
+ duplicated.
+ * if line ends with ',' and contains
+ '(float__N__)(', the float element is duplicated
+
+ * Remeshing fields components are expanded as follows :
+ All code between '__RCOMPONENT_S__' and
+ '__RCOMPONENT_E__' flags are duplicated n times with n
the number of components to compute. In this duplicated code, the
- flag '<code>__ID__</code>' is replaced by index of a range of lenght
- the number of components. A flag '<code>__RCOMPONENT_S__P__</code>'
- may be used and the duplicated elements are separated by ',' (for
- function parameters expanding).
-
- Examples with a 4-width vector:\n
- \code
- float__N__ x; -> float4 x;
-
- x.s__NN__ = 1.0f; -> x.s0 = 1.0f;
- x.s1 = 1.0f;
- x.s2 = 1.0f;
- x.s3 = 1.0f;
-
- x = (int__N__)(\__NN__, -> x = (int4)(0,
- ); 1,
- 2,
- 3,
- );
- \endcode
-
- Examples with a 2 components expansion:\n
- __RCOMP_P __global const float* var__ID__,
- -> __global const float* var0,__global const float* var1,
-
- __RCOMP_I var__ID__[i] = 0.0;
- -> var0[i] = 0.0;var1[i] = 0.0;
-
- aFunction(__RCOMP_P var__ID__, __RCOMP_P other__ID__);
- -> aFunction(var0, var1, other0, other1);
- \endcode
+ flag '__ID__' is replaced by index of a range of lenght
+ the number of components. A flag '__RCOMPONENT_S__P__'
+ may be used and the duplicated elements are separated with ','
+ (for function parameters expanding).
+
+ Examples with a 4-width vector code::
+
+ float__N__ x; -> float4 x;
+
+ x.s__NN__ = 1.0f; -> x.s0 = 1.0f;
+ x.s1 = 1.0f;
+ x.s2 = 1.0f;
+ x.s3 = 1.0f;
+
+ x = (int__N__)(__NN__, -> x = (int4)(0,
+ ); 1,
+ 2,
+ 3,
+ );
+
+ Examples with a 2 components expansion code::
+
+ __RCOMP_P __global const float* var__ID__,
+ -> __global const float* var0,__global const float* var1,
+
+ __RCOMP_I var__ID__[i] = 0.0;
+ -> var0[i] = 0.0;var1[i] = 0.0;
+
+ aFunction(__RCOMP_P var__ID__, __RCOMP_P other__ID__);
+ -> aFunction(var0, var1, other0, other1);
+
"""
src = ""
# replacement for floatN elements
@@ -679,14 +822,23 @@ Dumped OpenCL Kernel '{}'
return src
def global_allocation(self, array):
+ """Allocate and returns an opencl buffer
+
+ Parameters
+ ----------
+ array : numpy array
+ source buffer, on host
+ """
+ # create an opencl buffer from input array
clBuff = cl.Buffer(self.ctx,
cl.mem_flags.ALLOC_HOST_PTR, size=array.nbytes)
# Touch the buffer on device to performs the allocation
- # Transfers a single element in device (the precision no matters here)
+ # Transfers a single element in device (the precision does not matter)
e = np.zeros((1,), dtype=np.float64)
cl.enqueue_copy(self.queue, clBuff, e,
buffer_origin=(0, 0, 0), host_origin=(0, 0, 0),
region=(e.nbytes,)).wait()
+ # update memory counter
self.available_mem -= clBuff.size
return clBuff
@@ -739,7 +891,7 @@ def get_opengl_shared_environment(platform_id=None,
device_id=None,
device_type=None, precision=HYSOP_REAL,
comm=None):
- """Build or get an OpenCL environment.
+ """Build or get an OpenCL environment with openGL properties.
Parameters
----------
@@ -754,12 +906,12 @@ def get_opengl_shared_environment(platform_id=None,
Default : HYSOP_REAL
comm : mpi communicator, optional
Communicator which handles the OpenCL env.
- Default = hysop.mpi.main_comm
+ Default = hysop.core.mpi.main_comm
Returns
-------
- :class:`~hysop.gpu.tools.OpenCLEnvironment`
- handling OpenCL platform, device, context and queue
+ :class:`~hysop.gpu.tools.OpenClEnvironment`
+ object handling OpenCL platform, device, context and queue
The context is obtained with gl-shared properties depending on the OS.
"""
@@ -769,7 +921,7 @@ def get_opengl_shared_environment(platform_id=None,
device_id = __DEFAULT_DEVICE_ID__
global __cl_env
if __cl_env is None:
- __cl_env = OpenCLEnvironment(platform_id, device_id, device_type,
+ __cl_env = OpenClEnvironment(platform_id, device_id, device_type,
precision, gl_sharing=True, comm=comm)
else:
__cl_env.modify(platform_id, device_id, device_type,
@@ -796,12 +948,13 @@ def get_opencl_environment(platform_id=None,
Default : HYSOP_REAL
comm : mpi communicator, optional
Communicator which handles the OpenCL env.
- Default = hysop.mpi.main_comm
+ Default = hysop.core.mpi.main_comm
Returns
-------
- :class:`~hysop.gpu.tools.OpenCLEnvironment`
- handling OpenCL platform, device, context and queue
+
+ :class:`~hysop.gpu.tools.OpenClEnvironment`
+ object handling OpenCL platform, device, context and queue
"""
if platform_id is None:
@@ -810,7 +963,7 @@ def get_opencl_environment(platform_id=None,
device_id = __DEFAULT_DEVICE_ID__
global __cl_env
if __cl_env is None:
- __cl_env = OpenCLEnvironment(platform_id, device_id, device_type,
+ __cl_env = OpenClEnvironment(platform_id, device_id, device_type,
precision, comm=comm)
else:
__cl_env.modify(platform_id, device_id, device_type,
@@ -819,8 +972,8 @@ def get_opencl_environment(platform_id=None,
def explore():
- """Print environment details"""
- print "OpenCL exploration : "
+ """Scan system and print OpenCL environment details"""
+ print("OpenCL exploration : ")
platforms = cl.get_platforms()
platforms_info = ["name", "version", "vendor", "profile", "extensions"]
devices_info = ["name",
@@ -850,11 +1003,11 @@ def explore():
"preferred_vector_width_float",
"preferred_vector_width_int"]
for pltfm in platforms:
- print "Platform:", pltfm.name
+ print("Platform:", pltfm.name)
for pltfm_info in platforms_info:
- print " |-", pltfm_info, ':', eval("pltfm." + pltfm_info)
+ print(" |-", pltfm_info, ':', eval("pltfm." + pltfm_info))
devices = pltfm.get_devices()
for dvc in devices:
- print " |- Device:", dvc.name
+ print(" |- Device:", dvc.name)
for dvc_info in devices_info:
- print " |-", dvc_info, ':', eval("dvc." + dvc_info)
+ print(" |-", dvc_info, ':', eval("dvc." + dvc_info))
diff --git a/hysop/gpu/visu/__init__.py b/hysop/old/gpu.old/visu/__init__.py
similarity index 100%
rename from hysop/gpu/visu/__init__.py
rename to hysop/old/gpu.old/visu/__init__.py
diff --git a/hysop/gpu/visu/gpu-mc.cl b/hysop/old/gpu.old/visu/gpu-mc.cl
similarity index 100%
rename from hysop/gpu/visu/gpu-mc.cl
rename to hysop/old/gpu.old/visu/gpu-mc.cl
diff --git a/hysop/gpu/visu/marchingcube.py b/hysop/old/gpu.old/visu/marchingcube.py
similarity index 94%
rename from hysop/gpu/visu/marchingcube.py
rename to hysop/old/gpu.old/visu/marchingcube.py
index 47b166fae0c0ae41fdba72c8b311c71dfb4badcb..36e89b0bb3a204352c112a2da585ddc867052bd5 100644
--- a/hysop/gpu/visu/marchingcube.py
+++ b/hysop/old/gpu.old/visu/marchingcube.py
@@ -10,8 +10,8 @@ from math import log
import ctypes
from hysop.constant import HYSOP_REAL
-from hysop.gpu import cl
-from hysop.gpu.tools import get_opencl_environment
+from hysop.backend.device.opencl import cl
+from hysop.backend.device.opencl.opencl_tools import get_opencl_environment
class Marching_Cube(object):
@@ -82,7 +82,7 @@ class Marching_Cube(object):
self._cl_env.macros['**HP_SIZE**'] = self._size_
self.prg = self._cl_env.build_src(self.usr_src, options)
kernel_name = 'constructHPLevel' + self.field.name.split('_D')[0]
- self.numMethod = KernelLauncher(eval('self.prg.' + kernel_name),
+ self.numMethod = OpenClKernelLauncher(eval('self.prg.' + kernel_name),
self.queue,
self.gwi,
self.lwi)
diff --git a/hysop/old/numerics.old/__init__.py b/hysop/old/numerics.old/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/numerics/differential_operations.py b/hysop/old/numerics.old/differential_operations.py
similarity index 99%
rename from hysop/numerics/differential_operations.py
rename to hysop/old/numerics.old/differential_operations.py
index c6ba5544573d8f50095bf5f44746e8035ad8a285..df23e54f8874f598892aa6e6aede4b7a9447758a 100755
--- a/hysop/numerics/differential_operations.py
+++ b/hysop/old/numerics.old/differential_operations.py
@@ -39,7 +39,7 @@ from hysop.constants import debug, XDIR, YDIR, ZDIR
from abc import ABCMeta
from hysop.numerics.finite_differences import FDC4, FDC2, FD2C2
import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.tools.misc import WorkSpaceTools, Utils
@@ -60,7 +60,7 @@ class DifferentialOperation(object):
"""
Parameters
----------
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
indices : list of slices, optional
Represents the local mesh on which the operation
will be applied,
@@ -308,7 +308,7 @@ class DivRhoV(DifferentialOperation):
iout = None
fd_scheme = self.method(topo.mesh.space_step,
self._wk_indices,
- indices_out=iout)
+ output_indices=iout)
self._fd_work = self.method(topo.mesh.space_step,
self._wk_indices)
msg = 'Ghost layer is too small for the chosen FD scheme.'
diff --git a/hysop/old/numerics.old/extras_f/arnoldi.f95 b/hysop/old/numerics.old/extras_f/arnoldi.f95
new file mode 100644
index 0000000000000000000000000000000000000000..0fef4f5fca58717d404424588688dff57cbf7d60
--- /dev/null
+++ b/hysop/old/numerics.old/extras_f/arnoldi.f95
@@ -0,0 +1,220 @@
+!=========================================================================
+!Computation of global modes using a time stepping (snapshots) technique
+!=========================================================================
+!=========================================================================
+!Reads snapshots, constructs the Hessenberg matrix
+!and computes the eigen-values/eigen-functions
+!=========================================================================
+module arnoldi
+
+ use precision
+ use parameters
+
+ implicit none
+
+contains
+
+ !======================
+ subroutine arnoldi3d(Mu,ncli,nt,nfp,nmodes,Tps)
+ implicit none
+ integer, intent(in) :: ncli ! number of snapshot
+ integer, intent(in) :: nt ! total number of points per snapshot
+ integer, intent(in) :: nmodes ! number of desired modes
+ integer, intent(in) :: nfp ! number of desired eigen functions
+ real(wp), intent(in) :: Tps ! sampling time step
+ real(wp), dimension(:,:), intent(inout) :: Mu ! snapshots
+
+ real(wp), dimension(:,:), allocatable :: un ! orthonomalized Krylov basis
+ real(wp), dimension(:,:), allocatable :: Hessenberg ! Hessenberg matrix
+ complex(wp), dimension(:), allocatable :: VP ! eigenvalues
+ complex(wp), dimension(:,:), allocatable :: FP, FP_J ! eigen functions
+ real(wp), dimension(:), allocatable :: reslog, res ! residuals
+ integer, dimension(:), allocatable :: t ! sorting array
+ real(wp), dimension(:), allocatable :: tab !
+ real(wp) :: norm, prod, error !
+
+ integer :: i,j,nmax
+
+ allocate(un(nt,ncli),Hessenberg(ncli,ncli-1),VP(ncli-1),FP(ncli-1,ncli-1),FP_J(nt,ncli))
+
+ nmax=0
+ VP=(0.,0.); FP=(0.,0.); FP_J=(0.,0.)
+ Hessenberg=0.
+
+ !==================================
+ ! Arnoldi method
+ !==================================
+
+ norm = dot_product(Mu(:,1),Mu(:,1))
+ norm = sqrt(norm)
+ un(:,1) = Mu(:,1)/norm ! first normalized vector u1
+
+ do j=2,ncli ! construct a normalized base u2... un
+ un(:,j)=Mu(:,j) ! w=Mu_j (We have Mu_j=U(:,j+1))
+ do i=1,j-1
+ Hessenberg(i,j-1)=dot_product(un(:,i),un(:,j))
+ un(:,j)=un(:,j)-un(:,i)*Hessenberg(i,j-1)
+ enddo
+
+ norm = dot_product(un(:,j),un(:,j))
+ Hessenberg(j,j-1) = sqrt(norm)
+
+ un(:,j) = un(:,j)/Hessenberg(j,j-1)! normalization
+
+ enddo
+
+ ! do i=1,nt
+ ! print *, 'Krylov basis:', un(i,:)
+ ! enddo
+
+ do i=1,ncli-1
+ print *, 'Hessenberg matrix:', Hessenberg(i,:)
+ enddo
+
+
+ !Check orthonormalization
+ !==================================
+
+ print *,'check ortho'
+
+ prod=0.
+ do i=1,ncli
+ do j=1,ncli
+ prod=dot_product(un(:,j),un(:,i))
+ if (abs(prod).gt.1e-14) then
+ print *,i,j,abs(prod)
+ endif
+ enddo
+ enddo
+
+
+ !Eigen-values and Eigen-functions related to Hessenberg matrix
+ ! +
+ !Eigen-values related to Jacobian matrix ==> spectra
+ !==============================================================
+
+ open(unit=10, file='spectrum.dat')
+ open(unit=11, file='spectrum_log.dat')
+
+ call spectrum(Hessenberg(1:ncli-1,:),ncli-1,VP,FP)
+
+ do i=1,ncli-1
+ write(10,*) dble(VP(i)), aimag(VP(i))
+ write(11,*) dble(log(VP(i)))/Tps, ATAN(aimag(VP(i)/DBLE(VP(i))))/Tps
+ enddo
+ close(10)
+ close(11)
+
+ !Eigen-functions related to Jacobian matrix
+ !==========================================
+ FP_J(1:nt,1:ncli-1)=matmul(un(1:nt,1:ncli-1),FP(1:ncli-1,1:ncli-1))
+ ! do i=1,nt
+ ! print *, 'FP_J', (FP_J(i,j),j=1,ncli-1)
+ ! enddo
+
+ !Residual calculation with respect to each mode
+ !==============================================
+
+ allocate(res(ncli-1),reslog(ncli-1))
+ error = Hessenberg(ncli,ncli-1)
+ print *,'last Hess',Hessenberg(ncli,ncli-1)
+
+ do i=1,ncli-1
+ res(i) = abs(FP(ncli-1,i))*error
+ reslog(i)=-log10(res(i))
+ print *,'residual',reslog(i),res(i)
+ enddo
+
+
+ !Modes are sorted with respect to residual
+ !==========================================
+ allocate(t(ncli-1))
+
+ do i=1,ncli-1
+ t(i)=i
+ enddo
+
+ call sort(reslog,ncli-1,t)
+
+ open(unit=201,file='spectrum_res.dat')
+ write(201,*)'VARIABLES ="WR","WI","RES"'
+
+ do i=1,nmodes
+ write(201,100) dble(log(VP(t(i))))/Tps,&
+ ATAN(aimag(VP(t(i))/DBLE(VP(t(i)))))/Tps,&
+ res(t(i))
+ enddo
+ close(201)
+ !
+ !Write the associated eigen functions
+ !====================================
+ ! allocate(tab(nfp))
+ !
+ ! open(unit=107, file='table.dat')
+ ! open(unit=108, file='spectrum_sorted.dat')
+ !
+ ! do i=1,nfp
+ !! call ecriture(FP_J(:,t(h)))
+ ! write(108,*) ATAN(aimag(VP(t(i))/DBLE(VP(t(i)))))/Tps,&
+ ! dble(log(VP(t(i))))/Tps
+ ! enddo
+ ! close(108)
+ !
+100 format (5(2x,e19.13))
+
+ end subroutine arnoldi3d
+
+ !===================
+ !Spectrum subroutine
+ !===================
+ subroutine spectrum(A,n,VP,VR)
+ implicit none
+ integer :: INFO
+ integer :: n,LWORK
+ real(wp), dimension(n,n) :: A
+ real(wp), dimension(:), allocatable :: RWORK
+ complex(wp), dimension(1,n) :: VL
+ complex(wp), dimension(n,n) :: VR
+ complex(wp), dimension(:), allocatable :: WORK
+ complex(wp), dimension(n):: VP
+
+ LWORK=4*n
+ allocate(WORK(LWORK),RWORK(2*n))
+ call ZGEEV('N','V', n, A*(1.,0.), n, VP, VL, 1, VR, n,&
+ WORK, LWORK, RWORK, INFO )
+ print *, 'VP', VP
+
+ end subroutine spectrum
+
+ !==================
+ !Sorting subroutine
+ !==================
+ subroutine sort(t,n,ind)
+ implicit none
+ integer :: i, j, n, tp1
+ real(wp), dimension(1:n) :: t
+ real(wp) :: temp
+ integer, dimension(1:n) :: ind
+
+ do i=1,n
+ do j=i+1,n
+ if ((t(i))<(t(j))) then
+
+ temp=t(i)
+ tp1=ind(i)
+
+ t(i)=t(j)
+ ind(i)=ind(j)
+
+ t(j)=temp
+ ind(j)=tp1
+
+ endif
+ enddo
+ enddo
+
+ return
+
+ end subroutine sort
+
+end module arnoldi
diff --git a/hysop/old/numerics.old/extras_f/arnoldi2py.pyf b/hysop/old/numerics.old/extras_f/arnoldi2py.pyf
new file mode 100644
index 0000000000000000000000000000000000000000..7a2d95d5a161228a6d589f69cfe143f43619a8c2
--- /dev/null
+++ b/hysop/old/numerics.old/extras_f/arnoldi2py.pyf
@@ -0,0 +1,14 @@
+! -*- f90 -*-
+! Note: the context of this file is case sensitive.
+
+module arnoldi ! in arnoldi2py.f90
+ use precision
+ subroutine arnoldi3d(Mu,ncli,nt,nfp,nmodes,Tps) ! in arnoldi2py.f90:arnoldi2py
+ real(kind=wp) dimension(:,:),intent(inout) :: Mu
+ integer intent(in) :: ncli
+ integer intent(in) :: nt
+ integer intent(in) :: nfp
+ integer intent(in) :: nmodes
+ real(kind=wp) intent(in) :: Tps
+ end subroutine arnoldi3d
+end module arnoldi
diff --git a/src/fftw/fft2d.f90 b/hysop/old/numerics.old/fftw_f/fft2d.f90
similarity index 93%
rename from src/fftw/fft2d.f90
rename to hysop/old/numerics.old/fftw_f/fft2d.f90
index ab7277265594af7cdfb44d9806fbff97974a0064..8dbeefccde39be5b4d61f99dcd806391a227ab52 100755
--- a/src/fftw/fft2d.f90
+++ b/hysop/old/numerics.old/fftw_f/fft2d.f90
@@ -19,8 +19,9 @@
!! dedicated to tests and validation.
module fft2d
- use client_data
-
+ use, intrinsic :: iso_c_binding
+ use precision
+ use parameters
implicit none
include 'fftw3-mpi.f03'
@@ -79,8 +80,8 @@ contains
subroutine init_c2c_2d(resolution,lengths)
!! global domain resolution
- integer, dimension(2), intent(in) :: resolution
- real(mk),dimension(2), intent(in) :: lengths
+ integer(kind=ip), dimension(2), intent(in) :: resolution
+ real(wp),dimension(2), intent(in) :: lengths
!! Size of the local memory required for fftw (cbuffer)
integer(C_INTPTR_T) :: alloc_local
@@ -130,7 +131,7 @@ contains
call computeKxC(lengths(c_X))
call computeKy(lengths(c_Y))
- normFFT = 1./(fft_resolution(c_X)*fft_resolution(c_Y))
+ normFFT = ONE/(fft_resolution(c_X)*fft_resolution(c_Y))
!! call fft2d_diagnostics(alloc_local)
is2DUpToDate = .true.
@@ -142,8 +143,8 @@ contains
!> Execute fftw forward transform, according to the pre-defined plans.
subroutine c2c_2d(inputData,velocity_x,velocity_y)
- complex(mk),dimension(:,:) :: velocity_x,velocity_y
- complex(mk),dimension(:,:),intent(in) :: inputData
+ complex(wp),dimension(:,:) :: velocity_x,velocity_y
+ complex(wp),dimension(:,:),intent(in) :: inputData
integer(C_INTPTR_T) :: i, j
@@ -190,8 +191,8 @@ contains
!! @param[in] resolution global domain resolution
subroutine init_r2c_2d(resolution,lengths)
- integer, dimension(2), intent(in) :: resolution
- real(mk),dimension(2), intent(in) :: lengths
+ integer(kind=ip), dimension(2), intent(in) :: resolution
+ real(wp),dimension(2), intent(in) :: lengths
!! Size of the local memory required for fftw (cbuffer)
integer(C_INTPTR_T) :: alloc_local,halfLength
@@ -233,7 +234,7 @@ contains
call computeKx(lengths(c_X))
call computeKy(lengths(c_Y))
- normFFT = 1./(fft_resolution(c_X)*fft_resolution(c_Y))
+ normFFT = ONE/(fft_resolution(c_X)*fft_resolution(c_Y))
!! call fft2d_diagnostics(alloc_local)
!!$
!!$ write(*,'(a,i5,a,16f10.4)') 'kx[',rank,'] ', kx
@@ -248,8 +249,8 @@ contains
!! @param input data
subroutine r2c_scalar_2d(inputData, ghosts)
- real(mk),dimension(:,:), intent(in) :: inputData
- integer, dimension(2), intent(in) :: ghosts
+ real(wp),dimension(:,:), intent(in) :: inputData
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
integer(C_INTPTR_T) :: i, j, ig, jg
! init
@@ -278,8 +279,8 @@ contains
!! @param[in] input data
subroutine r2c_2d(input_x, input_y, ghosts)
- real(mk),dimension(:,:), intent(in) :: input_x, input_y
- integer, dimension(2), intent(in) :: ghosts
+ real(wp),dimension(:,:), intent(in) :: input_x, input_y
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
integer(C_INTPTR_T) :: i, j, ig, jg
! init
@@ -300,8 +301,8 @@ contains
!> Backward transform
subroutine c2r_2d(velocity_x,velocity_y, ghosts)
- real(mk),dimension(:,:),intent(inout) :: velocity_x,velocity_y
- integer, dimension(2), intent(in) :: ghosts
+ real(wp),dimension(:,:),intent(inout) :: velocity_x,velocity_y
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
integer(C_INTPTR_T) :: i, j, ig, jg
call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
@@ -330,8 +331,8 @@ contains
!> Backward transform for scalar field
subroutine c2r_scalar_2d(omega, ghosts)
- real(mk),dimension(:,:),intent(inout) :: omega
- integer, dimension(2), intent(in) :: ghosts
+ real(wp),dimension(:,:),intent(inout) :: omega
+ integer(kind=ip), dimension(2), intent(in) :: ghosts
integer(C_INTPTR_T) :: i, j, ig, jg
call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
@@ -365,7 +366,7 @@ contains
!> @param lengths size of the domain
subroutine computeKx(length)
- real(mk),intent(in) :: length
+ real(wp),intent(in) :: length
!! Local loops indices
integer(C_INTPTR_T) :: i
@@ -383,7 +384,7 @@ contains
!> @param lengths size of the domain
subroutine computeKxC(length)
- real(mk),intent(in) :: length
+ real(wp),intent(in) :: length
!! Local loops indices
integer(C_INTPTR_T) :: i
@@ -420,7 +421,7 @@ contains
!> Computation of frequencies coeff, over non-distributed direction(s)
!> @param lengths size of the domain
subroutine computeKy(length)
- real(mk), intent(in) :: length
+ real(wp), intent(in) :: length
!! Local loops indices
integer(C_INTPTR_T) :: i
@@ -491,7 +492,7 @@ contains
do i = 1,local_resolution(c_X)
do j = 1, fft_resolution(c_Y)
- coeff = 1./(1. + nudt * (kx(i)**2+ky(j)**2))
+ coeff = ONE/(ONE + nudt * (kx(i)**2+ky(j)**2))
dataout1(j,i) = coeff*dataout1(j,i)
end do
end do
@@ -533,13 +534,13 @@ contains
subroutine fft2d_diagnostics(nbelem)
integer(C_INTPTR_T), intent(in) :: nbelem
complex(C_DOUBLE_COMPLEX) :: memoryAllocated
- memoryAllocated = real(nbelem*sizeof(memoryAllocated),mk)*1e-6
+ memoryAllocated = real(nbelem*sizeof(memoryAllocated),wp)*1e-6
write(*,'(a,i5,a,i12,f10.2)') '[',rank,'] size of each buffer (elements / memory in MB):', &
nbelem, memoryAllocated
write(*,'(a,i5,a,2i12)') '[',rank,'] size of kx,y,z vectors (number of elements):', &
size(kx), size(ky)
write(*,'(a,i5,a,4i5)') '[',rank,'] local resolution and offset :', local_resolution, local_offset
- memoryAllocated = 2*memoryAllocated + real(sizeof(kx) + sizeof(ky), mk)*1e-6
+ memoryAllocated = 2*memoryAllocated + real(sizeof(kx) + sizeof(ky), wp)*1e-6
write(*,'(a,i5,a,f10.2)') '[',rank,'] Total memory used for fftw buffers (MB):', memoryAllocated
end subroutine fft2d_diagnostics
@@ -548,8 +549,8 @@ contains
!! @param datashape local shape of the input field for the fftw process
!! @param offset index of the first component of the local field (in each dir) in the global set of indices
subroutine getParamatersTopologyFFTW2d(datashape,offset)
- integer(C_INTPTR_T), intent(out),dimension(2) :: datashape
- integer(C_INTPTR_T), intent(out),dimension(2) :: offset
+ integer(kind=ip), intent(out),dimension(2) :: datashape
+ integer(kind=ip), intent(out),dimension(2) :: offset
integer(C_INTPTR_T) :: offsetx = 0
datashape = (/fft_resolution(c_X), local_resolution(c_Y)/)
offset = (/ offsetx, local_offset(c_Y)/)
@@ -559,8 +560,8 @@ contains
!! @param[in] resolution global domain resolution
subroutine init_r2c_2dBIS(resolution,lengths)
- integer, dimension(2), intent(in) :: resolution
- real(mk),dimension(2), intent(in) :: lengths
+ integer(kind=ip), dimension(2), intent(in) :: resolution
+ real(wp),dimension(2), intent(in) :: lengths
!! Size of the local memory required for fftw (cbuffer)
integer(C_INTPTR_T) :: alloc_local,halfLength,howmany
integer(C_INTPTR_T), dimension(2) :: n
@@ -607,7 +608,7 @@ contains
call computeKx(lengths(c_X))
call computeKy(lengths(c_Y))
- normFFT = 1./(fft_resolution(c_X)*fft_resolution(c_Y))
+ normFFT = ONE/(fft_resolution(c_X)*fft_resolution(c_Y))
!! call fft2d_diagnostics(alloc_local)
end subroutine init_r2c_2dBIS
diff --git a/src/fftw/fft3d.f90 b/hysop/old/numerics.old/fftw_f/fft3d.f90
similarity index 93%
rename from src/fftw/fft3d.f90
rename to hysop/old/numerics.old/fftw_f/fft3d.f90
index b9b5d922b540ba3b63107178c962eda0fab1ef78..23580aca7229ed2f6a37fec5f35624d46e81a0d3 100755
--- a/src/fftw/fft3d.f90
+++ b/hysop/old/numerics.old/fftw_f/fft3d.f90
@@ -15,8 +15,11 @@
!! dedicated to tests and validation.
module fft3d
- use client_data
+ use, intrinsic :: iso_c_binding
use mpi
+ use precision
+ use parameters
+
implicit none
include 'fftw3-mpi.f03'
@@ -80,8 +83,8 @@ contains
!! @param[in] lengths width of each side of the domain
subroutine init_c2c_3d(resolution,lengths)
- integer, dimension(3), intent(in) :: resolution
- real(mk),dimension(3), intent(in) :: lengths
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
!! Size of the local memory required for fftw (cbuffer)
integer(C_INTPTR_T) :: alloc_local
@@ -143,7 +146,7 @@ contains
!! call fft3d_diagnostics(alloc_local)
- normFFT = 1./(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
manycase = .false.
is3DUpToDate = .true.
@@ -158,8 +161,8 @@ contains
!! @param[in] velocity_y 3d scalar field, y-component of the output vector field
!! @param[in] velocity_z 3d scalar field, z-component of the output vector field
subroutine c2c_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z)
- complex(mk),dimension(:,:,:) :: velocity_x,velocity_y,velocity_z
- complex(mk),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
+ complex(wp),dimension(:,:,:) :: velocity_x,velocity_y,velocity_z
+ complex(wp),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
integer(C_INTPTR_T) :: i,j,k
! Copy input data into the fftw buffer
@@ -205,8 +208,8 @@ contains
!! @param[in] lengths width of each side of the domain
subroutine init_r2c_3d(resolution,lengths)
- integer, dimension(3), intent(in) :: resolution
- real(mk),dimension(3), intent(in) :: lengths
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
!! Size of the local memory required for fftw (cbuffer)
integer(C_INTPTR_T) :: alloc_local,halfLength
@@ -263,7 +266,7 @@ contains
call computeKy(lengths(c_Y))
call computeKz(lengths(c_Z))
- normFFT = 1./(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
!! call fft3d_diagnostics(alloc_local)
manycase = .false.
is3DUpToDate = .true.
@@ -275,8 +278,8 @@ contains
!! @param[in] lengths width of each side of the domain
subroutine init_r2c_scalar_3d(resolution,lengths)
- integer, dimension(3), intent(in) :: resolution
- real(mk),dimension(3), intent(in) :: lengths
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
!! Size of the local memory required for fftw (cbuffer)
integer(C_INTPTR_T) :: alloc_local,halfLength
@@ -317,7 +320,7 @@ contains
call computeKy(lengths(c_Y))
call computeKz(lengths(c_Z))
- normFFT = 1./(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
!! call fft3d_diagnostics(alloc_local)
manycase = .false.
is3DUpToDate = .true.
@@ -331,9 +334,9 @@ contains
!! @param[in] ghosts, number of points in the ghost layer of input fields.
subroutine r2c_3d(omega_x,omega_y,omega_z, ghosts)
- real(mk),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
- integer, dimension(3), intent(in) :: ghosts
- !real(mk) :: start
+ real(wp),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ !real(wp) :: start
integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
! ig, jg, kg are used to take into account
@@ -368,9 +371,9 @@ contains
!! @param[in,out] velocity_z 3d scalar field, z-component of the output vector field
!! @param[in] ghosts, number of points in the ghost layer of in/out velocity field.
subroutine c2r_3d(velocity_x,velocity_y,velocity_z, ghosts)
- real(mk),dimension(:,:,:),intent(inout) :: velocity_x,velocity_y,velocity_z
- integer, dimension(3), intent(in) :: ghosts
- real(mk) :: start
+ real(wp),dimension(:,:,:),intent(inout) :: velocity_x,velocity_y,velocity_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp) :: start
integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
start = MPI_WTIME()
call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
@@ -398,9 +401,9 @@ contains
!! @param[in] ghosts, number of points in the ghost layer of input field.
subroutine r2c_scalar_3d(scalar, ghosts)
- real(mk),dimension(:,:,:),intent(in) :: scalar
- integer, dimension(3), intent(in) :: ghosts
- real(mk) :: start
+ real(wp),dimension(:,:,:),intent(in) :: scalar
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp) :: start
integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
! ig, jg, kg are used to take into account
@@ -429,9 +432,9 @@ contains
!! @param[in,out] scalar 3d scalar field
!! @param[in] ghosts, number of points in the ghost layer of in/out scalar field.
subroutine c2r_scalar_3d(scalar, ghosts)
- real(mk),dimension(:,:,:),intent(inout) :: scalar
- integer, dimension(3), intent(in) :: ghosts
- real(mk) :: start
+ real(wp),dimension(:,:,:),intent(inout) :: scalar
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp) :: start
integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
start = MPI_WTIME()
call fftw_mpi_execute_dft_c2r(plan_backward1,dataout1,rdatain1)
@@ -459,8 +462,8 @@ contains
!! @param[in] lengths width of each side of the domain
subroutine init_r2c_3d_many(resolution,lengths)
- integer, dimension(3), intent(in) :: resolution
- real(mk),dimension(3), intent(in) :: lengths
+ integer(kind=ip), dimension(3), intent(in) :: resolution
+ real(wp),dimension(3), intent(in) :: lengths
!! Size of the local memory required for fftw (cbuffer)
integer(C_INTPTR_T) :: alloc_local,halfLength,howmany, blocksize
integer(C_INTPTR_T),dimension(3) :: n
@@ -502,7 +505,7 @@ contains
call computeKy(lengths(c_Y))
call computeKz(lengths(c_Z))
- normFFT = 1./(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
+ normFFT = one/(fft_resolution(c_X)*fft_resolution(c_Y)*fft_resolution(c_Z))
!! call fft3d_diagnostics(alloc_local,1)
manycase = .true.
@@ -517,8 +520,8 @@ contains
!! @param input data
subroutine r2c_3d_many(omega_x,omega_y,omega_z)
- real(mk),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
- real(mk) :: start
+ real(wp),dimension(:,:,:),intent(in) :: omega_x,omega_y,omega_z
+ real(wp) :: start
integer(C_INTPTR_T) :: i,j,k
! init
@@ -544,8 +547,8 @@ contains
!! @param[in,out] velocity_y 3d scalar field, y-component of the output vector field
!! @param[in,out] velocity_z 3d scalar field, z-component of the output vector field
subroutine c2r_3d_many(velocity_x,velocity_y,velocity_z)
- real(mk),dimension(:,:,:),intent(inout) :: velocity_x,velocity_y,velocity_z
- real(mk) :: start
+ real(wp),dimension(:,:,:),intent(inout) :: velocity_x,velocity_y,velocity_z
+ real(wp) :: start
integer(C_INTPTR_T) :: i,j,k
start = MPI_WTIME()
@@ -571,7 +574,7 @@ contains
!> @param lengths size of the domain
subroutine computeKx(length)
- real(mk),intent(in) :: length
+ real(wp),intent(in) :: length
!! Local loops indices
integer(C_INTPTR_T) :: i
@@ -624,7 +627,7 @@ contains
!> Computation of frequencies coeff, over non-distributed direction(s)
!> @param length size of the domain
subroutine computeKz(length)
- real(mk),intent(in) :: length
+ real(wp),intent(in) :: length
!! Local loops indices
integer(C_INTPTR_T) :: i
@@ -711,7 +714,7 @@ contains
do j = 1,local_resolution(c_Y)
do k = 1, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
- coeff = Icmplx/(1. + nudt * (kx(i)**2+ky(j)**2+kz(k)**2))
+ coeff = Icmplx/(one + nudt * (kx(i)**2+ky(j)**2+kz(k)**2))
buffer1 = dataout1(i,k,j)
buffer2 = dataout2(i,k,j)
dataout1(i,k,j) = coeff*(ky(j)*dataout3(i,k,j)-kz(k)*dataout2(i,k,j))
@@ -736,7 +739,7 @@ contains
do j = 1,local_resolution(c_Y)
do k = 1, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
- coeff = 1./(1. + nudt * (kx(i)**2+ky(j)**2+kz(k)**2))
+ coeff = one/(one + nudt * (kx(i)**2+ky(j)**2+kz(k)**2))
dataout1(i,k,j) = coeff*dataout1(i,k,j)
dataout2(i,k,j) = coeff*dataout2(i,k,j)
dataout3(i,k,j) = coeff*dataout3(i,k,j)
@@ -784,7 +787,7 @@ contains
dataout2(1,1,1) = dataout2(1,1,1)
dataout3(1,1,1) = dataout3(1,1,1)
else
- coeff = 1./(ky(1)**2)
+ coeff = one/(ky(1)**2)
buffer2 = dataout2(1,1,1)
dataout1(1,1,1) = dataout1(1,1,1)
dataout2(1,1,1) = dataout2(1,1,1) - coeff*ky(1)*(ky(1)*buffer2)
@@ -793,7 +796,7 @@ contains
! !! mind the transpose -> index inversion between y and z
do i = 2, local_resolution(c_X)
- coeff = 1./(kx(i)**2+ky(1)**2+kz(1)**2)
+ coeff = one/(kx(i)**2+ky(1)**2+kz(1)**2)
buffer1 = dataout1(i,1,1)
buffer2 = dataout2(i,1,1)
buffer3 = dataout3(i,1,1)
@@ -805,7 +808,7 @@ contains
! !! mind the transpose -> index inversion between y and z
do k = 2, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
- coeff = 1./(kx(i)**2+ky(1)**2+kz(k)**2)
+ coeff = one/(kx(i)**2+ky(1)**2+kz(k)**2)
buffer1 = dataout1(i,k,1)
buffer2 = dataout2(i,k,1)
buffer3 = dataout3(i,k,1)
@@ -819,7 +822,7 @@ contains
do j = 2,local_resolution(c_Y)
do k = 1, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
- coeff = 1./(kx(i)**2+ky(j)**2+kz(k)**2)
+ coeff = one/(kx(i)**2+ky(j)**2+kz(k)**2)
buffer1 = dataout1(i,k,j)
buffer2 = dataout2(i,k,j)
buffer3 = dataout3(i,k,j)
@@ -870,20 +873,20 @@ contains
if(local_offset(c_Y) == 0) then
dataout1(1,1,1) = 0.0
else
- coeff = -1./(ky(1)**2)
+ coeff = -one/(ky(1)**2)
dataout1(1,1,1) = coeff*dataout1(1,1,1)
endif
! !! mind the transpose -> index inversion between y and z
do i = 2, local_resolution(c_X)
- coeff = -1./(kx(i)**2+ky(1)**2)
+ coeff = -one/(kx(i)**2+ky(1)**2)
dataout1(i,1,1) = coeff*dataout1(i,1,1)
end do
! !! mind the transpose -> index inversion between y and z
do k = 2, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
- coeff = -1./(kx(i)**2+ky(1)**2+kz(k)**2)
+ coeff = -one/(kx(i)**2+ky(1)**2+kz(k)**2)
dataout1(i,k,1) = coeff*dataout1(i,k,1)
end do
end do
@@ -892,7 +895,7 @@ contains
do j = 2,local_resolution(c_Y)
do k = 1, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
- coeff = -1./(kx(i)**2+ky(j)**2+kz(k)**2)
+ coeff = -one/(kx(i)**2+ky(j)**2+kz(k)**2)
dataout1(i,k,j) = coeff*dataout1(i,k,j)
end do
end do
@@ -970,7 +973,7 @@ contains
do j = 1,local_resolution(c_Y)
do k = 1, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
- coeff = Icmplx/(1. + nudt * kx(i)**2+ky(j)**2+kz(k)**2)
+ coeff = Icmplx/(one + nudt * kx(i)**2+ky(j)**2+kz(k)**2)
buffer1 = dataout_many(1,i,k,j)
buffer2 = dataout_many(2,i,k,j)
dataout_many(1,i,k,j) = coeff*(ky(j)*dataout_many(3,i,k,j)-kz(k)*dataout_many(2,i,k,j))
@@ -1014,13 +1017,13 @@ contains
else
nbFields = 3
end if
- memoryAllocated = real(nbelem*sizeof(memoryAllocated),mk)*1e-6
+ memoryAllocated = real(nbelem*sizeof(memoryAllocated),wp)*1e-6
write(*,'(a,i5,a,i12,f10.2)') '[',rank,'] size of each buffer (elements / memory in MB):', &
nbelem, memoryAllocated
write(*,'(a,i5,a,3i12)') '[',rank,'] size of kx,y,z vectors (number of elements):', &
size(kx), size(ky),size(kz)
write(*,'(a,i5,a,6i5)') '[',rank,'] local resolution and offset :', local_resolution, local_offset
- memoryAllocated = nbFields*memoryAllocated + real(sizeof(kx) + sizeof(ky) + sizeof(kz), mk)*1e-6
+ memoryAllocated = nbFields*memoryAllocated + real(sizeof(kx) + sizeof(ky) + sizeof(kz), wp)*1e-6
write(*,'(a,i5,a,f10.2)') '[',rank,'] Total memory used for fftw buffers (MB):', memoryAllocated
end subroutine fft3d_diagnostics
@@ -1029,22 +1032,20 @@ contains
!! @param datashape local shape of the input field for the fftw process
!! @param offset index of the first component of the local field (in each dir) in the global set of indices
subroutine getParamatersTopologyFFTW3d(datashape,offset)
- integer(C_INTPTR_T), intent(out),dimension(3) :: datashape
- integer(C_INTPTR_T), intent(out),dimension(3) :: offset
- integer(C_INTPTR_T) :: zero = 0
+ integer(kind=ip), intent(out),dimension(3) :: datashape
+ integer(kind=ip), intent(out),dimension(3) :: offset
+ integer(C_INTPTR_T) :: i_zero = 0
datashape = (/fft_resolution(c_X), fft_resolution(c_Y), local_resolution(c_Z)/)
- offset = (/zero, zero, local_offset(c_Z)/)
-
+ offset = (/i_zero, i_zero, local_offset(c_Z)/)
end subroutine getParamatersTopologyFFTW3d
-
!> forward transform - The result is saved in local buffers
!! @param[in] field 3d scalar field, x-component of the input vector field
!! @param[in] ghosts, number of points in the ghost layer of input fields.
subroutine r2c_3d_scal(field, ghosts)
- real(mk),dimension(:,:,:),intent(in) :: field
- integer, dimension(3), intent(in) :: ghosts
+ real(wp),dimension(:,:,:),intent(in) :: field
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
!real(8) :: start
integer(C_INTPTR_T) :: i,j,k, ig, jg, kg
@@ -1072,28 +1073,28 @@ contains
!> Compute spectrum of the given data
subroutine filter_spectrum_3d(spectrum,wavelengths,length)
- real(mk),dimension(:),intent(inout) :: spectrum
- real(mk),dimension(:),intent(inout) :: wavelengths
- real(mk),intent(in) :: length
+ real(wp),dimension(:),intent(inout) :: spectrum
+ real(wp),dimension(:),intent(inout) :: wavelengths
+ real(wp),intent(in) :: length
integer(C_INTPTR_T) :: i,j,k
- real(mk) :: c
- real(mk) :: kk,dk,kc,eps
- integer(C_INTPTR_T) :: ik
+ real(wp) :: c
+ real(wp) :: kk,dk,kc,eps
+ integer(C_INTPTR_T) :: indk
spectrum = 0
- dk = 2.0_mk*pi/length
+ dk = 2.0_wp*pi/length
kc = pi*fft_resolution(c_X)/length
- eps=kc/1000000.0_mk
+ eps=kc/1000000.0_wp
!! mind the transpose -> index inversion between y and z
- c = 1._mk/real(fft_resolution(c_Z)*fft_resolution(c_Y)*fft_resolution(c_X),mk)
+ c = one/real(fft_resolution(c_Z)*fft_resolution(c_Y)*fft_resolution(c_X),wp)
c = c * c
do j = 1,local_resolution(c_Y)
do k = 1, fft_resolution(c_Z)
do i = 1, local_resolution(c_X)
kk=sqrt(kx(i)**2+ky(j)**2+kz(k)**2)
if ((kk.gt.eps).and.(kk.le.kc)) then
- ik=1+int(kk/dk+0.5_mk)
- spectrum(ik) = spectrum(ik) + real(dataout1(i,j,k)*conjg(dataout1(i,j,k)), mk) * c
+ indk=1+int(kk/dk+0.5_wp)
+ spectrum(indk) = spectrum(indk) + real(dataout1(i,j,k)*conjg(dataout1(i,j,k)), wp) * c
end if
end do
end do
diff --git a/hysop/old/numerics.old/fftw_f/fftw2py.f90 b/hysop/old/numerics.old/fftw_f/fftw2py.f90
new file mode 100755
index 0000000000000000000000000000000000000000..09517a4ca3034a9800a76e99c94ff9656963e2a9
--- /dev/null
+++ b/hysop/old/numerics.old/fftw_f/fftw2py.f90
@@ -0,0 +1,330 @@
+!> @file fftw2py.f90
+!! Fortran to python interface file.
+
+!> Interface to mpi-fftw (fortran) utilities
+module fftw2py
+
+ use precision
+ use parameters
+ !> 2d case
+ use fft2d
+ !> 3d case
+ use fft3d
+ use, intrinsic :: iso_c_binding
+ use mpi, only : mpi_comm_dup, mpi_wtime
+ implicit none
+
+contains
+
+ !> Initialisation of fftw context : create plans and memory buffers
+ !! @param[in] resolution global resolution of the discrete domain
+ !! @param[in] lengths width of each side of the domain
+ !! @param[in] comm MPI communicator
+ !! @param[out] datashape local dimension of the input/output field
+ !! @param[out] offset absolute index of the first component of the local field
+ subroutine init_fftw_solver(resolution,lengths,comm,datashape,offset,dim,fftw_type_real)
+
+ integer, intent(in) :: dim
+ integer(kind=ip), dimension(dim),intent(in) :: resolution
+ real(wp),dimension(dim), intent(in) :: lengths
+ integer(kind=ip), dimension(dim), intent(out) :: datashape
+ integer(kind=ip), dimension(dim), intent(out) :: offset
+ integer, intent(in) :: comm
+ logical, optional :: fftw_type_real
+ !f2py optional :: dim=len(resolution)
+ !f2py intent(hide) dim
+ !f2py logical optional, intent(in) :: fftw_type_real = 1
+
+ integer :: ierr
+
+ ! Duplicate comm into client_data::main_comm (used later in fft2d and fft3d)
+ call mpi_comm_dup(comm, main_comm, ierr)
+
+ if(fftw_type_real) then
+ if(dim == 2) then
+ !print*, "Init fftw/poisson solver for a 2d problem"
+ call init_r2c_2d(resolution,lengths)
+ else
+ !print*, "Init fftw/poisson solver for a 3d problem"
+ call init_r2c_3d(resolution,lengths)
+ end if
+ else
+ if(dim == 2) then
+ !print*, "Init fftw/poisson solver for a 2d problem"
+ call init_c2c_2d(resolution,lengths)
+ else
+ !print*, "Init fftw/poisson solver for a 3d problem"
+ call init_c2c_3d(resolution,lengths)
+ end if
+ end if
+
+ if(dim==2) then
+ call getParamatersTopologyFFTW2d(datashape,offset)
+ else
+ call getParamatersTopologyFFTW3d(datashape,offset)
+ end if
+ end subroutine init_fftw_solver
+
+
+ !> Initialisation of fftw context : create plans and memory buffers
+ !! @param[in] resolution global resolution of the discrete domain
+ !! @param[in] lengths width of each side of the domain
+ !! @param[in] comm MPI communicator
+ !! @param[out] datashape local dimension of the input/output field
+ !! @param[out] offset absolute index of the first component of the local field
+ subroutine init_fftw_solver_scalar(resolution,lengths,comm,datashape,offset,dim,fftw_type_real)
+
+ integer, intent(in) :: dim
+ integer(kind=ip), dimension(dim),intent(in) :: resolution
+ real(wp),dimension(dim), intent(in) :: lengths
+ integer(kind=ip), dimension(dim), intent(out) :: datashape
+ integer(kind=ip), dimension(dim), intent(out) :: offset
+ integer, intent(in) :: comm
+ logical, optional :: fftw_type_real
+ !f2py optional :: dim=len(resolution)
+ !f2py intent(hide) dim
+ !f2py logical optional, intent(in) :: fftw_type_real = 1
+
+ integer :: ierr
+
+ ! Duplicate comm into client_data::main_comm (used later in fft2d and fft3d)
+ call mpi_comm_dup(comm, main_comm, ierr)
+
+ !print*, "Init fftw/poisson solver for a 3d problem"
+ call init_r2c_scalar_3d(resolution,lengths)
+
+ call getParamatersTopologyFFTW3d(datashape,offset)
+
+ end subroutine init_fftw_solver_scalar
+
+ !> Free memory allocated for fftw-related objects (plans and buffers)
+ subroutine clean_fftw_solver(dim)
+
+ integer, intent(in) :: dim
+ if(dim == 2) then
+ call cleanFFTW_2d()
+ else
+ call cleanFFTW_3d()
+ end if
+ end subroutine clean_fftw_solver
+
+ !> Solve
+ !! \f[ \nabla (\nabla \times velocity) = - \omega \f]
+ !! velocity being a 2D vector field and omega a 2D scalar field.
+ subroutine solve_poisson_2d(omega,velocity_x,velocity_y, ghosts_vort, ghosts_velo)
+ real(wp),dimension(:,:),intent(in):: omega
+ real(wp),dimension(size(omega,1),size(omega,2)),intent(out) :: velocity_x,velocity_y
+ integer(kind=ip), dimension(2), intent(in) :: ghosts_vort, ghosts_velo
+ !f2py intent(in,out) :: velocity_x,velocity_y
+
+ call r2c_scalar_2d(omega, ghosts_vort)
+
+ call filter_poisson_2d()
+
+ call c2r_2d(velocity_x,velocity_y, ghosts_velo)
+ !!print *, "fortran resolution time : ", MPI_WTime() - start
+
+ end subroutine solve_poisson_2d
+
+ !> Solve
+ !! \f{eqnarray*} \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
+ !! omega being a 2D scalar field.
+ subroutine solve_diffusion_2d(nudt, omega, ghosts_vort)
+ real(wp), intent(in) :: nudt
+ real(wp),dimension(:,:),intent(inout):: omega
+ integer(kind=ip), dimension(2), intent(in) :: ghosts_vort
+ !f2py intent(in,out) :: omega
+
+ call r2c_scalar_2d(omega, ghosts_vort)
+
+ call filter_diffusion_2d(nudt)
+
+ call c2r_scalar_2d(omega, ghosts_vort)
+
+ end subroutine solve_diffusion_2d
+
+ !> Solve
+ !! \f{eqnarray*} \Delta \psi &=& - \omega \\ velocity = \nabla\times\psi \f}
+ !! velocity and omega being 3D vector fields.
+ subroutine solve_poisson_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z, ghosts_vort, ghosts_velo)
+ real(wp),dimension(:,:,:),intent(in):: omega_x,omega_y,omega_z
+ real(wp),dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(out) :: velocity_x,velocity_y,velocity_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts_vort, ghosts_velo
+ real(wp) :: start
+ !f2py intent(in,out) :: velocity_x,velocity_y,velocity_z
+ start = MPI_WTime()
+ call r2c_3d(omega_x,omega_y,omega_z, ghosts_vort)
+
+ call filter_poisson_3d()
+
+ call c2r_3d(velocity_x,velocity_y,velocity_z, ghosts_velo)
+ !!print *, "fortran resolution time : ", MPI_WTime() - start
+
+ end subroutine solve_poisson_3d
+
+ !> Solve
+ !! \f{eqnarray*} \Delta \psi &=& - \omega \\ velocity = \nabla\times\psi \f}
+ !! velocity being a 2D complex vector field and omega a 2D complex scalar field.
+ subroutine solve_poisson_2d_c(omega,velocity_x,velocity_y)
+ complex(wp),dimension(:,:),intent(in):: omega
+ complex(wp),dimension(size(omega,1),size(omega,2)),intent(out) :: velocity_x,velocity_y
+ !f2py intent(in,out) :: velocity_x,velocity_y
+
+ call c2c_2d(omega,velocity_x,velocity_y)
+
+ end subroutine solve_poisson_2d_c
+
+ !> Solve
+ !! \f{eqnarray*} \Delta \psi &=& - \omega \\ velocity = \nabla\times\psi \f}
+ !! velocity and omega being 3D complex vector fields.
+ subroutine solve_poisson_3d_c(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_Z)
+ complex(wp),dimension(:,:,:),intent(in):: omega_x,omega_y,omega_z
+ complex(wp),dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(out) :: velocity_x,velocity_y,velocity_z
+ !f2py intent(in,out) :: velocity_x,velocity_y,velocity_z
+
+ call c2c_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z)
+
+ end subroutine solve_poisson_3d_c
+
+ !> Solve
+ !! \f{eqnarray*} \omega &=& \nabla \times v \\ \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
+ !! velocity and omega being 3D vector fields.
+ subroutine solve_curl_diffusion_3d(nudt,velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z, ghosts_velo, ghosts_vort)
+ real(wp), intent(in) :: nudt
+ real(wp),dimension(:,:,:),intent(in):: velocity_x,velocity_y,velocity_z
+ real(wp),dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(out) :: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts_vort, ghosts_velo
+ !f2py intent(in,out) :: omega_x,omega_y,omega_z
+
+ call r2c_3d(velocity_x,velocity_y,velocity_z, ghosts_velo)
+
+ call filter_curl_diffusion_3d(nudt)
+
+ call c2r_3d(omega_x,omega_y,omega_z, ghosts_vort)
+
+ end subroutine solve_curl_diffusion_3d
+
+ !> Solve
+ !! \f{eqnarray*} \frac{\partial \omega}{\partial t} &=& \nu \Delta \omega \f}
+ !! omega being 3D vector field.
+ subroutine solve_diffusion_3d(nudt,omega_x,omega_y,omega_z, ghosts)
+ real(wp), intent(in) :: nudt
+ real(wp),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ !f2py intent(in,out) :: omega_x,omega_y,omega_z
+
+ call r2c_3d(omega_x,omega_y,omega_z, ghosts)
+
+ call filter_diffusion_3d(nudt)
+
+ call c2r_3d(omega_x,omega_y,omega_z, ghosts)
+
+ end subroutine solve_diffusion_3d
+
+ !> Perform solenoidal projection to ensure divergence free vorticity field
+ !! \f{eqnarray*} \omega ' &=& \omega - \nabla\pi \f}
+ !! omega being a 3D vector field.
+ subroutine projection_om_3d(omega_x,omega_y,omega_z, ghosts)
+ real(wp),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ !f2py intent(in,out) :: omega_x,omega_y,omega_z
+
+ call r2c_3d(omega_x,omega_y,omega_z, ghosts)
+
+ call filter_projection_om_3d()
+
+ call c2r_3d(omega_x,omega_y,omega_z, ghosts)
+
+ end subroutine projection_om_3d
+
+ !> Projects vorticity values from fine to coarse grid :
+ !! @param[in] dxf, dyf, dzf: grid filter size = domainLength/(CoarseRes-1)
+ !! in the following, omega is the 3D vorticity vector field.
+ subroutine multires_om_3d(dxf, dyf, dzf, omega_x,omega_y,omega_z, ghosts)
+ real(wp), intent(in) :: dxf, dyf, dzf
+ real(wp),dimension(:,:,:),intent(inout):: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+
+ !f2py intent(in,out) :: omega_x,omega_y,omega_z
+
+ call r2c_3d(omega_x,omega_y,omega_z, ghosts)
+
+ call filter_multires_om_3d(dxf, dyf, dzf)
+
+ call c2r_3d(omega_x,omega_y,omega_z, ghosts)
+
+ end subroutine multires_om_3d
+
+ !> Compute the pressure from the velocity field, solving a Poisson equation.
+ !! \f{eqnarray*} \Delta p ' &=& rhs \f}
+ !! with rhs depending on the first derivatives of the velocity field
+ !! @param[in, out] pressure
+ !! in the following, pressure is used as inout parameter. It must contains the rhs of poisson equation.
+ subroutine pressure_3d(pressure, ghosts)
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp),dimension(:,:,:),intent(inout):: pressure
+ !f2py intent(in,out) :: pressure
+
+ call r2c_scalar_3d(pressure, ghosts)
+
+ call filter_pressure_3d()
+
+ call c2r_scalar_3d(pressure, ghosts)
+
+ end subroutine pressure_3d
+
+ !> Solve
+ !! \f{eqnarray*} \omega &=& \nabla \times v
+ !! velocity and omega being 3D vector fields.
+ subroutine solve_curl_3d(velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z, ghosts_velo, ghosts_vort)
+ real(wp),dimension(:,:,:),intent(in):: velocity_x,velocity_y,velocity_z
+ real(wp),dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(out) :: omega_x,omega_y,omega_z
+ integer(kind=ip), dimension(3), intent(in) :: ghosts_velo, ghosts_vort
+ !f2py intent(in,out) :: omega_x,omega_y,omega_z
+
+ call r2c_3d(velocity_x,velocity_y,velocity_z, ghosts_velo)
+
+ call filter_curl_3d()
+
+ call c2r_3d(omega_x,omega_y,omega_z, ghosts_vort)
+
+ end subroutine solve_curl_3d
+
+
+ !> Solve
+ !! \f{eqnarray*} \omega &=& \nabla \times v
+ !! velocity and omega being 2D vector and scalar fields.
+ subroutine solve_curl_2d(velocity_x,velocity_y, omega_z, ghosts_velo, ghosts_vort)
+ real(wp), dimension(:,:), intent(in):: velocity_x,velocity_y
+ real(wp), dimension(size(velocity_x,1), size(velocity_x,2)), intent(out) :: omega_z
+ integer(kind=ip), dimension(2), intent(in) :: ghosts_velo, ghosts_vort
+ !f2py intent(in,out) :: omega_z
+
+ call r2c_2d(velocity_x,velocity_y, ghosts_velo)
+
+ call filter_curl_2d()
+
+ call c2r_scalar_2d(omega_z, ghosts_vort)
+
+ end subroutine solve_curl_2d
+
+ !> Compute spectrum of a scalar field
+ !! @param[in] field
+ !! @param[out] spectrum
+ subroutine spectrum_3d(field, spectrum, wavelengths, ghosts, length)
+ real(wp),dimension(:,:,:),intent(in):: field
+ integer(kind=ip), dimension(3), intent(in) :: ghosts
+ real(wp),dimension(:), intent(inout) :: spectrum
+ real(wp),dimension(:), intent(inout) :: wavelengths
+ real(wp),intent(in) :: length
+ !f2py intent(in) :: field
+ !f2py intent(inout) :: spectrum
+ !f2py intent(inout) :: wavelengths
+
+ call r2c_3d_scal(field, ghosts)
+
+ call filter_spectrum_3d(spectrum, wavelengths, length)
+
+ end subroutine spectrum_3d
+
+end module fftw2py
diff --git a/hysop/old/numerics.old/fftw_f/fftw2py.pyf b/hysop/old/numerics.old/fftw_f/fftw2py.pyf
new file mode 100644
index 0000000000000000000000000000000000000000..74ac41ee1c12458b18ea26880d940ab6f0a52d9f
--- /dev/null
+++ b/hysop/old/numerics.old/fftw_f/fftw2py.pyf
@@ -0,0 +1,131 @@
+! -*- f90 -*-
+! Note: the context of this file is case sensitive.
+
+module fftw2py ! in fftw2py.f90
+ use fft2d
+ use fft3d
+ use precision
+ use parameters
+ use mpi
+ subroutine init_fftw_solver(resolution,lengths,comm,datashape,offset,dim,fftw_type_real) ! in fftw2py.f90:fftw2py
+ integer(kind=ip), dimension(dim),intent(in) :: resolution
+ real(kind=wp) dimension(dim),intent(in),depend(dim) :: lengths
+ integer intent(in) :: comm
+ integer(kind=ip) dimension(dim),intent(out),depend(dim) :: datashape
+ integer(kind=ip) dimension(dim),intent(out),depend(dim) :: offset
+ integer, optional,intent(hide), depend(resolution) :: dim=len(resolution)
+ logical, optional,intent(in) :: fftw_type_real=1
+ end subroutine init_fftw_solver
+ subroutine init_fftw_solver_scalar(resolution,lengths,comm,datashape,offset,dim,fftw_type_real) ! in fftw2py.f90:fftw2py
+ integer(kind=ip) dimension(dim),intent(in) :: resolution
+ real(kind=wp) dimension(dim),intent(in),depend(dim) :: lengths
+ integer intent(in) :: comm
+ integer(ip) dimension(dim),intent(out),depend(dim) :: datashape
+ integer(ip) dimension(dim),intent(out),depend(dim) :: offset
+ integer, optional,intent(hide), ,depend(resolution) :: dim=len(resolution)
+ logical, optional,intent(in) :: fftw_type_real=1
+ end subroutine init_fftw_solver_scalar
+ subroutine clean_fftw_solver(dim) ! in fftw2py.f90:fftw2py
+ integer intent(in) :: dim
+ end subroutine clean_fftw_solver
+ subroutine solve_poisson_2d(omega,velocity_x,velocity_y,ghosts_vort,ghosts_velo) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:),intent(in) :: omega
+ real(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_x
+ real(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_y
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_vort
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_velo
+ end subroutine solve_poisson_2d
+ subroutine solve_diffusion_2d(nudt,omega,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: nudt
+ real(kind=wp) dimension(:,:),intent(in,out) :: omega
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_vort
+ end subroutine solve_diffusion_2d
+ subroutine solve_poisson_3d(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z,ghosts_vort,ghosts_velo) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in) :: omega_z
+ real(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_x
+ real(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_y
+ real(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_vort
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_velo
+ end subroutine solve_poisson_3d
+ subroutine solve_poisson_2d_c(omega,velocity_x,velocity_y) ! in fftw2py.f90:fftw2py
+ complex(kind=wp) dimension(:,:),intent(in) :: omega
+ complex(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_x
+ complex(kind=wp) dimension(size(omega,1),size(omega,2)),intent(in,out),depend(omega,omega) :: velocity_y
+ end subroutine solve_poisson_2d_c
+ subroutine solve_poisson_3d_c(omega_x,omega_y,omega_z,velocity_x,velocity_y,velocity_z) ! in fftw2py.f90:fftw2py
+ complex(kind=wp) dimension(:,:,:),intent(in) :: omega_x
+ complex(kind=wp) dimension(:,:,:),intent(in) :: omega_y
+ complex(kind=wp) dimension(:,:,:),intent(in) :: omega_z
+ complex(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_x
+ complex(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_y
+ complex(kind=wp) dimension(size(omega_x,1),size(omega_y,2),size(omega_z,3)),intent(in,out),depend(omega_x,omega_y,omega_z) :: velocity_z
+ end subroutine solve_poisson_3d_c
+ subroutine solve_curl_diffusion_3d(nudt,velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: nudt
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_x
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_y
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_z
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_x
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_y
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_velo
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_vort
+ end subroutine solve_curl_diffusion_3d
+ subroutine solve_diffusion_3d(nudt,omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: nudt
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine solve_diffusion_3d
+ subroutine projection_om_3d(omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine projection_om_3d
+ subroutine multires_om_3d(dxf,dyf,dzf,omega_x,omega_y,omega_z,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) intent(in) :: dxf
+ real(kind=wp) intent(in) :: dyf
+ real(kind=wp) intent(in) :: dzf
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_x
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_y
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine multires_om_3d
+ subroutine pressure_3d(pressure,ghosts) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: pressure
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ end subroutine pressure_3d
+ subroutine solve_curl_3d(velocity_x,velocity_y,velocity_z,omega_x,omega_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_x
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_y
+ real(kind=wp) dimension(:,:,:),intent(in) :: velocity_z
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_x
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_y
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_y,2),size(velocity_z,3)),intent(in,out),depend(velocity_x,velocity_y,velocity_z) :: omega_z
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_velo
+ integer(kind=ip) dimension(3),intent(in) :: ghosts_vort
+ end subroutine solve_curl_3d
+ subroutine solve_curl_2d(velocity_x,velocity_y,omega_z,ghosts_velo,ghosts_vort) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:),intent(in) :: velocity_x
+ real(kind=wp) dimension(:,:),intent(in) :: velocity_y
+ real(kind=wp) dimension(size(velocity_x,1),size(velocity_x,2)),intent(in,out),depend(velocity_x,velocity_x) :: omega_z
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_velo
+ integer(kind=ip) dimension(2),intent(in) :: ghosts_vort
+ end subroutine solve_curl_2d
+ subroutine spectrum_3d(field,spectrum,wavelengths,ghosts,length) ! in fftw2py.f90:fftw2py
+ real(kind=wp) dimension(:,:,:),intent(in) :: field
+ real(kind=wp) dimension(:),intent(in,out) :: spectrum
+ real(kind=wp) dimension(:),intent(in,out) :: wavelengths
+ integer(kind=ip) dimension(3),intent(in) :: ghosts
+ real(kind=wp) intent(in) :: length
+ end subroutine spectrum_3d
+
+end module fftw2py
+
+! This file was auto-generated with f2py (version:2).
+! See http://cens.ioc.ee/projects/f2py2e/
diff --git a/hysop/numerics/finite_differences.py b/hysop/old/numerics.old/finite_differences.py
similarity index 97%
rename from hysop/numerics/finite_differences.py
rename to hysop/old/numerics.old/finite_differences.py
index 7c0d3e221fc73882031ef0913bab6f363bb10914..18580128968a35466e89da9cdc08116c01098b4a 100644
--- a/hysop/numerics/finite_differences.py
+++ b/hysop/old/numerics.old/finite_differences.py
@@ -50,7 +50,7 @@ from abc import ABCMeta, abstractmethod
from hysop.constants import debug
from hysop.numerics.stencil import Stencil, StencilGenerator
from hysop.numerics.stencil import CenteredStencil, CenteredStencilGenerator
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
@@ -72,6 +72,9 @@ class FiniteDifference(object):
or result += the derivative of tab according to dir:
>> scheme.compute_and_add(tab, dir, result)
+
+ >>> from hysop import Box
+ >>> domain = Box()
Notes FP :
Compute method is much more performant than compute and add
@@ -87,7 +90,7 @@ class FiniteDifference(object):
def __new__(cls, *args, **kw):
return object.__new__(cls, *args, **kw)
- def __init__(self, step, indices, indices_out=None):
+ def __init__(self, step, indices, output_indices=None):
"""
Parameters
@@ -98,9 +101,9 @@ class FiniteDifference(object):
Represents the local mesh on which finite-differences
will be applied, like compute_index
in :class:`~hysop.domain.mesh.Mesh`.
- indices_out : list of slices, optional
+ output_indices : list of slices, optional
set which indices of result will be modified. By default,
- indices_out = indices
+ output_indices = indices
Attributes
----------
@@ -121,24 +124,24 @@ class FiniteDifference(object):
self._coeff = None
# List of slices representing the mesh on which fd scheme is applied
self.indices = indices
- if indices_out is None or indices_out is False:
+ if output_indices is None or output_indices is False:
# This is the default case. It means that
# result shape is unknown. It will
# be the same as input tab shape during call
# and input/output indices are the same:
# we compute result[indices] = scheme(tab[indices])
self.output_indices = self.indices
- elif isinstance(indices_out, list):
+ elif isinstance(output_indices, list):
# In that case, result shape remains unknown but
# the position where result is written is not the
# same as input indices.
# We compute:
- # result[indices_out] = scheme(tab[indices])
- # Warning : result shape/indices_out compliance
+ # result[output_indices] = scheme(tab[indices])
+ # Warning : result shape/output_indices compliance
# is not checked!
- self.output_indices = indices_out
+ self.output_indices = output_indices
- elif indices_out is True:
+ elif output_indices is True:
# Here, output shape is fixed to the minimal required
# shape, computed with indices.
# So, we compute:
diff --git a/hysop/old/numerics.old/interpolation.py b/hysop/old/numerics.old/interpolation.py
new file mode 100644
index 0000000000000000000000000000000000000000..8b0adbbe171a26f4812795bd43bddc3cc9f21841
--- /dev/null
+++ b/hysop/old/numerics.old/interpolation.py
@@ -0,0 +1,524 @@
+"""Interpolation methods
+
+.. currentmodule hysop.numerics
+
+* :class:`~interpolation.Linear`
+
+"""
+from hysop.constants import HYSOP_INTEGER, EPS
+from hysop.tools.misc import WorkSpaceTools
+import numpy as np
+from hysop.tools.numpywrappers import npw
+from abc import ABCMeta
+try:
+ from hysop.f2hysop import interpolation as finterpol
+except:
+ finterpol = None
+
+
+class Interpolation(object):
+ """Common interface to all 'interpolation-like' numerical methods
+ (interpolation, remesh)
+ """
+ __metaclass__ = ABCMeta
+ ghosts_layer_size = 0
+
+ def __init__(self, topo_source, direction,
+ topo_target=None, rwork=None, iwork=None):
+ """"Common interface to all 'interpolation-like' numerical methods
+ (interpolation, remesh)
+
+ Parameters
+ -----------
+ topo_source, topo_target : :class:`~hysop.core.mpi.topology.Cartesian`
+ mpi process and data distribution for source and target
+ (see Notes for details)
+ direction : int
+ direction of interpolation
+ rwork, iwork : list of numpy arrays
+ internal work spaces for real (work) and integer (iwork) data.
+
+ Attributes
+ ----------
+ ghosts_layer_size : int, static
+ minimal number of points required inside the ghost layer
+ for this scheme.
+
+ Notes
+ -----
+ * 'source' concerned all data related to the grid on which the field
+ to interpolate is known, and 'target' is used for data related
+ to the grid on which the field values must be computed using
+ interpolation.
+ * topo_target is required if and only if source and target grid
+ have different resolution.
+ """
+ self.direction = direction
+ self.topo_source = topo_source
+ if topo_target is None:
+ topo_target = topo_source
+ self.topo_target = topo_target
+ # Check ghost layer size (min required in the interpolation direction)
+ msg = 'Ghost layer is too small for the chosen scheme.'
+ required_ghost_layer = self.ghosts_layer_size
+ assert topo_source.ghosts()[direction] >= required_ghost_layer, msg
+
+ # work arrays
+ self._rwork, self._iwork = self._set_work_arrays(
+ rwork=rwork, iwork=iwork)
+
+ # indices of grid points that will be remeshed:
+ # - at most the resolution in remeshed direction
+ # --> update during call,
+ # (for example, it may depend on the number of particles)
+ # - all grid points except ghosts in other directions
+ ic = self.topo_source.mesh.compute_index
+ # grid indices in 'source' grid
+ self._icoords = np.ix_(
+ *(np.arange(ic[i].start, ic[i].stop)
+ for i in xrange(topo_source.domain.dimension)))
+ self._inv_dx = 1. / self.topo_source.mesh.space_step
+
+ #source_res = topo_source.mesh.resolution
+ #target_res = topo_target.mesh.resolution
+ #msg = 'Interpolation error : only implemented in 3D.'
+ #assert topo_source.domain.dimension == 3, msg
+ #assert topo_target.domain.dimension == 3, msg
+ #if (source_res == target_res).all():
+ # msg = 'Interpolation error : the two grids have the same '
+ # msg += 'resolution, interpolation is useless.'
+ #shape_cfc = (source_res[0], target_res[2], source_res[1])
+ #shape_ccf = (source_res[0], source_res[1], target_res[2])
+ #shape_ccc = (source_res[0], source_res[2], source_res[1])
+ #shape_ccf2 = (source_res[0], source_res[2], target_res[2])
+ #self._rwork = [npw.zeros(shape_cfc), npw.zeros(shape_ccf),
+ # npw.zeros(shape_ccc), npw.zeros(shape_ccf2)]
+ self.hsource = topo_source.mesh.space_step
+ self.htarget = topo_target.mesh.space_step
+ self.topo_target.build_subcomms()
+ self.sub_comms = self.topo_target.sub_comms
+ self.neighbours = self.topo_target.sub_neighbours
+ if finterpol is not None:
+ finterpol.initialize_interpolation_kernel('L4_4')
+
+ # indices of points on which interpolation occurs.
+ # This corresponds to the mesh of topo_target
+ # but is updated at each call, depending on the
+ # size of 'positions' argument and of the direction of interpolation.
+ self._target_indices = list(self.topo_target.mesh.compute_index)
+
+ def reset_target_indices(self, new_indices):
+ """Reset list of indices of points on which interpolation occurs.
+ Only useful when 'positions' argument shape is not equal
+ to topo_target.mesh shape, e.g. when a threshold is used
+ to initialize particles.
+
+ Parameters
+ ----------
+ new_indices : a list of slices
+ a slice per direction to define the range of
+ indices of interest. Like topo.mesh.compute_index attribute.
+ """
+ self._target_indices = list(new_indices)
+
+ def _set_work_arrays(self, rwork=None, iwork=None):
+ """Check and/or allocate internal work buffers.
+
+ Parameters
+ ----------
+ rwork, iwork : list of numpy arrays
+ internal work spaces for real (rwork) and integer (iwork) data.
+
+ """
+ wk_prop = self.get_work_properties(self.topo_target)
+ noghosts_shape = (np.prod(self.topo_target.mesh.compute_resolution),)
+ if wk_prop['rwork'] is None:
+ result_r = []
+ else:
+ result_r = WorkSpaceTools.check_work_array(len(wk_prop['rwork']),
+ noghosts_shape, rwork)
+ if wk_prop['iwork'] is None:
+ result_i = []
+ else:
+ result_i = WorkSpaceTools.check_work_array(len(wk_prop['iwork']),
+ noghosts_shape, iwork,
+ data_type=HYSOP_INTEGER)
+ return result_r, result_i
+
+ @staticmethod
+ def get_work_properties(topo):
+ """Get properties of internal work arrays.
+
+ Returns
+ -------
+ dictionnary
+ keys = 'rwork' and 'iwork', values = list of shapes of internal
+ arrays required by this method (real arrays for rwork, integer
+ arrays for iwork).
+
+ Parameters
+ ----------
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
+ topology on which the method will be applied.
+ """
+ # default is None, None.
+ # This function must be reimplemented in derived classes
+ # (but we cannot combine abstract and static in python2.7 ...)
+ return {'rwork': None, 'iwork': None}
+
+ def _assert_target_in_source(self, target_coords):
+ """Check if target grid is strictly included
+ into source grid
+
+ This is required to be sure that 'left' and 'right'
+ points exist for each point on target grid.
+ This obviously depends on the interpolation order.
+ """
+ source_coords = self.topo_source.mesh.coords[self.direction]
+ assert np.min(target_coords) >= source_coords.flat[0]
+ assert np.max(target_coords) < source_coords.flat[-1]
+ return True
+
+ def _compute_iy(self, positions, work):
+ """Compute distance between points to be interpolated and their
+ closest point on the left.
+
+ Parameters
+ ----------
+ positions : numpy array
+ points to be interpolated. positions shape == topo.mesh.resolution
+ except in direction of interpolation where any number of points
+ is allowed, with a max of points equal to the number of grid
+ points in this direction (excluding ghosts).
+ work : numpy array.
+ Used as local buffer. work must be of the same shape
+ as positions and contains iy in return,
+ i_y = (xp - xg)/dx
+
+ Returns
+ -------
+ left_points_indices : list of numpy arrays or slices
+ indices in source grid of neighbours (left) points for
+ each point in positions.
+
+ Usage : field[left_points_indices] will return the array of
+ 'left' points (in current direction)
+ while field[target_indices] = current points
+
+ Remark
+ ------
+ No memory allocation in this function --> everything is taken
+ from rwork or iwork
+ """
+ # local origin and space step in current direction
+ x0 = self.topo_source.mesh.origin[self.direction]
+ #i_y = work
+ # memory optim: check if input work 'belongs' to rwork
+ #assert npw.arrays_share_data(i_y, work)
+ # -- set indices of closest grid points, on the left --
+ # Initialized with source grid coordinates
+ left_points_indices = list(self._icoords)
+ # = [self._icoords[i] for i in xrange(dimension)]
+ # pick memory from self._iwork
+ iwork_dir = WorkSpaceTools.check_work_array(
+ 1, work.shape, self._iwork, data_type=HYSOP_INTEGER)
+ # we need an array (filled later) for current direction
+ left_points_indices[self.direction] = iwork_dir[0]
+ # check memory consumption
+ assert npw.arrays_share_data(left_points_indices[self.direction],
+ self._iwork[0])
+ # -- compute distance between particles positions and
+ # closest grid point, on the left --
+ work[...] = (positions[self._target_indices] - x0) *\
+ self._inv_dx[self.direction]
+ #self._assert_particles_roundoff(work, self._target_indices)
+ # update interpolation point indices (in self._iwork)
+ left_points_indices[self.direction][...] = \
+ npw.asintegerarray(np.floor(work[...]))
+ work[...] -= left_points_indices[self.direction][...]
+ nmax = self.topo_source.mesh.resolution[self.direction]
+ # Ensure all points belongs to local domain
+ # (including ghosts)
+ assert left_points_indices[self.direction].max() < nmax
+ assert left_points_indices[self.direction].min() >= 0
+ return left_points_indices
+
+ @staticmethod
+ def _assert_particles_roundoff(work, ic):
+ """trick to avoid case where particle is very close to
+ grid point and 'floor' result in wrong grid
+ point because of numerical eps.
+ For example, if xp - xi == -1e-15, floor(xp)=xi-1
+ which is not what is expected.
+
+ Done in 'assertion' --> only in debug mode.
+ """
+ work[1][ic] = np.ceil(work[0][ic])
+ ilist = np.where(work[1][ic] - work[0][ic] < 10. * EPS)
+ work[0][ic][ilist] = work[1][ic][ilist]
+ return True
+
+ def _xy(self, vin, vout):
+ """Interpolate a field along X and Y-axis
+
+ Parameters
+ ----------
+ vin : list of numpy arrays
+ field on the source grid
+ vout : list of numpy arrays
+ field on the target/source grid
+ Notes
+ -----
+ * vout and vin must have the same resolution along
+ the first direction.
+ """
+ # Permutation to prepare first interpolation
+ for i in xrange(3):
+ self._rwork[2][:, i, :] = vin[:, :, i]
+ # Interpolation along last dir = Y
+ # in : vpermut(nc_x, nc_z, nc_y)
+ # out : vm(nc_x, nf_y, nc_z)
+ finterpol.interpol_lastdir_permut(self._rwork[2], self.hsource[:2],
+ self._rwork[3], self.htarget[:2],
+ self.neighbours[:, YDIR],
+ self.sub_comms[YDIR])
+ # Interpolation along X
+ # in : vm(nc_x, nf_y, nc_z)
+ # out : vout(nf_x, nf_y, nc_z)
+ finterpol.interpol_firstdir_no_com(self._rwork[3],
+ self.hsource[:2],
+ vout, self.htarget[:2])
+
+ def _yz(self, vin, vout):
+ """Interpolate a field along Y and Z-axis
+
+ Parameters
+ ----------
+ vin : list of numpy arrays
+ field on the source grid
+ vout : list of numpy arrays
+ field on the target/source grid
+ Notes
+ -----
+ * vout and vin must have the same resolution along
+ the first direction.
+ """
+ # Interpolation along Z + permutation between Y and Z
+ # in : vin(nc_x, nc_y, nc_z)
+ # out : vtmp(nc_x, nf_z, nc_y)
+ finterpol.interpol_lastdir_permut(vin, self.hsource[1:],
+ self._rwork[0], self.htarget[1:],
+ self.neighbours[:, ZDIR],
+ self.sub_comms[ZDIR])
+ # Interpolation along Y
+ # (=third direction thanks to previous permutation)
+ # + permutation between Y and Z
+ # in : vtmp(nc_x, nf_z, nc_y)
+ # out : vout(nc_x, nf_y, nf_z)
+ finterpol.interpol_lastdir_permut(self._rwork[0], self.hsource[XDIR],
+ vout, self.htarget[XDIR],
+ self.neighbours[YDIR, :],
+ self.sub_comms[YDIR])
+
+ def _xz_permut(self, vin, vout):
+ """Interpolate a field along X and Z-axis, result order = Y,X,Z
+
+ Parameters
+ ----------
+ vin : list of numpy arrays
+ field on the source grid
+ vout : list of numpy arrays
+ field on the target grid
+
+ Notes
+ -----
+ * vout and vin must have the same resolution along
+ the first direction.
+ """
+ # Interpolation along Z
+ # Interpolation along Z
+ # in : vin(nc_x, nc_y, nc_z)
+ # out : vtmp(nc_x, nc_y, nf_z)
+ finterpol.interpol_lastdir(vin, self.hsource[::2],
+ self._rwork[1], self.htarget[::2],
+ self.neighbours[:, ZDIR],
+ self.sub_comms[ZDIR])
+ # Interpolation along X
+ # in : vtmp(nc_x, nc_y, nf_z)
+ # out : vout(nc_y, nf_x, nf_z)
+ finterpol.interpol_firstdir_permut_no_com(self._rwork[1],
+ self.hsource[::2],
+ vout, self.htarget[::2])
+
+ def _xy_permut(self, vin, vout):
+ """Interpolate a field along X and Y-axis, result order = Z,X,Y
+
+ Parameters
+ ----------
+ vin : list of numpy arrays
+ field on the source grid
+ vout : list of numpy arrays
+ field on the target grid
+
+ Notes
+ -----
+ * vout and vin must have the same resolution along
+ the first direction.
+ """
+ # Permutation to prepare first interpolation
+ for i in xrange(3):
+ self._rwork[2][:, i, :] = vin[:, :, i]
+ # Interpolation along last dir = Y
+ # in : vpermut(nc_x, nc_z, nc_y)
+ # out : vm(nc_x, nc_z, nf_y)
+ finterpol.interpol_lastdir(self._rwork[2], self.hsource[:2],
+ self._rwork[3], self.htarget[:2],
+ self.neighbours[:, YDIR],
+ self.sub_comms[YDIR])
+ # Interpolation along X
+ # in : vm(nc_x, nc_z, nf_y)
+ # out : vout(nc_z, nf_x, nf_y)
+ finterpol.interpol_firstdir_permut_no_com(self._rwork[3],
+ self.hsource[:2],
+ vout, self.htarget[:2])
+
+ def _2d_3d_vect(self, vin, vout):
+ """Interpolate each component of a vector along a transverse direction
+ """
+ # For Vx, interpolation along Y and Z
+ self._yz(vin[XDIR], vtmp[XDIR])
+ # For Vy, interpolation along Z (with communications)
+ # then along X (no communication required)
+ self._xz_permut(vin[YDIR], vtmp[YDIR])
+ # For Vz, interpolation along Y (with communications)
+ # then along X (no communication required)
+ self._xy_permut(vin[ZDIR], vtmp[ZDIR])
+
+ finterpol.interpol_firstdir_no_com(vtmp[XDIR], self.hsource[XDIR],
+ vout[XDIR], self.htarget[XDIR])
+ finterpol.interpol_firstdir(vtmp[YDIR], self.hsource[YDIR],
+ vout[YDIR], self.htarget[YDIR],
+ self.neighbours[:, YDIR],
+ self.sub_comms[YDIR])
+ finterpol.interpol_firstdir(vtmp[ZDIR], self.hsource[ZDIR],
+ vout[ZDIR], self.htarget[ZDIR],
+ self.neighbours[:, ZDIR],
+ self.sub_comms[ZDIR])
+
+ def _3d(self, vin, vout):
+ """3D interpolation of a field to a targetr grid - no transpositions.
+ """
+ # rwork = vtmp(nf_x, nc_y, nc_z)
+ finterpol.interpol_firstdir_no_com(vin, self.hsource[XDIR],
+ self._rwork[0], self.htarget[XDIR])
+ self._yz(self._rwork[0], vout)
+
+
+class Linear(Interpolation):
+ """Linear interpolation of a field"""
+
+ ghosts_layer_size = 1
+
+ def __init__(self, interpolated_field, **kwds):
+ """
+ Parameters
+ ----------
+ interpolated_field : numpy array
+ data to be interpolated
+ kwds : base class parameters
+
+ Notes
+ -----
+ * topo argument corresponds to the topology of field interpolated_field
+ * it would be probably better to pass interpolated_field
+ during __call__ but interpolation is used as rhs in odesolvers and
+ call function must fit with rhs arg list.
+
+ """
+ self.interpolated_field = interpolated_field
+ super(Linear, self).__init__(**kwds)
+
+ @staticmethod
+ def get_work_properties(topo):
+ """Get properties of internal work arrays.
+
+ Returns
+ -------
+ dictionnary
+ keys = 'rwork' and 'iwork', values = list of shapes of internal
+ arrays required by this method (real arrays for rwork, integer
+ arrays for iwork).
+
+ Parameters
+ ----------
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
+ topology on which the method will be applied.
+ """
+ noghosts_shape = (np.prod(topo.mesh.compute_resolution),)
+ return {'rwork': [noghosts_shape, ], 'iwork': [noghosts_shape, ]}
+
+ def __call__(self, t, positions, result):
+ """interpolate values at nodes positions using linear interpolation.
+
+ Parameters
+ ----------
+ t : double
+ current time.
+ positions : list of numpy arrays
+ coordinates of points where to interpolate
+ result : list of numpy arrays
+
+ Returns
+ -------
+ result
+
+ Notes
+ -----
+ * since interpolation function is likely to be used
+ as right-hand side of an ode solver, the list of arguments must fit
+ with the integrator requirements, which explains the 't' argument
+ unused below but required, or the positions and result as lists.
+ """
+ assert isinstance(positions, list)
+ assert isinstance(result, list)
+ assert result[0].shape == positions[0].shape
+ assert (self.interpolated_field.shape ==
+ self.topo_source.mesh.resolution).all()
+ #assert self._assert_target_in_source(positions)
+ # linear interpolation:
+ # input = interpolated_field (field values at points xi),
+ # pos, a vector of p points
+ # output = res(pos), interpolation of interpolated_field at points pos
+ # intf =interpolated_field
+ # res(pos_p) = (pos_p - xi)/h . intf_i+1 + (x_i+1 - pos_p)/h . intf_i
+ # = iy.intf_i+1 + (1 - iy).intf_i
+ # where iy = (pos_p - x0)/h - i, i = floor((pos_p - x0)/h)
+
+ # number of points to interpolate
+ nb_points = positions[0].shape[self.direction]
+ # indices of points where we need interpolation
+ self._target_indices[self.direction] = slice(0, nb_points)
+ # pick buffer memory from self._rwork
+ # wk[0] shares memory with rwork[0] but data are rearranged
+ # according to positions[0].shape.
+ print nb_points, self.direction
+ wk = WorkSpaceTools.check_work_array(
+ 1, positions[0][self._target_indices].shape, self._rwork)
+ # memory optim: check if input work 'belongs' to rwork
+ assert npw.arrays_share_data(self._rwork[0], wk[0])
+ left_points_indices = self._compute_iy(positions[0], wk[0])
+ assert npw.arrays_share_data(left_points_indices[self.direction],
+ self._iwork[0])
+ print self.interpolated_field[left_points_indices].shape
+ #refsize = positions[0].size
+ #refshape = positions[0].shape
+ #wk.append(result[0][])
+ #res = WorkSpaceTools.check_work_array(1, refshape, result)
+ result[0][self._target_indices] = \
+ self.interpolated_field[left_points_indices] * (1. - wk[0][...])
+ # compute 'right points' indices
+ left_points_indices[self.direction] += 1
+
+ result[0][self._target_indices] += \
+ self.interpolated_field[left_points_indices] * wk[0][...]
+ return result
diff --git a/hysop/numerics/method.py b/hysop/old/numerics.old/method.py
similarity index 89%
rename from hysop/numerics/method.py
rename to hysop/old/numerics.old/method.py
index 119d8088dd2f7555b881325b9c0d16a63786bca4..7125c1a081d4fe2efe4abbebd39ca01d65f69675 100644
--- a/hysop/numerics/method.py
+++ b/hysop/old/numerics.old/method.py
@@ -6,8 +6,7 @@ Abstract interface to numerical methods.
from abc import ABCMeta, abstractmethod
from hysop.constants import debug
-
-class NumMethod(object):
+class NumericalMethod(object):
""" Abstract description of numerical method. """
__metaclass__ = ABCMeta
@@ -17,7 +16,7 @@ class NumMethod(object):
return object.__new__(cls, *args, **kw)
@staticmethod
- def getWorkLengths(nb_components=None, domain_dim=None):
+ def get_work_lengths(nb_components=None, domain_dim=None):
"""
Compute the number of required work arrays for this method.
@param nb_components : number of components of the
diff --git a/hysop/numerics/odesolvers.py b/hysop/old/numerics.old/odesolvers.py
similarity index 83%
rename from hysop/numerics/odesolvers.py
rename to hysop/old/numerics.old/odesolvers.py
index 1ef90454caee2dccefc7ae143851999d217505ac..e10d82d2780f3e66843f654f0270d674c44bc23e 100755
--- a/hysop/numerics/odesolvers.py
+++ b/hysop/old/numerics.old/odesolvers.py
@@ -8,14 +8,17 @@
* :class:`~odesolvers.RK4`,
* :class:`~odesolvers.ODESolver` (abstract base class).
+See :ref:`odesolvers`
"""
from abc import ABCMeta, abstractmethod
from hysop.constants import WITH_GUESS
from hysop.numerics.update_ghosts import UpdateGhosts
-import hysop.tools.numpywrappers as npw
from hysop.tools.misc import WorkSpaceTools
+from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta
+
+from hysop.tools.numpywrappers import npw
import numpy as np
@@ -30,13 +33,13 @@ class ODESolver(object):
__metaclass__ = ABCMeta
def __init__(self, nb_components, topo, f=None, indices=None,
- rwork=None, optim=None):
+ rwork=None, optim=None, wk_shape=None, need_synchro=False):
"""
Parameters
----------
nb_components : int
number of components of the right-hand side.
- topo : :class:`~hysop.mpi.topology.Cartesian`
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
mpi process and data distribution
f : python function, optional.
right hand side of the equation to solve.
@@ -55,6 +58,13 @@ class ODESolver(object):
optim : int, optional
the level of optimization (memory management).
Default = None.
+ wk_shape: tuple, optional
+ shape of the internal work vector. Default = input topo
+ resolution.
+ need_synchro: boolean, optional
+ Set to true if y parameter of the rhs needs an update
+ of its ghost points before each call. This might be
+ the case if rhs is an interpolation. Default=False
Notes
-----
@@ -64,6 +74,9 @@ class ODESolver(object):
system is solved. This is the default behavior
* optim = WITH_GUESS : in that case, work must contain a first
evaluation of f(t,y) before each call.
+ * wk_shape might be usefull when the advected field shape
+ in advection dir is lower than topo shape (for instance when
+ pushing particles with a threshhold parameter).
"""
# RHS.
@@ -87,19 +100,21 @@ class ODESolver(object):
#self.output_indices = None
# work arrays
- self.rwork = self._set_work_arrays(topo, rwork=rwork)
- self._synchronize = UpdateGhosts(topo, self._nb_components)
+ self.rwork = self._set_work_arrays(topo, wk_shape, rwork=rwork)
+ if need_synchro:
+ self._synchronize = UpdateGhosts(topo, self._nb_components)
+ self.compute_rhs = self._update_rhs_with_synchro
+ else:
+ self.compute_rhs = self.f
- def _set_work_arrays(self, topo, reduce_output_shape=False, rwork=None):
+ def _set_work_arrays(self, topo, wk_shape=False, rwork=None):
"""Check and allocate internal work buffers.
"""
wk_prop = self.get_work_properties(self._nb_components, topo)['rwork']
if wk_prop is None:
return []
- if reduce_output_shape:
- subsize = np.asarray([self.in_indices[i].stop -
- self.in_indices[i].start
- for i in xrange(len(self.in_indices))])
+ if wk_shape:
+ subsize = wk_shape
else:
subsize = topo.mesh.resolution
@@ -113,10 +128,23 @@ class ODESolver(object):
----------
nb_components: integer,
number of components of the right-hand-side
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
topology on which the integrator will be applied.
"""
+ # def update_rhs_local(self, t, y, result):
+ # """Return rhs value, no synchronization between mpi domains.
+ # """
+ # return self.f(t, y, result)
+
+ def _update_rhs_with_synchro(self, t, y, result):
+ """"Return rhs value, but first
+ synchronize y values between mpi domains
+ (i.e. ghost points update)
+ """
+ self._synchronize(y)
+ return self.f(t, y, result)
+
def __call__(self, t, y, dt, result):
"""Apply integrator
@@ -160,7 +188,7 @@ class ODESolver(object):
result may be equal to y.
"""
self.rwork[:self._nb_components] = \
- self.f(t, y, self.rwork[:self._nb_components])
+ self.compute_rhs(t, y, self.rwork[:self._nb_components])
return self._core(t, y, dt, result)
@abstractmethod
@@ -200,7 +228,7 @@ class Euler(ODESolver):
----------
nb_components: integer,
number of components of the right-hand-side
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
topology on which the integrator will be applied.
"""
@@ -260,7 +288,7 @@ class RK2(ODESolver):
----------
nb_components: integer,
number of components of the right-hand-side
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
topology on which the integrator will be applied.
"""
@@ -294,9 +322,10 @@ class RK2(ODESolver):
Note : since result may be equal to y, it can not
be used as a temporary workspace.
"""
+ i_y = self.in_indices
for i in xrange(self._nb_components):
- cond = [y[i] is self.rwork[j] for j in xrange(len(self.rwork))]
- assert cond.count(True) is 0
+ for j in xrange(len(self.rwork)):
+ assert not npw.arrays_share_data(y[i], self.rwork[j])
assert len(result) == self._nb_components
work0 = self.rwork[:self._nb_components]
yn = self.rwork[self._nb_components:2 * self._nb_components]
@@ -306,19 +335,20 @@ class RK2(ODESolver):
# result = y + dt * k2
# yn
+ #print ic, y[0].shape
for i in xrange(self._nb_components):
- np.add(y[i], work0[i] * 0.5 * dt, yn[i])
+ np.add(y[i][i_y], work0[i] * 0.5 * dt, yn[i])
+ #np.add(y[i][ic], work0[i] * 0.5 * dt, yn[i])
- # Update ghosts
- self._synchronize.apply(yn)
# k2 in work0
- work0 = self.f(t + 0.5 * dt, yn, work0)
+ work0 = self.compute_rhs(t + 0.5 * dt, yn, work0)
# *= dt
for i in xrange(self._nb_components):
#np.multiply(work0[i], dt, work0[i])
work0[i] *= dt
# result = y + work0
- np.add(work0[i], y[i], result[i])
+ np.add(work0[i], y[i][i_y], result[i][i_y])
+ #np.add(work0[i], y[i][ic], result[i])
return result
@@ -341,7 +371,7 @@ class RK3(ODESolver):
----------
nb_components: integer,
number of components of the right-hand-side
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
topology on which the integrator will be applied.
"""
@@ -394,18 +424,14 @@ class RK3(ODESolver):
for i in xrange(self._nb_components):
np.add(y[i], work0[i] * dt / 3, yn[i])
- # Update ghosts
- self._synchronize.apply(yn)
# k2 in kn
- kn = self.f(t + dt / 3, yn, kn)
+ kn = self.compute_rhs(t + dt / 3, yn, kn)
# yn
for i in xrange(self._nb_components):
np.add(y[i], 2 * dt / 3 * kn[i], yn[i])
- # Update ghosts
- self._synchronize.apply(yn)
# k3 in kn
- kn = self.f(t + 2 * dt / 3, yn, kn)
+ kn = self.compute_rhs(t + 2 * dt / 3, yn, kn)
# k1 + 3 * k3 in work0
for i in xrange(self._nb_components):
np.add(work0[i], 3 * kn[i], work0[i])
@@ -433,7 +459,7 @@ class RK4(ODESolver):
nb_components: integer,
number of components of the right-hand-side
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
topology on which the integrator will be applied.
"""
shape = (np.prod(topo.mesh.resolution),)
@@ -481,10 +507,8 @@ class RK4(ODESolver):
for i in xrange(self._nb_components):
np.add(y[i], work0[i] * dt / 2, yn[i])
- # Update ghosts
- self._synchronize.apply(yn)
# k2 in kn
- kn = self.f(t + dt / 2, yn, kn)
+ kn = self.compute_rhs(t + dt / 2, yn, kn)
# k1 + 2 * k2 in work0
for i in xrange(self._nb_components):
@@ -492,10 +516,8 @@ class RK4(ODESolver):
# yn
np.add(y[i], dt / 2 * kn[i], yn[i])
- # Update ghosts
- self._synchronize.apply(yn)
# k3 in kn
- kn = self.f(t + dt / 2, yn, kn)
+ kn = self.compute_rhs(t + dt / 2, yn, kn)
# k1 + 2 * k2 + 2 * k3 in work0
for i in xrange(self._nb_components):
@@ -503,10 +525,8 @@ class RK4(ODESolver):
# yn
np.add(y[i], dt * kn[i], yn[i])
- # Update ghosts
- self._synchronize.apply(yn)
# K4 in kn
- kn = self.f(t + dt, yn, kn)
+ kn = self.compute_rhs(t + dt, yn, kn)
# k1 + 2 * k2 + 2 * k3 + k4
for i in xrange(self._nb_components):
diff --git a/hysop/numerics/remeshing.py b/hysop/old/numerics.old/remeshing.py
similarity index 60%
rename from hysop/numerics/remeshing.py
rename to hysop/old/numerics.old/remeshing.py
index 5492bc3e2d6c167093dbd185009094a8e627ea0a..2464b76741f2c22d8bdef5e2438d98f7c54e0408 100644
--- a/hysop/numerics/remeshing.py
+++ b/hysop/old/numerics.old/remeshing.py
@@ -1,30 +1,51 @@
+"""Remeshing methods
+
+.. currentmodule:: hysop.numerics.remeshing
+
+* :class:`~Remeshing` : remeshing method
+
+Available formulas are :
+* :class:`~Linear`
+* :class:`~L2_1`
+* :class:`~L2_2`
+* :class:`~L2_3`
+* :class:`~L2_4`
+* :class:`~L4_2`
+* :class:`~L4_3`
+* :class:`~L4_4`
+* :class:`~M8Prime`
+* :class:`~L6_3`
+* :class:`~L6_4`
+* :class:`~L6_5`
+* :class:`~L6_6`
+* :class:`~L8_4`
+* :class:`RemeshFormula`, abstract base class for formulas
+
"""
-@file remeshing.py
-"""
-from hysop.constants import np, HYSOP_INDEX
-from hysop.numerics.method import NumMethod
-import hysop.tools.numpywrappers as npw
+import numpy as np
+from hysop.tools.numpywrappers import npw
+from hysop.tools.misc import WorkSpaceTools
+from hysop.numerics.interpolation.interpolation import Interpolation
+from hysop.core.mpi import Wtime
-class Remeshing(NumMethod):
- """Remshing"""
+class Remeshing(Interpolation):
+ """Remeshing schemes"""
+
+ def __init__(self, kernel, **kwds):
+ """Create a remeshing numeric method based on given formula.
+
+ Parameters
+ -----------
+ kernel : :class:`~hysop.numerics.remeshing.RemeshFormula`
+ remeshing formula.
+ kwds : base class parameters
+
+ Notes
+ -----
+ * topo arg must correspond to the topology of the remeshed field
+ i.e. topology of the targeted grid.
- def __init__(self, kernel, dim, topo, d, work, iwork):
- """
- Create a remeshing numeric method based on given formula.
- @param dim : problem dimension
- @param dx : mesh space step
- @param origin : mesh lower point
- @param formula : Remeshing formula to use.
- @param work : Work arrays (floats)
- @param iwork : Work arrays (integers)
- work must be a list containing (2 elements):
- - numpy float array like y[0] (used to store particles contributions)
- - numpy float array like y[0] (used to store distance to grid points)
- iwork must be a list containing (dim elements( in the order):):
- - numpy integer array of shape like y[0]
- - numpy integer array of shape like y[0] (if in 2D and 3D)
- - numpy integer array of shape like y[0] (if in 3D)
Availables formulas :
- 'l2_1' : Labmda2,1 : (=M'4) 4 point formula, C1 regularity
- 'l2_2' : Labmda2,2 : 4 point formula, C2 regularity
@@ -38,115 +59,81 @@ class Remeshing(NumMethod):
- 'l8_4' : Labmda8,4 : 10 point formula, C4 regularity
- 'm8prime' : M8prime formula
"""
- NumMethod.__init__(self)
self._kernel = kernel()
- self.dir = d
- self._dim = dim
- self.work = work
- self.iwork = iwork
- assert len(self.work) == 2
- assert len(self.iwork) == self._dim
+ self.ghosts_layer_size = self._kernel.ghosts_layer_size
+ super(Remeshing, self).__init__(**kwds)
self.shift = self._kernel.shift
self.weights = self._kernel.weights
- self.topo = topo
- self._slice_all = [slice(None, None, None)
- for dd in xrange(dim)]
-
- if self._dim == 3:
- if self.dir == 0:
- self._affect_working_arrays = self._affect_work_3D_X
- if self.dir == 1:
- self._affect_working_arrays = self._affect_work_3D_Y
- if self.dir == 2:
- self._affect_working_arrays = self._affect_work_3D_Z
- if self._dim == 2:
- if self.dir == 0:
- self._affect_working_arrays = self._affect_work_2D_X
- if self.dir == 1:
- self._affect_working_arrays = self._affect_work_2D_Y
- if self._dim == 1:
- if self.dir == 0:
- self._affect_working_arrays = self._affect_work_1D
-
- def slice_i_along_d(self, i, d):
- l = list(self._slice_all)
- l[d] = i
- return tuple(l)
@staticmethod
- def getWorkLengths(nb_components=None, domain_dim=1):
- return 2, domain_dim
-
- def _affect_work_1D(self, resol):
- return (self.work[0], self.work[1], tuple(self.iwork))
-
- def _affect_work_2D_X(self, resol):
- self.iwork[1][...] = np.indices((resol[1],))[0].astype(
- HYSOP_INDEX)[np.newaxis, :]
- return (self.work[0], self.work[1], tuple(self.iwork))
-
- def _affect_work_2D_Y(self, resol):
- self.iwork[0][...] = np.indices((resol[0],))[0].astype(
- HYSOP_INDEX)[:, np.newaxis]
- return (self.work[0], self.work[1], tuple(self.iwork))
-
- def _affect_work_3D_X(self, resol):
- self.iwork[1][...] = np.indices((resol[1],))[0].astype(
- HYSOP_INDEX)[np.newaxis, :, np.newaxis]
- self.iwork[2][...] = np.indices((resol[2],))[0].astype(
- HYSOP_INDEX)[np.newaxis, np.newaxis, :]
- return (self.work[0], self.work[1], tuple(self.iwork))
-
- def _affect_work_3D_Y(self, resol):
- self.iwork[0][...] = np.indices((resol[0],))[0].astype(
- HYSOP_INDEX)[:, np.newaxis, np.newaxis]
- self.iwork[2][...] = np.indices((resol[2],))[0].astype(
- HYSOP_INDEX)[np.newaxis, np.newaxis, :]
- return (self.work[0], self.work[1], tuple(self.iwork))
-
- def _affect_work_3D_Z(self, resol):
- self.iwork[0][...] = np.indices((resol[0],))[0].astype(
- HYSOP_INDEX)[:, np.newaxis, np.newaxis]
- self.iwork[1][...] = np.indices((resol[1],))[0].astype(
- HYSOP_INDEX)[np.newaxis, :, np.newaxis]
- return (self.work[0], self.work[1], tuple(self.iwork))
+ def get_work_properties(topo):
+ """Get properties of internal work arrays.
+
+ Returns
+ -------
+ dictionnary
+ keys = 'rwork' and 'iwork', values = list of shapes of internal
+ arrays required by this method (real arrays for rwork, integer
+ arrays for iwork).
+
+ Parameters
+ ----------
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
+ topology on which the method will be applied.
+ """
+ noghosts_shape = (np.prod(topo.mesh.compute_resolution),)
+ return {'rwork': [noghosts_shape, ] * 2, 'iwork': [noghosts_shape, ]}
def __call__(self, ppos, pscal, result):
- """
- Remesh particles at position p_pos with scalar p_scal along
+ """Apply remeshing scheme : remesh particles at
+ position p_pos with scalar p_scal along
direction d.
- @param p_pos : particle position
- @param p_scal : particle scalar
- @param result : a predefined list of numpy arrays to solve the result
- @return remeshed scalar on grid
+ Parameters
+ ----------
+ ppos : numpy array
+ particle positions
+ pscal : list of numpy arrays
+ field(s) value on particles
+ result : list of numpy arrays
+
+ Returns
+ -------
+ result, the scalar field(s) remeshed on the grid.
"""
- d = self.dir
- mesh = self.topo.mesh
- resolution = self.topo.mesh.discretization.resolution
- origin = self.topo.domain.origin
- dx = mesh.space_step
- tmp, i_y, index = self._affect_working_arrays(mesh.resolution)
-
- floor = result # use res array as working array
- floor[...] = (ppos - origin[d]) / dx[d]
- i_y[...] = floor
- floor[...] = np.floor(floor)
- i_y[...] -= floor
-
- # Gobal indices
- index[d][...] = (floor.astype(HYSOP_INDEX) - self.shift) \
- % (resolution[d] - 1)
- result[...] = 0. # reset res array (no more uses to floor variable)
- for w_id, w in enumerate(self.weights):
- if w_id > 0:
- index[d][...] = (index[d] + 1) % (resolution[d] - 1)
- tmp[...] = self._kernel(w_id, i_y, tmp)
- tmp *= pscal
- for i in xrange(mesh.resolution[d]):
- sl = self.slice_i_along_d(i, d)
- index_sl = tuple([ind[sl] for ind in index])
- result[index_sl] = result[index_sl] + tmp[sl]
+ assert np.asarray([pscal[i].shape == ppos.shape
+ for i in xrange(len(pscal))]).all()
+ assert len(result) == len(pscal)
+ assert np.asarray([result[i].shape ==
+ tuple(self.topo_target.mesh.resolution)
+ for i in xrange(len(result))]).all()
+ # number of particles
+ nb_points = ppos.shape[self.direction]
+ self._target_indices[self.direction] = slice(0, nb_points)
+ # pick buffer memory from self._rwork
+ # wk[0] --> iy, wk[1] --> used in weights accumulation below
+ wk = WorkSpaceTools.check_work_array(
+ 2, ppos[self._target_indices].shape, self._rwork)
+ assert npw.arrays_share_data(self._rwork[0], wk[0])
+ left_points_indices = self._compute_iy(ppos, wk[0])
+ assert npw.arrays_share_data(left_points_indices[self.direction],
+ self._iwork[0])
+ # shift iwork, so that iwork[direction][p] is the index
+ # of the first grid point in the remesh stencil of particle p
+ left_points_indices[self.direction][...] -= self.shift
+ for i in xrange(len(result)):
+ result[i][...] = 0.0
+ # Now, accumulate particles contributions into result
+ # for each remeshed field
+ for i in xrange(len(pscal)):
+ for k, _ in enumerate(self.weights):
+ # compute w_k(iy)
+ wk[1][...] = self._kernel(k, wk[0], wk[1])
+ wk[1][...] *= pscal[i][self._target_indices]
+ result[i][left_points_indices] += wk[1][...]
+ # shift to next grid point
+ left_points_indices[self.direction] += 1
+ left_points_indices[self.direction] -= len(self.weights)
return result
@@ -158,16 +145,32 @@ class RemeshFormula(object):
self.weights = None
def __call__(self, w, x, res):
- """Compute remeshing weights."""
+ """Compute remeshing weights.
+
+ Parameters
+ ----------
+ w : int
+ index (position in weight list) of the required weight
+ x : numpy array
+ relative position of the particle
+ res : numpy array
+ remeshed values
+ return res.
+
+ res = sum_i=0..n-1 w_i.x^(n-i), n = len(weight[w])
+ """
res[...] = self.weights[w][0]
for c in self.weights[w][1:]:
- res[...] *= x
+ res[...] *= x[...]
res[...] += c
return res
class Linear(RemeshFormula):
"""Linear kernel."""
+
+ ghosts_layer_size = 1
+
def __init__(self):
super(Linear, self).__init__()
self.shift = 0
@@ -179,6 +182,9 @@ class Linear(RemeshFormula):
class L2_1(RemeshFormula):
"""L2_1 kernel."""
+
+ ghosts_layer_size = 2
+
def __init__(self):
super(L2_1, self).__init__()
self.shift = 1
@@ -192,6 +198,9 @@ class L2_1(RemeshFormula):
class L2_2(RemeshFormula):
"""L2_2 kernel."""
+
+ ghosts_layer_size = 3
+
def __init__(self):
super(L2_2, self).__init__()
self.shift = 1
@@ -205,6 +214,9 @@ class L2_2(RemeshFormula):
class L2_3(RemeshFormula):
"""L2_3 kernel."""
+
+ ghosts_layer_size = 4
+
def __init__(self):
super(L2_3, self).__init__()
self.shift = 1
@@ -218,6 +230,9 @@ class L2_3(RemeshFormula):
class L2_4(RemeshFormula):
"""L2_4 kernel."""
+
+ ghosts_layer_size = 5
+
def __init__(self):
super(L2_4, self).__init__()
self.shift = 1
@@ -231,6 +246,9 @@ class L2_4(RemeshFormula):
class L4_2(RemeshFormula):
"""L4_2 kernel."""
+
+ ghosts_layer_size = 3
+
def __init__(self):
super(L4_2, self).__init__()
self.shift = 2
@@ -246,6 +264,9 @@ class L4_2(RemeshFormula):
class L4_3(RemeshFormula):
"""L4_3 kernel."""
+
+ ghosts_layer_size = 4
+
def __init__(self):
super(L4_3, self).__init__()
self.shift = 2
@@ -261,31 +282,46 @@ class L4_3(RemeshFormula):
class L4_4(RemeshFormula):
"""L4_4 kernel."""
+
+ ghosts_layer_size = 5
+
def __init__(self):
super(L4_4, self).__init__()
self.shift = 2
self.weights = [
npw.asrealarray([-46, 207, -354, 273, -80, 1, -2, -1, 2, 0]) / 24.,
- npw.asrealarray([230, -1035, 1770, -1365, 400, -4, 4, 16, -16, 0]) / 24.,
- npw.asrealarray([-460, 2070, -3540, 2730, -800, 6, 0, -30, 0, 24]) / 24.,
- npw.asrealarray([460, -2070, 3540, -2730, 800, -4, -4, 16, 16, 0]) / 24.,
- npw.asrealarray([-230, 1035, -1770, 1365, -400, 1, 2, -1, -2, 0]) / 24.,
+ npw.asrealarray([230, -1035, 1770, -1365,
+ 400, -4, 4, 16, -16, 0]) / 24.,
+ npw.asrealarray([-460, 2070, -3540, 2730, -800,
+ 6, 0, -30, 0, 24]) / 24.,
+ npw.asrealarray([460, -2070, 3540, -2730, 800,
+ -4, -4, 16, 16, 0]) / 24.,
+ npw.asrealarray([-230, 1035, -1770, 1365, -400,
+ 1, 2, -1, -2, 0]) / 24.,
npw.asrealarray([46, -207, 354, -273, 80, 0, 0, 0, 0, 0]) / 24.,
]
class M8Prime(RemeshFormula):
"""M8Prime kernel."""
+
+ ghosts_layer_size = 4
+
def __init__(self):
super(M8Prime, self).__init__()
self.shift = 3
self.weights = [
npw.asrealarray([-10, 21, 28, -105, 70, 35, -56, 17]) / 3360.,
- npw.asrealarray([70, -175, -140, 770, -560, -350, 504, -102]) / 3360.,
- npw.asrealarray([-210, 609, 224, -2135, 910, 2765, -2520, 255]) / 3360.,
- npw.asrealarray([350, -1155, 0, 2940, 0, -4900, 0, 3020]) / 3360.,
- npw.asrealarray([-350, 1295, -420, -2135, -910, 2765, 2520, 255]) / 3360.,
- npw.asrealarray([210, -861, 532, 770, 560, -350, -504, -102]) / 3360.,
+ npw.asrealarray([70, -175, -140, 770, -560, -350,
+ 504, -102]) / 3360.,
+ npw.asrealarray([-210, 609, 224, -2135, 910, 2765,
+ -2520, 255]) / 3360.,
+ npw.asrealarray([350, -1155, 0, 2940, 0, -4900, 0,
+ 3020]) / 3360.,
+ npw.asrealarray([-350, 1295, -420, -2135, -910, 2765,
+ 2520, 255]) / 3360.,
+ npw.asrealarray([210, -861, 532, 770, 560, -350, -504,
+ -102]) / 3360.,
npw.asrealarray([-70, 315, -280, -105, -70, 35, 56, 17]) / 3360.,
npw.asrealarray([10, -49, 56, 0, 0, 0, 0, 0]) / 3360.,
]
@@ -293,16 +329,24 @@ class M8Prime(RemeshFormula):
class L6_3(RemeshFormula):
"""L6_3 kernel."""
+
+ ghosts_layer_size = 4
+
def __init__(self):
super(L6_3, self).__init__()
self.shift = 3
self.weights = [
npw.asrealarray([-89, 312, -370, 140, 15, 4, -12, 0]) / 720.,
- npw.asrealarray([623, -2183, 2581, -955, -120, -54, 108, 0]) / 720.,
- npw.asrealarray([-1869, 6546, -7722, 2850, 195, 540, -540, 0]) / 720.,
- npw.asrealarray([3115, -10905, 12845, -4795, 0, -980, 0, 720]) / 720.,
- npw.asrealarray([-3115, 10900, -12830, 4880, -195, 540, 540, 0]) / 720.,
- npw.asrealarray([1869, -6537, 7695, -2985, 120, -54, -108, 0]) / 720.,
+ npw.asrealarray([623, -2183, 2581, -955, -120, -54, 108,
+ 0]) / 720.,
+ npw.asrealarray([-1869, 6546, -7722, 2850, 195, 540, -540,
+ 0]) / 720.,
+ npw.asrealarray([3115, -10905, 12845, -4795, 0, -980, 0,
+ 720]) / 720.,
+ npw.asrealarray([-3115, 10900, -12830, 4880, -195, 540,
+ 540, 0]) / 720.,
+ npw.asrealarray([1869, -6537, 7695, -2985, 120, -54, -108,
+ 0]) / 720.,
npw.asrealarray([-623, 2178, -2566, 1010, -15, 4, 12, 0]) / 720.,
npw.asrealarray([89, -311, 367, -145, 0, 0, 0, 0]) / 720.,
]
@@ -310,70 +354,122 @@ class L6_3(RemeshFormula):
class L6_4(RemeshFormula):
"""L6_4 kernel."""
+
+ ghosts_layer_size = 5
+
def __init__(self):
super(L6_4, self).__init__()
self.shift = 3
self.weights = [
- npw.asrealarray([290, -1305, 2231, -1718, 500, -5, 15, 4, -12, 0]) / 720.,
- npw.asrealarray([-2030, 9135, -15617, 12027, -3509, 60, -120, -54, 108, 0]) / 720.,
- npw.asrealarray([6090, -27405, 46851, -36084, 10548, -195, 195, 540, -540, 0]) / 720.,
- npw.asrealarray([-10150, 45675, -78085, 60145, -17605, 280, 0, -980, 0, 720]) / 720.,
- npw.asrealarray([10150, -45675, 78085, -60150, 17620, -195, -195, 540, 540, 0]) / 720.,
- npw.asrealarray([-6090, 27405, -46851, 36093, -10575, 60, 120, -54, -108, 0]) / 720.,
- npw.asrealarray([2030, -9135, 15617, -12032, 3524, -5, -15, 4, 12, 0]) / 720.,
- npw.asrealarray([-290, 1305, -2231, 1719, -503, 0, 0, 0, 0, 0]) / 720.,
+ npw.asrealarray([290, -1305, 2231, -1718, 500, -5, 15, 4,
+ -12, 0]) / 720.,
+ npw.asrealarray([-2030, 9135, -15617, 12027, -3509, 60,
+ -120, -54, 108, 0]) / 720.,
+ npw.asrealarray([6090, -27405, 46851, -36084, 10548, -195,
+ 195, 540, -540, 0]) / 720.,
+ npw.asrealarray([-10150, 45675, -78085, 60145, -17605, 280,
+ 0, -980, 0, 720]) / 720.,
+ npw.asrealarray([10150, -45675, 78085, -60150, 17620, -195,
+ -195, 540, 540, 0]) / 720.,
+ npw.asrealarray([-6090, 27405, -46851, 36093, -10575, 60, 120,
+ -54, -108, 0]) / 720.,
+ npw.asrealarray([2030, -9135, 15617, -12032, 3524, -5, -15, 4,
+ 12, 0]) / 720.,
+ npw.asrealarray([-290, 1305, -2231, 1719, -503, 0, 0, 0, 0,
+ 0]) / 720.,
]
class L6_5(RemeshFormula):
"""L6_5 kernel."""
+
+ ghosts_layer_size = 6
+
def __init__(self):
super(L6_5, self).__init__()
self.shift = 3
self.weights = [
- npw.asrealarray([-1006, 5533, -12285, 13785, -7829, 1803, -3, -5, 15, 4, -12, 0]) / 720.,
- npw.asrealarray([7042, -38731, 85995, -96495, 54803, -12620, 12, 60, -120, -54, 108, 0]) / 720.,
- npw.asrealarray([-21126, 116193, -257985, 289485, -164409, 37857, -15, -195, 195, 540, -540, 0]) / 720.,
- npw.asrealarray([35210, -193655, 429975, -482475, 274015, -63090, 0, 280, 0, -980, 0, 720]) / 720.,
- npw.asrealarray([-35210, 193655, -429975, 482475, -274015, 63085, 15, -195, -195, 540, 540, 0]) / 720.,
- npw.asrealarray([21126, -116193, 257985, -289485, 164409, -37848, -12, 60, 120, -54, -108, 0]) / 720.,
- npw.asrealarray([-7042, 38731, -85995, 96495, -54803, 12615, 3, -5, -15, 4, 12, 0]) / 720.,
- npw.asrealarray([1006, -5533, 12285, -13785, 7829, -1802, 0, 0, 0, 0, 0, 0]) / 720.,
+ npw.asrealarray([-1006, 5533, -12285, 13785, -7829, 1803,
+ -3, -5, 15, 4, -12, 0]) / 720.,
+ npw.asrealarray([7042, -38731, 85995, -96495, 54803, -12620,
+ 12, 60, -120, -54, 108, 0]) / 720.,
+ npw.asrealarray([-21126, 116193, -257985, 289485, -164409,
+ 37857, -15, -195, 195, 540, -540, 0]) / 720.,
+ npw.asrealarray([35210, -193655, 429975, -482475, 274015,
+ -63090, 0, 280, 0, -980, 0, 720]) / 720.,
+ npw.asrealarray([-35210, 193655, -429975, 482475, -274015,
+ 63085, 15, -195, -195, 540, 540, 0]) / 720.,
+ npw.asrealarray([21126, -116193, 257985, -289485, 164409,
+ -37848, -12, 60, 120, -54, -108, 0]) / 720.,
+ npw.asrealarray([-7042, 38731, -85995, 96495, -54803, 12615,
+ 3, -5, -15, 4, 12, 0]) / 720.,
+ npw.asrealarray([1006, -5533, 12285, -13785, 7829, -1802,
+ 0, 0, 0, 0, 0, 0]) / 720.,
]
+
class L6_6(RemeshFormula):
"""L6_6 kernel."""
+
+ ghosts_layer_size = 7
+
def __init__(self):
super(L6_6, self).__init__()
self.shift = 3
self.weights = [
- npw.asrealarray([3604, -23426, 63866, -93577, 77815, -34869, 6587, 1, -3, -5, 15, 4, -12, 0]) / 720.,
- npw.asrealarray([-25228, 163982, -447062, 655039, -544705, 244083, -46109, -6, 12, 60, -120, -54, 108, 0]) / 720.,
- npw.asrealarray([75684, -491946, 1341186, -1965117, 1634115, -732249, 138327, 15, -15, -195, 195, 540, -540, 0]) / 720.,
- npw.asrealarray([-126140, 819910, -2235310, 3275195, -2723525, 1220415, -230545, -20, 0, 280, 0, -980, 0, 720]) / 720.,
- npw.asrealarray([126140, -819910, 2235310, -3275195, 2723525, -1220415, 230545, 15, 15, -195, -195, 540, 540, 0]) / 720.,
- npw.asrealarray([-75684, 491946, -1341186, 1965117, -1634115, 732249, -138327, -6, -12, 60, 120, -54, -108, 0]) / 720.,
- npw.asrealarray([25228, -163982, 447062, -655039, 544705, -244083, 46109, 1, 3, -5, -15, 4, 12, 0]) / 720.,
- npw.asrealarray([-3604, 23426, -63866, 93577, -77815, 34869, -6587, 0, 0, 0, 0, 0, 0, 0]) / 720.,
+ npw.asrealarray([3604, -23426, 63866, -93577, 77815, -34869,
+ 6587, 1, -3, -5, 15, 4, -12, 0]) / 720.,
+ npw.asrealarray([-25228, 163982, -447062, 655039, -544705,
+ 244083, -46109, -6, 12, 60, -120, -54, 108,
+ 0]) / 720.,
+ npw.asrealarray([75684, -491946, 1341186, -1965117, 1634115,
+ -732249, 138327, 15, -15, -195, 195, 540, -540,
+ 0]) / 720.,
+ npw.asrealarray([-126140, 819910, -2235310, 3275195, -2723525,
+ 1220415, -230545, -20, 0, 280, 0, -980, 0,
+ 720]) / 720.,
+ npw.asrealarray([126140, -819910, 2235310, -3275195, 2723525,
+ -1220415, 230545, 15, 15, -195, -195, 540, 540,
+ 0]) / 720.,
+ npw.asrealarray([-75684, 491946, -1341186, 1965117, -1634115,
+ 732249, -138327, -6, -12, 60, 120, -54, -108,
+ 0]) / 720.,
+ npw.asrealarray([25228, -163982, 447062, -655039, 544705, -244083,
+ 46109, 1, 3, -5, -15, 4, 12, 0]) / 720.,
+ npw.asrealarray([-3604, 23426, -63866, 93577, -77815, 34869, -6587,
+ 0, 0, 0, 0, 0, 0, 0]) / 720.,
]
class L8_4(RemeshFormula):
"""L8_4 kernel."""
+
+ ghosts_layer_size = 5
+
def __init__(self):
super(L8_4, self).__init__()
self.shift = 4
self.weights = [
- npw.asrealarray([-3569, 16061, -27454, 21126, -6125, 49, -196, -36, 144, 0]) / 40320.,
- npw.asrealarray([32121, -144548, 247074, -190092, 55125, -672, 2016, 512, -1536, 0]) / 40320.,
- npw.asrealarray([-128484, 578188, -988256, 760312, -221060, 4732, -9464, -4032, 8064, 0]) / 40320.,
- npw.asrealarray([299796, -1349096, 2305856, -1774136, 517580, -13664, 13664, 32256, -32256, 0]) / 40320.,
- npw.asrealarray([-449694, 2023630, -3458700, 2661540, -778806, 19110, 0, -57400, 0, 40320]) / 40320.,
- npw.asrealarray([449694, -2023616, 3458644, -2662016, 780430, -13664, -13664, 32256, 32256, 0]) / 40320.,
- npw.asrealarray([-299796, 1349068, -2305744, 1775032, -520660, 4732, 9464, -4032, -8064, 0]) / 40320.,
- npw.asrealarray([128484, -578168, 988176, -760872, 223020, -672, -2016, 512, 1536, 0]) / 40320.,
- npw.asrealarray([-32121, 144541, -247046, 190246, -55685, 49, 196, -36, -144, 0]) / 40320.,
- npw.asrealarray([3569, -16060, 27450, -21140, 6181, 0, 0, 0, 0, 0]) / 40320.,
+ npw.asrealarray([-3569, 16061, -27454, 21126, -6125, 49, -196,
+ -36, 144, 0]) / 40320.,
+ npw.asrealarray([32121, -144548, 247074, -190092, 55125, -672,
+ 2016, 512, -1536, 0]) / 40320.,
+ npw.asrealarray([-128484, 578188, -988256, 760312, -221060, 4732,
+ -9464, -4032, 8064, 0]) / 40320.,
+ npw.asrealarray([299796, -1349096, 2305856, -1774136, 517580,
+ -13664, 13664, 32256, -32256, 0]) / 40320.,
+ npw.asrealarray([-449694, 2023630, -3458700, 2661540, -778806,
+ 19110, 0, -57400, 0, 40320]) / 40320.,
+ npw.asrealarray([449694, -2023616, 3458644, -2662016, 780430,
+ -13664, -13664, 32256, 32256, 0]) / 40320.,
+ npw.asrealarray([-299796, 1349068, -2305744, 1775032, -520660,
+ 4732, 9464, -4032, -8064, 0]) / 40320.,
+ npw.asrealarray([128484, -578168, 988176, -760872, 223020, -672,
+ -2016, 512, 1536, 0]) / 40320.,
+ npw.asrealarray([-32121, 144541, -247046, 190246, -55685, 49, 196,
+ -36, -144, 0]) / 40320.,
+ npw.asrealarray([3569, -16060, 27450, -21140, 6181, 0, 0, 0,
+ 0, 0]) / 40320.,
]
@@ -384,23 +480,24 @@ def polynomial_optimisation():
"""
def test_form(func, r, a, s, *args):
tt = 0.
- for i in xrange(10):
+ for _ in xrange(10):
r[...] = 0.
- t = MPI.Wtime()
+ t = Wtime()
r[...] = func(a, *args)
- tt += (MPI.Wtime() - t)
+ tt += (Wtime() - t)
print tt, s
- from hysop.mpi import MPI
nb = 128
a = npw.asrealarray(np.random.random((nb, nb, nb)))
r = np.zeros_like(a)
temp = np.zeros_like(a)
- lambda_p = lambda x: 1. + 2. * x + 3. * x ** 2 + 4. *x ** 3 + 5. * x ** 4 + \
- 6. * x ** 5 + 7. * x ** 6 + 8. * x ** 7 + 9. * x ** 8 + 10. * x ** 9 + \
- 11. * x ** 10
- lambda_h = lambda x: (x * (x * (x * (x * (x * (x * (x * (x * (11. * x + 10.) + 9.) + \
- 8.) + 7.) + 6.) + 5.) + 4.) + 3.) + 2.) + 1.
+ lambda_p = lambda x: 1. + 2. * x + 3. * x ** 2 + 4. * x ** 3 + \
+ 5. * x ** 4 + 6. * x ** 5 + 7. * x ** 6 + \
+ 8. * x ** 7 + 9. * x ** 8 + 10. * x ** 9 + \
+ 11. * x ** 10
+ lambda_h = lambda x: (x * (x * (x * (x * (x * (x * (x * (
+ x * (11. * x + 10.) + 9.) + 8.) + 7.) + 6.) + 5.) + 4.) + 3.) + 2.) + 1.
+
coeffs = coeffs = npw.asrealarray(np.arange(11, 0, -1))
def func_h(x, r):
@@ -555,7 +652,8 @@ def polynomial_optimisation():
(77815. + (-93577. + (63866. + (-23426. + 3604. * y) * y) * y) * y) * y) * y) \
* y) * y) * y) * y) * y) * y) * y / 720.
res_test[...] = w_test(a)
- w_test_coeffs = npw.asrealarray([3604, -23426, 63866, -93577, 77815, -34869, 6587,
+ w_test_coeffs = npw.asrealarray([3604, -23426, 63866, -93577,
+ 77815, -34869, 6587,
1, -3, -5, 15, 4, -12, 0]) / 720.
res_test_coeff[...] = w_test_coeffs[0]
for c in w_test_coeffs[1:]:
diff --git a/hysop/old/numerics.old/tests/__init__.py b/hysop/old/numerics.old/tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/numerics/tests/test_differential_operations.py b/hysop/old/numerics.old/tests/test_differential_operations.py
similarity index 99%
rename from hysop/numerics/tests/test_differential_operations.py
rename to hysop/old/numerics.old/tests/test_differential_operations.py
index 35139d349581f95166786b4410f1947957b9d5a5..89c0fcc3fe688e4029446fed08d563a5d2ae95a9 100755
--- a/hysop/numerics/tests/test_differential_operations.py
+++ b/hysop/old/numerics.old/tests/test_differential_operations.py
@@ -2,7 +2,7 @@
from hysop import Field, Box
import numpy as np
import hysop.numerics.differential_operations as diffop
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.tools.parameters import Discretization
from hysop.domain.subsets import SubBox
import math as m
diff --git a/hysop/numerics/tests/test_finite_differences.py b/hysop/old/numerics.old/tests/test_finite_differences.py
similarity index 87%
rename from hysop/numerics/tests/test_finite_differences.py
rename to hysop/old/numerics.old/tests/test_finite_differences.py
index b098eb7b03b12cb43fd210fe543a9e8795af8a60..b5d8df6878493a7acd3f2befaec3a4af50f2fd21 100644
--- a/hysop/numerics/tests/test_finite_differences.py
+++ b/hysop/old/numerics.old/tests/test_finite_differences.py
@@ -1,7 +1,7 @@
"""FD schemes tests
"""
from hysop.numerics.finite_differences import FDC2, FDC4, FD2C2
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop import Box, Discretization, Field
import numpy as np
from hysop.domain.subsets import SubBox
@@ -116,9 +116,9 @@ def check_fd_schemes_reduce_output(discr, formulas):
ind = topo.mesh.compute_index
hh = topo.mesh.space_step
sc = {
- FDC2(hh, ind, indices_out=True): [refd, 0, 2],
- FDC4(hh, ind, indices_out=True): [refd, 0, 4],
- FD2C2(hh, ind, indices_out=True): [ref2d, 1, 2]
+ FDC2(hh, ind, output_indices=True): [refd, 0, 2],
+ FDC4(hh, ind, output_indices=True): [refd, 0, 4],
+ FD2C2(hh, ind, output_indices=True): [ref2d, 1, 2]
}
shape = np.asarray(topo.mesh.resolution).copy()
shape -= 2 * g
@@ -136,9 +136,9 @@ def check_fd_schemes_reduce_all(discr, formulas):
subbox = SubBox(parent=topo.domain, origin=orig, length=sl)
ind = subbox.discretize(topo)[0]
sc = {
- FDC2(hh, ind, indices_out=True): [refd, 0, 2],
- FDC4(hh, ind, indices_out=True): [refd, 0, 4],
- FD2C2(hh, ind, indices_out=True): [ref2d, 1, 2]
+ FDC2(hh, ind, output_indices=True): [refd, 0, 2],
+ FDC4(hh, ind, output_indices=True): [refd, 0, 4],
+ FD2C2(hh, ind, output_indices=True): [ref2d, 1, 2]
}
shape = subbox.mesh[topo].resolution
result = npw.zeros(shape)
@@ -159,9 +159,9 @@ def check_fd_schemes_setiout(discr, formulas):
result = npw.zeros(shape)
iout = [slice(3, shape[i] - 3) for i in xrange(len(shape))]
sc = {
- FDC2(hh, ind, indices_out=iout): [refd, 0, 2],
- FDC4(hh, ind, indices_out=iout): [refd, 0, 4],
- FD2C2(hh, ind, indices_out=iout): [ref2d, 1, 2]
+ FDC2(hh, ind, output_indices=iout): [refd, 0, 2],
+ FDC4(hh, ind, output_indices=iout): [refd, 0, 4],
+ FD2C2(hh, ind, output_indices=iout): [ref2d, 1, 2]
}
run_schemes(sc, f1d, result, ind, hh, iout)
@@ -188,12 +188,3 @@ def test_fd_3d_reduce_all():
def test_fd_3d_setiout():
check_fd_schemes_setiout(d3d, [f3d, ref_f3d, ref2_f3d])
-
-
-if __name__ == '__main__':
- test_fd_2d()
- test_fd_3d()
- test_fd_3d_reduce_input()
- test_fd_3d_reduce_output()
- test_fd_3d_reduce_all()
- test_fd_3d_setiout()
diff --git a/hysop/old/numerics.old/tests/test_interpolation.py b/hysop/old/numerics.old/tests/test_interpolation.py
new file mode 100644
index 0000000000000000000000000000000000000000..945e0053790b9c1c083c89361cd8219e805ea42c
--- /dev/null
+++ b/hysop/old/numerics.old/tests/test_interpolation.py
@@ -0,0 +1,123 @@
+"""Test interpolation schemes
+"""
+from hysop.numerics.interpolation.interpolation import Linear
+from hysop.tools.numpywrappers import npw
+from hysop import Box, Discretization
+import numpy as np
+cos = np.cos
+
+disc = [None, ] * 3
+g = 1
+nx = 33
+ny = 69
+nz = 129
+disc[0] = Discretization([nx, ], [g, ])
+disc[1] = Discretization([nx, ny], [g, g])
+disc[2] = Discretization([nx, ny, nz], [g, g, g])
+doms = [None, ] * 3
+topos = [None, ] * 3
+rworks = [None, ] * 3
+iworks = [None, ] * 3
+for case in xrange(3):
+ dim = case + 1
+ doms[case] = Box(origin=[0.] * dim, length=[4. * np.pi, ] * dim)
+ topos[case] = doms[case].create_topology(disc[case])
+ refsize = (np.prod(topos[case].mesh.compute_resolution) + 324, )
+ iworks[case] = [npw.int_zeros(refsize)]
+ rworks[case] = [npw.zeros(refsize)]
+dx = topos[2].mesh.space_step
+
+
+def run_interp(dimension, velo=0., with_work=False):
+ """Interpolate a field and compare with reference
+ (cosine function), for a given domain dimension
+ """
+ topo = topos[dimension - 1]
+ rwork, iwork = None, None
+ if with_work:
+ rwork = rworks[dimension - 1]
+ iwork = iworks[dimension - 1]
+ ind = topo.mesh.compute_index
+ field = npw.zeros(topo.mesh.resolution)
+ for direction in xrange(topo.domain.dimension):
+ # lref = doms[dimension - 1].length[direction]
+ h = topo.mesh.space_step[direction]
+ x = topo.mesh.coords[direction]
+ field[...] = np.cos(x)
+ # select a set of points which are advected randomly and interpolated
+ # --> 1 point over two from the original mesh
+ shape = list(topo.mesh.resolution)
+ coords = topo.mesh.coords[direction]
+ ic = [slice(0, coords.shape[i]) for i in xrange(topo.domain.dimension)]
+ ic[direction] = slice(0, topo.mesh.resolution[direction] - 3, 2)
+ shape[direction] = topo.mesh.coords[direction][ic].shape[direction]
+ positions = npw.random(shape) * velo
+ positions[...] += topo.mesh.coords[direction][ic]
+ interp = Linear(field, direction=direction, topo_source=topo,
+ rwork=rwork, iwork=iwork)
+ result = [npw.zeros_like(positions)]
+ result = interp(0., [positions], result)
+ reference = npw.zeros_like(result[0])
+ reference[...] = np.cos(positions)
+ tol = 0.5 * h ** 2
+ assert np.allclose(result[0][ind], reference[ind], rtol=tol)
+
+
+def test_linear_interpolation_1d_velocity_null():
+ """Linear interpolation on 1d domain"""
+ run_interp(1)
+
+
+def test_linear_interpolation_1d():
+ """Linear interpolation on 1d domain"""
+ run_interp(1, 0.5 * dx[0])
+
+
+def test_linear_interpolation_2d_velocity_null():
+ """Linear interpolation on 2d domain"""
+ run_interp(2)
+
+
+def test_linear_interpolation_2d():
+ """Linear interpolation on 2d domain"""
+ run_interp(2, 0.5 * dx[1])
+
+
+def test_linear_interpolation_3d_velocity_null():
+ """Linear interpolation on 3d domain"""
+ run_interp(3)
+
+
+def test_linear_interpolation_3d():
+ """Linear interpolation on 3d domain"""
+ run_interp(3, 0.5 * dx[2])
+
+
+def test_linear_interpolation_1d_wk_velocity_null():
+ """Linear interpolation on 1d domain, external work arrays"""
+ run_interp(1, 0., True)
+
+
+def test_linear_interpolation_1d_wk():
+ """Linear interpolation on 1d domain, external work arrays"""
+ run_interp(1, 0.5 * dx[0], True)
+
+
+def test_linear_interpolation_2d_wk_velocity_null():
+ """Linear interpolation on 2d domain, external work arrays"""
+ run_interp(2, 0., True)
+
+
+def test_linear_interpolation_2d_wk():
+ """Linear interpolation on 2d domain, external work arrays"""
+ run_interp(2, 0.5 * dx[1], True)
+
+
+def test_linear_interpolation_3d_wk_velocity_null():
+ """Linear interpolation on 3d domain, external work arrays"""
+ run_interp(3, 0., True)
+
+
+def test_linear_interpolation_3d_wk():
+ """Linear interpolation on 3d domain, external work arrays"""
+ run_interp(3, 0.5 * dx[2], True)
diff --git a/hysop/numerics/tests/test_odesolvers.py b/hysop/old/numerics.old/tests/test_odesolvers.py
similarity index 82%
rename from hysop/numerics/tests/test_odesolvers.py
rename to hysop/old/numerics.old/tests/test_odesolvers.py
index b75b58418116b2d85df91718fbd0260984050f48..eea7c8dd25d61c2658cc47c785ce053390f04735 100755
--- a/hysop/numerics/tests/test_odesolvers.py
+++ b/hysop/old/numerics.old/tests/test_odesolvers.py
@@ -2,7 +2,7 @@
"""
# -*- coding: utf-8 -*-
from hysop.numerics.odesolvers import Euler, RK2, RK3, RK4
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import math
import numpy as np
from hysop.tools.parameters import Discretization
@@ -87,8 +87,8 @@ def integrate_3d(integ, nb_steps):
npw.zeros(local_res_3d)]
# work = None
i = 1
- xref = local_res_3d[0] // 3.
- yref = local_res_3d[1] // 2.4
+ xref = local_res_3d[0] // 3
+ yref = local_res_3d[1] // 2
zref = local_res_3d[2] // 5
ref = npw.zeros((nb_steps, 4))
ref[0, 1] = y[0][xref, yref, zref]
@@ -112,30 +112,43 @@ def integrate_3d(integ, nb_steps):
def run_integ(integrator, order):
+ """apply 'integrator' (== Euler, RK3 ...)
+ and check error according to input order. 1D case
+ """
nb_steps = 100
wk_prop = integrator.get_work_properties(1, topo)['rwork']
work = []
for shape in wk_prop:
work.append(npw.zeros(shape))
- dt, err = integrate(integrator(1, topo, f=rhs, rwork=work), nb_steps)
+ dt, err = integrate(integrator(nb_components=1, topo=topo,
+ f=rhs, rwork=work), nb_steps)
assert err < dt ** order
def run_integ_3d(integrator, order):
+ """apply 'integrator' (== Euler, RK3 ...)
+ and check error according to input order. 3D case.
+
+ """
nb_steps = 50
wk_prop = integrator.get_work_properties(3, topo3d)['rwork']
work = []
for shape in wk_prop:
work.append(npw.zeros(shape))
- dt, err = integrate_3d(integrator(3, topo3d, f=rhs3d, rwork=work),
+ dt, err = integrate_3d(integrator(nb_components=3, topo=topo3d,
+ f=rhs3d, rwork=work),
nb_steps)
for e in err:
assert e < dt ** order
def run_integ_3d_no_work(integrator, order):
+ """apply 'integrator' (== Euler, RK3 ...)
+ and check error according to input order. 3D case.
+ """
nb_steps = 50
- dt, err = integrate_3d(integrator(3, topo3d, f=rhs3d), nb_steps)
+ dt, err = integrate_3d(integrator(nb_components=3, topo=topo3d,
+ f=rhs3d), nb_steps)
for e in err:
assert e < dt ** order
@@ -177,6 +190,7 @@ def test_rk4_3d():
def test_user_defined_common_workspace():
+ """One work space for all integrators"""
integrators = {Euler: 1, RK2: 2, RK3: 3, RK4: 4}
nb_steps = 50
wk_prop = {}
@@ -184,7 +198,7 @@ def test_user_defined_common_workspace():
wk_prop[integ] = integ.get_work_properties(3, topo3d)['rwork']
work = WorkSpaceTools.allocate_common_workspaces(wk_prop.values())
for integ in integrators:
- dt, err = integrate_3d(integ(3, topo3d, rhs3d, work), nb_steps)
+ dt, err = integrate_3d(integ(nb_components=3, topo=topo3d,
+ f=rhs3d, rwork=work), nb_steps)
for e in err:
assert e < dt ** integrators[integ]
-
diff --git a/hysop/old/numerics.old/tests/test_remesh.py b/hysop/old/numerics.old/tests/test_remesh.py
new file mode 100644
index 0000000000000000000000000000000000000000..43578c35827defe7a3d199353778c97ca2b2cd85
--- /dev/null
+++ b/hysop/old/numerics.old/tests/test_remesh.py
@@ -0,0 +1,196 @@
+"""Test remesh schemes
+"""
+from hysop.numerics.remeshing import Linear, L2_1, Remeshing
+from hysop.tools.numpywrappers import npw
+from hysop.constants import EPS
+from hysop import Box, Discretization
+import numpy as np
+cos = np.cos
+
+disc = [None, ] * 3
+g = 2
+nx = 65
+ny = 49
+nz = 57
+disc[0] = Discretization([nx, ], [g, ])
+disc[1] = Discretization([nx, ny], [g, g])
+disc[2] = Discretization([nx, ny, nz], [g, g, g])
+doms = [None, ] * 3
+topos = [None, ] * 3
+rworks = [None, ] * 3
+iworks = [None, ] * 3
+for case in xrange(3):
+ dim = case + 1
+ doms[case] = Box(origin=[0.] * dim, length=[4. * np.pi, ] * dim)
+ topos[case] = doms[case].create_topology(disc[case])
+ refsize = (np.prod(topos[case].mesh.resolution) + 324, )
+ iworks[case] = [npw.int_zeros(refsize)]
+ rworks[case] = [npw.zeros(refsize), npw.zeros(refsize)]
+dx = [0., 0. , 0.] # topos[2].mesh.space_step
+
+
+def run_remesh(kernel, dimension, velo=0., with_work=False):
+ """Interpolate a field and compare with reference
+ (cosine function), for a given domain dimension
+ """
+ topo = topos[dimension - 1]
+ rwork, iwork = None, None
+ if with_work:
+ rwork = rworks[dimension - 1]
+ iwork = iworks[dimension - 1]
+ ind = topo.mesh.compute_index
+ lenfield = 2
+ fieldp = [None, ] * lenfield
+ result = [None, ] * lenfield
+ reference = [None, ] * lenfield
+ for direction in xrange(topo.domain.dimension):
+ h = topo.mesh.space_step[direction]
+ x = topo.mesh.coords[direction]
+ reference = [npw.zeros(topo.mesh.resolution)
+ for _ in xrange(lenfield)]
+ reference[0][...] = np.cos(x)
+ if lenfield > 1:
+ reference[1][...] = np.sin(x)
+ shape = topo.mesh.resolution.copy()
+ shape[direction] -= 2 * g
+ # note : this should work for any number of points
+ # in direction, as soon as work array is large enough
+ # + EPS to be sure that particles are (almost) on grid
+ # but on the right of the grid point when velo=0
+ positions = npw.random(shape) * velo
+ positions[...] += 10 * EPS
+ positions[...] += topo.mesh.compute_coords[direction]
+ for i in xrange(lenfield):
+ fieldp[i] = npw.zeros_like(positions)
+ result[i] = npw.zeros_like(reference[i])
+ fieldp[0][...] = np.cos(positions)
+ if lenfield > 1:
+ fieldp[1][...] = np.sin(positions)
+ remesh = Remeshing(kernel, topo_source=topo, direction=direction,
+ rwork=rwork, iwork=iwork)
+ result = remesh(positions, fieldp, result)
+ tol = 0.5 * h ** 2
+ #plt.plot(x.flat[2:-2], result[ind], 'o-', x.flat[2:-2], reference[ind], '+-')
+ #plt.show()
+ for i in xrange(lenfield):
+ assert np.allclose(result[i][ind], reference[i][ind], rtol=tol)
+
+
+def test_linear_remesh_1d_velocity_null():
+ """Linear remesh on 1d domain"""
+ run_remesh(Linear, 1)
+
+
+def test_linear_remesh_1d():
+ """Linear remesh on 1d domain"""
+ run_remesh(Linear, 1, 0.3 * dx[0])
+
+
+def test_linear_remesh_2d_velocity_null():
+ """Linear remesh on 2d domain"""
+ run_remesh(Linear, 2)
+
+
+def test_linear_remesh_2d():
+ """Linear remesh on 2d domain"""
+ run_remesh(Linear, 2, 0.3 * dx[1])
+
+
+def test_linear_remesh_3d_velocity_null():
+ """Linear remesh on 3d domain"""
+ run_remesh(Linear, 3)
+
+
+def test_linear_remesh_3d():
+ """Linear remesh on 3d domain"""
+ run_remesh(Linear, 3, 0.3 * dx[2])
+
+
+def test_linear_remesh_1d_wk_velocity_null():
+ """Linear remesh on 1d domain, external work arrays"""
+ run_remesh(Linear, 1, 0., True)
+
+
+def test_linear_remesh_1d_wk():
+ """Linear remesh on 1d domain, external work arrays"""
+ run_remesh(Linear, 1, 0.3 * dx[0], True)
+
+
+def test_linear_remesh_2d_wk_velocity_null():
+ """Linear remesh on 2d domain, external work arrays"""
+ run_remesh(Linear, 2, 0., True)
+
+
+def test_linear_remesh_2d_wk():
+ """Linear remesh on 2d domain, external work arrays"""
+ run_remesh(Linear, 2, 0.3 * dx[1], True)
+
+
+def test_linear_remesh_3d_wk_velocity_null():
+ """Linear remesh on 3d domain, external work arrays"""
+ run_remesh(Linear, 3, 0., True)
+
+
+def test_linear_remesh_3d_wk():
+ """Linear remesh on 3d domain, external work arrays"""
+ run_remesh(Linear, 3, 0.3 * dx[2], True)
+
+
+def test_l21_remesh_1d_velocity_null():
+ """L2_1 remesh on 1d domain"""
+ run_remesh(L2_1, 1)
+
+
+def test_l21_remesh_1d():
+ """L2_1 remesh on 1d domain"""
+ run_remesh(L2_1, 1, 0.3 * dx[0])
+
+
+def test_l21_remesh_2d_velocity_null():
+ """L2_1 remesh on 2d domain"""
+ run_remesh(L2_1, 2)
+
+
+def test_l21_remesh_2d():
+ """L2_1 remesh on 2d domain"""
+ run_remesh(L2_1, 2, 0.3 * dx[1])
+
+
+def test_l21_remesh_3d_velocity_null():
+ """L2_1 remesh on 3d domain"""
+ run_remesh(L2_1, 3)
+
+
+def test_l21_remesh_3d():
+ """L2_1 remesh on 3d domain"""
+ run_remesh(L2_1, 3, 0.3 * dx[2])
+
+
+def test_l21_remesh_1d_wk_velocity_null():
+ """L2_1 remesh on 1d domain, external work arrays"""
+ run_remesh(L2_1, 1, 0., True)
+
+
+def test_l21_remesh_1d_wk():
+ """L2_1 remesh on 1d domain, external work arrays"""
+ run_remesh(L2_1, 1, 0.3 * dx[0], True)
+
+
+def test_l21_remesh_2d_wk_velocity_null():
+ """L2_1 remesh on 2d domain, external work arrays"""
+ run_remesh(L2_1, 2, 0., True)
+
+
+def test_l21_remesh_2d_wk():
+ """L2_1 remesh on 2d domain, external work arrays"""
+ run_remesh(L2_1, 2, 0.3 * dx[1], True)
+
+
+def test_l21_remesh_3d_wk_velocity_null():
+ """L2_1 remesh on 3d domain, external work arrays"""
+ run_remesh(L2_1, 3, 0., True)
+
+
+def test_l21_remesh_3d_wk():
+ """L2_1 remesh on 3d domain, external work arrays"""
+ run_remesh(L2_1, 3, 0.3 * dx[2], True)
diff --git a/hysop/old/numerics.old/tests/test_update_ghosts.py b/hysop/old/numerics.old/tests/test_update_ghosts.py
new file mode 100755
index 0000000000000000000000000000000000000000..d86c3d2c7626398181210b48518639e6312f7ffd
--- /dev/null
+++ b/hysop/old/numerics.old/tests/test_update_ghosts.py
@@ -0,0 +1,266 @@
+"""Test ghost points synchronization
+"""
+from hysop.numerics.update_ghosts import UpdateGhosts, UpdateGhostsFull
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.tools.parameters import Discretization
+from hysop.core.mpi import main_rank
+from hysop.tools.numpywrappers import npw
+import numpy as np
+
+
+def get_gh_slices(topo):
+ """Return indices of ghost points"""
+ tab = Field(topo.domain, name='temp')
+ tabd = tab.discretize(topo)[0]
+ tabd[...] = 0.
+ tabd[topo.mesh.compute_index] = 1.
+ return np.where(tabd == 0.)
+
+
+def get_ghosts_indices(topo):
+ """Return indices of points inside the ghost layers
+ for a given topology
+
+ gh_s[d] : for points at the beginning of the domain
+ in direction d.
+ gh_e[d] : for points at the end of the domain
+ in direction d.
+
+ Corner points are not included.
+ """
+ gh_s = []
+ gh_e = []
+ ghosts = topo.ghosts()
+ sl_start = [slice(0, ghosts[d]) for d in xrange(topo.domain.dimension)]
+ sl_end = [slice(-ghosts[d], None, None)
+ for d in xrange(topo.domain.dimension)]
+ for j in xrange(topo.domain.dimension):
+ gh_s.append(list(topo.mesh.compute_index))
+ gh_e.append(list(topo.mesh.compute_index))
+ gh_s[j][j] = sl_start[j]
+ gh_e[j][j] = sl_end[j]
+ return gh_s, gh_e
+
+
+def get_corners_indices(topo):
+ """Return indices of points inside the ghost layers
+ for a given topology
+
+ gh_s[d] : for points at the beginning of the domain
+ in direction d.
+ gh_e[d] : for points at the end of the domain
+ in direction d.
+
+ Corner points are included.
+ """
+ gh_s = []
+ gh_e = []
+ ghosts = topo.ghosts()
+ sl_start = [slice(0, ghosts[d]) for d in xrange(topo.domain.dimension)]
+ sl_end = [slice(-ghosts[d], None, None)
+ for d in xrange(topo.domain.dimension)]
+ for j in xrange(topo.domain.dimension):
+ gh_s.append(list(topo.mesh.local_index))
+ gh_e.append(list(topo.mesh.local_index))
+ gh_s[j][j] = sl_start[j]
+ gh_e[j][j] = sl_end[j]
+
+ start, end = get_ghosts_indices(topo)
+ tab = np.zeros((topo.mesh.resolution), dtype=np.int16)
+ tab[topo.mesh.compute_index] = 1
+ for d in xrange(topo.domain.dimension):
+ tab[start[d]] = 1
+ tab[end[d]] = 1
+ corners = np.where(tab == 0)
+
+ corners = [list(topo.mesh.local_index), ] * (2 ** (topo.domain.dimension))
+
+ dimension = topo.domain.dimension
+ corners_size = 2 ** dimension
+ corners = [None, ] * corners_size
+ val = npw.int_zeros(corners_size)
+ if dimension == 1:
+ return [], 0.
+ elif dimension == 2:
+ corners[0] = [sl_start[0], sl_start[1]]
+ corners[1] = [sl_start[0], sl_end[1]]
+ corners[2] = [sl_end[0], sl_start[1]]
+ corners[3] = [sl_end[0], sl_end[1]]
+ val[0] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] - 1, topo.proc_coords[1] - 1])
+ val[1] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] - 1, topo.proc_coords[1] + 1])
+ val[2] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] + 1, topo.proc_coords[1] - 1])
+ val[3] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] + 1, topo.proc_coords[1] + 1])
+ elif dimension == 3:
+ corners[0] = [sl_start[0], sl_start[1], sl_start[2]]
+ corners[1] = [sl_start[0], sl_start[1], sl_end[2]]
+ corners[2] = [sl_start[0], sl_end[1], sl_start[2]]
+ corners[3] = [sl_start[0], sl_end[1], sl_end[2]]
+ corners[4] = [sl_end[0], sl_start[1], sl_start[2]]
+ corners[5] = [sl_end[0], sl_start[1], sl_end[2]]
+ corners[6] = [sl_end[0], sl_end[1], sl_start[2]]
+ corners[7] = [sl_end[0], sl_end[1], sl_end[2]]
+ val[0] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] - 1,
+ topo.proc_coords[1] - 1,
+ topo.proc_coords[2] - 1])
+ val[1] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] - 1,
+ topo.proc_coords[1] - 1,
+ topo.proc_coords[2] + 1])
+ val[2] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] - 1,
+ topo.proc_coords[1] + 1,
+ topo.proc_coords[2] - 1])
+ val[3] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] - 1,
+ topo.proc_coords[1] + 1,
+ topo.proc_coords[2] + 1])
+ val[4] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] + 1,
+ topo.proc_coords[1] - 1,
+ topo.proc_coords[2] - 1])
+ val[5] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] + 1,
+ topo.proc_coords[1] - 1,
+ topo.proc_coords[2] + 1])
+ val[6] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] + 1,
+ topo.proc_coords[1] + 1,
+ topo.proc_coords[2] - 1])
+ val[7] = topo.comm.Get_cart_rank(
+ [topo.proc_coords[0] + 1,
+ topo.proc_coords[1] + 1,
+ topo.proc_coords[2] + 1])
+
+# print "youou ", corners
+ return corners, val
+
+
+def run_synchro(ghosts, cutdir=None, full=False):
+ """Build domain, fields and topology
+ for a given ghost layer size and
+ distributed directions.
+ Then call synchronization and check.
+ """
+ dimension = len(ghosts)
+ dom = Box(length=[1., ] * dimension)
+ f = Field(dom, is_vector=True, name='f')
+ discr = Discretization([33, ] * dimension, ghosts=ghosts)
+ topo = dom.create_topology(discr, cutdir=cutdir)
+ df = f.discretize(topo)
+ # initialize + 0 in ghost layer
+ nbc = f.nb_components
+ for i in xrange(nbc):
+ df[i][...] = main_rank
+ #df[i][topo.mesh.compute_index] = topo.rank
+
+ for i in xrange(df.nb_components):
+ assert np.allclose(df[i], main_rank)
+
+ if full:
+ sync = UpdateGhostsFull(topo, nbc)
+
+ else:
+ sync = UpdateGhosts(topo, nbc)
+
+ start, end = get_ghosts_indices(topo)
+ corners, val = get_corners_indices(topo)
+
+ sync.apply(df.data)
+ nghb = topo.neighbours_tmp
+ for i in xrange(df.nb_components):
+ assert np.allclose(df[i][topo.mesh.compute_index], main_rank)
+ for d in xrange(topo.domain.dimension):
+ assert np.allclose(df[i][start[d]], nghb[d][0])
+ assert np.allclose(df[i][end[d]], nghb[d][1])
+ if full:
+ for d in xrange(len(corners)):
+ assert np.allclose(df[i][corners[d]], val[d])
+
+
+def test_1_1_simple():
+ """ 1D domain, 1D topo, simple update
+ """
+ run_synchro([1, ])
+
+
+def test_2_1_simple():
+ """ 2D domain, 1D topo, simple update
+ """
+ run_synchro([1, 1], [True, False])
+
+
+def test_2_2_simple():
+ """ 2D domain, 2D topo, simple update
+ """
+ run_synchro([1, 1])
+
+
+def test_3_1_simple():
+ """ 3D domain, 1D topo, simple update
+ """
+ run_synchro([1, 1, 1], [True, False, False])
+
+
+def test_3_2_simple():
+ """ 3D domain, 1D topo, simple update
+ """
+ run_synchro([1, 1, 1], [True, False, True])
+
+
+def test_3_3_simple():
+ """ 3D domain, 1D topo, simple update
+ """
+ run_synchro([1, 1, 1])
+
+
+def test_3_3_bis():
+ """ 3D domain, 3D topo, different ghost size in each dir
+ """
+ run_synchro([1, 3, 2])
+
+
+def test_1_1_full():
+ """ 1D domain, 1D topo, corners update
+ """
+ run_synchro([1, ], full=True)
+
+
+def test_2_1_full():
+ """ 2D domain, 1D topo, corners update
+ """
+ run_synchro([1, 1], [True, False], full=True)
+
+
+def test_2_2_full():
+ """ 2D domain, 2D topo, corners update
+ """
+ run_synchro([1, 1], full=True)
+
+
+def test_3_1_full():
+ """ 3D domain, 1D topo, corners update
+ """
+ run_synchro([1, 1, 1], [True, False, False], full=True)
+
+
+def test_3_2_full():
+ """ 3D domain, 2D topo, corners update
+ """
+ run_synchro([1, 1, 1], [True, False, True], full=True)
+
+
+def test_3_3_full():
+ """ 3D domain, 3D topo, corners update
+ """
+ run_synchro([1, 1, 1], full=True)
+
+def test_3_2_bis_full():
+ """ 3D domain, 2D topo, corners update, different ghost size in each dir
+ """
+ run_synchro([1, 3, 2], [True, False, True], full=True)
diff --git a/hysop/numerics/update_ghosts.py b/hysop/old/numerics.old/update_ghosts.py
similarity index 59%
rename from hysop/numerics/update_ghosts.py
rename to hysop/old/numerics.old/update_ghosts.py
index 7e6df40c2baca2ad51dc5c7da0d24a994ce42148..3189002b68c20364e988bfd09f3809fd46368028 100644
--- a/hysop/numerics/update_ghosts.py
+++ b/hysop/old/numerics.old/update_ghosts.py
@@ -21,8 +21,8 @@ Usage :
up([field1, field2])
"""
-from hysop.constants import debug, PERIODIC, HYSOP_MPI_REAL
-import hysop.tools.numpywrappers as npw
+from hysop.constants import debug, PERIODIC, hysop.core.mpi_REAL
+from hysop.tools.numpywrappers import npw
import numpy as np
@@ -35,7 +35,7 @@ class UpdateGhosts(object):
"""
Parameters
----------
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
data and mpi process distribution
nb_elements : int
number of arrays that will be update
@@ -60,10 +60,12 @@ class UpdateGhosts(object):
self._g_tonext = []
# Indices of points to be sent to previous neighbour.
self._g_toprevious = []
- # Buffers that contains ghosts points to be sent (list, one per dir)
- self._sendbuffer = []
- # Buffers for reception (list, one per dir)
- self._recvbuffer = []
+ # Buffers that contains ghosts points to be sent
+ self._sendbuffer = None
+ # List of sizes of buffer to be sent/recv in each direction
+ self._buffer_size = []
+ # Buffers for reception
+ self._recvbuffer = None
# domain dimension
self._dim = self.topology.domain.dimension
@@ -75,30 +77,47 @@ class UpdateGhosts(object):
self._memoryblocksize = np.prod(self.memshape)
# Number of numpy arrays that will be updated
self.nb_elements = nb_elements
+
+ # list of functions, _apply[d] corresponds to the synchronization
+ # used in direction d, either
+ # - local (non-distributed) --> apply BC
+ # - distributed --> mpi comm
+ self._apply = [None, ] * self._dim
+ # distributed (mpi) directions
+ self.exchange_dir = []
+ if self.topology.size > 1:
+ self.exchange_dir = [d for d in xrange(self._dim)
+ if self.topology.cutdir[d]]
+ for d in self.exchange_dir:
+ self._apply[d] = self._apply_in_dir
+ for d in self.topology.bc_dirs:
+ self._apply[d] = self._apply_bc_in_dir
+
if self.topology.size > 1: # else no need to set buffers ...
# Size computation below assumes that what we send in one
# dir has the same size as what we receive from process in the
# same dir ...
- exchange_dir = [d for d in xrange(self._dim)
- if self.topology.cutdir[d]]
# A temporary array used to calculate slices sizes
temp = np.zeros(self.memshape, dtype=np.int8)
- for d in exchange_dir:
+ for d in self.exchange_dir:
buffsize = 0
buffsize += temp[self._g_tonext[d]].size * self.nb_elements
- self._sendbuffer.append(npw.zeros((buffsize)))
- self._recvbuffer.append(npw.zeros((buffsize)))
+ self._buffer_size.append(buffsize)
+ self._recvbuffer = npw.zeros(max(self._buffer_size))
+ self._sendbuffer = npw.zeros(max(self._buffer_size))
def _setup_slices(self):
"""Compute slices used to describe what to send
and receive in ghosts points.
-
"""
+ # all points
defslice = [slice(None, None, None)] * self._dim
+ # no points
nogh_slice = [slice(0)] * self._dim
for d in xrange(self._dim):
if self.ghosts[d] > 0:
+ # get ghost points indices in current direction ...
self._g_fromprevious.append(list(defslice))
self._g_fromprevious[d][d] = slice(self.ghosts[d])
self._g_fromnext.append(list(defslice))
@@ -111,6 +130,8 @@ class UpdateGhosts(object):
-self.ghosts[d])
other_dim = self._other_dim(d)
+ # ... and only compute points indices in other directions
+ # i.e. 'corner' points are not taken into account.
for d2 in other_dim:
self._g_fromprevious[d][d2] = slice(self.ghosts[d2],
-self.ghosts[d2])
@@ -121,12 +142,29 @@ class UpdateGhosts(object):
self._g_tonext[d][d2] = slice(self.ghosts[d2],
-self.ghosts[d2])
else:
+ # empty lists of indices
self._g_fromprevious.append(list(nogh_slice))
self._g_fromnext.append(list(nogh_slice))
self._g_toprevious.append(list(nogh_slice))
self._g_tonext.append(list(nogh_slice))
+ self._g_fromprevious = self._immutable(self._g_fromprevious)
+ self._immutable(self._g_fromnext)
+ self._immutable(self._g_toprevious)
+ self._immutable(self._g_tonext)
+
+ @staticmethod
+ def _immutable(var):
+ """Convert list of lists to immutable tuples
+ """
+ assert isinstance(var, list)
+ for i in xrange(len(var)):
+ var[i] = tuple(var[i])
+ return tuple(var)
+
def _other_dim(self, d):
+ """utility to get all directions except d
+ """
return [x for x in xrange(self._dim) if x != d]
def __call__(self, variables):
@@ -145,43 +183,71 @@ class UpdateGhosts(object):
assert (self.topology.domain.boundaries == PERIODIC).all(),\
'Only implemented for periodic boundary conditions.'
assert isinstance(variables, list)
- dirs = [d for d in xrange(self._dim)
- if self.topology.shape[d] == 1]
+ dirs = self.topology.bc_dirs
for d in dirs:
- self._apply_bc_in_dir(variables, d)
+ self._apply_bc_in_dir(variables, d, 0)
- def _apply_bc_in_dir(self, variables, d):
+ def _apply_bc_in_dir(self, variables, d, i):
"""Apply periodic boundary condition in direction d."""
+ assert (self.topology.domain.boundaries == PERIODIC).all(),\
+ 'Only implemented for periodic boundary conditions.'
for v in variables:
assert v.shape == self.memshape
v[self._g_fromprevious[d]] = v[self._g_tonext[d]]
v[self._g_fromnext[d]] = v[self._g_toprevious[d]]
+ return i
+ # @debug
+ # def apply(self, variables):
+ # """Update ghosts points values:
+ # mpi communications and boundary conditions.
+
+ # Parameters
+ # ----------
+ # variables : list of numpy arrays
+ # arrays that must be synchronized.
+ # """
+ # assert isinstance(variables, list)
+ # # Apply boundary conditions for distributed directions ...
+ # i = 0
+ # for d in self.exchange_dir:
+ # self._apply_in_dir(variables, d, i)
+ # # update position in buffers list
+ # i += 1
+ # # ... and for non-distributed directions.
+ # self.apply_bc(variables)
@debug
def apply(self, variables):
- """
- Compute ghosts values from mpi communications and boundary conditions.
+ """Update ghosts points values:
+ mpi communications and boundary conditions.
+
+ Parameters
+ ----------
+ variables : list of numpy arrays
+ arrays that must be synchronized.
"""
assert isinstance(variables, list)
- exchange_dir = []
- if self.topology.size > 1:
- exchange_dir = [d for d in xrange(self._dim)
- if self.topology.cutdir[d]]
+ # Apply boundary conditions all directions ...
i = 0
- for d in exchange_dir:
- self._apply_in_dir(variables, d, i)
- # update index in neighbours list
- i += 1
- # End of loop through send/recv directions.
- # Apply boundary conditions for non-distributed directions
- self.apply_bc(variables)
+ for d in xrange(self._dim):
+ i = self._apply[d](variables, d, i)
def _apply_in_dir(self, variables, d, i):
"""Communicate ghosts values in direction d for neighbour
- in direction i of the topology"""
+ in direction i of the topology
+
+ Parameters
+ ----------
+ variables : list of numpy arrays
+ arrays to be synchronized
+ d : int
+ direction of synchronization
+ i : int
+ counter, current position in buffers.
+ """
comm = self.topology.comm
rank = self.topology.rank
- neighbours = self.topology.neighbours
+ neighbours = self.topology.neighbours_tmp[d]
# 1 - Fill in buffers
# Loop through all variables that are distributed
pos = 0
@@ -189,15 +255,18 @@ class UpdateGhosts(object):
for v in variables:
assert v.shape == self.memshape
nextpos += v[self._g_tonext[d]].size
- self._sendbuffer[i][pos:nextpos] = v[self._g_tonext[d]].flat
+ self._sendbuffer[pos:nextpos] = v[self._g_tonext[d]].flat
pos = nextpos
# 2 - Send to next receive from previous
- dest_rk = neighbours[1, i]
- from_rk = neighbours[0, i]
- comm.Sendrecv([self._sendbuffer[i], HYSOP_MPI_REAL],
+ dest_rk = neighbours[1]
+ from_rk = neighbours[0]
+ sendbuffer = self._sendbuffer[:self._buffer_size[i]]
+ recvbuffer = self._recvbuffer[:self._buffer_size[i]]
+
+ comm.Sendrecv([sendbuffer, hysop.core.mpi_REAL],
dest=dest_rk, sendtag=rank,
- recvbuf=self._recvbuffer[i],
+ recvbuf=recvbuffer,
source=from_rk, recvtag=from_rk)
# 3 - fill variables with recvbuffer and update sendbuffer
@@ -207,17 +276,17 @@ class UpdateGhosts(object):
for v in variables:
nextpos += v[self._g_fromprevious[d]].size
v[self._g_fromprevious[d]].flat = \
- self._recvbuffer[i][pos:nextpos]
- self._sendbuffer[i][pos:nextpos] = \
+ self._recvbuffer[pos:nextpos]
+ self._sendbuffer[pos:nextpos] = \
v[self._g_toprevious[d]].flat
pos = nextpos
# 4 -Send to previous and receive from next
- dest_rk = neighbours[0, i]
- from_rk = neighbours[1, i]
- comm.Sendrecv([self._sendbuffer[i], HYSOP_MPI_REAL],
+ dest_rk = neighbours[0]
+ from_rk = neighbours[1]
+ comm.Sendrecv([sendbuffer, hysop.core.mpi_REAL],
dest=dest_rk, sendtag=rank,
- recvbuf=self._recvbuffer[i],
+ recvbuf=recvbuffer,
source=from_rk, recvtag=from_rk)
# 5 - fill variables with recvbuffer
pos = 0
@@ -225,9 +294,12 @@ class UpdateGhosts(object):
for v in variables:
nextpos += v[self._g_fromprevious[d]].size
v[self._g_fromnext[d]].flat = \
- self._recvbuffer[i][pos:nextpos]
+ self._recvbuffer[pos:nextpos]
pos = nextpos
+ # update position in buffers list
+ return i + 1
+
class UpdateGhostsFull(UpdateGhosts):
"""Ghost points synchronization for a list of numpy arrays
@@ -250,27 +322,22 @@ class UpdateGhostsFull(UpdateGhosts):
# if d == 0:
return [x for x in xrange(self._dim) if x > d]
- @debug
- def apply(self, variables):
- """Apply either mpi communications
- or local boundary conditions to fill ghosts.
- Loop over directions and switch among local BC or mpi comm.
- """
- assert isinstance(variables, list)
- exchange_dir = []
- if self.topology.size > 1:
- exchange_dir = [d for d in xrange(self._dim)
- if self.topology.cutdir[d]]
- local_bc_dir = [d for d in xrange(self._dim)
- if self.topology.shape[d] == 1]
- assert len(exchange_dir) + len(local_bc_dir) == self._dim
-
- i = 0
- for d in xrange(self._dim):
- if d in local_bc_dir:
- self._apply_bc_in_dir(variables, d)
- elif d in exchange_dir:
- self._apply_in_dir(variables, d, i)
- # update index in neighbours list
- i += 1
- # End of loop through send/recv directions.
+ # @debug
+ # def apply(self, variables):
+ # """Apply either mpi communications
+ # or local boundary conditions to fill ghosts.
+ # Loop over directions and switch among local BC or mpi comm.
+ # """
+ # assert isinstance(variables, list)
+ # local_bc_dir = self.topology.bc_dirs
+ # assert len(self.exchange_dir) + len(local_bc_dir) == self._dim
+
+ # i = 0
+ # for d in xrange(self._dim):
+ # if d in local_bc_dir:
+ # self._apply_bc_in_dir(variables, d)
+ # elif d in self.exchange_dir:
+ # self._apply_in_dir(variables, d, i)
+ # # update position in buffers list
+ # i += 1
+ # # End of loop through send/recv directions.
diff --git a/hysop/numerics/utils.py b/hysop/old/numerics.old/utils.py
similarity index 94%
rename from hysop/numerics/utils.py
rename to hysop/old/numerics.old/utils.py
index 34cd0b8eaff68a6beb79d76b8dbf64fd21ba75dd..727a05348327ee775a1f3dfce57d6fc8099a8e3e 100644
--- a/hysop/numerics/utils.py
+++ b/hysop/old/numerics.old/utils.py
@@ -1,5 +1,11 @@
+"""Tools (static methods) to manage slices or arrays.
+
+.. currentmodule hysop.numerics.utils
+
+
+"""
from hysop.constants import XDIR, YDIR, ZDIR
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
diff --git a/hysop/old/operator.old/__init__.py b/hysop/old/operator.old/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5fd789f846149728d69238261e3c35fc637070f3
--- /dev/null
+++ b/hysop/old/operator.old/__init__.py
@@ -0,0 +1,3 @@
+"""Package for operators (discrete and continuous) description
+
+"""
diff --git a/hysop/operator/absorption_BC.py b/hysop/old/operator.old/absorption_BC.py
similarity index 95%
rename from hysop/operator/absorption_BC.py
rename to hysop/old/operator.old/absorption_BC.py
index 4d27323be8ef208f5144740406e2781e97919ff1..f86c2013a5492117737c04027454afbce191bf3e 100755
--- a/hysop/operator/absorption_BC.py
+++ b/hysop/old/operator.old/absorption_BC.py
@@ -62,8 +62,8 @@ class AbsorptionBC(Computational):
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
self.discrete_op =\
- AbsorptionBC_D(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
+ AbsorptionBC_D(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
req_flowrate=self.req_flowrate,
x_coords_absorp=self.x_coords_absorp,
cb=self.cb, rwork=rwork, iwork=iwork)
diff --git a/hysop/old/operator.old/absorption_bc.py b/hysop/old/operator.old/absorption_bc.py
new file mode 100755
index 0000000000000000000000000000000000000000..4d196afe3f736314081048aaf634220b38ee6b83
--- /dev/null
+++ b/hysop/old/operator.old/absorption_bc.py
@@ -0,0 +1,126 @@
+"""Operator to kill the vorticity at the outlet boundary
+(i.e. removal of the periodic BC in the flow direction
+by vorticity absorption in order to set the far field
+velocity to u_inf at the inlet)
+
+See :ref:`absorption_bc`.
+
+"""
+from hysop.constants import debug
+from hysop.operator.discrete.absorption_bc import AbsorptionBC as Dab
+from hysop.operator.computational import Computational
+from hysop.operator.continuous import opsetup
+from hysop.domain.subsets import SubBox
+import numpy as np
+
+
+class AbsorptionBC(Computational):
+ """
+ The periodic boundary condition is modified at the outlet
+ in the flow direction in order to discard
+ in the dowstream region the eddies coming
+ periodically from the outlet.
+ The far field velocity is set to u_inf at the inlet.
+ """
+
+ @debug
+ def __init__(self, velocity, vorticity, req_flowrate,
+ x_range, filter_func=None, **kwds):
+ """
+ Parameters
+ ----------
+ velocity, vorticity : :class:`~hysop.fields.continuous.Field`
+ req_flowrate : double
+ required value for the flow rate
+ (used to set the u_inf velocity value at the inlet)
+ x_range : list or numpy array
+ x-coordinates delimitating the absorption domain
+ like [x_beginning, x_end]
+ filter_func: list of python functions, optional
+ functions used to compute the filter and its differential.
+ **kwds : extra parameters for base class
+
+
+ Notes
+ -----
+ * if set, filter_func[0] and filter_func[1] must be python function
+ returning a numpy array. For example to apply a sine inside
+ the absorption area use :
+
+ .. code::
+
+ def func(x):
+ return np.sin(x)
+
+ """
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ super(AbsorptionBC, self).__init__(variables=[velocity,
+ vorticity], **kwds)
+ # velocity variable
+ self.velocity = velocity
+ # vorticity variable
+ self.vorticity = vorticity
+
+ self.input = [self.velocity, self.vorticity]
+ self.output = [self.vorticity]
+ # Expected value for the flow rate through input surface
+ self.req_flowrate = req_flowrate
+ # x-coordinates delimitating the absorption band at the outlet
+ self._filter_func = filter_func
+ self.absorption_box = self.build_absorption_box(x_range)
+ # on_proc[topo] = True if this operator has to work on the
+ # current process, i.e. if absorption_box has points
+ # on the current process.
+ self.on_proc = {}
+
+ def discretize(self):
+ super(AbsorptionBC, self)._standard_discretize()
+ assert self._single_topo, 'Multi-resolution case is not allowed.'
+ topo = self.discrete_fields[self.vorticity].topology
+ self.absorption_box.discretize(topo)
+ self.on_proc[topo] = self.absorption_box.on_proc[topo]
+
+ def build_absorption_box(self, x_range):
+ """Build a box to define the area where the absorption
+ filter will be applied
+
+ Parameters
+ ----------
+ x_range : list or numpy array
+ x right and left positions of the box.
+ """
+ # setup for the absorption filter definition
+ dom = self.vorticity.domain
+ borig = dom.origin.copy()
+ borig[0] = x_range[0]
+ blength = dom.length.copy()
+ blength[0] = x_range[1] - x_range[0]
+ return SubBox(parent=dom, origin=borig, length=blength)
+
+ def get_work_properties(self):
+ super(AbsorptionBC, self).get_work_properties()
+ wd = self.discrete_fields[self.vorticity]
+ subshape = self.absorption_box.mesh[wd.topology].resolution
+ subsize = np.prod(subshape)
+ return {'rwork': (subsize, ), 'iwork': None}
+
+ @debug
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ if not self._is_uptodate:
+ # if self.on_proc[self.discrete_fields[self.vorticity].topology]:
+ self.discrete_op =\
+ Dab(velocity=self.discrete_fields[self.velocity],
+ vorticity=self.discrete_fields[self.vorticity],
+ req_flowrate=self.req_flowrate,
+ absorption_box=self.absorption_box,
+ rwork=rwork, iwork=iwork,
+ filter_func=self._filter_func)
+
+ # Output setup
+ self._set_io('absorption_BC', (1, 2 + self.domain.dimension))
+ self.discrete_op.set_writer(self._writer)
+ self._is_uptodate = True
+
+ def wait(self):
+ print "TEMP WAIT FOR TEST"
diff --git a/hysop/operator/adapt_timestep.py b/hysop/old/operator.old/adapt_timestep.py
similarity index 89%
rename from hysop/operator/adapt_timestep.py
rename to hysop/old/operator.old/adapt_timestep.py
index 4d76f35165779c42f269fffe52181715c3c83ff6..0275e110331823c72da824da1ff5857a1a1ccdf8 100755
--- a/hysop/operator/adapt_timestep.py
+++ b/hysop/old/operator.old/adapt_timestep.py
@@ -5,12 +5,12 @@ See :ref:`adaptive_time_step` for details.
"""
from hysop.constants import debug
-from hysop.methods_keys import TimeIntegrator, SpaceDiscretisation
+from hysop.methods import TimeIntegrator, SpaceDiscretization
from hysop.operator.discrete.adapt_timestep import AdaptiveTimeStepD
from hysop.operator.continuous import opsetup
from hysop.operator.computational import Computational
import hysop.default_methods as default
-from hysop.mpi import main_comm, MPI
+from hysop.core.mpi import main_comm, MPI
from hysop.numerics.differential_operations import MaxDiagGradV, \
DiagAndStretch, StrainCriteria, StretchLike, StrainAndStretch
@@ -75,7 +75,7 @@ class AdaptiveTimeStep(Computational):
**kwds)
if self.method is None:
self.method = default.ADAPT_TIME_STEP
- assert SpaceDiscretisation in self.method.keys()
+ assert SpaceDiscretization in self.method.keys()
assert TimeIntegrator in self.method.keys()
# Definition of criterion for dt_advec computation
if criteria is None:
@@ -112,13 +112,13 @@ class AdaptiveTimeStep(Computational):
"""Create intercommunicators, if required (i.e. if there are several
tasks defined in the domain).
"""
- task_is_source = self._mpis.task_id == self.domain.current_task()
+ task_is_source = self.mpi_params.task_id == self.domain.current_task()
tasks_list = self.domain.tasks_list()
- others = (v for v in tasks_list if v != self._mpis.task_id)
+ others = (v for v in tasks_list if v != self.mpi_params.task_id)
if task_is_source:
remote_leader = set([tasks_list.index(i) for i in others])
else:
- remote_leader = set([tasks_list.index(self._mpis.task_id)])
+ remote_leader = set([tasks_list.index(self.mpi_params.task_id)])
for rk in remote_leader:
self._intercomms[rk] = self.domain.comm_task.Create_intercomm(
@@ -127,7 +127,7 @@ class AdaptiveTimeStep(Computational):
def get_work_properties(self):
super(AdaptiveTimeStep, self).get_work_properties()
diffop = None
- topo = self.discreteFields[self.velocity].topology
+ topo = self.discrete_fields[self.velocity].topology
if 'gradU' in self.criteria:
diffop = MaxDiagGradV
if 'stretch' in self.criteria:
@@ -144,15 +144,15 @@ class AdaptiveTimeStep(Computational):
return {'rwork': None, 'iwork': None}
def discretize(self):
- nb_ghosts = self.method[SpaceDiscretisation].ghosts_layer_size
+ nb_ghosts = self.method[SpaceDiscretization].ghosts_layer_size
super(AdaptiveTimeStep, self)._standard_discretize(nb_ghosts)
@debug
@opsetup
def setup(self, rwork=None, iwork=None):
self.discrete_op =\
- AdaptiveTimeStepD(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
+ AdaptiveTimeStepD(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
self.simulation, method=self.method,
time_range=self.time_range,
criteria=self.criteria,
@@ -166,8 +166,8 @@ class AdaptiveTimeStep(Computational):
self._is_uptodate = True
def wait(self):
- task_is_source = self._mpis.task_id == self.domain.current_task()
- rank = self._mpis.rank
+ task_is_source = self.mpi_params.task_id == self.domain.current_task()
+ rank = self.mpi_params.rank
dt = self.simulation.time_step
for rk in self._intercomms:
if task_is_source:
diff --git a/hysop/old/operator.old/advection.py b/hysop/old/operator.old/advection.py
new file mode 100644
index 0000000000000000000000000000000000000000..f0384bb271cfb41c4ebf5cd44bdb1cb0a8669e63
--- /dev/null
+++ b/hysop/old/operator.old/advection.py
@@ -0,0 +1,580 @@
+"""Advection of a field.
+
+See :ref:`advection` in user guide.
+"""
+from __future__ import print_function
+from abc import ABCMeta, abstractmethod
+from hysop.constants import debug, DirectionLabels, ZDIR
+from hysop import __SCALES_ENABLED__, Field, __GPU_ENABLED__
+from hysop.operator.computational import Computational
+from hysop.methods import TimeIntegrator, Interpolation,\
+ Remesh, Support, Splitting, MultiScale
+from hysop.numerics.remeshing import Remeshing, L2_1
+from hysop.operator.continuous import opsetup, opapply
+import hysop.default_methods as default
+from hysop.tools.parameters import Discretization
+from hysop.core.mpi.topology import Cartesian
+from hysop.tools.numpywrappers import npw
+from hysop.problem.simulation import O2, SplittingParameters
+from hysop.operator.discrete.particle_advection import ParticleAdvection
+import numpy as np
+if __GPU_ENABLED__:
+ from hysop.backend.device.opencl.gpu_particle_advection import GPUParticleAdvection
+ from hysop.backend.device.opencl.multi_gpu_particle_advection import MultiGPUParticleAdvection
+if __SCALES_ENABLED__:
+ from hysop.f2hysop import scales2py as scales
+
+
+class AdvectionBase(Computational):
+ """Abstract interface to advection operators
+ """
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, velocity, advected_fields=None,
+ discretization_fields=None, **kwds):
+ """
+ Parameters
+ ----------
+ velocity : :class:`hysop.field.continuous.Field`
+ the velocity field
+ advected_field: a list of :class:`hysop.field.continuous.Field`,
+ optional
+ fields to be advected
+ discretization_fields : :class:`hysop.core.mpi.topology.Cartesian`
+ or :class:`tools.parameters.Discretization`
+ Defined the data/mpi distribution for advected_fields.
+ Default = same as velocity
+ kwds : base class arguments.
+
+ Notes
+ -----
+ * one single discretization for all advected fields
+ * velocity discretization may be different
+ * to limit advection to one or two directions, set
+ directions=[0, 2] (advection in x and z dirs).
+
+ """
+ # --- check inputs for fields (advected and velocity) ---
+ msg = 'discretization argument is required in Advection.'
+ assert 'discretization' in kwds, msg
+ msg = 'Wrong input for advection operator:'
+ msg += ' "variables" attribute is not allowed. Check manual.'
+ assert 'variables' not in kwds, msg
+ # advected_fields :
+ # == field or [field1, field2, ...] ==> same discretization for all,
+ # equal to velocity discretization if discretization_fields is None
+ self.advected_fields = []
+ if advected_fields is not None:
+ if not isinstance(advected_fields, list):
+ assert isinstance(advected_fields, Field)
+ advected_fields = [advected_fields]
+ self.advected_fields = advected_fields
+ # velocity field
+ if discretization_fields is not None:
+ dfields = discretization_fields
+ else:
+ dfields = kwds['discretization']
+ variables = {velocity: kwds['discretization']}
+ for field in advected_fields:
+ variables[field] = dfields
+ kwds.pop('discretization')
+ super(AdvectionBase, self).__init__(variables=variables, **kwds)
+ # velocity field
+ self.velocity = velocity
+ assert velocity.nb_components == self.domain.dimension
+
+ # --- Set default method, if required ---
+ if self.method is None:
+ self.method = default.ADVECTION
+
+ # --- Set name ---
+ vars_str = "_("
+ for vv in self.advected_fields:
+ vars_str += vv.name + ","
+ self.name += vars_str[0:-1] + ')'
+
+ self.config = {}
+ self.input = [var for var in self.variables]
+ self.output = [var for var in self.variables
+ if var is not self.velocity]
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
+
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ if self._is_uptodate:
+ return
+ # select discretization of the advected fields
+ advected_discrete_fields = [self.discrete_fields[v]
+ for v in self.variables
+ if v is not self.velocity]
+ toporef = advected_discrete_fields[0].topology
+ msg = 'All advected fields must have the same topology.'
+ for f in advected_discrete_fields:
+ assert f.topology == toporef, msg
+
+ # call specific setup (see derived class)
+ self._setup(advected_discrete_fields, rwork, iwork)
+ self._is_uptodate = True
+
+ def advected_fields_topology(self):
+ """Returns the topology used for advected fields
+ """
+ msg = 'Operator must be discretized'
+ assert self._is_discretized, msg
+ return self.discrete_fields[self.advected_fields[0]].topology
+
+ def velocity_topology(self):
+ """Returns the topology used for velocity
+ """
+ msg = 'Operator must be discretized'
+ assert self._is_discretized, msg
+ return self.discrete_fields[self.velocity].topology
+
+ @abstractmethod
+ def _setup(self, advected_discrete_fields, rwork=None, iwork=None):
+ """Setup specific to advection implementation (see derived class)
+ """
+
+
+class Advection(AdvectionBase):
+ """Python or GPU advection
+ """
+ @debug
+ def __init__(self, directions=None, **kwds):
+ """
+ Parameters
+ ----------
+ directions : list of int, optional
+ direction(s) in which advection must be performed. Default = all.
+ kwds : base class arguments.
+
+ """
+ super(Advection, self).__init__(**kwds)
+ self.extra_args = {} ### TO BE REVIEWED ###
+ if directions is None:
+ directions = [i for i in xrange(self.domain.dimension)]
+ assert isinstance(directions, list)
+ self.directions = directions
+ assert TimeIntegrator in self.method.keys()
+ assert Interpolation in self.method.keys()
+ assert Remesh in self.method.keys()
+ if Splitting not in self.method.keys():
+ self.method[Splitting] = O2
+ self.discrete_op = [None] * self.domain.dimension
+
+ # Fields on particles
+ self.particle_fields = None
+
+ # Positions of the particles
+ self.particle_positions = None
+
+ # number of components of the rhs (time integration)
+ self._rhs_size = 1
+
+ # check if advection is done on gpu
+ if Support in self.method:
+ self._gpu_advection = self.method[Support].find('gpu') >= 0
+ else:
+ self._gpu_advection = False
+ self.splitting = None
+ self._old_dir = 0
+
+ def discretize(self):
+ """Discretization (create topologies and discretize fields)
+ """
+ if self._is_discretized:
+ return
+ cutdir = [False] * self.domain.dimension
+ cutdir[-1] = True
+ # call standard discretization (from computational base class)
+ self._standard_discretize(cutdir=cutdir)
+ # check if velocity and fields are defined with the same resolution
+ if self._single_topo:
+ self.method[MultiScale] = None
+ else:
+ # set a default value for interpolation method
+ if MultiScale not in self.method or\
+ self.method[MultiScale] is None:
+ self.method[MultiScale] = L2_1
+ mscale = self.method[MultiScale]
+ min_ghosts = mscale.ghosts_layer_size
+ # get ghost layer size used for velocity field
+ ghosts_v = self.variables[self.velocity].ghosts()
+ # and check if it fits with interpolation method
+ msg = 'Ghost layer required for velocity. Size min = '
+ msg += str(min_ghosts) + " (" + str(ghosts_v) + " given)"
+ assert (ghosts_v >= min_ghosts).all(), msg
+ self._is_discretized = True
+
+ def get_work_properties(self):
+ assert self._is_discretized
+ # Shape of reference comes from fields, not from velocity
+ advected_discrete_fields = [self.discrete_fields[v]
+ for v in self.variables
+ if v is not self.velocity]
+ topo = advected_discrete_fields[0].topology
+ # Find number and shape of required work arrays
+ if not self._gpu_advection:
+ # -- pure python advection --
+ # work array shape depends on the time integrator
+ # interpolation scheme and remeshing scheme
+ ti_work = self.method[TimeIntegrator].get_work_properties(
+ self._rhs_size, topo)
+ ti_rwork_length = len(ti_work['rwork'])
+ iw_prop = self.method[Interpolation].get_work_properties(topo)
+ rw_prop = Remeshing.get_work_properties(topo)
+ interp_iwork_length = len(iw_prop['iwork'])
+ interp_rwork_length = len(iw_prop['rwork'])
+ remesh_iwork_length = len(rw_prop['iwork'])
+ remesh_rwork_length = len(rw_prop['rwork'])
+ iwork_length = max(interp_iwork_length, remesh_iwork_length)
+ rwork_length = max(ti_rwork_length + interp_rwork_length,
+ remesh_rwork_length)
+
+ else:
+ # -- GPU advection --
+ # no work array
+ iwork_length, rwork_length = 0, 0
+
+ # buffers for fields on particles
+ rwork_length += np.sum([f.nb_components for f in self.advected_fields])
+ if not self._gpu_advection or \
+ self.method[Support].find('gpu_2k') >= 0:
+ rwork_length += 1 # work array for positions
+ memsize = np.prod(topo.mesh.resolution)
+ return {'rwork': [(memsize,)] * rwork_length,
+ 'iwork': [(memsize,)] * iwork_length}
+
+ def _setup(self, advected_discrete_fields, rwork=None, iwork=None):
+ for i in self.directions:
+ ref_shape = advected_discrete_fields[0].topology.shape[i]
+ if self._gpu_advection:
+ if ref_shape == 1:
+ DA = GPUParticleAdvection
+ else:
+ DA = MultiGPUParticleAdvection
+ else:
+ DA = ParticleAdvection
+
+ self.discrete_op[i] = DA(
+ velocity=self.discrete_fields[self.velocity],
+ fields_on_grid=advected_discrete_fields,
+ direction=i, method=self.method,
+ rwork=rwork, iwork=iwork)
+ #**self.extra_args)
+
+ if i == 0:
+ # work arrays can be shared between directions.
+ rwork = self.discrete_op[i]._rwork
+ iwork = self.discrete_op[i]._iwork
+
+ # set splitting parameters (depends on method)
+ self.splitting = self.method[Splitting](self.domain.dimension)
+ assert isinstance(self.splitting, SplittingParameters)
+
+ # configure gpu
+ if self._gpu_advection:
+ self._configure_gpu()
+
+ def _configure_gpu(self):
+ """Setup for gpu related things (Memory ...)
+ """
+ splitting_nbSteps = len(self.splitting)
+ for d in xrange(self.domain.dimension):
+ dOp = self.discrete_op[d]
+ assert len(dOp.exec_list) == splitting_nbSteps, \
+ "Discrete operator execution " + \
+ "list and splitting steps sizes must be equal " + \
+ str(len(dOp.exec_list)) + " != " + \
+ str(splitting_nbSteps)
+ s = ""
+ device_id = self.discrete_op[0].cl_env._device_id
+ gpu_comm = self.discrete_op[0].cl_env.gpu_comm
+ gpu_rank = gpu_comm.Get_rank()
+ if gpu_rank == 0:
+ s += "=== OpenCL buffers allocated"
+ s += " on Device:{0} ===\n".format(device_id)
+ s += "Global memory used:\n"
+ total_gmem = 0
+ for d in xrange(self.domain.dimension):
+ g_mem_d = 0
+ # allocate all variables in advec_dir
+ for df in self.discrete_op[d].variables:
+ if not df.gpu_allocated:
+ df.allocate()
+ g_mem_df = gpu_comm.allreduce(df.mem_size)
+ g_mem_d += g_mem_df
+ if gpu_rank == 0:
+ s += " Advection" + DirectionLabels[d] + ": {0:9d}".format(g_mem_d)
+ s += "Bytes ({0:5d} MB)\n".format(g_mem_d / (1024 ** 2))
+ total_gmem += g_mem_d
+ if gpu_rank == 0:
+ s += " Total : {0:9d}".format(total_gmem)
+ s += "Bytes ({0:5d} MB)\n".format(total_gmem / (1024 ** 2))
+ s += "Local memory used:\n"
+ total_lmem = 0
+ for d in xrange(self.domain.dimension):
+ l_mem_d = gpu_comm.allreduce(
+ self.discrete_op[d].size_local_alloc)
+ if gpu_rank == 0:
+ s += " Advection" + DirectionLabels[d] + ": {0:9d}".format(l_mem_d)
+ s += "Bytes ({0:5d} MB)\n".format(l_mem_d / (1024 ** 2))
+ total_lmem += l_mem_d
+ if gpu_rank == 0:
+ s += " Total : {0:9d}".format(total_lmem) + "Bytes"
+ print(s)
+
+ @debug
+ @opapply
+ def apply(self, simulation=None):
+ """Redefinition of apply for advection --> dimensional splitting.
+
+ Parameters
+ ----------
+ simulation : `:class::~hysop.problem.simulation.Simulation`
+
+ """
+ assert simulation is not None
+ for split_id, split in enumerate(self.splitting()):
+ simulation.set_split(split_id, split)
+ self.discrete_op[simulation.current_dir].apply(simulation)
+ #, split[1], split_id, self._old_dir)
+ simulation.next_split()
+
+ @debug
+ def finalize(self):
+ """Memory cleaning.
+ """
+ for i in self.directions:
+ self.discrete_op[i].finalize()
+
+ def get_profiling_info(self):
+ if self._is_uptodate:
+ for d in self.directions:
+ self.profiler += self.discrete_op[d].profiler
+
+ def __str__(self):
+ """
+ Common printings for operators
+ """
+ short_name = str(self.__class__).rpartition('.')[-1][0:-2]
+ for i in self.directions:
+ if self.discrete_op[i] is not None:
+ s = str(self.discrete_op[i])
+ else:
+ s = short_name + " operator. Not discretised."
+ return s + "\n"
+
+
+class ScalesAdvection(AdvectionBase):
+ """Advection based on fortran (scales) interface
+ """
+ @debug
+ def __init__(self, cutdir=None, **kwds):
+ """
+ Parameters
+ ----------
+ cutdir : list of bool
+ cutdir[d] = True to distribute data in direction d.
+
+ kwds : base class arguments.
+
+ Notes
+ -----
+ * In scales cutdir[0] must be False, i.e. data are not
+ distributed in the first dir, which corresponds to contiguous
+ memory layout (fortran).
+ * Scales assumes that all subdomains have the same
+ local resolution.
+ * No ghosts points allowed in scales (at the moment)
+
+ """
+ super(ScalesAdvection, self).__init__(**kwds)
+ assert Remesh in self.method.keys()
+ msg = 'Scales is not available for your configuration.'
+ assert __SCALES_ENABLED__, msg
+ msg = 'Scales Advection is only implemented in 3D.'
+ assert self.domain.dimension == 3, msg
+ # Default splitting = Strang
+ if Splitting not in self.method.keys():
+ self.method[Splitting] = 'strang'
+ if cutdir is None:
+ cutdir = [False, ] * self.domain.dimension
+ cutdir[-1] = True
+ self.cutdir = cutdir
+
+ def scales_parameters(self):
+ """
+ Return the name of the particular method used in scales
+ and the type of splitting.
+ """
+ order = None
+ for o in ['p_O2', 'p_O4', 'p_L2',
+ 'p_M4', 'p_M6', 'p_M8',
+ 'p_44', 'p_64', 'p_66', 'p_84']:
+ if self.method[Remesh].find(o) >= 0:
+ order = o
+ if order is None:
+ print('Unknown advection method, turn to default (p_M6).')
+ order = 'p_M6'
+
+ # - Extract splitting form self.method (default strang) -
+ splitting = 'strang'
+ for s in ['classic', 'strang', 'particle']:
+ if self.method[Splitting].find(s) >= 0:
+ splitting = s
+
+ return order, splitting
+
+ def discretize(self):
+ """
+ Discretization (create topologies and discretize fields)
+ Available methods :
+ - 'scales' : SCALES fortran routines (3d only, list of vector
+ and/or scalar)
+ - 'gpu' : OpenCL kernels (2d and 3d, single field, scalar or vector)
+ - other : Pure python (2d and 3d, list of vector and/or scalar)
+ """
+ if self._is_discretized:
+ return
+ # Check if topos need to be created
+ build_topos = self._check_variables()
+ order, splitting = self.scales_parameters()
+
+ # Scales, single resolution
+ if self._single_topo:
+ if build_topos:
+ # In that case, self._discretization must be
+ # a Discretization object, used for all fields.
+ # We use it to initialize scales solver
+ topo = self._create_scales_topo(self._discretization,
+ order, splitting)
+ for v in self.variables:
+ self.variables[v] = topo
+ else:
+ # In that case, self._discretization must be
+ # a Cartesian object, used for all fields.
+ # We use it to initialize scales solver
+ assert isinstance(self._discretization, Cartesian)
+ topo = self._discretization
+ msg = 'input topology is not compliant with scales.'
+ #assert topo.dimension == 1, msg
+ msg = 'Ghosts points not yet implemented for scales operators.'
+ assert (topo.mesh.discretization.ghosts == 0).all(), msg
+
+ nbcells = topo.mesh.discretization.resolution - 1
+ topodims = topo.shape
+ scalesres, global_start = \
+ scales.init_advection_solver(nbcells,
+ self.domain.length,
+ npw.asintegerarray(topodims),
+ self.mpi_params.comm.py2f(),
+ order=order,
+ dim_split=splitting)
+
+ assert (topo.shape == topodims).all()
+ assert (topo.mesh.resolution == scalesres).all()
+ assert (topo.mesh.start() == global_start).all()
+
+ msg = 'Scales Advection not yet implemented with ghosts points.'
+ assert (topo.ghosts() == 0).all(), msg
+
+ # Scales, multi-resolution
+ else:
+ if build_topos[self.velocity]:
+ # Resolution used for velocity
+ v_resol = self.variables[self.velocity].resolution - 1
+
+ else:
+ topo = self.variables[self.velocity]
+ v_resol = topo.mesh.discretization.resolution
+
+ vbuild = [v for v in self.variables if build_topos[v]]
+ for v in vbuild:
+ self.variables[v] = self._create_scales_topo(
+ self.variables[v], order, splitting)
+
+ topo = self.variables.values()[0]
+ self._check_scales_topo(topo, order, splitting)
+
+ # Init multiscale in scales
+ scales.init_multiscale(v_resol[0], v_resol[1], v_resol[2],
+ self.method[MultiScale])
+
+ # All topos are built, we can discretize fields.
+ self._discretize_vars()
+
+ advected_discrete_fields = [self.discrete_fields[f]
+ for f in self.advected_fields]
+ toporef = advected_discrete_fields[0].topology
+ msg = 'All advected fields must have the same topology.'
+ for f in advected_discrete_fields:
+ assert f.topology == toporef, msg
+
+ if self._single_topo:
+ self.method[MultiScale] = None
+
+ def _create_scales_topo(self, d3d, order, splitting):
+ """set specific MPI layout for scales.
+ """
+ comm = self.mpi_params.comm
+ topodims = [1, 1, comm.Get_size()]
+ msg = 'Wrong type for parameter discretization (at init).'
+ msg += str(self._discretization)
+ assert isinstance(d3d, Discretization), msg
+ nbcells = d3d.resolution - 1
+ scalesres, global_start = \
+ scales.init_advection_solver(nbcells,
+ self.domain.length,
+ npw.asintegerarray(topodims),
+ comm.py2f(),
+ order=order,
+ dim_split=splitting)
+ # Create the topo (plane, cut through ZDIR)
+ return self.domain.create_plane_topology_from_mesh(
+ global_start=global_start, localres=scalesres,
+ discretization=d3d, cdir=ZDIR)
+
+ def _check_scales_topo(self, toporef, order, splitting):
+ """Check if input topo fits with scales requirements
+ """
+ # In that case, self._discretization must be
+ # a Cartesian object, used for all fields.
+ # We use it to initialize scales solver
+ comm = self.mpi_params.comm
+ #topodims = [1, 1, comm.Get_size()]
+ nbcells = toporef.mesh.discretization.resolution - 1
+
+ scalesres, global_start = \
+ scales.init_advection_solver(nbcells, self.domain.length,
+ npw.asintegerarray(toporef.shape),
+ comm.py2f(),
+ order=order, dim_split=splitting)
+ for v in self.variables:
+ topo = self.variables[v]
+ assert isinstance(topo, Cartesian), str(topo)
+ #assert (topo.shape == topodims).all(), \
+ # str(topo.shape) + ' != ' + str(topodims)
+ assert not self._single_topo or \
+ (topo.mesh.resolution == scalesres).all(), \
+ str(topo.mesh.resolution) + ' != ' + str(scalesres)
+ assert not self._single_topo or \
+ (topo.mesh.start() == global_start).all(), \
+ str(topo.mesh.start()) + ' != ' + str(global_start)
+
+ def _setup(self, advected_discrete_fields, rwork=None, iwork=None):
+ # Check resolutions to set multiscale case, if required.
+ if not self._single_topo and MultiScale not in self.method:
+ self.method[MultiScale] = L2_1
+ # - Create the discrete_op from the
+ # list of discrete fields -
+ from hysop.operator.discrete.scales_advection import \
+ ScalesAdvection as SD
+ self.discrete_op = SD(
+ self.discrete_fields[self.velocity],
+ advected_discrete_fields, method=self.method,
+ rwork=rwork, iwork=iwork,
+ **self.config)
diff --git a/hysop/old/operator.old/advection_dir.py b/hysop/old/operator.old/advection_dir.py
new file mode 100644
index 0000000000000000000000000000000000000000..7f1cd5f6bef99a3561af4105afc691be9fd33475
--- /dev/null
+++ b/hysop/old/operator.old/advection_dir.py
@@ -0,0 +1,155 @@
+"""Advection of a field in a given direction
+
+See :ref:`advection` in user guide.
+
+"""
+from hysop.constants import debug, DirectionLabels
+from hysop.methods import Support, TimeIntegrator, Interpolation
+from hysop.numerics.remeshing import Remeshing
+from hysop.operator.computational import Computational
+import numpy as np
+from hysop.operator.continuous import opsetup, opapply
+from hysop.operator.advection import Advection
+
+
+class AdvectionDir(Computational):
+ """Advection of a scalar or vector field in a given direction,
+ assuming incompressible flow.
+ """
+
+ @debug
+ def __init__(self, parent, direction, **kwds):
+ """"
+ Parameters
+ ----------
+ parent : :class:`hysop.operator.advection.Advection`
+ main advection operator
+ direction: int
+ direction of advection
+ kwds : base class arguments.
+ """
+ assert isinstance(parent, Advection)
+ self.parent = parent
+ # advected_fields :
+ self.advected_fields = parent.advected_fields
+ # velocity field
+ self.velocity = parent.velocity
+ self._kwds = kwds
+ super(AdvectionDir, self).__init__(variables=parent.variables, **kwds)
+
+ self.method = parent.method
+ self.input = parent.input
+ self.output = parent.output
+ self.name = parent.name + DirectionLabels[direction]
+
+ # direction to advect
+ self.direction = direction
+
+ # Fields on particles
+ self.particle_fields = None
+
+ # Positions of the particles
+ self.particle_positions = None
+
+ # number of components of the rhs (time integration)
+ self._rhs_size = 1
+
+ # check if advection is done on gpu
+ self._gpu_advection = self.method[Support].find('gpu') >= 0
+
+ @debug
+ def discretize(self):
+ if self._is_discretized:
+ return
+
+ # everything is done in parent ...
+ self.variables = self.parent.variables
+ self.discrete_fields = self.parent.discrete_fields
+ self._is_discretized = True
+
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ # select discretization of the advected fields
+ advected_discrete_fields = [self.discrete_fields[v]
+ for v in self.variables
+ if v is not self.velocity]
+ # GPU advection ...
+ if self._gpu_advection:
+ topo_shape = advected_discrete_fields[0].topology.shape
+ if topo_shape[self.direction] == 1:
+ from hysop.backend.device.opencl.gpu_particle_advection \
+ import GPUParticleAdvection as advec
+ else:
+ from hysop.backend.device.opencl.multi_gpu_particle_advection \
+ import MultiGPUParticleAdvection as advec
+ else:
+ # pure-python advection
+ from hysop.operator.discrete.particle_advection \
+ import ParticleAdvection as advec
+
+ self.discrete_op = advec(
+ velocity=self.discrete_fields[self.velocity],
+ fields_on_grid=advected_discrete_fields,
+ direction=self.direction,
+ rwork=rwork, iwork=iwork,
+ **self._kwds)
+
+ self._is_uptodate = True
+
+ def get_work_properties(self):
+ super(AdvectionDir, self).get_work_properties()
+ # Shape of reference comes from fields, not from velocity
+ advected_discrete_fields = [self.discrete_fields[v]
+ for v in self.variables
+ if v is not self.velocity]
+ topo = advected_discrete_fields[0].topology
+ # Find number and shape of required work arrays
+ if not self._gpu_advection:
+ # -- pure python advection --
+ # work array shape depends on the time integrator
+ # interpolation scheme and remeshing scheme
+ ti_work = self.method[TimeIntegrator].get_work_properties(
+ self._rhs_size, topo)
+ ti_rwork_length = len(ti_work['rwork'])
+ iw_prop = self.method[Interpolation].get_work_properties(topo)
+ rw_prop = Remeshing.get_work_properties(topo)
+ interp_iwork_length = len(iw_prop['iwork'])
+ interp_rwork_length = len(iw_prop['rwork'])
+ remesh_iwork_length = len(rw_prop['iwork'])
+ remesh_rwork_length = len(rw_prop['rwork'])
+ iwork_length = max(interp_iwork_length, remesh_iwork_length)
+ rwork_length = max(ti_rwork_length + interp_rwork_length,
+ remesh_rwork_length)
+ else:
+ # -- GPU advection --
+ # no work array
+ iwork_length, rwork_length = 0, 0
+
+ # buffers for fields on particles
+ rwork_length += np.sum([f.nb_components for f in self.advected_fields])
+ if not self._gpu_advection or \
+ self.method[Support].find('gpu_2k') >= 0:
+ rwork_length += 1 # work array for positions
+ memsize = np.prod(topo.mesh.resolution)
+ return {'rwork': [memshape] * rwork_length,
+ 'iwork': [memshape] * iwork_length}
+
+ @debug
+ @opapply
+ def apply(self, simulation=None, dt_coeff=1.0, split_id=0, old_dir=0):
+ """
+
+ Parameters
+ ----------
+
+ simulation : `:class::~hysop.problem.simulation.Simulation`
+ dt_coeff : double
+ split_id : int, optional
+ old_dir : int, optional
+ """
+ if not self._single_topo and not self._gpu_advection:
+ raise ValueError("Multiscale advection is not yet supported "
+ "in pure Python, use Scales or GPU.")
+
+ self.discrete_op.apply(simulation,
+ dt_coeff, split_id, old_dir)
diff --git a/hysop/old/operator.old/analytic.py b/hysop/old/operator.old/analytic.py
new file mode 100644
index 0000000000000000000000000000000000000000..c3523900674525a503073861bd07c4fbf1b6267a
--- /dev/null
+++ b/hysop/old/operator.old/analytic.py
@@ -0,0 +1,70 @@
+"""Initialize fields on a grid, with a user-defined function
+"""
+from hysop.constants import debug
+from hysop.operator.continuous import opsetup, opapply
+from hysop.operator.computational import Computational
+from hysop.methods import Support
+
+
+class Analytic(Computational):
+ """
+ Applies an analytic formula, given by user, on its fields.
+ """
+
+ @debug
+ def __init__(self, formula=None, vectorize_formula=False, **kwds):
+ """ Apply a user-defined formula onto a list of fields.
+
+ Parameters
+ ----------
+ formula : python function
+ the formula to be applied
+ vectorize_formula : boolean, optional
+ true if formula must be vectorized (numpy), default = false.
+
+ Notes
+ -----
+ see :ref:`analytical_operator` for details on
+ the authorized signature for input formula or check
+ test_analytic.py
+ """
+ super(Analytic, self).__init__(**kwds)
+ isGPU = False
+ if 'method' in kwds.keys() and Support in kwds['method'].keys():
+ isGPU = kwds['method'][Support].find('gpu') >= 0
+ if formula is not None:
+ # A formula applied to all variables of this operator
+ self.formula = formula
+ for v in self.variables:
+ v.set_formula(formula, vectorize_formula)
+ elif not isGPU:
+ vref = self.variables.keys()[0]
+ assert vref.formula is not None
+ self.formula = vref.formula
+ # Only one formula allowed per operator
+ for v in self.variables:
+ assert v.formula is self.formula
+
+ self.output = self.variables
+
+ def discretize(self):
+ super(Analytic, self)._standard_discretize()
+
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ self._is_uptodate = True
+
+ @debug
+ @opapply
+ def apply(self, simulation=None):
+ assert simulation is not None, \
+ "Missing simulation value for computation."
+ for v in self.variables:
+ topo = self.discrete_fields[v].topology
+ v.initialize(time=simulation.time, topo=topo)
+
+ def get_profiling_info(self):
+ pass
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
diff --git a/hysop/operator/baroclinic.py b/hysop/old/operator.old/baroclinic.py
similarity index 86%
rename from hysop/operator/baroclinic.py
rename to hysop/old/operator.old/baroclinic.py
index 7937b55a558377a6420c858b106630bfb1aed6c5..5eae4221aa53aef2f5922d87c162c593bd4038a5 100644
--- a/hysop/operator/baroclinic.py
+++ b/hysop/old/operator.old/baroclinic.py
@@ -6,7 +6,7 @@ MultiPhase Rot Grad P
"""
from hysop.operator.computational import Computational
from hysop.operator.discrete.baroclinic import Baroclinic as BD
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4
from hysop.constants import debug
import hysop.default_methods as default
@@ -48,10 +48,10 @@ class Baroclinic(Computational):
self.viscosity = viscosity
self.input = [self.velocity, self.vorticity, self.density]
self.output = [self.vorticity]
- assert SpaceDiscretisation in self.method.keys()
+ assert SpaceDiscretization in self.method.keys()
def discretize(self):
- if self.method[SpaceDiscretisation] is FDC4:
+ if self.method[SpaceDiscretization] is FDC4:
nbGhosts = 2
else:
raise ValueError("Unknown method for space discretization of the\
@@ -67,14 +67,16 @@ class Baroclinic(Computational):
Create a discrete Baroclinic operator from given specifications.
"""
self.discrete_op = \
- BD(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
- self.discreteFields[self.density],
+ BD(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
+ self.discrete_fields[self.density],
self.viscosity,
method=self.method)
self._is_uptodate = True
-
def initialize_velocity(self):
self.discrete_op.initialize_velocity()
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
diff --git a/hysop/operator/baroclinic_from_rhs.py b/hysop/old/operator.old/baroclinic_from_rhs.py
similarity index 88%
rename from hysop/operator/baroclinic_from_rhs.py
rename to hysop/old/operator.old/baroclinic_from_rhs.py
index a352c4e645ec6579d1ce390fa257a46a3544f066..42aba93d9a63f0dfb81f10a4cbaf091fe6c4392c 100644
--- a/hysop/operator/baroclinic_from_rhs.py
+++ b/hysop/old/operator.old/baroclinic_from_rhs.py
@@ -6,7 +6,7 @@ MultiPhase baroclinic term
"""
from hysop.operator.computational import Computational
from hysop.operator.discrete.baroclinic_from_rhs import BaroclinicFromRHS as BD
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4
from hysop.constants import debug
import hysop.default_methods as default
@@ -36,7 +36,7 @@ class BaroclinicFromRHS(Computational):
self.rhs = rhs
self.input = [self.vorticity, self.rhs]
self.output = [self.vorticity]
- assert SpaceDiscretisation in self.method.keys()
+ assert SpaceDiscretization in self.method.keys()
def discretize(self):
super(BaroclinicFromRHS, self)._standard_discretize()
@@ -49,8 +49,8 @@ class BaroclinicFromRHS(Computational):
Create a discrete Baroclinic operator from given specifications.
"""
self.discrete_op = \
- BD(self.discreteFields[self.vorticity],
- self.discreteFields[self.rhs],
+ BD(self.discrete_fields[self.vorticity],
+ self.discrete_fields[self.rhs],
method=self.method)
self._is_uptodate = True
diff --git a/hysop/operator/computational.py b/hysop/old/operator.old/computational.py
similarity index 90%
rename from hysop/operator/computational.py
rename to hysop/old/operator.old/computational.py
index 6a7f622fa02fd4dd6e634d137ccbe905ee8e8a10..3c798ffa58579a92fa2f43e57a261ce9c4775e90 100755
--- a/hysop/operator/computational.py
+++ b/hysop/old/operator.old/computational.py
@@ -3,14 +3,14 @@
"""
from abc import ABCMeta, abstractmethod
from hysop.constants import debug
-from hysop.operator.continuous import Operator, opapply
-from hysop.mpi.topology import Cartesian
+from hysop.operator.continuous import OperatorBase, opapply
+from hysop.core.mpi.topology import Cartesian
from hysop.tools.parameters import Discretization
-from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
+from hysop import __FFTW_ENABLED__
-class Computational(Operator):
+class Computational(OperatorBase):
"""
Abstract base class for computational operators.
@@ -37,7 +37,7 @@ class Computational(Operator):
Parameters
----------
- discretization : :class:`hysop.mpi.topology.Cartesian`
+ discretization : :class:`hysop.core.mpi.topology.Cartesian`
or :class:`tools.parameters.Discretization`
Defined the data mpi distribution. See Notes below.
method : :class:`hysop.method`
@@ -52,7 +52,8 @@ class Computational(Operator):
super(Computational, self).__init__(**kwds)
# Set mpi related stuff
- self._set_domain_and_tasks()
+ if self.variables:
+ self._set_domain_and_tasks()
# A dictionnary of parameters, to define numerical methods used
# used to discretize the operator.
@@ -201,7 +202,7 @@ class Computational(Operator):
return build_topos
- def _standard_discretize(self, min_ghosts=0):
+ def _standard_discretize(self, min_ghosts=0, cutdir=None):
"""
This functions provides a standard way to discretize the operator,
but some operators may need a specific discretization process.
@@ -213,21 +214,23 @@ class Computational(Operator):
if self._single_topo:
# One topo for all fields ...
if build_topos:
- topo = self._build_topo(self._discretization, min_ghosts)
+ topo = self._build_topo(self._discretization, min_ghosts,
+ cutdir)
for v in self.variables:
self.variables[v] = topo
else:
- # Topo is already built, just check its ghosts
+ # Topo is already built, just check its ghosts and cutdir
msg = 'The proposed ghost layer is not large enough.'
ghosts = self.variables.values()[0].mesh.discretization.ghosts
assert (ghosts >= min_ghosts).all(), msg
-
+ if cutdir is not None:
+ assert (self.variables.values()[0].cutdir == cutdir).all()
else:
# ... or one topo for each field.
for v in self.variables:
if build_topos[v]:
self.variables[v] = self._build_topo(self.variables[v],
- min_ghosts)
+ min_ghosts, cutdir)
build_topos[v] = False
else:
assert (self.variables[v].ghosts() >= min_ghosts).all()
@@ -235,16 +238,16 @@ class Computational(Operator):
# All topos are built, we can discretize fields.
self._discretize_vars()
- def _build_topo(self, discretization, min_ghosts):
- """Build an mpi topology and its mesh from a given
+ def _build_topo(self, discretization, min_ghosts, cutdir=None):
+ """Build a mpi topology and its mesh from a given
discretization.
-
"""
# Reset ghosts if necessary
ghosts = discretization.ghosts
ghosts[ghosts < min_ghosts] = min_ghosts
# build a topology from the given discretization
- return self.domain.create_topology(discretization)
+ return self.domain.create_topology(discretization=discretization,
+ cutdir=cutdir)
def _fftw_discretize(self):
"""
@@ -255,18 +258,21 @@ class Computational(Operator):
"""
if self._is_discretized:
return
+
+ assert __FFTW_ENABLED__
+ from hysop.f2hysop import fftw2py
+
build_topos = self._check_variables()
assert self._single_topo, 'All fields must use the same topology.'
# Get local mesh parameters from fftw
- comm = self._mpis.comm
- from hysop.f2hysop import fftw2py
+ comm = self.mpi_params.comm
if build_topos:
# In that case, self._discretization must be
# a Discretization object, used for all fields.
# We use it to initialize scales solver
msg = 'Wrong type for parameter discretization (at init).'
assert isinstance(self._discretization, Discretization), msg
- resolution = npw.asintarray(self._discretization.resolution)
+ resolution = npw.asintegerarray(self._discretization.resolution)
localres, global_start = fftw2py.init_fftw_solver(
resolution, self.domain.length, comm=comm.py2f())
# Create the topo (plane, cut through ZDIR)
@@ -286,11 +292,11 @@ class Computational(Operator):
from hysop.constants import ORDER
if ORDER == 'C':
- assert topo.shape[0] == self._mpis.comm.Get_size(), msg
+ assert topo.shape[0] == self.mpi_params.comm.Get_size(), msg
else:
- assert topo.shape[-1] == self._mpis.comm.Get_size(), msg
+ assert topo.shape[-1] == self.mpi_params.comm.Get_size(), msg
- resolution = npw.asintarray(topo.mesh.discretization.resolution)
+ resolution = npw.asintegerarray(topo.mesh.discretization.resolution)
localres, global_start = fftw2py.init_fftw_solver(
resolution, self.domain.length, comm=comm.py2f())
@@ -341,7 +347,7 @@ class Computational(Operator):
self.discrete_op.computation_time()
self.time_info = self.discrete_op.time_info
else:
- from hysop.mpi import main_rank
+ from hysop.core.mpi import main_rank
short_name = str(self.__class__).rpartition('.')[-1][0:-2]
s = '[' + str(main_rank) + '] ' + short_name
s += " : operator not discretized --> no computation, time = 0."
diff --git a/hysop/operator/continuous.py b/hysop/old/operator.old/continuous.py
similarity index 92%
rename from hysop/operator/continuous.py
rename to hysop/old/operator.old/continuous.py
index b58306ded6765d7d7e9e0dc23679df16bd3e2ec3..e6a3b37018247cb38fddae387c9b3c4b5c2d67a4 100755
--- a/hysop/operator/continuous.py
+++ b/hysop/old/operator.old/continuous.py
@@ -3,11 +3,12 @@
"""
from abc import ABCMeta, abstractmethod
from hysop.constants import debug
-from hysop.tools.profiler import Profiler, profile
+from hysop.tools.profiler import Profiler
from hysop.tools.io_utils import IOParams, IO
from hysop.tools.parameters import MPIParams
import hysop.tools.io_utils as io
import inspect
+from hysop.tools.profiler import ftime
class Operator(object):
@@ -22,7 +23,7 @@ class Operator(object):
@debug
@abstractmethod
def __init__(self, variables=None, mpi_params=None,
- io_params=None):
+ io_params=None, **kwds):
"""
Parameters
----------
@@ -40,7 +41,7 @@ class Operator(object):
are :class:`hysop.fields.continuous.Fields`.
The values of the dict can be either
- :class:`hysop.mpi.topology.Cartesian`
+ :class:`hysop.core.mpi.topology.Cartesian`
or :class:`hysop.tools.parameters.Discretization`::
op = Analytic(variables = [velo, vorti], ...)
@@ -58,6 +59,8 @@ class Operator(object):
the geometry on which this operator applies
"""
+ super(OperatorBase,self).__init__(**kwds)
+
# 1 ---- Variables setup ----
# List of hysop.continuous.Fields involved in the operator.
if isinstance(variables, list):
@@ -89,11 +92,11 @@ class Operator(object):
self.domain = None
"""Physical domain of definition for the operator """
# mpi context
- self._mpis = mpi_params
+ self.mpi_params = mpi_params
# tools for profiling
self.profiler = None
- # Remark : domain, _mpis and profiler will be set properly in
+ # Remark : domain, mpi_params and profiler will be set properly in
# _set_domain_and_tasks, called in derived class, since it may
# require some specific initialization (check domain ...)
@@ -135,8 +138,8 @@ class Operator(object):
assert v.domain is self.domain, 'All variables of the operator\
must be defined on the same domain.'
# Set/check mpi context
- if self._mpis is None:
- self._mpis = MPIParams(comm=self.domain.comm_task,
+ if self.mpi_params is None:
+ self.mpi_params = MPIParams(comm=self.domain.comm_task,
task_id=self.domain.current_task())
# Set profiler
@@ -198,7 +201,7 @@ class Operator(object):
ready to apply.
In derived classes, called through @opsetup decorator.
"""
- if not self.domain.current_task() == self._mpis.task_id:
+ if not self.domain.current_task() == self.mpi_params.task_id:
self.ontask = False
self._error_()
@@ -265,20 +268,17 @@ class Operator(object):
# default values for iop
self.io_params = IOParams(filename, fileformat=IO.ASCII)
else:
- if self.io_params.fileformat is not IO.ASCII:
- self.io_params.fileformat = IO.ASCII
- msg = 'Warning, wrong file format for operator output.'
- msg += 'This will be reset to ASCII.'
- print msg
+ msg = 'Error, wrong file format for operator output.'
+ assert self.io_params.fileformat is IO.ASCII, msg
self._writer = io.Writer(io_params=self.io_params,
- mpi_params=self._mpis,
+ mpi_params=self.mpi_params,
buffshape=buffshape)
def task_id(self):
"""
Returns the id of the task on which this operator works.
"""
- return self._mpis.task_id
+ return self.mpi_params.task_id
def opsetup(f):
@@ -310,8 +310,6 @@ def opsetup(f):
return decorator
-from hysop.tools.profiler import ftime
-
def opapply(f):
"""
@@ -323,8 +321,8 @@ def opapply(f):
"""decorate 'apply' method"""
# get 'continuous' base class and run its apply function
# --> call wait function of ops in wait_list
- t0 = ftime()
name = inspect.getmro(args[0].apply.im_class)
+ t0 = ftime()
name[-2].apply(args[0])
#t0 = ftime()
res = f(*args, **kwargs)
@@ -344,7 +342,7 @@ class Tools(object):
"""
Returns true if op operates on a GPU
"""
- from hysop.methods_keys import Support
+ from hysop.methods import Support
try:
is_device = \
diff --git a/hysop/operator/curlAndDiffusion.py b/hysop/old/operator.old/curlAndDiffusion.py
similarity index 87%
rename from hysop/operator/curlAndDiffusion.py
rename to hysop/old/operator.old/curlAndDiffusion.py
index 8b86d2bff462b80e59862a6aa7746417db7d271b..6b9ffc207a2c66da6c6e85fe8260d80357cd4e5e 100644
--- a/hysop/operator/curlAndDiffusion.py
+++ b/hysop/old/operator.old/curlAndDiffusion.py
@@ -5,7 +5,7 @@
Operator for diffusion problem.
"""
-from hysop.operator.continuous import Operator
+from hysop.operator.continuous import OperatorBase
try:
from hysop.f2hysop import fftw2py
except ImportError:
@@ -15,7 +15,7 @@ from hysop.constants import debug
from hysop.operator.continuous import opsetup
-class CurlDiffusion(Operator):
+class CurlDiffusion(OperatorBase):
"""
Diffusion operator
\f{eqnarray*}
@@ -50,7 +50,7 @@ class CurlDiffusion(Operator):
Create a discrete Diffusion operator from given specifications.
"""
if self._comm is None:
- from hysop.mpi import main_comm as comm
+ from hysop.core.mpi import main_comm as comm
else:
comm = self._comm
@@ -68,11 +68,11 @@ class CurlDiffusion(Operator):
topodims,
comm=comm)
vd = v.discretize(topo)
- self.discreteFields[v] = vd
+ self.discrete_fields[v] = vd
self.discrete_op =\
- DiffusionFFT(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
+ DiffusionFFT(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
self.method, **self.config)
self.discrete_op.setup()
diff --git a/hysop/old/operator.old/custom.py b/hysop/old/operator.old/custom.py
new file mode 100644
index 0000000000000000000000000000000000000000..67c644f30a6ee63807f4cb261237dcb085550ee1
--- /dev/null
+++ b/hysop/old/operator.old/custom.py
@@ -0,0 +1,65 @@
+"""Interface to set a user-defined operator
+"""
+from hysop.operator.computational import Computational
+from hysop.operator.discrete.custom import Custom as CO
+from hysop.operator.continuous import opsetup
+
+
+class Custom(Computational):
+ """User-defined generic operator
+ """
+ def __init__(self, function, in_fields, out_fields=None,
+ diagnostics_shape=None, **kwds):
+ """
+
+ Parameters
+ ----------
+ in_fields: list of :class:`~hysop.fields.discrete.DiscreteField`
+ input fields args. for function, see notes below
+ out_fields: list of :class:`~hysop.fields.discrete.DiscreteField`
+ output fields args for function, see notes below
+ function: python function
+ a user defined function, called by this op.apply method.
+ diagnostics_shape: tuple, optional
+ shape of the data expected to be written into file.
+
+ Notes
+ -----
+ A function is used to set the behavior of the current operator,
+ during apply call.
+ This function must look like::
+
+ def some_func(simulation, in_fields, out_fields, diagnostics=None):
+ # do things ...
+
+ and compute out_fields values and optionnaly some diagnostics.
+ See :ref:`custom`
+ """
+ super(Custom, self).__init__(**kwds)
+ self.function = function
+ self.input = in_fields
+ if out_fields is not None:
+ self.output = out_fields
+ self._diagnostics_shape = diagnostics_shape
+
+ def discretize(self):
+ super(Custom, self)._standard_discretize()
+
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ if not self._is_uptodate:
+ self.discrete_op = CO(
+ in_fields=[self.discrete_fields[f] for f in self.input],
+ out_fields=[self.discrete_fields[f] for f in self.output],
+ function=self.function,
+ variables=self.discrete_fields.values())
+ if self._diagnostics_shape is not None:
+ assert isinstance(self._diagnostics_shape, tuple)
+ assert len(self._diagnostics_shape) == 2
+ self._set_io(self.function.__name__, self._diagnostics_shape)
+ self.discrete_op.set_writer(self._writer)
+
+ self._is_uptodate = True
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
diff --git a/hysop/operator/density.py b/hysop/old/operator.old/density.py
similarity index 90%
rename from hysop/operator/density.py
rename to hysop/old/operator.old/density.py
index bca08336193f0af769965a359be925e855945877..560855b44e785dceb64a05caa847697d97dc6661 100644
--- a/hysop/operator/density.py
+++ b/hysop/old/operator.old/density.py
@@ -39,8 +39,8 @@ class DensityVisco(Computational):
"""
self.discrete_op = \
- DensityVisco_d(density=self.discreteFields[self.density],
- viscosity=self.discreteFields[self.viscosity],
+ DensityVisco_d(density=self.discrete_fields[self.density],
+ viscosity=self.discrete_fields[self.viscosity],
method=self.method)
self._is_uptodate = True
diff --git a/hysop/operator/differential.py b/hysop/old/operator.old/differential.py
similarity index 84%
rename from hysop/operator/differential.py
rename to hysop/old/operator.old/differential.py
index 676d635b04ce0e94f2fa78979e498069648790a9..dd3c86ba7b888aca068b457d8c3d0d01e8842063 100644
--- a/hysop/operator/differential.py
+++ b/hysop/old/operator.old/differential.py
@@ -13,7 +13,7 @@ from hysop.constants import debug
from hysop.operator.computational import Computational
from hysop.operator.discrete.differential import CurlFFT, CurlFD,\
GradFD, DivAdvectionFD
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.operator.continuous import opsetup
from hysop.numerics.finite_differences import FiniteDifference
import hysop.default_methods as default
@@ -73,7 +73,7 @@ class Differential(Computational):
At the time, two space-discretization methods : based on
FFT or on Finite Differences.
"""
- space_d = self.method[SpaceDiscretisation]
+ space_d = self.method[SpaceDiscretization]
if space_d is 'fftw':
super(Differential, self)._fftw_discretize()
@@ -96,8 +96,8 @@ class Differential(Computational):
Main step : setup for discrete operators.
"""
self.discrete_op = self._discrete_op_class(
- invar=self.discreteFields[self.invar],
- outvar=self.discreteFields[self.outvar],
+ invar=self.discrete_fields[self.invar],
+ outvar=self.discrete_fields[self.outvar],
method=self.method, rwork=rwork)
self._is_uptodate = True
@@ -107,13 +107,13 @@ class Curl(Differential):
"""
def _init_space_discr_method(self):
- if self.method[SpaceDiscretisation] is 'fftw' and __FFTW_ENABLED__:
+ if self.method[SpaceDiscretization] is 'fftw' and __FFTW_ENABLED__:
op_class = CurlFFT
- elif not isinstance(self.method[SpaceDiscretisation], str):
- if self.method[SpaceDiscretisation].mro()[1] is FiniteDifference:
+ elif not isinstance(self.method[SpaceDiscretization], str):
+ if self.method[SpaceDiscretization].mro()[1] is FiniteDifference:
op_class = CurlFD
else:
- raise ValueError("The required Space Discretisation is\
+ raise ValueError("The required Space Discretization is\
not available for Curl.")
return op_class
@@ -121,7 +121,7 @@ class Curl(Differential):
super(Curl, self).get_work_properties()
res = {'rwork': None, 'iwork': None}
# Only FD methods need internal work space
- if self.method[SpaceDiscretisation].mro()[1] is FiniteDifference:
+ if self.method[SpaceDiscretization].mro()[1] is FiniteDifference:
toporef = self.variables[self.invar]
res = NumCurl.get_work_properties(toporef)
return res
@@ -132,10 +132,10 @@ class Grad(Differential):
"""
def _init_space_discr_method(self):
- if self.method[SpaceDiscretisation].mro()[1] is FiniteDifference:
+ if self.method[SpaceDiscretization].mro()[1] is FiniteDifference:
op_class = GradFD
else:
- raise ValueError("The required Space Discretisation is\
+ raise ValueError("The required Space Discretization is\
not available for Grad.")
return op_class
@@ -147,10 +147,10 @@ class DivAdvection(Differential):
"""Computes outVar = -nabla .(invar . nabla(nvar))
"""
def _init_space_discr_method(self):
- if self.method[SpaceDiscretisation].mro()[1] is FiniteDifference:
+ if self.method[SpaceDiscretization].mro()[1] is FiniteDifference:
op_class = DivAdvectionFD
else:
- raise ValueError("The required Space Discretisation is\
+ raise ValueError("The required Space Discretization is\
not available for DivAdvection.")
return op_class
@@ -158,7 +158,7 @@ class DivAdvection(Differential):
super(DivAdvection, self).get_work_properties()
res = {'rwork': None, 'iwork': None}
# Only FD methods need internal work space
- if self.method[SpaceDiscretisation].mro()[1] is FiniteDifference:
+ if self.method[SpaceDiscretization].mro()[1] is FiniteDifference:
toporef = self.variables[self.invar]
res = NumDA.get_work_properties(toporef)
return res
diff --git a/hysop/old/operator.old/diffusion.py b/hysop/old/operator.old/diffusion.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ea8784cfaf36c43b0a9f49d4a6ed4a731128795
--- /dev/null
+++ b/hysop/old/operator.old/diffusion.py
@@ -0,0 +1,149 @@
+# -*- coding: utf-8 -*-
+"""Operator for diffusion problem.
+
+See :ref:`diffusion` in HySoP user guide.
+
+
+"""
+from hysop.operator.computational import Computational
+from hysop.operator.discrete.diffusion_fft import DiffusionFFT,\
+ CurlAndDiffusionFFT
+from hysop.constants import debug
+from hysop.operator.continuous import opsetup
+from hysop.methods import SpaceDiscretization, GhostUpdate
+from hysop import __FFTW_ENABLED__, __GPU_ENABLED__
+if __GPU_ENABLED__:
+ from hysop.backend.device.opencl.gpu_diffusion import GPUDiffusion
+
+
+class Diffusion(Computational):
+ """Diffusion of a field.
+ """
+
+ _authorized_methods = ['fftw', 'on_gpu']
+
+ @debug
+ def __init__(self, viscosity, vorticity, **kwds):
+ """Diffusion operator.
+ See :ref:`diffusion` in HySoP user guide.
+
+ Parameters
+ ----------
+ viscosity : double
+ constant viscosity value
+ vorticity : :class:`~hysop.fields.continuous.Field`
+ vorticity field, in/out parameter.
+ kwds : base class parameters.
+ """
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ super(Diffusion, self).__init__(variables=[vorticity], **kwds)
+ if 'method' not in kwds:
+ import hysop.default_methods as default
+ self.method = default.DIFFUSION
+ else:
+ self.method = kwds.pop('method')
+
+ msg = 'Diffusion : unknown method for space discretization'
+ assert self.method[SpaceDiscretization] in self._authorized_methods,\
+ msg
+
+ msg = 'Diffusion : on_gpu resolution is not available on your system.'
+ if self.method[SpaceDiscretization] is 'on_gpu':
+ assert __GPU_ENABLED__, msg
+
+ # input/output field, solution of the problem
+ self.vorticity = vorticity
+ # viscosity
+ self.viscosity = viscosity
+ # kwds required for gpu discrete operator
+ self.kwds = kwds.copy()
+ if 'discretization' in self.kwds:
+ self.kwds.pop('discretization')
+ self.input = [self.vorticity]
+ self.output = [self.vorticity]
+
+ def discretize(self):
+ if self.method[SpaceDiscretization] is 'fftw' and __FFTW_ENABLED__:
+ super(Diffusion, self)._fftw_discretize()
+ elif self.method[SpaceDiscretization] is 'on_gpu':
+ super(Diffusion, self)._standard_discretize()
+ else:
+ raise AttributeError("Method not yet implemented.")
+
+ @debug
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ if self.method[SpaceDiscretization] is 'fftw':
+ dop = DiffusionFFT
+ elif self.method[SpaceDiscretization] is 'on_gpu':
+ dop = GPUDiffusion
+
+ self.discrete_op = dop(
+ viscosity=self.viscosity,
+ vorticity=self.discrete_fields[self.vorticity],
+ method=self.method, **self.kwds)
+ self._is_uptodate = True
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
+
+
+class CurlAndDiffusion(Computational):
+ """Solve curl of velocity and its diffusion in one shot
+ (in Fourier domain).
+ """
+
+ _authorized_methods = ['fftw']
+
+ @debug
+ def __init__(self, viscosity, velocity, vorticity, **kwds):
+ """Diffusion operator.
+ See :ref:`diffusion` in HySoP user guide.
+
+ Parameters
+ ----------
+ viscosity : double
+ constant viscosity value
+ velocity : :class:`~hysop.fields.continuous.Field
+ vorticity field, in/out parameter.
+ vorticity : :class:`~hysop.fields.continuous.Field
+ vorticity field, in/out parameter.
+ kwds : base class parameters.
+
+ Notes:
+ * vorticity parameter is optional since the field
+ can be provided in the usual way for operators using
+ variables parameter::
+
+ op = Diffusion(variables={vorticity: topo}, ...)
+
+ """
+ self.viscosity = viscosity
+ self.velocity = velocity
+ self.vorticity = vorticity
+ msg = 'fftw required for CurlAndDiffusion. '
+ msg += 'Try to recompile with WITH_FFTW=ON'
+ assert __FFTW_ENABLED__, msg
+ msg = 'CurlAndDiffusion : unknown method for space discretization'
+ self.method = {SpaceDiscretization: 'fftw', GhostUpdate: True}
+ self.input = [self.velocity]
+ self.output = [self.vorticity]
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ super(CurlAndDiffusion, self).__init__(
+ variables=[velocity, vorticity], **kwds)
+
+ def discretize(self):
+ super(CurlAndDiffusion, self)._fftw_discretize()
+
+ @debug
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ self.discrete_op = CurlAndDiffusionFFT(
+ viscosity=self.viscosity,
+ velocity=self.discrete_fields[self.velocity],
+ vorticity=self.discrete_fields[self.vorticity],
+ method=self.method)
+ self._is_uptodate = True
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
diff --git a/hysop/old/operator.old/discrete/__init__.py b/hysop/old/operator.old/discrete/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/old/operator.old/discrete/absorption_bc.py b/hysop/old/operator.old/discrete/absorption_bc.py
new file mode 100755
index 0000000000000000000000000000000000000000..5fbe363a65c36c9bce73c3f86a88fdb0b22b81d2
--- /dev/null
+++ b/hysop/old/operator.old/discrete/absorption_bc.py
@@ -0,0 +1,150 @@
+# -*- coding: utf-8 -*-
+"""Operator to kill the vorticity at the outlet boundary
+(i.e. removal of the periodic BC in the flow direction
+by vorticity absorption in order to set the far field
+velocity to u_inf at the inlet)
+"""
+
+from hysop.constants import debug, np
+from hysop.operator.discrete.discrete import DiscreteOperator
+from hysop.fields.variable_parameter import VariableParameter
+from hysop.tools.profiler import profile
+from hysop.tools.numpywrappers import npw
+from hysop.constants import YDIR, ZDIR
+from hysop.tools.misc import WorkSpaceTools
+
+
+class AbsorptionBC(DiscreteOperator):
+ """
+ The periodic boundary condition is modified at the outlet
+ in the flow direction in order to discard
+ in the downstream region the eddies coming
+ periodically from the outlet.
+ The vorticity absorption conserves div(omega)=0.
+ The far field velocity is set to u_inf at the inlet.
+ """
+
+ @debug
+ def __init__(self, velocity, vorticity, req_flowrate,
+ absorption_box, filter_func=None, **kwds):
+ """
+ Parameters
+ ----------
+ velocity, vorticity : :class:`~hysop.fields.discrete.DiscreteField`
+ req_flowrate : double
+ required value for the flow rate
+ absorption_box : :class:`~hysop.subsets.SubBox`
+ a box representing the area where filter is applied.
+ filter_func: list of python functions, optional
+ functions used to compute the filter and its differential.
+ **kwds : extra parameters for base class
+
+
+ Notes
+ -----
+ * if set, filter_func[0] and filter_func[1] must be python function
+ returning a numpy array. For example to apply a sine inside
+ the absorption area use :
+
+ .. code::
+
+ def func(x):
+ return np.sin(x)
+
+ """
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ # velocity discrete field
+ self.velocity = velocity
+ # vorticity discrete field
+ self.vorticity = vorticity
+ self.absorption_box = absorption_box
+ super(AbsorptionBC, self).__init__(
+ variables=[velocity, vorticity], **kwds)
+ # If 2D problem, vorticity must be a scalar
+ if self._dim == 2:
+ assert self.vorticity.nb_components == 1
+ assert (self._dim > 2),\
+ "Wrong problem dimension: only 3D cases are implemented."
+ topo = self.vorticity.topology
+ xcoords = topo.mesh.coords[0]
+ self.input = self.variables
+ self.output = [self.vorticity]
+ # Expected value for the flow rate through self.surfRef
+ msg = 'Wrong type or length for input req_flowrate.'
+ if not isinstance(req_flowrate, VariableParameter):
+ self.req_flowrate = VariableParameter(
+ data=np.asarray(req_flowrate))
+ assert np.asarray(req_flowrate).size == self._dim, msg
+ else:
+ self.req_flowrate = req_flowrate
+
+ t_dir = [1, 2]
+ dsurf = npw.prod(self.absorption_box.real_length[topo][t_dir])
+ self._inv_ds = 1. / dsurf
+ if self.absorption_box.on_proc[topo]:
+ ind = self.absorption_box.ind[topo][0]
+
+ if filter_func is None:
+ self.absorption_filter = None
+ self.diff_filter = None
+ self._set_default_filter(xcoords[ind[0]])
+ else:
+ assert isinstance(filter_func, list)
+ self.absorption_filter = filter_func[0](xcoords[ind[0]])
+ self.diff_filter = filter_func[1](xcoords[ind[0]])
+
+ def _set_default_filter(self, x):
+ """Default values for the filter in the absorption box
+ """
+ xb = x[0]
+ xe = x[-1]
+ xc = xb + (xe - xb) / 2.0
+ eps = 10.
+ form = np.tanh(eps * (x - xc))
+ self.absorption_filter = form - np.tanh(eps * (xe - xc))
+ coeff = 1.0 / (np.tanh(eps * (xb - xc)) - np.tanh(eps * (xe - xc)))
+ self.absorption_filter[...] *= coeff
+ self.diff_filter = eps * (1.0 - form ** 2)
+ self.diff_filter *= coeff
+
+ def _set_work_arrays(self, rwork=None, iwork=None):
+
+ # Reference shape comes from the box at the end of the domain
+ subshape = tuple(
+ self.absorption_box.mesh[self.vorticity.topology].resolution)
+ self._rwork = WorkSpaceTools.check_work_array(1, subshape, rwork)
+
+ @debug
+ @profile
+ def apply(self, simulation=None):
+ if not self.absorption_box.on_proc[self.vorticity.topology]:
+ return
+ # the required flowrate value is updated (depending on time)
+ self.req_flowrate.update(simulation)
+ # \warning : the flow rate value is divided by area of input surf.
+ req_flowrate_val = self.req_flowrate.data * self._inv_ds
+
+ ind = self.absorption_box.ind[self.vorticity.topology][0]
+ # 1 - filter * periodic vorticity:
+ for d in xrange(self.vorticity.nb_components):
+ np.multiply(self.vorticity[d][ind], self.absorption_filter,
+ self.vorticity[d][ind])
+
+ # 2 - nabla filter X periodic velocity + nabla(1-filter) X uinf
+ # uinf - vz
+ np.subtract(req_flowrate_val, self.velocity[ZDIR][ind],
+ self._rwork[0])
+ # wk = filter' * (uinf - vz )
+ np.multiply(self.diff_filter, self._rwork[0], self._rwork[0])
+ # add the result into vorticity
+ np.add(self.vorticity.data[YDIR][ind], self._rwork[0],
+ self.vorticity.data[YDIR][ind])
+ # and now, w_z ...
+ # vy - uinf
+ np.subtract(self.velocity[YDIR][ind], req_flowrate_val,
+ self._rwork[0])
+ # wk = filter' * (uinf - vy )
+ np.multiply(self.diff_filter, self._rwork[0], self._rwork[0])
+ # add the result into vorticity
+ np.add(self.vorticity.data[ZDIR][ind], self._rwork[0],
+ self.vorticity.data[ZDIR][ind])
diff --git a/hysop/operator/discrete/adapt_timestep.py b/hysop/old/operator.old/discrete/adapt_timestep.py
similarity index 96%
rename from hysop/operator/discrete/adapt_timestep.py
rename to hysop/old/operator.old/discrete/adapt_timestep.py
index ac32343fa6e43c8d6af6feedc44e028110de390b..0e302ee61f053713dc2fa15d026baaca671a6f03 100755
--- a/hysop/operator/discrete/adapt_timestep.py
+++ b/hysop/old/operator.old/discrete/adapt_timestep.py
@@ -3,14 +3,14 @@
"""
from hysop.constants import debug
-from hysop.methods_keys import TimeIntegrator, SpaceDiscretisation
+from hysop.methods import TimeIntegrator, SpaceDiscretization
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.numerics.differential_operations import MaxDiagGradV, \
DiagAndStretch, StrainCriteria, StretchLike, StrainAndStretch
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.numerics.update_ghosts import UpdateGhosts
-from hysop.mpi import MPI
-from hysop.constants import np, HYSOP_MPI_REAL
+from hysop.core.mpi import MPI
+from hysop.constants import np, hysop.core.mpi_REAL
from hysop.tools.profiler import profile
from hysop.problem.simulation import Simulation
from hysop.tools.misc import WorkSpaceTools
@@ -119,7 +119,7 @@ class AdaptiveTimeStepD(DiscreteOperator):
if self._diffop_name is not None:
self._diff_op = self._diffop_name(
topo=self.velocity.topology,
- method=self.method[SpaceDiscretisation],
+ method=self.method[SpaceDiscretization],
work=self._rwork)
self._needs_synchro = True
# Ghost synchronisation operator.
@@ -254,8 +254,8 @@ class AdaptiveTimeStepD(DiscreteOperator):
# mpi reduction
self.velocity.topology.comm.Allreduce(
- sendbuf=[buff, 7, HYSOP_MPI_REAL],
- recvbuf=[self.diagnostics, 7, HYSOP_MPI_REAL],
+ sendbuf=[buff, 7, hysop.core.mpi_REAL],
+ recvbuf=[self.diagnostics, 7, hysop.core.mpi_REAL],
op=MPI.MAX)
ind = self._used_functions.keys()
time_step = np.min(list(self.diagnostics[ind]) +
diff --git a/hysop/operator/discrete/baroclinic.py b/hysop/old/operator.old/discrete/baroclinic.py
similarity index 98%
rename from hysop/operator/discrete/baroclinic.py
rename to hysop/old/operator.old/discrete/baroclinic.py
index cacdd39f705fd17530f9caa75ecf1c710a151425..5e14e8e3beffa23d223d3b50badaf794acdbfa68 100644
--- a/hysop/operator/discrete/baroclinic.py
+++ b/hysop/old/operator.old/discrete/baroclinic.py
@@ -6,10 +6,10 @@ Discrete MultiPhase Rot Grad P
from hysop.operator.discrete.discrete import DiscreteOperator
import hysop.numerics.differential_operations as diff_op
from hysop.constants import debug, XDIR, YDIR, ZDIR, np
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.update_ghosts import UpdateGhosts
from hysop.tools.profiler import ftime
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
class Baroclinic(DiscreteOperator):
@@ -62,7 +62,7 @@ class Baroclinic(DiscreteOperator):
self._gradOp = diff_op.GradS(
self.velocity.topology,
indices=self.velocity.topology.mesh.compute_index,
- method=self.method[SpaceDiscretisation])
+ method=self.method[SpaceDiscretization])
# Gravity vector
self._gravity = npw.asrealarray([0., 0., -9.81])
diff --git a/hysop/operator/discrete/baroclinic_from_rhs.py b/hysop/old/operator.old/discrete/baroclinic_from_rhs.py
similarity index 95%
rename from hysop/operator/discrete/baroclinic_from_rhs.py
rename to hysop/old/operator.old/discrete/baroclinic_from_rhs.py
index 4f7d6355d7d2186fcb8933fdacecff9e5e3a9948..6d0e69627846cfe55bdac20c2d5572e3fbe8b1d0 100644
--- a/hysop/operator/discrete/baroclinic_from_rhs.py
+++ b/hysop/old/operator.old/discrete/baroclinic_from_rhs.py
@@ -6,10 +6,10 @@ Discrete MultiPhase Rot Grad P
from hysop.operator.discrete.discrete import DiscreteOperator
import hysop.numerics.differential_operations as diff_op
from hysop.constants import debug, XDIR, YDIR, ZDIR, np
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.update_ghosts import UpdateGhosts
from hysop.tools.profiler import ftime
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
class BaroclinicFromRHS(DiscreteOperator):
diff --git a/hysop/old/operator.old/discrete/custom.py b/hysop/old/operator.old/discrete/custom.py
new file mode 100644
index 0000000000000000000000000000000000000000..85929894c8827ed5a30e5fd182085b68abe2c715
--- /dev/null
+++ b/hysop/old/operator.old/discrete/custom.py
@@ -0,0 +1,55 @@
+"""User-defined discrete operator"""
+
+from hysop.operator.discrete.discrete import DiscreteOperator
+
+
+class Custom(DiscreteOperator):
+ """User-defined operator: action defined by an external function.
+ """
+ def __init__(self, function, in_fields, out_fields=None, **kwds):
+ """
+
+ Parameters
+ ----------
+ in_fields: list of :class:`~hysop.fields.discrete.DiscreteField`
+ input fields args. for function, see notes below
+ out_fields: list of :class:`~hysop.fields.discrete.DiscreteField`
+ output fields args for function, see notes below
+ function: python function
+ a user defined function, called by this op.apply method.
+
+ Notes
+ -----
+ A function is used to set the behavior of the current operator,
+ during apply call.
+ This function must look like::
+
+ def some_func(simulation, in_fields, out_fields=None, diag=None):
+ # do things ...
+
+ and compute out_fields values.
+ """
+ # callback for apply function
+ self.function = function
+ super(Custom, self).__init__(**kwds)
+ # in/out fields must obviously belong to variables
+ self.input = in_fields
+ if out_fields is not None:
+ self.input += out_fields
+ self.output = out_fields
+ msg = 'Custom: all in/out fields must belong to op variables.'
+ assert set(self.input).intersection(set(self.variables)) == \
+ set(self.input), msg
+ self._in_fields = in_fields
+ self._out_fields = out_fields
+
+ def apply(self, simulation=None):
+ if self._writer is not None:
+ diagnostics = self._writer.buffer
+ else:
+ diagnostics = None
+ self.function(simulation, self._in_fields, self._out_fields,
+ diagnostics)
+ ite = simulation.current_iteration
+ if self._writer is not None and self._writer.do_write(ite):
+ self._writer.write()
diff --git a/hysop/operator/discrete/density.py b/hysop/old/operator.old/discrete/density.py
similarity index 100%
rename from hysop/operator/discrete/density.py
rename to hysop/old/operator.old/discrete/density.py
diff --git a/hysop/operator/discrete/differential.py b/hysop/old/operator.old/discrete/differential.py
similarity index 95%
rename from hysop/operator/discrete/differential.py
rename to hysop/old/operator.old/discrete/differential.py
index 1046ac0c59149090a518170bff6a058235da7b71..a9b550e23eb972a9d8759cf3dc31ae2d6747d725 100644
--- a/hysop/operator/discrete/differential.py
+++ b/hysop/old/operator.old/discrete/differential.py
@@ -1,5 +1,5 @@
# -*- coding: utf-8 -*-
-"""Discretisation of the differential operators (curl, grad ...)
+"""Discretization of the differential operators (curl, grad ...)
..currentmodule hysop.operator.discrete.differential
* :class:`~CurlFFT`,
@@ -15,7 +15,7 @@ from hysop.numerics.differential_operations import Curl, GradV,\
DivAdvection
from abc import ABCMeta, abstractmethod
from hysop.numerics.update_ghosts import UpdateGhosts
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
import hysop.default_methods as default
from hysop.tools.profiler import profile
from hysop.tools.misc import WorkSpaceTools
@@ -116,7 +116,7 @@ class CurlFD(Differential):
self._synchronize = UpdateGhosts(self.invar.topology,
self.invar.nb_components)
self._function = Curl(topo=self.invar.topology, work=self._rwork,
- method=self.method[SpaceDiscretisation])
+ method=self.method[SpaceDiscretization])
def _set_work_arrays(self, rwork=None, iwork=None):
work_prop = Curl.get_work_properties(self.invar.topology)
@@ -145,7 +145,7 @@ class GradFD(Differential):
dim = self.domain.dimension
assert self.outvar.nb_components == dim * self.invar.nb_components
self._function = GradV(topo=self.invar.topology,
- method=self.method[SpaceDiscretisation])
+ method=self.method[SpaceDiscretization])
@debug
@profile
@@ -166,7 +166,7 @@ class DivAdvectionFD(Differential):
self.invar.nb_components)
assert self.outvar.nb_components == 1
self._function = DivAdvection(topo=self.invar.topology,
- method=self.method[SpaceDiscretisation],
+ method=self.method[SpaceDiscretization],
work=self._rwork)
def _set_work_arrays(self, rwork=None, iwork=None):
diff --git a/hysop/old/operator.old/discrete/diffusion_fft.py b/hysop/old/operator.old/discrete/diffusion_fft.py
new file mode 100644
index 0000000000000000000000000000000000000000..a9d19c347ca7ed164d68159a8244594c9a0824db
--- /dev/null
+++ b/hysop/old/operator.old/discrete/diffusion_fft.py
@@ -0,0 +1,134 @@
+# -*- coding: utf-8 -*-
+"""Discrete Diffusion operator using FFTW (fortran)
+
+See :ref:`diffusion` in HySoP user guide.
+
+"""
+try:
+ from hysop.f2hysop import fftw2py
+except ImportError:
+ msg = 'fftw package not available for your hysop install.'
+ msg += 'Try to recompile with WITH_FFTW=ON'
+ raise ImportError(msg)
+
+from hysop.operator.discrete.discrete import DiscreteOperator
+from hysop.constants import debug
+from hysop.tools.profiler import profile
+
+
+class DiffusionFFT(DiscreteOperator):
+ """Discretized Poisson operator based on FFTW.
+ See details in hysop.operator.diffusion.
+
+ """
+ @debug
+ def __init__(self, viscosity, vorticity, **kwds):
+ """Discrete diffusion operator, based on fftw solver.
+
+ Parameters
+ ----------
+ viscosity : double
+ constant viscosity value
+ vorticity : :class:`~hysop.fields.discrete.DiscreteField`
+ vorticity field, in/out parameter
+ kwds : base class arguments
+ """
+ # Discretization of the solution field
+ self.vorticity = vorticity
+ # Viscosity.
+ self.viscosity = viscosity
+ dim = self.vorticity.dimension
+ if dim == 3:
+ self._apply = self.apply_3d
+ elif dim == 2:
+ self._apply = self.apply_2d
+ else:
+ raise AttributeError(dim + "D case not yet implemented.")
+ # Base class initialisation
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ super(DiffusionFFT, self).__init__(variables=[vorticity],
+ **kwds)
+ self.input = [self.vorticity]
+ self.output = [self.vorticity]
+
+ @debug
+ @profile
+ def apply(self, simulation=None):
+ assert simulation is not None, \
+ "Missing dt value for diffusion computation."
+ dt = simulation.time_step
+ ghosts = self.vorticity.topology.ghosts()
+ self._apply(dt, ghosts)
+
+ def apply_2d(self, dt, ghosts):
+ """2d implementation of apply function"""
+ self.vorticity.data = fftw2py.solve_diffusion_2d(
+ self.viscosity * dt, self.vorticity.data, ghosts)
+
+ def apply_3d(self, dt, ghosts):
+ """3d implementation of apply function"""
+ self.vorticity.data[0], self.vorticity.data[1],\
+ self.vorticity.data[2] = \
+ fftw2py.solve_diffusion_3d(self.viscosity * dt,
+ self.vorticity.data[0],
+ self.vorticity.data[1],
+ self.vorticity.data[2],
+ ghosts)
+
+ def finalize(self):
+ """
+ Clean memory (fftw plans and so on)
+ """
+ pass
+ # TODO : fix bug that occurs when several finalize
+ # of fft operators are called.
+ # fftw2py.clean_fftw_solver(self.vorticity.dimension)
+
+
+class CurlAndDiffusionFFT(DiscreteOperator):
+ """Discretized Curl/Diffusion operator based on FFTW.
+ See details in hysop.operator.diffusion.
+
+ """
+ @debug
+ def __init__(self, viscosity, velocity, vorticity, **kwds):
+ """Solve diffusion problem in Fourier
+ domain (velocity curl + diffusion in one shot)
+
+ Parameters
+ ----------
+ viscosity : double
+ constant viscosity value
+ velocity : :class:`~hysop.fields.discrete.DiscreteField`
+ velocity field, input parameter
+ vorticity : :class:`~hysop.fields.discrete.DiscreteField`
+ velocity field, output parameter
+ kwds : base class arguments (vorticity, viscosity ...)
+ """
+ self.velocity = velocity
+ self.vorticity = vorticity
+ self.viscosity = viscosity
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ super(CurlAndDiffusionFFT, self).__init__(
+ variables=[velocity, vorticity], **kwds)
+ self.input = [self.velocity]
+ self.output = [self.vorticity]
+ msge = 'CurlAndDiffusion: only implemented for 3d domain.'
+ assert self.velocity.dimension == 3, msge
+
+ @debug
+ @profile
+ def apply(self, simulation=None):
+ dt = simulation.time_step
+ gh_velo = self.velocity.topology.ghosts()
+ gh_vorti = self.vorticity.topology.ghosts()
+ self.vorticity.data[0], self.vorticity.data[1],\
+ self.vorticity.data[2] = \
+ fftw2py.solve_curl_diffusion_3d(self.viscosity * dt,
+ self.velocity.data[0],
+ self.velocity.data[1],
+ self.velocity.data[2],
+ self.vorticity.data[0],
+ self.vorticity.data[1],
+ self.vorticity.data[2],
+ gh_velo, gh_vorti)
diff --git a/hysop/operator/discrete/discrete.py b/hysop/old/operator.old/discrete/discrete.py
similarity index 91%
rename from hysop/operator/discrete/discrete.py
rename to hysop/old/operator.old/discrete/discrete.py
index 94e5418a36211662fa301e44a68349ff8d862da7..9ab1cfb7a33394c7953a0a782ac9b17e635b11f1 100755
--- a/hysop/operator/discrete/discrete.py
+++ b/hysop/old/operator.old/discrete/discrete.py
@@ -2,7 +2,7 @@
"""
from abc import ABCMeta, abstractmethod
from hysop.constants import debug
-from hysop.methods_keys import GhostUpdate
+from hysop.methods import GhostUpdate
from hysop.tools.profiler import Profiler
@@ -20,8 +20,7 @@ class DiscreteOperator(object):
@debug
@abstractmethod
- def __init__(self, variables, rwork=None, iwork=None, method=None,
- mpi_params=None):
+ def __init__(self, variables, rwork=None, iwork=None, method=None):
"""
Parameters
-----------
@@ -34,9 +33,6 @@ class DiscreteOperator(object):
method : dictionnary, optional
internal solver parameters (discretisation ...).
If None, use default method from hysop.default_method.py.
- mpi_params : :class:`hysop.tools.parameters.MPIParams
- parameters to set mpi context. See Notes below.
-
Attributes
----------
@@ -46,13 +42,6 @@ class DiscreteOperator(object):
input : fields used as input (i.e. read-only)
output : fields used as in/out (i.e. modified during apply call)
- Notes
- -----
-
- Methods : to be done ...
-
- MPIParams : to be done ...
-
"""
if isinstance(variables, list):
# variables
@@ -166,8 +155,7 @@ class DiscreteOperator(object):
def get_extra_args_from_method(op, key, default_value):
- """
- Returns the given extra arguments dictionary from method attribute.
+ """Returns the given extra arguments dictionary from method attributes.
Parameters
-----------
@@ -179,8 +167,18 @@ def get_extra_args_from_method(op, key, default_value):
default value when ExtraArgs is not in op.method or
key is not in op.method[ExtraArgs]
+ Usage
+ -----
+
+ .. code::
+
+ method = {ExtraArgs: {'device_id': 2, user_src: ['./ker.cl']}
+ op = SomeOp(..., method=method)
+ val = get_extra_args_from_method(op, device_id, 6)
+ # set val to 2. If device_id or ExtraArgs does not exist, set val to 8.
+
"""
- from hysop.methods_keys import ExtraArgs
+ from hysop.methods import ExtraArgs
try:
return op.method[ExtraArgs][key]
except KeyError:
diff --git a/hysop/operator/discrete/drag_and_lift.py b/hysop/old/operator.old/discrete/drag_and_lift.py
similarity index 99%
rename from hysop/operator/discrete/drag_and_lift.py
rename to hysop/old/operator.old/discrete/drag_and_lift.py
index dce448e4c06a2520c4e66628439d845136616d04..7ab5e36df6d56f7fd1a7664929f2faa05346b17f 100644
--- a/hysop/operator/discrete/drag_and_lift.py
+++ b/hysop/old/operator.old/discrete/drag_and_lift.py
@@ -3,7 +3,7 @@
"""
from hysop.numerics.update_ghosts import UpdateGhosts
from hysop.operator.discrete.discrete import DiscreteOperator
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from abc import ABCMeta, abstractmethod
from hysop.numerics.utils import Utils
from hysop.constants import XDIR, YDIR, ZDIR
diff --git a/hysop/operator/discrete/energy_enstrophy.py b/hysop/old/operator.old/discrete/energy_enstrophy.py
similarity index 96%
rename from hysop/operator/discrete/energy_enstrophy.py
rename to hysop/old/operator.old/discrete/energy_enstrophy.py
index 06c77227017485e7f467f425ccfb56f415a9fe98..e29c4a5ef4c62d7ba7cbd830e818ad0782f04f31 100644
--- a/hysop/operator/discrete/energy_enstrophy.py
+++ b/hysop/old/operator.old/discrete/energy_enstrophy.py
@@ -3,7 +3,7 @@
"""
from hysop.constants import debug
from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.tools.misc import WorkSpaceTools
@@ -99,10 +99,10 @@ class EnergyEnstrophy(DiscreteOperator):
self.velocity.topology.comm.Allreduce(sendbuff, recvbuff)
# the other way :
#energy = self.velocity.topology.allreduce(local_energy,
- # HYSOP_MPI_REAL,
+ # hysop.core.mpi_REAL,
# op=MPI.SUM)
#enstrophy = self.velocity.topology.allreduce(local_enstrophy,
- # HYSOP_MPI_REAL,
+ # hysop.core.mpi_REAL,
# op=MPI.SUM)
# Update global values
diff --git a/hysop/operator/discrete/forcing.py b/hysop/old/operator.old/discrete/forcing.py
similarity index 100%
rename from hysop/operator/discrete/forcing.py
rename to hysop/old/operator.old/discrete/forcing.py
diff --git a/hysop/operator/discrete/low_pass_filt.py b/hysop/old/operator.old/discrete/low_pass_filt.py
similarity index 100%
rename from hysop/operator/discrete/low_pass_filt.py
rename to hysop/old/operator.old/discrete/low_pass_filt.py
diff --git a/hysop/operator/discrete/monitoringPoints.py b/hysop/old/operator.old/discrete/monitoringPoints.py
similarity index 99%
rename from hysop/operator/discrete/monitoringPoints.py
rename to hysop/old/operator.old/discrete/monitoringPoints.py
index 46fa8cd6be11250fa67da8869d9c0f0f53662bd2..ca7f83bfdfa5a25e843a71abce76b218b5424b0e 100644
--- a/hysop/operator/discrete/monitoringPoints.py
+++ b/hysop/old/operator.old/discrete/monitoringPoints.py
@@ -6,7 +6,7 @@ at a particular monitoring point in the wake
"""
from hysop.constants import debug
from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import scitools.filetable as ft
import numpy as np
from hysop.operator.discrete.discrete import DiscreteOperator
diff --git a/hysop/operator/discrete/multiphase_gradp.py b/hysop/old/operator.old/discrete/multiphase_gradp.py
similarity index 97%
rename from hysop/operator/discrete/multiphase_gradp.py
rename to hysop/old/operator.old/discrete/multiphase_gradp.py
index 91ab67e1226de7961c3ce72ce5a2b1320527f69c..f9f7318e08a51f14c2996d1fe75d5bf6d9bba46f 100644
--- a/hysop/operator/discrete/multiphase_gradp.py
+++ b/hysop/old/operator.old/discrete/multiphase_gradp.py
@@ -6,9 +6,9 @@ Discrer operator of the pressure gradient in a multiphasic flow.
from hysop.operator.discrete.discrete import DiscreteOperator
import hysop.numerics.differential_operations as diff_op
from hysop.constants import debug, XDIR, YDIR, ZDIR, np
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.update_ghosts import UpdateGhosts
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.operator.discrete.discrete import get_extra_args_from_method
@@ -58,7 +58,7 @@ class GradP(DiscreteOperator):
self._gradOp = diff_op.GradS(
self.velocity.topology,
indices=self.velocity.topology.mesh.compute_index,
- method=self.method[SpaceDiscretisation])
+ method=self.method[SpaceDiscretization])
# Gravity vector
self._gravity = npw.asrealarray(
diff --git a/hysop/operator/discrete/multiresolution_filter.py b/hysop/old/operator.old/discrete/multiresolution_filter.py
similarity index 75%
rename from hysop/operator/discrete/multiresolution_filter.py
rename to hysop/old/operator.old/discrete/multiresolution_filter.py
index 4639aa25b23190a2f26ac06136e84952ccbb3b87..22eda6c63de230c0599eeeaa4b1dc12d24181eba 100644
--- a/hysop/operator/discrete/multiresolution_filter.py
+++ b/hysop/old/operator.old/discrete/multiresolution_filter.py
@@ -1,37 +1,47 @@
+"""Filter values from a fine grid to a coarse grid.
+
"""
-@file multiresolution_filter.py
-Filter values from a fine grid to a coarse grid.
-"""
-from hysop.constants import debug, np, HYSOP_MPI_REAL
+from hysop.constants import debug, np, hysop.core.mpi_REAL
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
-from hysop.methods_keys import Remesh
-from hysop.methods import Rmsh_Linear, L2_1
-from hysop.numerics.remeshing import RemeshFormula
+from hysop.tools.numpywrappers import npw
+from hysop.methods import Remesh
+from hysop.numerics.remeshing import RemeshFormula, Linear, L2_1
class FilterFineToCoarse(DiscreteOperator):
+ """Discretized operator for filtering from fine to coarse grid.
"""
- Discretized operator for filtering from fine to coarse grid.
- """
+
+ authorized_methods = [Linear, L2_1]
+
def __init__(self, field_in, field_out, **kwds):
+ """
+ Parameters
+ ----------
+ field_in, field_out : lists of
+ :class:`~hysop.fields.discrete.DiscreteFields`
+ kwds : base class parameters
+
+ """
self.field_in, self.field_out = field_in, field_out
+ # Note : since discrete operators are usually
+ # supposed to work on one single topology,
+ # only field_in is passed to base class.
+
+ # mesh_out must be set before base class init,
+ # to set rwork properly
+
+ self._mesh_out = self.field_out[0].topology.mesh
+ self.gh_out = self.field_out[0].topology.ghosts()
super(FilterFineToCoarse, self).__init__(
variables=self.field_in, **kwds)
self.input = [self.field_in]
self.output = [self.field_out]
self._mesh_in = self.field_in[0].topology.mesh
- self._mesh_out = self.field_out[0].topology.mesh
- self.gh_out = self.field_out[0].topology.ghosts()
gh_in = self.field_in[0].topology.ghosts()
- if self.method[Remesh] is Rmsh_Linear:
- assert (self.gh_out >= 1).all()
- elif self.method[Remesh] is L2_1:
- assert (self.gh_out >= 2).all()
- else:
- raise ValueError('This scheme (' + self.method[Remesh].__name__ +
- ') is not yet implemented for filter.')
+ self._rmsh_method = self._check_method()
+
resol_in = self._mesh_in.resolution - 2 * gh_in
resol_out = self._mesh_out.resolution - 2 * self.gh_out
pts_per_cell = resol_in / resol_out
@@ -91,24 +101,6 @@ class FilterFineToCoarse(DiscreteOperator):
self._sl_coarse = []
# Weights associated to offsets in coarse grid
self._w_coarse = []
- try:
- assert issubclass(self.method[Remesh], RemeshFormula), \
- "This operator works with a RemeshingFormula."
- self._rmsh_method = self.method[Remesh]()
- except KeyError:
- self._rmsh_method = Rmsh_Linear()
- if isinstance(self._rmsh_method, Rmsh_Linear):
- # Linear interpolation
- assert np.all(self.gh_out >= 1), "Output data must have at least" \
- "1 ghosts in all directions (" + str(self.gh_out) + " given)"
- elif isinstance(self._rmsh_method, L2_1):
- # L2_1 interpolation
- assert np.all(self.gh_out >= 2), "Output data must have at least" \
- "2 ghosts in all directions (" + str(self.gh_out) + " given)"
- else:
- raise ValueError("The multiresolution filter is implemented for " +
- "Linear or L2_1 interpolation (" +
- str(self.method[Remesh]) + " given).")
for i_x in xrange(len(self._rmsh_method.weights)):
for i_y in xrange(len(self._rmsh_method.weights)):
for i_z in xrange(len(self._rmsh_method.weights)):
@@ -129,16 +121,44 @@ class FilterFineToCoarse(DiscreteOperator):
self._rmsh_method.shift + i_z,
None)
))
- self._w_coarse.append(
- (i_x, i_y, i_z))
- if self._rwork is None:
- self._rwork = npw.zeros(resol_out)
+ self._w_coarse.append((i_x, i_y, i_z))
+
+ def _set_work_arrays(self, rwork=None, iwork=None):
+ subshape = tuple(self._mesh_out.resolution - 2 * self.gh_out)
+ subsize = np.prod(subshape)
+ if rwork is None:
+ self._rwork = [npw.zeros(subshape)]
+ else:
+ self._rwork = []
+ assert isinstance(rwork, list), 'rwork must be a list.'
+ assert len(rwork) >= 1, 'Wrong length for work arrays list.'
+ for wk in rwork[:1]:
+ assert wk.size >= subsize
+ self._rwork.append(wk.ravel()[:subsize].reshape(subshape))
+
+ def _check_method(self):
+ """Check remeshing method parameters.
+ """
+ try:
+ assert issubclass(self.method[Remesh], RemeshFormula), \
+ "This operator works with a RemeshingFormula."
+ rmsh_method = self.method[Remesh]()
+ except KeyError:
+ rmsh_method = Linear()
+
+ msg = 'Ghost layer must be increased for the chosen scheme.'
+ assert (self.gh_out >=
+ self.method[Remesh].ghosts_layer_size).all(), msg
+ msg = 'Remesh scheme not yet implemented.'
+ assert self.method[Remesh] in self.authorized_methods, msg
+ return rmsh_method
@debug
@profile
def apply(self, simulation=None):
assert simulation is not None, \
"Missing simulation value for computation."
+ wk = self._rwork[0]
for v_in, v_out in zip(self.field_in, self.field_out):
for d in xrange(v_in.nb_components):
for sl_coarse, iw_fun in zip(self._sl_coarse, self._w_coarse):
@@ -150,14 +170,14 @@ class FilterFineToCoarse(DiscreteOperator):
iw_fun[2], self.dist_coords[2], self._work_weight[2])
# Loop over fine grid points sharing the same coarse cell
for sl in self._sl:
- self._rwork[...] = v_in[d][sl]
+ wk[...] = v_in[d][sl]
# Compute weights
- self._rwork[...] *= self._work_weight[0][sl[0], :, :]
- self._rwork[...] *= self._work_weight[1][:, sl[1], :]
- self._rwork[...] *= self._work_weight[2][:, :, sl[2]]
- self._rwork[...] *= self.scale_factor
+ wk[...] *= self._work_weight[0][sl[0], :, :]
+ wk[...] *= self._work_weight[1][:, sl[1], :]
+ wk[...] *= self._work_weight[2][:, :, sl[2]]
+ wk[...] *= self.scale_factor
# Add contributions in data
- v_out[d][sl_coarse] += self._rwork[...]
+ v_out[d][sl_coarse] += wk[...]
self._exchange_ghosts()
def _exchange_ghosts_local_d(self, d):
@@ -167,8 +187,12 @@ class FilterFineToCoarse(DiscreteOperator):
sl_gh = [slice(None) for _ in xrange(self._dim)]
sl[d] = slice(1 * s_gh, 2 * s_gh)
sl_gh[d] = slice(-1 * s_gh, None)
+ # Add ghost points values at the end of the domain in direction
+ # d into corresponding points at the beginning of the domain.
for v_out in self.field_out:
v_out.data[0][tuple(sl)] += v_out.data[0][tuple(sl_gh)]
+ # Add ghost points values at the beginning of the domain in direction
+ # d into corresponding points at the end of the domain.
sl[d] = slice(-2 * s_gh, -1 * s_gh)
sl_gh[d] = slice(0, 1 * s_gh)
for v_out in self.field_out:
@@ -199,17 +223,17 @@ class FilterFineToCoarse(DiscreteOperator):
l_rk = v_out.topology.neighbours[0, d - first_cut_dir]
recv_r = self._comm.Irecv(
[self._gh_from_r[d], self._gh_from_r[d].size,
- HYSOP_MPI_REAL],
+ hysop.core.mpi_REAL],
source=r_rk, tag=1234 + r_rk + 19 * d)
recv_l = self._comm.Irecv(
[self._gh_from_l[d], self._gh_from_l[d].size,
- HYSOP_MPI_REAL],
+ hysop.core.mpi_REAL],
source=l_rk, tag=4321 + l_rk + 17 * d)
send_l = self._comm.Issend(
- [self._gh_to_l[d], self._gh_to_l[d].size, HYSOP_MPI_REAL],
+ [self._gh_to_l[d], self._gh_to_l[d].size, hysop.core.mpi_REAL],
dest=l_rk, tag=1234 + self._comm_rank + 19 * d)
send_r = self._comm.Issend(
- [self._gh_to_r[d], self._gh_to_r[d].size, HYSOP_MPI_REAL],
+ [self._gh_to_r[d], self._gh_to_r[d].size, hysop.core.mpi_REAL],
dest=r_rk, tag=4321 + self._comm_rank + 17 * d)
send_r.wait()
recv_l.wait()
diff --git a/hysop/old/operator.old/discrete/particle_advection.py b/hysop/old/operator.old/discrete/particle_advection.py
new file mode 100644
index 0000000000000000000000000000000000000000..58847e118d7d5121954e2591008f9b3bbeea5dc0
--- /dev/null
+++ b/hysop/old/operator.old/discrete/particle_advection.py
@@ -0,0 +1,305 @@
+"""Advection solver, particular method, pure-python version
+
+"""
+from hysop.constants import debug, WITH_GUESS, HYSOP_REAL, HYSOP_INTEGER, EPS
+from hysop.methods import TimeIntegrator, Interpolation, Remesh
+from hysop.operator.discrete.discrete import DiscreteOperator
+from hysop.default_methods import ADVECTION
+import numpy as np
+from hysop.numerics.remeshing import Remeshing
+from hysop.tools.profiler import profile
+from hysop.tools.misc import WorkSpaceTools
+from hysop.tools.numpywrappers import npw
+
+
+class ParticleAdvection(DiscreteOperator):
+ """
+ Particular method for advection of a list of fields in a given direction.
+ """
+
+ @debug
+ def __init__(self, velocity, fields_on_grid, direction, **kwds):
+ """
+ Parameters
+ ----------
+ velocity : :class:`~hysop.fields.discrete.DiscreteField`
+ advection velocity (discretized)
+ fields_on_grid : list of :class:`~hysop.fields.discrete.DiscreteField`
+ discrete field(s) to be advected
+ direction : int
+ advection direction
+ kwds : extra parameters for base class
+
+ """
+ msg = 'Scales advection init : variables parameter is useless.'
+ msg += 'See user guide for details on the proper'
+ msg += ' way to build the operator.'
+ assert 'variables' not in kwds, msg
+ # Advection velocity
+ self.velocity = velocity
+
+ # set variables list ...
+ variables = [self.velocity]
+ if not isinstance(fields_on_grid, list):
+ self.fields_on_grid = [fields_on_grid]
+ else:
+ self.fields_on_grid = fields_on_grid
+ variables += self.fields_on_grid
+
+ if 'method' not in kwds:
+ kwds['method'] = ADVECTION
+ # number of components of the RHS (see time integrator)
+ self._rhs_size = 1
+ # dictionnary of internal buffers used
+ # to save fields values on particles
+ # --> link to _rwork
+ self.fields_on_part = None
+ # buffers for numerical methods
+ # --> just link to _rwork/_iwork components
+ self._rw_interp = None
+ self._iw_interp = None
+ self._rw_integ = None
+ self._rw_remesh = None
+ self._iw_remesh = None
+ # buffer used to save particles position
+ # --> link to _rwork
+ self.part_positions = None
+
+ super(ParticleAdvection, self).__init__(variables=variables, **kwds)
+
+ self.input = self.variables
+ self.output = [df for df in self.variables if df is not self.velocity]
+ self.direction = direction
+ # time integrator
+ self.num_advec = None
+ # remeshing method
+ self.num_remesh = None
+ # build and configure numerical methods
+ self._configure_numerical_methods()
+ # minimal value required for advected field
+ # on grid point to add a particle.
+ # If None, particles everywhere.
+ self._threshold = None
+ self._init_particles_on_grid = self._init_particles_everywhere
+ if self._threshold is not None:
+ self._init_particles_on_grid = self._init_particles_with_threshold
+
+ def _configure_numerical_methods(self):
+ """Function to set the numerical method for python operator and link them
+ to the proper working arrays.
+
+ Warning : must be called after _set_work_arrays
+ """
+
+ # --- numerical interpolation operator ---
+ # discrete field that will be interpolated
+ vd = self.velocity.data[self.direction]
+ # first field topology as reference
+ topo_fields = self.fields_on_grid[0].topology
+ # velocity 'grid'
+ topo_velo = self.velocity.topology
+ # -- Interpolation scheme --
+ # to interpolate velocity from topo_velo
+ # to the grid on which particles are initialized.
+ num_interpolate = \
+ self.method[Interpolation](vd, direction=self.direction,
+ topo_source=topo_velo,
+ topo_target=topo_fields,
+ rwork=self._rw_interp,
+ iwork=self._iw_interp)
+
+ # -- time integration --
+ # advection is performed only on 'computational points',
+ # not on ghosts
+ ic = topo_fields.mesh.compute_index
+ self.num_advec = self.method[TimeIntegrator](
+ self._rhs_size, rwork=self._rw_integ,
+ f=num_interpolate,
+ topo=topo_fields,
+ optim=WITH_GUESS,
+ indices=ic)
+
+ # -- remesh --
+ self.num_remesh = Remeshing(self.method[Remesh],
+ topo_source=topo_fields,
+ direction=self.direction,
+ rwork=self._rw_remesh,
+ iwork=self._iw_remesh)
+
+ def _set_work_arrays(self, rwork=None, iwork=None):
+
+ # Find number and shape of required work arrays
+
+ # topologies for advected field(s) grid
+ topo_fields = self.fields_on_grid[0].topology
+ # -- work arrays properties for interpolation --
+ # work arrays shape depends on the targeted grid, i.e. topo_fields.
+ interp_wp = self.method[Interpolation].get_work_properties(topo_fields)
+ interp_iwork_length = len(interp_wp['iwork'])
+ interp_rwork_length = len(interp_wp['rwork'])
+
+ # -- work arrays properties for time-integrator --
+ # depends on topo_fields.
+ ti_wp = self.method[TimeIntegrator].get_work_properties(
+ self._rhs_size, topo_fields)
+ ti_rwork_length = len(ti_wp['rwork'])
+ # -- work arrays properties for remeshing scheme --
+ # depends on topo_fields.
+ remesh_wp = Remeshing.get_work_properties(topo_fields)
+ remesh_iwork_length = len(remesh_wp['iwork'])
+ remesh_rwork_length = len(remesh_wp['rwork'])
+
+ # -- Find out the number of required work arrays --
+ # Interpolation and odesolver work arrays must be different
+ # but after interpolation/advection, work arrays can be reused
+ # by remeshing. So the number of required work arrays is
+ # equal to
+ # max(nb works_for_time_integrator + nb work_for_interpolation,
+ # nb works_for_remesh)
+ rwork_length = max(remesh_rwork_length,
+ ti_rwork_length + interp_rwork_length)
+ iwork_length = max(interp_iwork_length, remesh_iwork_length)
+
+ # -- Finally, particles positions and fields on particles
+ # values will also be in work array.
+ ppos_index = rwork_length
+ # max number of components for advected fields
+ nbc = max([f.nb_components for f in self.fields_on_grid])
+ rwork_length += nbc
+ rwork_length += 1 # work array for positions
+
+ # -- rwork organisation --
+
+ # rw = [ | rw_interp | rw_time_int | part_pos | fields_on_part |]
+ # | rw_remesh | ... |]
+
+ # work array shape depends on the time integrator
+ # interpolation scheme and remeshing scheme
+
+ # check and/or allocate work arrays according to properties above
+ # reshape stuff is done inside numerical methods.
+ # Here we just allocate flat memory.
+ subshape_field = tuple(topo_fields.mesh.compute_resolution)
+ subsize_interp_ti = interp_wp['rwork'] + ti_wp['rwork']
+ subsize_remesh = remesh_wp['rwork']
+ # list of shapes for rwork arrays (!flat arrays!)
+ subsize_rw = max(subsize_interp_ti, subsize_remesh)
+ # list of shapes for iwork arrays (!flat arrays!)
+ subsize_iw = max(interp_wp['iwork'], remesh_wp['iwork'])
+ # one array for particles positions
+ # and arrays for fields on particles
+ for i in xrange(nbc + 1):
+ subsize_rw.append((np.prod(subshape_field), ))
+
+ # Build iwork and rwork lists
+ self._rwork = WorkSpaceTools.check_work_array(rwork_length, subsize_rw,
+ rwork, HYSOP_REAL)
+ self._iwork = WorkSpaceTools.check_work_array(iwork_length, subsize_iw,
+ iwork, HYSOP_INTEGER)
+
+ # -- set connections for remesh, ti and interp methods --
+ # interpolation
+ self._rw_interp = [self._rwork[i] for i in xrange(interp_rwork_length)]
+ self._iw_interp = [self._iwork[i] for i in xrange(interp_iwork_length)]
+ assert np.asarray([npw.arrays_share_data(self._rw_interp[i],
+ self._rwork[i])
+ for i in xrange(interp_rwork_length)]).all()
+
+ # time integration
+ self._rw_integ = [self._rwork[i]
+ for i in xrange(interp_rwork_length,
+ interp_rwork_length +
+ ti_rwork_length)]
+ # remesh
+ self._rw_remesh = [self._rwork[i] for i in xrange(remesh_rwork_length)]
+ self._iw_remesh = [self._iwork[i] for i in xrange(remesh_iwork_length)]
+
+ # --- links to work for particles positions buffers ---
+ self._work_part_pos = ppos_index
+ self.part_positions = WorkSpaceTools.check_work_array(
+ 1, subshape_field, [self._rwork[ppos_index]])
+ assert npw.arrays_share_data(self.part_positions[0],
+ self._rwork[ppos_index])
+
+ # --- links to buffers for fields on particles ---
+ ppos_index += 1
+ self.fields_on_part = WorkSpaceTools.check_work_array(
+ nbc, subshape_field,
+ [self._rwork[i] for i in xrange(ppos_index, ppos_index + nbc)])
+ assert np.asarray(
+ [npw.arrays_share_data(self.fields_on_part[i],
+ self._rwork[ppos_index + i])
+ for i in xrange(nbc)]).all()
+
+ @debug
+ @profile
+ def apply(self, simulation=None):
+ #, dt_coeff=1., split_id=0, old_dir=0):
+ """
+ Advection algorithm:
+ - initialize particles and fields with their values on the grid.
+ --> x_p, f_p
+ - compute particle positions in splitting direction,
+ --> solve dx_p / dt = v_p
+ - remesh fields from particles to grid
+ --> f_g
+ """
+ assert simulation is not None, \
+ 'Simulation parameter is missing.'
+ t, dt = simulation.time, simulation.sub_step
+
+ # -- Initialize particles on the grid --
+ self._init_particles_on_grid()
+
+ # -- Advect particles --
+ # RHS of odesolver must be computed and save in odesolver._rwork[0]
+ # Notes :
+ # - ghost-synchro of the rhs (if needed) is done by the odesolver
+ # - interpolation of velocity field from grid to particles is done
+ # 'inside' the ode solver (rhs = interpolation scheme)
+ self.num_advec.rwork[0][...] = self.velocity.data[self.direction][...]
+ self.part_positions = self.num_advec(
+ t, self.part_positions, dt, result=self.part_positions)
+
+ # -- Remesh --
+ for fg in self.fields_on_grid:
+ # Initialize fields on particles with fields on grid values --
+ for d in xrange(fg.nb_components):
+ self.fields_on_part[d][...] = fg[d][...]
+ # Remesh all components of the field
+ fg = self.num_remesh(ppos=self.part_positions,
+ pscal=self.fields_on_part, result=fg)
+
+ def _init_particles_everywhere(self):
+ """Initialize particles on grid points
+ """
+ # indices of computation points (i.e. no ghosts)
+ topo = self.fields_on_grid[0].topology
+ ic = topo.mesh.compute_index
+ self.part_positions[0][...] = \
+ topo.mesh.coords[self.direction][ic[self.direction]] + 10 * EPS
+ # remark : we shift particles with EPS to avoid
+ # the case where, because of floating point precision
+ # xp (particle position) < xg (grid position),
+ # with xp - xg very small. If this happens,
+ # left point of xp will be xg - 1 rather than xg
+ # which is not what is expected.
+
+ def _init_particles_with_threshold(self):
+ """"Initialize particles on grid points where
+ advected field value is greater than a given threshold
+ """
+ raise AttributeError("Not yet implemented")
+ # first field is used as reference to check threshold
+ ref_field = self.fields_on_grid[0].data
+ topo = self.fields_on_grid[0].topology
+ ic = topo.mesh.compute_index
+ self._rwork[0][...] = 0.
+ for i in xrange(len(ref_field)):
+ self._rwork[0][...] += ref_field[i][ic] ** 2
+ self._rwork[0][...] = np.sqrt(self._rwork[0])
+ ipart = np.where(self._rwork < self._threshold)
+ part_shape = ref_field[0][ipart].shape
+ self.part_positions = WorkSpaceTools.check_work_array(
+ 1, part_shape, self._rwork[self._work_part_pos])
+ self.part_positions[0][...] = topo.mesh.coords[self.direction][ipart]
diff --git a/hysop/operator/discrete/particle_advection_dir.py b/hysop/old/operator.old/discrete/particle_advection_dir.py
similarity index 97%
rename from hysop/operator/discrete/particle_advection_dir.py
rename to hysop/old/operator.old/discrete/particle_advection_dir.py
index 552a3104963930ac3c090a684125230fbc778821..6227775bd45e46678adbe0885d434bcd5d007c5e 100644
--- a/hysop/operator/discrete/particle_advection_dir.py
+++ b/hysop/old/operator.old/discrete/particle_advection_dir.py
@@ -3,10 +3,10 @@
Base for directionally splitted advection solvers (pure-python and GPU version).
"""
from hysop.constants import debug, WITH_GUESS, HYSOP_REAL, HYSOP_INTEGER, SIZEOF_HYSOP_REAL, SIZEOF_HYSOP_INTEGER, ORDER
-from hysop.methods_keys import TimeIntegrator, Interpolation, Remesh, Support
+from hysop.methods import TimeIntegrator, Interpolation, Remesh, Support
from hysop.operator.discrete.discrete import DiscreteOperator
-from hysop.codegen.structs.mesh_info import MeshDir
-import hysop.tools.numpywrappers as npw
+from hysop.backend.device.codegen.structs.mesh_info import MeshDirection
+from hysop.tools.numpywrappers import npw
import hysop.default_methods as default
import numpy as np
from hysop.numerics.remeshing import Remeshing
@@ -37,7 +37,7 @@ class ParticleAdvectionDir(DiscreteOperator):
raise ValueError(msg)
if not isinstance(advected_fields, list):
advected_fields = [advected_fields]
- if not isinstance(direction, int) or (direction not in MeshDir.entries()):
+ if not isinstance(direction, int) or (direction not in MeshDirection.entries()):
raise ValueError("Invalid direction value '{}'.".format(direction))
if ('iwork' in kwds) or ('rwork' in kwds):
msg='rwork or iwork parameters are useless in {}.'.format(cls)
diff --git a/hysop/operator/discrete/penalization.py b/hysop/old/operator.old/discrete/penalization.py
similarity index 100%
rename from hysop/operator/discrete/penalization.py
rename to hysop/old/operator.old/discrete/penalization.py
diff --git a/hysop/operator/discrete/poisson_fft.py b/hysop/old/operator.old/discrete/poisson_fft.py
similarity index 64%
rename from hysop/operator/discrete/poisson_fft.py
rename to hysop/old/operator.old/discrete/poisson_fft.py
index 3027058fd38e52f41f047fc9b46a61bdfe3ac1d5..7d9050b670c60ef738a3fc93b38a0b4dfcf1192b 100644
--- a/hysop/operator/discrete/poisson_fft.py
+++ b/hysop/old/operator.old/discrete/poisson_fft.py
@@ -1,42 +1,48 @@
# -*- coding: utf-8 -*-
"""Discrete operator for Poisson problem (fftw based)
+
+.. currentmodule hysop.operator.discrete
+
"""
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.operator.discrete.reprojection import Reprojection
from hysop.constants import debug
from hysop.tools.profiler import profile
-from hysop import __FFTW_ENABLED__
-
-if __FFTW_ENABLED__:
+try:
from hysop.f2hysop import fftw2py
-
+except ImportError:
+ msg = 'fftw package not available for your hysop install.'
+ msg += 'Try to recompile with WITH_FFTW=ON'
+ raise ImportError(msg)
class PoissonFFT(DiscreteOperator):
- """
- Discretized Poisson operator based on FFTW.
+ """Discretized Poisson operator based on FFTW.
See details in hysop.operator.poisson
"""
@debug
def __init__(self, output_field, input_field, projection=None,
- filterSize=None, correction=None, formulation=None, **kwds):
- """
- Constructor.
- @param[out] output_field : discretization of the solution field
- @param[in] input_field : discretization of the RHS (mind the minus rhs!)
- @param projection : if None, no projection. Else:
- - either the value of the frequency of reprojection, never updated.
- - or Reprojection discrete operator. In that case, a criterion
- depending on the input_field will be computed at each time step, if
- criterion > threshold, then frequency projection is active.
- @param filterSize :
- @param correction : operator used to shift output_field according
- to a given input (fixed) flowrate.
- See hysop.operator.velocity_correction.
- Default = None.
+ filter_size=None, correction=None, formulation=None, **kwds):
+ """Poisson operator, incompressible flow.
+
+ Parameters
+ ----------
+ output_field : :class:`~hysop.fields.discrete.DiscreteField
+ solution field
+ input_field : :class:`~hysop.fields.discrete.DiscreteField
+ right-hand side
+ projection : double or tuple, optional
+ projection criterion, see notes below.
+ filter_size :
+ correction : :class:`~velocity_correction.VelocityCorrection_D
+ operator used to shift output_field according
+ to a given input (fixed) flowrate.
+ See hysop.operator.velocity_correction.
+ formulation :
+ kwds : base class parameters.
"""
# Base class initialisation
assert 'variables' not in kwds, 'variables parameter is useless.'
@@ -49,11 +55,13 @@ class PoissonFFT(DiscreteOperator):
# Solenoidal projection of input_field ?
self.projection = projection
# Filter size array = domainLength/(CoarseRes-1)
- self.filterSize = filterSize
+ self.filter_size = filter_size
# If 2D problem, input_field must be a scalar
- self.dim = self.output_field.domain.dimension
- if self.dim == 2:
+ self._dim = self.output_field.domain.dimension
+ if self._dim == 2:
assert self.input_field.nb_components == 1
+ assert (self._dim >= 2),\
+ "Wrong problem dimension: only 2D and 3D cases are implemented."
self.correction = correction
self.formulation = formulation
self.input = [self.input_field]
@@ -67,26 +75,24 @@ class PoissonFFT(DiscreteOperator):
self._select_solve()
def _select_solve(self):
-
"""
TODO : add pressure solver selection
f(output.nbComponents) + pb type 'pressure-poisson'
"""
-
- # Multiresolution ?
- multires = self.output_field.topology.mesh != self.input_field.topology.mesh
-
+ # Multiresolution?
+ multires = \
+ self.output_field.topology.mesh != self.input_field.topology.mesh
# connexion to the required apply function
- if self.dim == 2:
- self._solve = self._solve2D
- elif self.dim == 3:
+ if self._dim == 2:
+ self._solve = self._solve_2d
+ elif self._dim == 3:
# If there is a projection, input_field is also an output
if self.projection is not None:
self.output.append(self.input_field)
if multires:
- self._solve = self._solve3D_proj_multires
+ self._solve = self._solve_3d_proj_multires
else:
- self._solve = self._solve3D_proj
+ self._solve = self._solve_3d_proj
if isinstance(self.projection, Reprojection):
self.do_projection = self.do_projection_with_op
@@ -95,42 +101,34 @@ class PoissonFFT(DiscreteOperator):
else:
if multires:
- self._solve = self._solve3D_multires
+ self._solve = self._solve_3d_multires
elif self.formulation is not None:
self._solve = self._solve_3d_scalar_fd
else:
- self._solve = self._solve3D
- else:
- raise AttributeError('Not implemented for 1D problems.')
+ self._solve = self._solve_3d
- # Operator to shift output_field according to an input required flowrate
+ # swtich to the proper solving method (with or without correction)
if self.correction is not None:
self.solve = self._solve_and_correct
else:
self.solve = self._solve
-
- if not __FFTW_ENABLED__:
- self.solve = self._solve_error
-
- def _solve_error():
- """Error message when fftw fortran interface is not available.
- """
- msg = "Warning: fftw fortran interface is not available,"
- msg += "the fft solver does nothing."
- raise NotImplementedError('msg')
def do_projection_with_op(self, simu):
+ """Compute projection criterion and return
+ true if projection is needed.
+ """
self.projection.apply(simu)
ite = simu.current_iteration
return self.projection.do_projection(ite)
def do_projection_no_op(self, simu):
+ """return true if projection is needed.
+ """
ite = simu.current_iteration
return ite % self.projection == 0
- def _solve2D(self, simu=None):
- """
- Solve 2D poisson problem
+ def _solve_2d(self, simu=None):
+ """ Solve 2D poisson problem, no projection, no correction.
"""
ghosts_v = self.output_field.topology.ghosts()
ghosts_w = self.input_field.topology.ghosts()
@@ -141,75 +139,75 @@ class PoissonFFT(DiscreteOperator):
ghosts_w, ghosts_v)
def _project(self):
- """
- apply projection onto input_field
+ """apply projection onto input_field
"""
ghosts_w = self.input_field.topology.ghosts()
self.input_field.data[0], self.input_field.data[1], \
self.input_field.data[2] = \
- fftw2py.projection_om_3d(self.input_field.data[0],
- self.input_field.data[1],
- self.input_field.data[2], ghosts_w)
+ fftw2py.projection_om_3d(self.input_field.data[0],
+ self.input_field.data[1],
+ self.input_field.data[2], ghosts_w)
- def _solve3D_multires(self, simu=None):
- """
- 3D, multiresolution
+ def _solve_3d_multires(self, simu=None):
+ """3D, multiresolution
"""
# Projects input_field values from fine to coarse grid
# in frequencies space by nullifying the smallest modes
vortFilter = npw.copy(self.input_field.data)
vortFilter[0], vortFilter[1], vortFilter[2] = \
- fftw2py.multires_om_3d(self.filterSize[0], self.filterSize[1],
- self.filterSize[2], self.input_field.data[0],
- self.input_field.data[1],
- self.input_field.data[2])
+ fftw2py.multires_om_3d(self.filter_size[0], self.filter_size[1],
+ self.filter_size[2],
+ self.input_field.data[0],
+ self.input_field.data[1],
+ self.input_field.data[2])
# Solves Poisson equation using filter input_field
ghosts_v = self.output_field.topology.ghosts()
ghosts_w = self.input_field.topology.ghosts()
- self.output_field.data[0], self.output_field.data[1], self.output_field.data[2] = \
+ self.output_field.data[0], self.output_field.data[1],\
+ self.output_field.data[2] = \
fftw2py.solve_poisson_3d(vortFilter[0], vortFilter[1],
vortFilter[2], self.output_field.data[0],
self.output_field.data[1],
self.output_field.data[2],
ghosts_w, ghosts_v)
- def _solve3D_proj_multires(self, simu):
- """
- 3D, multiresolution, with projection
+ def _solve_3d_proj_multires(self, simu):
+ """3D, multiresolution, with projection
"""
if self.do_projection(simu):
self._project()
- self._solve3D_multires()
+ self._solve_3d_multires()
- def _solve3D_proj(self, simu):
- """
- 3D, with projection
+ def _solve_3d_proj(self, simu):
+ """3D, with projection
"""
if self.do_projection(simu):
self._project()
- self._solve3D()
+ self._solve_3d()
- def _solve3D(self,simu=None):
- """
- Basic solve
+ def _solve_3d(self,simu=None):
+ """Basic solve
"""
# Solves Poisson equation using usual input_field
ghosts_v = self.output_field.topology.ghosts()
ghosts_w = self.input_field.topology.ghosts()
- self.output_field.data[0], self.output_field.data[1], self.output_field.data[2] =\
+ self.output_field.data[0], self.output_field.data[1],\
+ self.output_field.data[2] =\
fftw2py.solve_poisson_3d(self.input_field.data[0],
self.input_field.data[1],
self.input_field.data[2],
self.output_field.data[0],
self.output_field.data[1],
- self.output_field.data[2], ghosts_w, ghosts_v)
+ self.output_field.data[2],
+ ghosts_w, ghosts_v)
def _solve_and_correct(self, simu):
+ """Solve Poisson problem and apply correction on velocity.
+ """
self._solve(simu.current_iteration)
self.correction.apply(simu)
-
def _solve_3d_scalar_fd(self, simu=None):
"""solve poisson-pressure like problem
input = 3D vector field
@@ -223,7 +221,7 @@ class PoissonFFT(DiscreteOperator):
ghosts = self.output_field.topology.ghosts()
self.output_field.data[0] = fftw2py.pressure_3d(
self.input_field.data[0], ghosts)
-
+
def _solve_3d_scalar(self, simu=None):
"""solve poisson-pressure like problem
input = 3D vector field
diff --git a/hysop/operator/discrete/profiles.py b/hysop/old/operator.old/discrete/profiles.py
similarity index 94%
rename from hysop/operator/discrete/profiles.py
rename to hysop/old/operator.old/discrete/profiles.py
index 97e1a3682ab610f0e5e47577e42649eb3067b8a2..f34e4cd6ebb612577652fbe44e879d7e156a59ff 100644
--- a/hysop/operator/discrete/profiles.py
+++ b/hysop/old/operator.old/discrete/profiles.py
@@ -5,7 +5,7 @@ Compute and print velo/vorti profiles
"""
from hysop.constants import debug
from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import scitools.filetable as ft
import numpy as np
from hysop.operator.discrete.discrete import DiscreteOperator
@@ -87,17 +87,6 @@ class Profiles(DiscreteOperator):
assert self._rwork[0].shape == shape_v
assert self._rwork[1].shape == shape_w
- def get_work_properties(self):
-
- v_ind = self.velocity.topology.mesh.compute_index
- w_ind = self.vorticity.topology.mesh.compute_index
- shape_v = self.velocity.data[0][v_ind].shape
- shape_w = self.velocity.data[0][w_ind].shape
- if shape_v == shape_w:
- return {'rwork': [shape_v], 'iwork': None}
- else:
- return {'rwork': [shape_v, shape_w], 'iwork': None}
-
@debug
@profile
def apply(self, simulation=None):
diff --git a/hysop/operator/discrete/reprojection.py b/hysop/old/operator.old/discrete/reprojection.py
similarity index 78%
rename from hysop/operator/discrete/reprojection.py
rename to hysop/old/operator.old/discrete/reprojection.py
index 86506809712df2b94b312f4d3e7aa85d334a86a7..87d9c39577a26e438d0b35c2bbb8a48a88f2c6a5 100644
--- a/hysop/operator/discrete/reprojection.py
+++ b/hysop/old/operator.old/discrete/reprojection.py
@@ -1,54 +1,55 @@
# -*- coding: utf-8 -*-
-"""
-@file reprojection.py
-Compute reprojection criterion and divergence maximum
+"""Compute reprojection criterion and divergence maximum
"""
import numpy as np
-from hysop.constants import debug, HYSOP_MPI_REAL
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.constants import debug
+from hysop.methods import SpaceDiscretization
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.numerics.finite_differences import FDC4
from hysop.numerics.differential_operations import GradV
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.numerics.update_ghosts import UpdateGhosts
-from hysop.mpi import MPI
+from hysop.core.mpi import MPI
from hysop.tools.profiler import profile
class Reprojection(DiscreteOperator):
- """
- Update the reprojection frequency, according to the current
+ """Update the reprojection frequency, according to the current
value of the vorticity field.
"""
def __init__(self, vorticity, threshold, frequency, **kwds):
"""
- Constructor.
- @param vorticity: discretization of the vorticity field
- @param threshold : update frequency when criterion is greater than
- this threshold
- @param frequency : set frequency of execution of the reprojection
+
+ Parameters
+ ----------
+ vorticity : :class:`~hysop.fields.discrete.DiscreteField
+ vorticity field
+ threshold : double
+ update frequency when criterion is greater than this threshold
+ frequency : double
+ frequency of execution of the reprojection
"""
+ # ensure that space discretisation method is set
if 'method' in kwds and kwds['method'] is None:
- kwds['method'] = {SpaceDiscretisation: FDC4}
+ kwds['method'] = {SpaceDiscretization: FDC4}
- ## vorticity field
+ # vorticity field
self.vorticity = vorticity
assert 'variables' not in kwds, 'variables parameter is useless.'
super(Reprojection, self).__init__(variables=[vorticity], **kwds)
- ## Frequency for reprojection
+ # Frequency for reprojection
self.frequency = frequency
- ## The initial value will be used as default during
+ # The initial value will be used as default during
# simulation
self._default_frequency = frequency
- # constant defining the reprojection criterion :
+ # constant threshold defining the reprojection criterion :
# if the latter is greater than this constant, then a reprojection
# is needed
self.threshold = threshold
- # local counter
self._counter = 0
- ## Numerical methods for space discretization
- assert SpaceDiscretisation in self.method
- self.method = self.method[SpaceDiscretisation]
+ # Numerical methods for space discretization
+ assert SpaceDiscretization in self.method
+ self.method = self.method[SpaceDiscretization]
self.input = [vorticity]
self.output = []
topo = self.vorticity.topology
@@ -123,7 +124,6 @@ class Reprojection(DiscreteOperator):
self._writer.write()
def do_projection(self, ite):
- """
- True if projection must be done
+ """True if projection must be done
"""
return ite % self.frequency == 0
diff --git a/hysop/operator/discrete/residual.py b/hysop/old/operator.old/discrete/residual.py
similarity index 98%
rename from hysop/operator/discrete/residual.py
rename to hysop/old/operator.old/discrete/residual.py
index f221ac09d3bc8d87186b4252551915f1e62a75c0..c79cbf84ffe54519925e1622cc80cb68d8f25a62 100644
--- a/hysop/operator/discrete/residual.py
+++ b/hysop/old/operator.old/discrete/residual.py
@@ -5,7 +5,7 @@ Compute and print the time evolution of the residual
"""
from hysop.constants import debug
from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import scitools.filetable as ft
import numpy as np
from hysop.operator.discrete.discrete import DiscreteOperator
diff --git a/hysop/operator/discrete/scales_advection.py b/hysop/old/operator.old/discrete/scales_advection.py
similarity index 51%
rename from hysop/operator/discrete/scales_advection.py
rename to hysop/old/operator.old/discrete/scales_advection.py
index 79064cecc0f2eef28072973cdd5c16893c073f1e..795a84f1c90e8150d90c8ffba7af12cdced14034 100644
--- a/hysop/operator/discrete/scales_advection.py
+++ b/hysop/old/operator.old/discrete/scales_advection.py
@@ -1,58 +1,70 @@
# -*- coding: utf-8 -*-
-"""
-@file scales_advection.py
-Discrete Advection operator based on scales library (Jean-Baptiste)
+"""Interface to scales solver (fortran)
"""
try:
from hysop.f2hysop import scales2py
except ImportError:
- from hysop.fakef2py import scales2py
+ msgE = 'scales package not available for your hysop install.'
+ msgE += 'Try to recompile with WITH_SCALES=ON'
+ raise ImportError(msgE)
from hysop.operator.discrete.discrete import DiscreteOperator
-from hysop.methods_keys import MultiScale
+from hysop.methods import MultiScale
from hysop.constants import debug
import math
ceil = math.ceil
class ScalesAdvection(DiscreteOperator):
+ """Advection process, based on scales library.
"""
- Advection process, based on scales library.
- """
+
+ _scales_remesh_kernels = ['p_M4', 'p_M8', 'p_44', 'p_64',
+ 'p_66', 'p_84', 'p_M6']
+ """Kernels available in scales"""
+ _scales_remesh_corrected_kernels = ['p_O2', 'p_O4', 'p_L2']
+ """Corrected kernels available in scales"""
@debug
def __init__(self, velocity, advected_fields, **kwds):
"""
- Constructor.
- @param velocity discrete field
- @param advected_fields : list of discrete fields to be advected
+ Parameters
+ ----------
+ velocity : :class:`~hysop.fields.discrete.DiscreteField`
+ advection velocity (discretized)
+ advected_fields : list of :class:`~hysop.fields.discrete.DiscreteField`
+ discrete field(s) to be advected
+ direction : int
+ advection direction
+ kwds : extra parameters for base class
"""
- ## Advection velocity
+ msg = 'Scales advection init : variables parameter is useless.'
+ msg += 'See user guide for details on the proper'
+ msg += ' way to build the operator.'
+ assert 'variables' not in kwds, msg
+ # Advection velocity
self.velocity = velocity
- if 'variables' in kwds:
- assert advected_fields is None, 'too many input arguments.'
- self.advected_fields = kwds['variables'].keys()
- kwds['variables'][self.velocity] = kwds['discretization']
- kwds.pop('discretization')
- super(ScalesAdvection, self).__init__(**kwds)
+ variables = [self.velocity]
+ if isinstance(advected_fields, list):
+ self.advected_fields = advected_fields
else:
- v = [self.velocity]
- if isinstance(advected_fields, list):
- self.advected_fields = advected_fields
- else:
- self.advected_fields = [advected_fields]
- v += self.advected_fields
- super(ScalesAdvection, self).__init__(variables=v, **kwds)
+ self.advected_fields = [advected_fields]
+ variables += self.advected_fields
+
+ msg = 'Scales advection init : method parameter is compulsory.'
+ assert 'method' in kwds, msg
+
+ super(ScalesAdvection, self).__init__(variables=variables, **kwds)
- self.input = [self.velocity]
+ self.input = self.variables
self.output = self.advected_fields
- # Scales functions for each field (depending if vector)
+ # Connection to the proper scales functions.
self._scales_func = []
- isMultiscale = self.method[MultiScale] is not None
+ is_multi_scale = self.method[MultiScale] is not None
for adF in self.advected_fields:
if adF.nb_components == 3:
- if isMultiscale:
+ if is_multi_scale:
# 3D interpolation of the velocity before advection
self._scales_func.append(
scales2py.solve_advection_inter_basic_vect)
@@ -62,7 +74,7 @@ class ScalesAdvection(DiscreteOperator):
else:
self._scales_func.append(scales2py.solve_advection_vect)
else:
- if isMultiscale:
+ if is_multi_scale:
self._scales_func.append(
scales2py.solve_advection_inter_basic)
else:
diff --git a/hysop/old/operator.old/discrete/spectrum.py b/hysop/old/operator.old/discrete/spectrum.py
new file mode 100755
index 0000000000000000000000000000000000000000..fc2caf128307a7d3d5628f115f95bdd79a1a0158
--- /dev/null
+++ b/hysop/old/operator.old/discrete/spectrum.py
@@ -0,0 +1,73 @@
+# -*- coding: utf-8 -*-
+"""Discrete Spectrum operator using FFTW
+"""
+from hysop.operator.discrete.discrete import DiscreteOperator
+from hysop.constants import debug, np, hysop.core.mpi_REAL
+from hysop.tools.profiler import profile
+from hysop.tools.numpywrappers import npw
+from hysop.core.mpi import MPI
+
+try:
+ from hysop.f2hysop import fftw2py
+except ImportError:
+ msgE = 'fftw package not available for your hysop install.'
+ msgE += 'Try to recompile with WITH_FFTW=ON'
+ raise ImportError(msgE)
+
+
+class FFTSpectrum(DiscreteOperator):
+ """Discretized Spectrum operator based on FFTW.
+ """
+ @debug
+ def __init__(self, field, **kwds):
+ """
+
+ Parameters
+ ----------
+ field: :class:`~hysop.fields.discrete.DiscreteField`
+ the input field for which spectrum will be computed
+ """
+ # Discretization of the input field
+ self.field = field
+ msg = 'Spectrum error: implemented only for 3D problems.'
+ assert self.field.dimension == 3, msg
+ if self.field.nb_components > 1:
+ raise AttributeError("Vector case not yet implemented.")
+ # Base class initialisation
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ super(FFTSpectrum, self).__init__(variables=[field],
+ **kwds)
+ self.input = [self.field]
+ l = np.min(self.field.topology.mesh.discretization.resolution)
+ self._tmp = npw.zeros(((l - 1) / 2, ))
+ self._kx = npw.zeros(((l - 1) / 2, ))
+ self.res = npw.zeros(((l - 1) / 2, ))
+
+ @debug
+ @profile
+ def apply(self, simulation=None):
+ assert simulation is not None, \
+ "Missing simulation parameter."
+ ite = simulation.current_iteration
+ ghosts = self.field.topology.ghosts()
+ fftw2py.spectrum_3d(self.field.data[0],
+ self._tmp, self._kx,
+ ghosts, np.min(self.domain.length))
+ if self.field.topology.size == 1:
+ self.res[...] = self._tmp
+ else:
+ self.field.topology.comm.Reduce(
+ [self._tmp, self.res.shape[0], hysop.core.mpi_REAL],
+ [self.res, self.res.shape[0], hysop.core.mpi_REAL],
+ op=MPI.SUM, root=0)
+
+ if self._writer is not None and self._writer.do_write(ite):
+ nbc = self.res.shape[0]
+ self._writer.buffer[0, 0:nbc] = self._kx
+ self._writer.buffer[0, nbc:] = self.res
+ self._writer.write()
+
+ def finalize(self):
+ """Clean memory (fftw plans and so on)
+ """
+ pass
diff --git a/hysop/operator/discrete/stretching.py b/hysop/old/operator.old/discrete/stretching.py
similarity index 82%
rename from hysop/operator/discrete/stretching.py
rename to hysop/old/operator.old/discrete/stretching.py
index 7e96a901d2621d26c52f62c2f01569b6feef344b..a9966d6f3ed0deda2735f6eeea8a331f7cd9ddf6 100755
--- a/hysop/operator/discrete/stretching.py
+++ b/hysop/old/operator.old/discrete/stretching.py
@@ -1,5 +1,5 @@
# -*- coding: utf-8 -*-
-"""Discretisation of the stretching operator.
+"""Discretization of the stretching operator.
Formulations:
@@ -9,10 +9,10 @@ Formulations:
"""
from hysop.constants import debug, WITH_GUESS
-from hysop.methods_keys import TimeIntegrator, SpaceDiscretisation
+from hysop.methods import TimeIntegrator, SpaceDiscretization
from hysop.operator.discrete.discrete import DiscreteOperator
-import hysop.numerics.differential_operations as diff_op
-import hysop.tools.numpywrappers as npw
+from hysop.numerics.differential_operations import GradVxW, DivWV
+from hysop.tools.numpywrappers import npw
from hysop.numerics.update_ghosts import UpdateGhosts
from hysop.tools.profiler import profile
from hysop.tools.misc import WorkSpaceTools
@@ -30,13 +30,19 @@ class Stretching(DiscreteOperator):
__metaclass__ = ABCMeta
@debug
- def __init__(self, velocity, vorticity, formulation, rhs, **kwds):
+ def __init__(self, velocity, vorticity, formulation,
+ rhs, extra_ghosts_fields=None, **kwds):
"""Abstract interface for stretching operator
Parameters
----------
velocity, vorticity : :class:`~hysop.fields.discrete.DiscreteField`
formulation : one of the discrete stretching classes.
+ rhs : python function
+ right-hand side for the time integrator
+ extra_ghosts_fields : int, optional
+ number of additional numpy arrays to be synchronized (mpi),
+ default = None, i.e. synchro of vorticity and velocity components.
**kwds : extra parameters for base class
"""
@@ -69,16 +75,19 @@ class Stretching(DiscreteOperator):
self.nb_components = 3 # Stretching only in 3D and for vector fields.
# prepare ghost points synchro for velocity and vorticity
+ nb_ghosts_fields = self.velocity.nb_components + \
+ self.vorticity.nb_components
+ if extra_ghosts_fields is not None:
+ nb_ghosts_fields += extra_ghosts_fields
self._synchronize = UpdateGhosts(self.velocity.topology,
- self.velocity.nb_components +
- self.vorticity.nb_components)
+ nb_ghosts_fields)
# A function to compute the gradient of the velocity.
# Work vector is provided in input.
self.strFunc = \
self.formulation(topo=self.velocity.topology,
work=self._str_work,
- method=self.method[SpaceDiscretisation])
+ method=self.method[SpaceDiscretization])
# Time integrator
self.timeIntegrator = \
self.method[TimeIntegrator](self.nb_components,
@@ -155,13 +164,14 @@ class Conservative(Stretching):
@profile
def __init__(self, **kwds):
+ # Right-hand side for time integration
def rhs(t, y, result):
"""rhs used in time integrator
"""
return self.strFunc(y, self.velocity.data, result)
- super(Conservative, self).__init__(formulation=diff_op.DivWV,
- rhs=rhs, **kwds)
+ super(Conservative, self).__init__(
+ formulation=DivWV, rhs=rhs, **kwds)
@profile
def _compute(self, dt, t):
@@ -182,8 +192,7 @@ class GradUW(Stretching):
self.strFunc(self.velocity.data, y, result, self.diagnostics)
return result
- super(GradUW, self).__init__(formulation=diff_op.GradVxW,
- rhs=rhs, **kwds)
+ super(GradUW, self).__init__(formulation=GradVxW, rhs=rhs, **kwds)
# stability constant
# Depends on time integration method
@@ -235,52 +244,61 @@ class StretchingLinearized(Stretching):
UpdateGhosts(self.vorticity_BF.topology,
self.vorticity_BF.nb_components)
self.usual_op = usual_op
+ # boolean used to switch between two rhs forms:
+ # either rhs(t, y) = div(y:u) (if true)
+ # or rhs(t,y) = div(y:w_bf) (if false)
+ self._divwu = True
- def rhs(t, y, result, form):
+ def rhs(t, y, result):
"""rhs used in time integrator
"""
- if form == "div(w:u)":
+ if self._divwu:
result = self.strFunc(y, self.velocity.data, result)
else:
result = self.strFunc(y, self.vorticity_BF.data, result)
return result
- super(StretchingLinearized, self).__init__(formulation=diff_op.DivWV,
- rhs=rhs, **kwds)
+ super(StretchingLinearized, self).__init__(
+ formulation=DivWV, rhs=rhs,
+ extra_ghosts_fields=self.vorticity_BF.nb_components,
+ **kwds)
- def _integrate(self, dt, t):
+ def _compute(self, dt, t):
# - Call time integrator (1st term over 3) -
# Init workspace with a first evaluation of the div(wb:u') term in the
# rhs of the integrator
+ self._divwu = True
self._ti_work[:self.nb_components] = \
self.timeIntegrator.f(t, self.vorticity_BF.data,
- self._ti_work[:self.nb_components],
- "div(w:u)")
+ self._ti_work[:self.nb_components])
# perform integration and save result in-place
self.vorticity.data = self.timeIntegrator(t, self.vorticity.data, dt,
result=self.vorticity.data)
# - Call time integrator (2nd term over 3) -
# Init workspace with a first evaluation of the div(u':wb) term in the
# rhs of the integrator
+ self._divwu = False
self._ti_work[:self.nb_components] = \
self.timeIntegrator.f(t, self.velocity.data,
- self._ti_work[:self.nb_components],
- "div(u:w)")
+ self._ti_work[:self.nb_components])
# perform integration and save result in-place
self.vorticity.data = self.timeIntegrator(t, self.vorticity.data, dt,
result=self.vorticity.data)
- def _compute(self, dt, t):
- # No subcycling for this formulation
- self._integrate(dt, t)
+ def apply(self, simulation=None):
+ assert simulation is not None, \
+ "Missing simulation value for computation."
+
+ # time step
+ dt = simulation.time_step
+ # current time
+ t = simulation.time
- def _apply(self, t, dt):
# Synchronize ghost points
- self._synchronize(self.velocity.data + self.vorticity.data)
- self._synchronize_vort_BF(self.vorticity_BF.data)
+ self._synchronize(self.velocity.data + self.vorticity.data +
+ self.vorticity_BF.data)
# Compute the 2 first "stretching" terms (div(wb:u') and div(u':wb))
# and update vorticity for each of them
self._compute(dt, t)
# Compute the 3rd stretching term (div(w':ub)) and update vorticity
- self.usual_op._apply(t, dt)
-
+ self.usual_op.apply(simulation)
diff --git a/hysop/operator/discrete/velocity_correction.py b/hysop/old/operator.old/discrete/velocity_correction.py
similarity index 64%
rename from hysop/operator/discrete/velocity_correction.py
rename to hysop/old/operator.old/discrete/velocity_correction.py
index c09104af5f9a0f59a617f738bada36ef3e5f3a1a..2cfb01adcd641b0ff4eb81db183190eadfb347cf 100755
--- a/hysop/operator/discrete/velocity_correction.py
+++ b/hysop/old/operator.old/discrete/velocity_correction.py
@@ -1,57 +1,66 @@
# -*- coding: utf-8 -*-
-"""
-@file operator/discrete/velocity_correction.py
+"""Operator used to shift velocity value
+ to fit with a required input flowrate.
-Correction of the velocity field.
-"""
+Check details in :ref:`velocity_correction` in HySoP user guide.
+
+"""
from hysop.constants import debug
from hysop.operator.discrete.discrete import DiscreteOperator
from hysop.fields.variable_parameter import VariableParameter
from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.constants import XDIR, YDIR, ZDIR
class VelocityCorrection_D(DiscreteOperator):
- """
- The velocity field is corrected after solving the
+ """The velocity field is corrected after solving the
Poisson equation. For more details about calculations,
- see the "velocity_correction.pdf" explanations document
- in Docs.
+ see :ref:`velocity_correction` in HySoP user guide.
"""
@debug
def __init__(self, velocity, vorticity, req_flowrate, cb, **kwds):
- """
- @param[in, out] velocity field to be corrected
- @param[in] vorticity field used to compute correction
- @param[in] req_flowrate : required value for the
- flowrate (VariableParameter object)
- @param[in] surf : surface (hysop.domain.obstacle.planes.SubPlane)
- used to compute reference flow rates. Default = surface at x_origin,
- normal to x-dir.
+ """Update velocity field (solution of Poisson equation)
+ in order to prescribe proper mean flow and ensure
+ the desired inlet flowrate.
+
+ Parameters
+ ----------
+ velocity : :class:`~hysop.fields.discrete.DiscreteField`
+ in/out velocity vector field.
+ vorticity : :class:`~hysop.fields.discrete.DiscreteField`
+ input vorticity vector field.
+ req_flowrate : a
+ :class:`~hysop.fields.variable_parameter.VariableParameter`
+ the desired inlet flowrate value
+ cb : :class:`~hysop.domain.control_box.ControlBox`
+ volume of control used to compute a reference for correction.
+ kwds : base class parameters
"""
assert 'variables' not in kwds, 'variables parameter is useless.'
super(VelocityCorrection_D, self).__init__(
variables=[velocity, vorticity], **kwds)
- ## velocity discrete field
+ # velocity discrete field
self.velocity = velocity
- ## vorticity discrete field
+ # vorticity discrete field
self.vorticity = vorticity
- ## domain dimension
- self.dim = self.velocity.domain.dimension
# If 2D problem, vorticity must be a scalar
- if self.dim == 2:
+ if self._dim == 2:
assert self.vorticity.nb_components == 1
- assert (self.dim >= 2),\
+ self._update_velocity_components = self._update_velocity_2d
+ elif self._dim == 3:
+ self._update_velocity_components = self._update_velocity_3d
+
+ assert (self._dim >= 2),\
"Wrong problem dimension: only 2D and 3D cases are implemented."
self.input = self.variables
self.output = [self.velocity]
- ## A reference topology
+ # A reference topology
self.topo = self.velocity.topology
- ## Volume of control
+ # Volume of control
self.cb = cb
self.cb.discretize(self.topo)
# A reference surface, i.e. input surface for flow in x direction
@@ -62,13 +71,13 @@ class VelocityCorrection_D(DiscreteOperator):
cb_length = self.cb.real_length[self.topo]
self._inv_ds = 1. / npw.prod(cb_length[sdirs])
self._inv_dvol = 1. / npw.prod(cb_length)
- ## Expected value for the flow rate through self.surfRef
+ # Expected value for the flow rate through self.surfRef
self.req_flowrate = req_flowrate
assert isinstance(self.req_flowrate, VariableParameter),\
"the required flowrate must be a VariableParameter object."
- ## The correction that must be applied on each
- ## component of the velocity.
- self.velocity_shift = npw.zeros(self.dim)
+ # The correction that must be applied on each
+ # component of the velocity.
+ self.velocity_shift = npw.zeros(self._dim)
nbf = self.velocity.nb_components + self.vorticity.nb_components
# temp buffer, used to save flow rates and mean
# values of vorticity
@@ -83,20 +92,19 @@ class VelocityCorrection_D(DiscreteOperator):
# surface for the flow.
self.x_coord = self.topo.mesh.coords[XDIR] - x0
- def computeCorrection(self):
- """
- Compute the required correction for the current state
+ def compute_correction(self):
+ """Compute the required correction for the current state
but do not apply it onto velocity.
"""
- ## Computation of the flowrates evaluated from
- ## current (ie non corrected) velocity
+ # Computation of the flowrates evaluated from
+ # current (ie non corrected) velocity
nbf = self.velocity.nb_components + self.vorticity.nb_components
localrates = npw.zeros((nbf))
for i in xrange(self.velocity.nb_components):
localrates[i] = self._in_surf.integrate_dfield_on_proc(
self.velocity, component=i)
start = self.velocity.nb_components
- ## Integrate vorticity over the whole domain
+ # Integrate vorticity over the whole domain
for i in xrange(self.vorticity.nb_components):
localrates[start + i] = self.cb.integrate_dfield_on_proc(
self.vorticity, component=i)
@@ -110,7 +118,7 @@ class VelocityCorrection_D(DiscreteOperator):
self.rates[:start] *= self._inv_ds
self.rates[start:] *= self._inv_dvol
-
+
# Set velocity_shift == [Vx_shift, vort_mean[Y], vort_mean[Z]]
# or (in 2D) velocity_shift == [Vx_shift, vort_mean]
# Velocity shift for main dir component
@@ -119,6 +127,20 @@ class VelocityCorrection_D(DiscreteOperator):
# Shifts in other directions depend on x coord
# and will be computed during apply.
+ def _update_velocity_2d(self, vort_mean):
+ """update velocity value, 2d case
+ """
+ self.velocity[YDIR][...] += self.req_flowrate_val[YDIR] +\
+ vort_mean[XDIR] * self.x_coord - self.rates[YDIR]
+
+ def _update_velocity_3d(self, vort_mean):
+ """update velocity value, 3d case
+ """
+ self.velocity[YDIR][...] += self.req_flowrate_val[YDIR] + \
+ vort_mean[ZDIR] * self.x_coord - self.rates[YDIR]
+ self.velocity[ZDIR][...] += self.req_flowrate_val[ZDIR] - \
+ vort_mean[YDIR] * self.x_coord - self.rates[ZDIR]
+
@debug
@profile
def apply(self, simulation=None):
@@ -129,10 +151,10 @@ class VelocityCorrection_D(DiscreteOperator):
self.req_flowrate_val = self.req_flowrate.data * self._inv_ds
# Computation of the required velocity shift
# for the current state
- self.computeCorrection()
+ self.compute_correction()
compute_index = self.topo.mesh.compute_index
- # Apply shift to velocity
+ # Apply shift to velocity (x component)
self.velocity[XDIR][compute_index] += self.velocity_shift[XDIR]
start = self.velocity.nb_components
# reminder : self.rates =[vx_shift, flowrates[Y], flowrate[Z],
@@ -146,14 +168,4 @@ class VelocityCorrection_D(DiscreteOperator):
self._writer.buffer[0, 2:] = vort_mean[...]
self._writer.write()
- if self.dim == 2:
- # Correction of the Y-velocity component
- self.velocity[YDIR][...] += self.req_flowrate_val[YDIR] + \
- vort_mean[XDIR] * self.x_coord - self.rates[YDIR]
-
- elif self.dim == 3:
- # Correction of the Y and Z-velocity components
- self.velocity[YDIR][...] += self.req_flowrate_val[YDIR] + \
- vort_mean[ZDIR] * self.x_coord - self.rates[YDIR]
- self.velocity[ZDIR][...] += self.req_flowrate_val[ZDIR] - \
- vort_mean[YDIR] * self.x_coord - self.rates[ZDIR]
+ self._update_velocity_components(vort_mean)
diff --git a/hysop/operator/drag_and_lift.py b/hysop/old/operator.old/drag_and_lift.py
similarity index 94%
rename from hysop/operator/drag_and_lift.py
rename to hysop/old/operator.old/drag_and_lift.py
index 0ded0b6fd0dd3694e6dd284b4bc774e670528533..f0bf05a4aaccd7cc874ff5bb210395e63a9ca53b 100755
--- a/hysop/operator/drag_and_lift.py
+++ b/hysop/old/operator.old/drag_and_lift.py
@@ -129,7 +129,7 @@ class MomentumForces(Forces):
import MomentumForces as DiscreteForce
# build the discrete operator
self.discrete_op = DiscreteForce(
- velocity=self.discreteFields[self.velocity],
+ velocity=self.discrete_fields[self.velocity],
penalisation_coeff=self._coeff,
obstacles=self.obstacles,
normalization=self.normalization)
@@ -203,12 +203,12 @@ class NocaForces(Forces):
if self.method is None:
import hysop.default_methods as default
self.method = default.FORCES
- from hysop.methods_keys import SpaceDiscretisation
+ from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4, FDC2
- assert SpaceDiscretisation in self.method.keys()
- if SpaceDiscretisation is FDC2:
+ assert SpaceDiscretization in self.method.keys()
+ if SpaceDiscretization is FDC2:
self._min_ghosts = 1
- elif SpaceDiscretisation is FDC4:
+ elif SpaceDiscretization is FDC4:
self._min_ghosts = 2
if surfdir is None:
@@ -240,7 +240,7 @@ class NocaForces(Forces):
super(NocaForces, self).get_work_properties()
shape_v = [None, ] * (self.domain.dimension + 1)
slist = self.voc.surf
- toporef = self.discreteFields[self.velocity].topology
+ toporef = self.discrete_fields[self.velocity].topology
for i in xrange(self.domain.dimension):
v_ind = slist[2 * i].mesh[toporef].ind4integ
shape_v[i] = self.velocity.data[i][v_ind].shape
@@ -253,11 +253,11 @@ class NocaForces(Forces):
@opsetup
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
- topo = self.discreteFields[self.velocity].topology
+ topo = self.discrete_fields[self.velocity].topology
self.voc.discretize(topo)
self.discrete_op = self.formulation(
- velocity=self.discreteFields[self.velocity],
- vorticity=self.discreteFields[self.vorticity],
+ velocity=self.discrete_fields[self.velocity],
+ vorticity=self.discrete_fields[self.vorticity],
nu=self.nu,
volume_of_control=self.voc,
surfdir=self._surfdir,
diff --git a/hysop/operator/energy_enstrophy.py b/hysop/old/operator.old/energy_enstrophy.py
similarity index 91%
rename from hysop/operator/energy_enstrophy.py
rename to hysop/old/operator.old/energy_enstrophy.py
index 5251e6502a9003d28bc8890fb88af8e41521e179..6f3d0cd9cb627ff6fbac10642d3f6058dc7bc865 100644
--- a/hysop/operator/energy_enstrophy.py
+++ b/hysop/old/operator.old/energy_enstrophy.py
@@ -47,8 +47,8 @@ class EnergyEnstrophy(Computational):
def get_work_properties(self):
super(EnergyEnstrophy, self).get_work_properties()
- vd = self.discreteFields[self.velocity]
- wd = self.discreteFields[self.vorticity]
+ vd = self.discrete_fields[self.velocity]
+ wd = self.discrete_fields[self.vorticity]
v_ind = vd.topology.mesh.compute_index
w_ind = wd.topology.mesh.compute_index
size_v = vd[0][v_ind].size
@@ -61,8 +61,8 @@ class EnergyEnstrophy(Computational):
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
- self.discrete_op = DEE(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
+ self.discrete_op = DEE(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
self.is_normalized,
rwork=rwork)
# Output setup
diff --git a/hysop/operator/forcing.py b/hysop/old/operator.old/forcing.py
similarity index 92%
rename from hysop/operator/forcing.py
rename to hysop/old/operator.old/forcing.py
index d5cf8314209699b25400d22fb62258d8711dafbc..678d88b4267e62d8662835d2283bf14bc796e692 100644
--- a/hysop/operator/forcing.py
+++ b/hysop/old/operator.old/forcing.py
@@ -13,7 +13,7 @@ from hysop.operator.discrete.forcing import ForcingConserv as DForcingCsv
from hysop.constants import debug
from hysop.operator.continuous import opsetup
import hysop.default_methods as default
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4,\
FDC2
from hysop.operator.differential import Curl
@@ -58,7 +58,7 @@ class Forcing(Computational):
@debug
def setup(self, rwork=None, iwork=None):
self.discrete_op = DForcing(
- variables=self.discreteFields.values(),
+ variables=self.discrete_fields.values(),
strength=self.strength,
rwork=rwork, iwork=iwork)
@@ -113,11 +113,11 @@ class ForcingConserv(Forcing):
def discretize(self):
- if self.method[SpaceDiscretisation] is FDC4:
+ if self.method[SpaceDiscretization] is FDC4:
# Finite differences method
# Minimal number of ghost points
nb_ghosts = 2
- elif self.method[SpaceDiscretisation] is FDC2:
+ elif self.method[SpaceDiscretization] is FDC2:
nb_ghosts = 1
else:
raise ValueError("Unknown method for space discretization of the\
@@ -144,9 +144,9 @@ class ForcingConserv(Forcing):
def setup(self, rwork=None, iwork=None):
self._curl.setup(rwork, iwork)
self.discrete_op = DForcingCsv(
- vorticity=self.discreteFields[self.vorticity],
- velocity=self.discreteFields[self.velocity],
- velocityFilt=self.discreteFields[self.velocityFilt],
+ vorticity=self.discrete_fields[self.vorticity],
+ velocity=self.discrete_fields[self.velocity],
+ velocityFilt=self.discrete_fields[self.velocityFilt],
curl=self._curl.discrete_op,
strength=self.strength,
rwork=rwork, iwork=iwork)
diff --git a/hysop/operator/low_pass_filt.py b/hysop/old/operator.old/low_pass_filt.py
similarity index 92%
rename from hysop/operator/low_pass_filt.py
rename to hysop/old/operator.old/low_pass_filt.py
index a86381ce800cef3ef4aab3a5ecd0dfe2d85b4ecb..0adfc7e1023f5f7ff9229916dcb99b17da435dbc 100644
--- a/hysop/operator/low_pass_filt.py
+++ b/hysop/old/operator.old/low_pass_filt.py
@@ -12,7 +12,7 @@ from hysop.operator.discrete.low_pass_filt import LowPassFiltConserv as DFiltCsv
from hysop.constants import debug
from hysop.operator.continuous import opsetup
import hysop.default_methods as default
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4,\
FDC2
from hysop.operator.differential import Curl
@@ -55,7 +55,7 @@ class LowPassFilt(Computational):
@debug
def setup(self, rwork=None, iwork=None):
self.discrete_op = DFilt(
- variables=self.discreteFields.values(),
+ variables=self.discrete_fields.values(),
cutFreq=self.cutFreq,
rwork=rwork, iwork=iwork)
@@ -110,11 +110,11 @@ class LowPassFiltConserv(LowPassFilt):
def discretize(self):
- if self.method[SpaceDiscretisation] is FDC4:
+ if self.method[SpaceDiscretization] is FDC4:
# Finite differences method
# Minimal number of ghost points
nb_ghosts = 2
- elif self.method[SpaceDiscretisation] is FDC2:
+ elif self.method[SpaceDiscretization] is FDC2:
nb_ghosts = 1
else:
raise ValueError("Unknown method for space discretization of the\
@@ -141,9 +141,9 @@ class LowPassFiltConserv(LowPassFilt):
def setup(self, rwork=None, iwork=None):
self._curl.setup(rwork, iwork)
self.discrete_op = DFiltCsv(
- vorticityFilt=self.discreteFields[self.vorticityFilt],
- velocity=self.discreteFields[self.velocity],
- velocityFilt=self.discreteFields[self.velocityFilt],
+ vorticityFilt=self.discrete_fields[self.vorticityFilt],
+ velocity=self.discrete_fields[self.velocity],
+ velocityFilt=self.discrete_fields[self.velocityFilt],
curl=self._curl.discrete_op,
cutFreq=self.cutFreq,
rwork=rwork, iwork=iwork)
diff --git a/hysop/operator/monitoringPoints.py b/hysop/old/operator.old/monitoringPoints.py
similarity index 89%
rename from hysop/operator/monitoringPoints.py
rename to hysop/old/operator.old/monitoringPoints.py
index 4626d22899dea2b613d3f8f5fa59dd52af3eab7a..73237c7dea0cf4b954445ca843a17a22172b00b1 100644
--- a/hysop/operator/monitoringPoints.py
+++ b/hysop/old/operator.old/monitoringPoints.py
@@ -43,8 +43,8 @@ class MonitoringPoints(Computational):
msg = 'The operator must be discretized '
msg += 'before any call to this function.'
raise RuntimeError(msg)
- vd = self.discreteFields[self.velocity]
- wd = self.discreteFields[self.vorticity]
+ vd = self.discrete_fields[self.velocity]
+ wd = self.discrete_fields[self.vorticity]
v_ind = vd.topology.mesh.compute_index
w_ind = wd.topology.mesh.compute_index
shape_v = vd[0][v_ind].shape
@@ -58,8 +58,8 @@ class MonitoringPoints(Computational):
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
- self.discrete_op = MonitD(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
+ self.discrete_op = MonitD(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
self.monitPt_coords, rwork=rwork)
# Output setup
self._set_io('monit', (1, 3))
diff --git a/hysop/operator/multiphase_baroclinic_rhs.py b/hysop/old/operator.old/multiphase_baroclinic_rhs.py
similarity index 87%
rename from hysop/operator/multiphase_baroclinic_rhs.py
rename to hysop/old/operator.old/multiphase_baroclinic_rhs.py
index ac506a9d30932a0440702428fdc462a3b59debc7..caa301a9030a8c071226ba0e46f90d8f69bdf68f 100644
--- a/hysop/operator/multiphase_baroclinic_rhs.py
+++ b/hysop/old/operator.old/multiphase_baroclinic_rhs.py
@@ -8,11 +8,11 @@ Computation of the baroclinic term in a multiphasic flow:
\f} with finite differences
"""
from hysop.operator.computational import Computational
-from hysop.methods_keys import SpaceDiscretisation, Support
+from hysop.methods import SpaceDiscretization, Support
from hysop.constants import debug, np
import hysop.default_methods as default
from hysop.operator.continuous import opsetup
-from hysop.gpu.gpu_multiphase_baroclinic_rhs import BaroclinicRHS
+from hysop.backend.device.opencl.gpu_multiphase_baroclinic_rhs import BaroclinicRHS
class MultiphaseBaroclinicRHS(Computational):
@@ -42,7 +42,7 @@ class MultiphaseBaroclinicRHS(Computational):
self.gradp = gradp
self.input = [self.rho, self.gradp]
self.output = [self.rhs, ]
- assert SpaceDiscretisation in self.method.keys()
+ assert SpaceDiscretization in self.method.keys()
msg = "This operator is implemented for GPU only"
assert Support in self.method.keys(), msg
assert self.method[Support] == 'gpu', msg
@@ -74,8 +74,8 @@ class MultiphaseBaroclinicRHS(Computational):
Create a discrete Baroclinic operator from given specifications.
"""
self.discrete_op = \
- BaroclinicRHS(self.discreteFields[self.rhs],
- self.discreteFields[self.rho],
- self.discreteFields[self.gradp],
+ BaroclinicRHS(self.discrete_fields[self.rhs],
+ self.discrete_fields[self.rho],
+ self.discrete_fields[self.gradp],
method=self.method)
self._is_uptodate = True
diff --git a/hysop/operator/multiphase_gradp.py b/hysop/old/operator.old/multiphase_gradp.py
similarity index 90%
rename from hysop/operator/multiphase_gradp.py
rename to hysop/old/operator.old/multiphase_gradp.py
index d1415f0fb2b74dc82c4a7cefe1785db842037c51..03a5900f8f168a8f5d0ead64b7a19637b1474b60 100644
--- a/hysop/operator/multiphase_gradp.py
+++ b/hysop/old/operator.old/multiphase_gradp.py
@@ -8,7 +8,7 @@ Computation of the pressure gradient in a multiphasic flow:
\f} with finite differences
"""
from hysop.operator.computational import Computational
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4
from hysop.constants import debug, np
import hysop.default_methods as default
@@ -48,10 +48,10 @@ class MultiphaseGradP(Computational):
self.viscosity = viscosity
self.input = [self.velocity, ]
self.output = [self.gradp, ]
- assert SpaceDiscretisation in self.method.keys()
+ assert SpaceDiscretization in self.method.keys()
def discretize(self):
- if self.method[SpaceDiscretisation] is FDC4:
+ if self.method[SpaceDiscretization] is FDC4:
nbGhosts = 2
else:
raise ValueError("Unknown method for space discretization of the\
@@ -67,8 +67,8 @@ class MultiphaseGradP(Computational):
Create a discrete Baroclinic operator from given specifications.
"""
self.discrete_op = \
- GradP(self.discreteFields[self.velocity],
- self.discreteFields[self.gradp],
+ GradP(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.gradp],
self.viscosity,
method=self.method)
self._is_uptodate = True
diff --git a/hysop/operator/multiresolution_filter.py b/hysop/old/operator.old/multiresolution_filter.py
similarity index 88%
rename from hysop/operator/multiresolution_filter.py
rename to hysop/old/operator.old/multiresolution_filter.py
index 01cc7d0a6b06c7e073ba8d709203e366761cc948..bae6c28ecaaa92bc1e43dda94d5571b4f9efad5d 100644
--- a/hysop/operator/multiresolution_filter.py
+++ b/hysop/old/operator.old/multiresolution_filter.py
@@ -5,7 +5,7 @@ from hysop.constants import debug
from hysop.operator.continuous import opsetup
from hysop.operator.computational import Computational
import hysop.default_methods as default
-from hysop.methods_keys import Support
+from hysop.methods import Support
class MultiresolutionFilter(Computational):
@@ -18,14 +18,14 @@ class MultiresolutionFilter(Computational):
"""
Parameters
----------
- d_in, d_out : :class:`hysop.mpi.topology.Cartesian`
+ d_in, d_out : :class:`hysop.core.mpi.topology.Cartesian`
or :class:`tools.parameters.Discretization`
data distribution for source (in) and target (out) grids.
kwds : base class parameters
"""
if 'method' not in kwds:
- kwds['method'] = default.MULTIRESOLUTION_FILER
+ kwds['method'] = default.MULTIRESOLUTION_FILTER
super(MultiresolutionFilter, self).__init__(**kwds)
self.d_in, self.d_out = d_in, d_out
self.input = self.variables
@@ -45,7 +45,7 @@ class MultiresolutionFilter(Computational):
def setup(self, rwork=None, iwork=None):
if Support in self.method.keys() and \
self.method[Support].find('gpu') >= 0:
- from hysop.gpu.gpu_multiresolution_filter \
+ from hysop.backend.device.opencl.gpu_multiresolution_filter \
import GPUFilterFineToCoarse as discreteFilter
else:
from hysop.operator.discrete.multiresolution_filter \
diff --git a/hysop/operator/penalization.py b/hysop/old/operator.old/penalization.py
similarity index 94%
rename from hysop/operator/penalization.py
rename to hysop/old/operator.old/penalization.py
index e9bf4653a359012d8496f5dbf056f3d919e878ed..ee20612801ff76363ee3800b2624dcc344527b24 100644
--- a/hysop/operator/penalization.py
+++ b/hysop/old/operator.old/penalization.py
@@ -17,7 +17,7 @@ from hysop.constants import debug
from hysop.operator.continuous import opsetup
from hysop.domain.subsets import Subset
import hysop.default_methods as default
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.methods import SpaceDiscretization
from hysop.numerics.finite_differences import FDC4,\
FDC2
from hysop.operator.differential import Curl
@@ -94,7 +94,7 @@ class Penalization(Computational):
@opsetup
def setup(self, rwork=None, iwork=None):
self.discrete_op = DPenalV(
- variables=self.discreteFields.values(), obstacles=self.obstacles,
+ variables=self.discrete_fields.values(), obstacles=self.obstacles,
coeff=self.coeff, rwork=rwork, iwork=iwork)
self._is_uptodate = True
@@ -142,11 +142,11 @@ class PenalizeVorticity(Penalization):
def discretize(self):
- if self.method[SpaceDiscretisation] is FDC4:
+ if self.method[SpaceDiscretization] is FDC4:
# Finite differences method
# Minimal number of ghost points
nb_ghosts = 2
- elif self.method[SpaceDiscretisation] is FDC2:
+ elif self.method[SpaceDiscretization] is FDC2:
nb_ghosts = 1
else:
raise ValueError("Unknown method for space discretization of the\
@@ -176,8 +176,8 @@ class PenalizeVorticity(Penalization):
def setup(self, rwork=None, iwork=None):
self._curl.setup(rwork, iwork)
self.discrete_op = DPenalW(
- vorticity=self.discreteFields[self.vorticity],
- velocity=self.discreteFields[self.velocity],
+ vorticity=self.discrete_fields[self.vorticity],
+ velocity=self.discrete_fields[self.velocity],
curl=self._curl.discrete_op,
obstacles=self.obstacles,
coeff=self.coeff, rwork=rwork, iwork=iwork)
diff --git a/hysop/old/operator.old/poisson.py b/hysop/old/operator.old/poisson.py
new file mode 100644
index 0000000000000000000000000000000000000000..e977091fc61fd56c8ecc200fd12b44fb67939f09
--- /dev/null
+++ b/hysop/old/operator.old/poisson.py
@@ -0,0 +1,146 @@
+# -*- coding: utf-8 -*-
+"""Operator to solve Poisson problem.
+
+See :ref:`poisson` in HySoP user guide.
+"""
+from hysop.operator.computational import Computational
+from hysop.operator.discrete.poisson_fft import PoissonFFT
+from hysop.constants import debug
+from hysop.operator.velocity_correction import VelocityCorrection
+from hysop.operator.reprojection import Reprojection
+from hysop.methods import SpaceDiscretization, Formulation
+from hysop.operator.continuous import opsetup
+from hysop import __FFTW_ENABLED__
+
+
+class Poisson(Computational):
+ """Solve Poisson problem (in: vorticity, out velocity)
+ for incompressible flow.
+ """
+
+ _authorized_methods = ['fftw']
+
+ @debug
+ def __init__(self, output_field, input_field, flowrate=None,
+ projection=None, **kwds):
+ """Poisson operator, incompressible flow.
+
+ Parameters
+ ----------
+ output_field : :class:`~hysop.fields.continuous.Field
+ solution field
+ input_field : :class:`~hysop.fields.continuous.Field`
+ right-hand side
+ flowrate: :class:`~hysop.fields.variable_parameter.VariableParameter`
+ or double, optional
+ flow rate value through input surface (normal to xdir),
+ used to calibrate solution, default=0.
+ projection : double or tuple, optional
+ projection criterion, see notes below.
+ kwds : base class parameters.
+
+
+ Notes:
+ * projection might be:
+ * None: no projection
+ * the value of the frequency of reprojection (constant)
+ * a tuple (frequency, threshold). In that case, a criterion
+ depending on the input_field will be computed at each time step,
+ and if criterion > threshold., then frequency projection is active.
+ * About method parameter:
+ - SpaceDiscretization == fftw
+ - Formulation = 'velocity' or 'pressure'
+ velocity : laplacian(phi) = -w and v = nabla X psi, in = vorticity, out = velo
+ pressure : laplacian(p) = -nabla.(u.nabla u, in = velo, out = pressure
+ """
+ # Warning : for fftw all variables must have
+ # the same resolution.
+ assert 'variables' not in kwds, 'variables parameter is useless.'
+ super(Poisson, self).__init__(variables=[output_field, input_field],
+ **kwds)
+ # solution of the problem
+ self.output_field = output_field
+ # -(right-hand side)
+ self.input_field = input_field
+ if self.method is None:
+ import hysop.default_methods as default
+ self.method = default.POISSON
+ if self.method[SpaceDiscretization] is 'fftw':
+ assert __FFTW_ENABLED__
+ msg = 'Poisson : unknown method for space discretization'
+ assert self.method[SpaceDiscretization] in self._authorized_methods,\
+ msg
+
+ # Set Poisson equation formulation :
+ # Velo Poisson eq or Pressure Poisson eq
+ self.formulation = None
+ if self.method[Formulation] is not 'velocity':
+ self.formulation = self.method[Formulation]
+
+ self.input = [self.input_field]
+ self.output = [self.output_field]
+ # Enable correction if required
+ if flowrate is not None:
+ self.withCorrection = True
+ self._flowrate = flowrate
+ else:
+ self.withCorrection = False
+ self.correction = None
+ self.projection = projection
+ self._config = kwds
+
+ if projection is not None:
+ self.output.append(self.input_field)
+
+ def discretize(self):
+ # Poisson solver based on fftw
+ if self.method[SpaceDiscretization] is 'fftw':
+ super(Poisson, self)._fftw_discretize()
+ # prepare correction and projection, if needed
+ if self.withCorrection:
+ toporef = self.discrete_fields[self.output_field].topology
+ if 'discretization' in self._config:
+ self._config['discretization'] = toporef
+ self.correction = VelocityCorrection(
+ self.output_field, self.input_field,
+ req_flowrate=self._flowrate, **self._config)
+ self.correction.discretize()
+
+ if isinstance(self.projection, tuple):
+ freq = self.projection[0]
+ threshold = self.projection[1]
+ self.projection = Reprojection(self.input_field,
+ threshold, freq,
+ **self._config)
+ self.projection.discretize()
+
+ @debug
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ # Activate correction, if required
+ if self.withCorrection:
+ self.correction.setup()
+ cd = self.correction.discrete_op
+ else:
+ cd = None
+
+ # Activate projection, if required
+ if isinstance(self.projection, Reprojection):
+ # Projection frequency is updated at each
+ # time step, and depends on the input_field
+ self.projection.setup(rwork=rwork)
+ projection_discr = self.projection.discrete_op
+ else:
+ projection_discr = self.projection
+
+ self.discrete_op = PoissonFFT(self.discrete_fields[self.output_field],
+ self.discrete_fields[self.input_field],
+ correction=cd,
+ rwork=rwork, iwork=iwork,
+ projection=projection_discr,
+ formulation=self.formulation)
+
+ self._is_uptodate = True
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
diff --git a/hysop/operator/profiles.py b/hysop/old/operator.old/profiles.py
similarity index 72%
rename from hysop/operator/profiles.py
rename to hysop/old/operator.old/profiles.py
index 3f74bbb2949f5415c8120e1b016876df0470421d..abee5ceddea44b43dfb0cc4225c2c9613d40728a 100644
--- a/hysop/operator/profiles.py
+++ b/hysop/old/operator.old/profiles.py
@@ -1,7 +1,4 @@
-# -*- coding: utf-8 -*-
-"""
-@file profiles.py
-Compute and print velo/vorti profiles
+"""Compute and print velo/vorti profiles
"""
from hysop.operator.discrete.profiles import Profiles as ProfD
from hysop.operator.computational import Computational
@@ -13,7 +10,7 @@ class Profiles(Computational):
Compute and print velo/vorti profiles
"""
- def __init__(self, velocity, vorticity, prof_coords,
+ def __init__(self, velocity, vorticity, prof_coords,
direction, beginMeanComput, **kwds):
"""
Constructor.
@@ -30,26 +27,23 @@ class Profiles(Computational):
assert 'variables' not in kwds, 'variables parameter is useless.'
super(Profiles, self).__init__(variables=[velocity, vorticity],
**kwds)
- ## velocity field
+ # velocity field
self.velocity = velocity
- ## vorticity field
+ # vorticity field
self.vorticity = vorticity
- ## X and Y coordinates of the profile
+ # X and Y coordinates of the profile
self.prof_coords = prof_coords
- ## profile direction (0, 1 or 2)
+ # profile direction (0, 1 or 2)
self.direction = direction
- ## time at which the computation of mean profile must begin
+ # time at which the computation of mean profile must begin
self.beginMeanComput = beginMeanComput
self.input = [velocity, vorticity]
self.output = []
def get_work_properties(self):
- if not self._is_discretized:
- msg = 'The operator must be discretized '
- msg += 'before any call to this function.'
- raise RuntimeError(msg)
- vd = self.discreteFields[self.velocity]
- wd = self.discreteFields[self.vorticity]
+ super(Profiles, self).get_work_properties()
+ vd = self.discrete_fields[self.velocity]
+ wd = self.discrete_fields[self.vorticity]
v_ind = vd.topology.mesh.compute_index
w_ind = wd.topology.mesh.compute_index
shape_v = vd[0][v_ind].shape
@@ -63,8 +57,8 @@ class Profiles(Computational):
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
- self.discrete_op = ProfD(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
+ self.discrete_op = ProfD(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
self.prof_coords, self.direction,
self.beginMeanComput,
rwork=rwork)
@@ -72,4 +66,3 @@ class Profiles(Computational):
self._set_io('profile', (1, 9))
self.discrete_op.set_writer(self._writer)
self._is_uptodate = True
-
diff --git a/hysop/old/operator.old/redistribute.py b/hysop/old/operator.old/redistribute.py
new file mode 100644
index 0000000000000000000000000000000000000000..2e5de956feb6df7e9308adae0fc0f41f5d8cb1db
--- /dev/null
+++ b/hysop/old/operator.old/redistribute.py
@@ -0,0 +1,650 @@
+"""Setup for data transfer/redistribution between topologies or operators
+
+`.. currentmodule : hysop.operator.redistribute
+
+* :class:`~RedistributeIntra` for topologies/operators defined
+ inside the same mpi communicator
+* :class:`~RedistributeInter` for topologies/operators defined
+ on two different mpi communicator
+* :class:`~RedistributeOverlap` for topologies defined
+ inside the same mpi parent communicator and
+ with a different number of processes
+* :class:`~Redistribute` abstract base class
+
+"""
+
+from hysop.operator.continuous import OperatorBase
+from abc import ABCMeta, abstractmethod
+from hysop.core.mpi.topology import Cartesian
+from hysop.operator.computational import Computational
+from hysop.operator.continuous import opsetup, opapply
+from hysop.core.mpi.bridge import Bridge, BridgeOverlap, BridgeInter
+from hysop.constants import DirectionLabels, debug
+
+
+class Redistribute(OperatorBase):
+ """Abstract interface to redistribute operators
+ """
+
+ __metaclass__ = ABCMeta
+
+ def __init__(self, source, target, component=None,
+ run_till=None, **kwds):
+ """
+ Parameters
+ ----------
+ source, target: :class:`~hysop.core.mpi.topology.Cartesian` or
+ :class:`~hysop.operator.computational.Computational
+ topologies or operators that own the source mesh and targeted mesh
+ component: int
+ which component of the field must be distributed (default = all)
+ run_till: list of :class:`~hysop.operator.computational.Computational
+ operators that must wait for the completion of this redistribute
+ before any apply.
+
+ """
+ # Base class initialisation
+ super(Redistribute, self).__init__(**kwds)
+
+ # Object (may be an operator or a topology) which handles the
+ # fields to be transfered
+ self._source = source
+ # Object (may an operator or a topology) which handles the fields
+ # to be filled in from source.
+ self._target = target
+
+ self.component = component
+ if component is None:
+ # All components are considered
+ self._range_components = lambda v: xrange(v.nb_components)
+ else:
+ # Only the given component is considered
+ assert self.component >= 0, 'component value must be positive.'
+ self._range_components = lambda v: (self.component)
+
+ # Bridge between topology of source and topology of target
+ self.bridge = None
+ # True if some MPI operations are running for the current operator.
+ self._has_requests = False
+ # Which operator must wait for this one before
+ # any computation
+ # Exp : run_till = op1 means that op1 will
+ # wait for the end of this operator before
+ # op1 starts its apply.
+ if run_till is None:
+ run_till = []
+
+ assert isinstance(run_till, list)
+ self._run_till = run_till
+
+ @abstractmethod
+ def setup(self, rwork=None, iwork=None):
+ """
+ Check/set the list of variables to be distributed
+
+ What must be set at setup?
+ ---> the list of continuous variables to be distributed
+ ---> the bridge (one for all variables, which means
+ that all vars must have the same topology in source
+ and the same topology in target.
+ ---> the list of discrete variables for source and
+ for target.
+ """
+ assert self.domain is not None
+ for v in self.variables:
+ assert v.domain is self.domain
+ super(Redistribute, self).setup(rwork, iwork)
+
+ def _check_operator(self, op):
+ """ ensure op properties:
+ * check if op is really a computational operator
+ * discretize op
+ * check if all required variables (if any) belong to op
+
+ Parameters
+ ----------
+ op : :class:`~hysop.operator.computational.Computational
+ :param: op : a computational operator
+
+ """
+ assert isinstance(op, Computational)
+ op.discretize()
+ msg = 'The variables to be distributed '
+ msg += 'do not belong to the input operator.'
+ if len(self.variables) > 0:
+ assert all(v in op.variables for v in self.variables), msg
+
+ def _set_variables(self):
+ """
+ Check/set the list of variables proceed by the current operator.
+ """
+ # Set list of variables.
+ # It depends on :
+ # - the type of source/target : Cartesian, Computational or None
+ # - the args variables : a list of variables or None
+ # Possible cases:
+ # - if source or target is None --> variables is required
+ # - if source and target are Cartesian --> variables is required
+ # - in all other cases, variables is optional.
+ # If variables are not set at init,
+ # they must be infered from source/target operators.
+ has_var = len(self.variables) > 0
+ vlist = (v for v in self.variables)
+
+ if self._source is None or self._target is None:
+ assert len(self.variables) > 0
+ self.variables = [v for v in vlist]
+ else:
+ source_is_topo = isinstance(self._source, Cartesian)
+ target_is_topo = isinstance(self._target, Cartesian)
+
+ # both source and target are topologies. Variables required.
+ if source_is_topo and target_is_topo:
+ msg = 'Redistribute, a list of variables is required at init.'
+ assert has_var, msg
+ self.variables = [v for v in vlist]
+
+ elif not source_is_topo and not target_is_topo:
+ # both source and target are operators
+ # --> intersection of their variables
+ vsource = self._source.variables
+ vtarget = self._target.variables
+ if not has_var:
+ vlist = (v for v in vsource if v in vtarget)
+ self.variables = [v for v in vlist]
+
+ elif source_is_topo:
+ # source = topo, target = operator
+ vtarget = self._target.variables
+ if not has_var:
+ vlist = (v for v in vtarget)
+ self.variables = [v for v in vlist]
+
+ else:
+ # source = operator, target = topo
+ vsource = self._source.variables
+ if not has_var:
+ vlist = (v for v in vsource)
+ self.variables = [v for v in vlist]
+
+ assert len(self.variables) > 0
+
+ # Variables is converted to a dict to be coherent with
+ # computational operators ...
+ self.variables = {key: None for key in self.variables}
+
+ # All variables must have the same domain
+ self.domain = self.variables.keys()[0].domain
+ for v in self.variables:
+ assert v.domain is self.domain
+
+ def _set_topology(self, current):
+ """This function check if current is valid, fits with self.variables
+ and get its topology to set self._topology.
+
+ Parameters
+ ----------
+ current : :class:`~hysop.core.mpi.topology.Cartesian` or
+ :class:`~hysop.core.mpi.operator.computational.Computational`
+
+ """
+ if isinstance(current, Cartesian):
+ result = current
+ for v in self.variables:
+ v.discretize(result)
+ elif isinstance(current, Computational):
+ self._check_operator(current)
+ vref = self.variables.keys()[0]
+ vcurrent = current.variables
+ result = vcurrent[vref]
+ # We ensure that all vars have
+ # the same topo in target/target.
+ for v in (v for v in self.variables if v is not vref):
+ assert vcurrent[v] is result
+ else:
+ msg = "the source/target is neither an operator or a topology."
+ raise AttributeError(msg)
+ assert result.task_id() == self.domain.current_task()
+ return result
+
+ def computation_time(self):
+ pass
+
+
+class RedistributeIntra(Redistribute):
+ """Data transfer between two operators/topologies.
+ Source and target must:
+ - be defined on the same communicator
+ - work on the same number of mpi process
+ - work with the same global resolution
+ """
+
+ def __init__(self, **kwds):
+ """Data transfer between two operators/topologies defined on the
+ same communicator
+
+ Source and target must:
+ * be defined on the same communicator
+ * work on the same number of mpi process
+ * work with the same global resolution
+ """
+
+ # Base class initialisation
+ super(RedistributeIntra, self).__init__(**kwds)
+
+ # Warning : comm from io_params will be used as
+ # reference for all mpi communication of this operator.
+ # --> rank computed in refcomm
+ # --> source and target must work inside refcomm
+ # If io_params is None, refcomm will COMM_WORLD.
+
+ # Dictionnary of discrete fields to be sent
+ self._vsource = {}
+ # Dictionnary of discrete fields to be overwritten
+ self._vtarget = {}
+
+ # dictionnary which maps rank with mpi derived type
+ # for send operations
+ self._send = {}
+ # dictionnay which maps rank with mpi derived type
+ # for send operations
+ self._receive = {}
+ # dictionnary which map rank/field name with a
+ # receive request
+ self._r_request = None
+ # dictionnary which map rank/field name with a
+ # send request
+ self._s_request = None
+
+ # Set list of variables and the domain.
+ self._set_variables()
+ # Set mpi related stuff
+ self._set_domain_and_tasks()
+
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ # At setup, source and topo must be either
+ # a hysop.core.mpi.topology.Cartesian or
+ # a computational operator.
+
+ msg = 'Redistribute error : undefined source of target.'
+ assert self._source is not None and self._target is not None, msg
+
+ t_source = self._set_topology(self._source)
+ t_target = self._set_topology(self._target)
+
+ source_res = t_source.mesh.discretization.resolution
+ target_res = t_target.mesh.discretization.resolution
+ msg = 'Redistribute error: source and target must '
+ msg += 'have the same global resolution.'
+ assert (source_res == target_res).all(), msg
+
+ # Set the dictionnaries of source/target variables
+ self._vsource = {v: v.discretize(t_source)
+ for v in self.variables}
+ self._vtarget = {v: v.discretize(t_target)
+ for v in self.variables}
+
+ # We can create the bridge
+ self.bridge = Bridge(t_source, t_target)
+
+ # Shape of reference is the shape of source/target mesh
+ self._send = self.bridge.send_types()
+ self._receive = self.bridge.recv_types()
+ self._set_synchro()
+ self._is_uptodate = True
+
+ def _set_synchro(self):
+ """
+ Set who must wait for who ...
+ """
+ # Check input operators
+ if isinstance(self._source, Computational):
+ # redistribute must wait for source if a variable of redistribute
+ # is an output from source.
+ for v in self.variables:
+ vout = v in self._source.output or False
+ if vout:
+ self.wait_for(self._source)
+ # And source must wait for redistribute
+ # if a variable of red. is an output from source.
+ self._source.wait_for(self)
+
+ if isinstance(self._target, Computational):
+ # target operator must wait for
+ # the end of this operator to apply.
+ self._run_till.append(self._target)
+
+ # Add this operator into wait list of
+ # operators listed in run_till
+ for op in self._run_till:
+ op.wait_for(self)
+
+ self._is_uptodate = True
+
+ def add_run_till_op(self, op):
+ """Add an operator to the wait list"""
+ self._run_till.append(op)
+ op.wait_for(self)
+
+ @opapply
+ def apply(self, simulation=None):
+ # Try different way to send vars?
+ # - Buffered : copy all data into a buffer and send/recv
+ # - Standard : one send/recv per component
+ # --- Standard send/recv ---
+ br = self.bridge
+
+ # reset send/recv requests
+ self._r_request = {}
+ self._s_request = {}
+
+ basetag = self.mpi_params.rank + 1
+ # Comm used for send/receive operations
+ # It must contains all proc. of source topo and
+ # target topo.
+ refcomm = self.bridge.comm
+ # Loop over all required components of each variable
+ for v in self.variables:
+ for d in self._range_components(v):
+ v_name = v.name + DirectionLabels[d]
+
+ # Deal with local copies of data
+ if br.has_local_inter():
+ vTo = self._vtarget[v].data[d]
+ vFrom = self._vsource[v].data[d]
+ vTo[br.local_target_ind()] = vFrom[br.local_source_ind()]
+
+ # Transfers to other mpi processes
+ for rk in self._receive:
+ recvtag = basetag * 989 + (rk + 1) * 99 + (d + 1) * 88
+ mpi_type = self._receive[rk]
+ vTo = self._vtarget[v].data[d]
+ self._r_request[v_name + str(rk)] = \
+ refcomm.Irecv([vTo, 1, mpi_type],
+ source=rk, tag=recvtag)
+ self._has_requests = True
+ for rk in self._send:
+ sendtag = (rk + 1) * 989 + basetag * 99 + (d + 1) * 88
+ mpi_type = self._send[rk]
+ vFrom = self._vsource[v].data[d]
+ self._s_request[v_name + str(rk)] = \
+ refcomm.Issend([vFrom, 1, mpi_type],
+ dest=rk, tag=sendtag)
+ self._has_requests = True
+
+ def wait(self):
+ if self._has_requests:
+ for rk in self._r_request:
+ self._r_request[rk].Wait()
+ for rk in self._s_request:
+ self._s_request[rk].Wait()
+ self._has_requests = False
+
+ def test_requests(self):
+ res = True
+ for rk in self._r_request.keys():
+ res = self._r_request[rk].Test()
+ if not res:
+ return res
+ for rk in self._s_request.keys():
+ res = self._s_request[rk].Test()
+ if not res:
+ return res
+
+ def test_single_request(self, rsend=None, rrecv=None):
+ """if neither rsend or rrecv is given return
+ True if all communication request are complete
+ else check for sending to rsend or receiving from rrecv.
+ Process ranks should be those in parent_comm.
+
+ Parameters
+ ----------
+ rsend : string
+ discrete variable name + DirectionLabels + rank of the process
+ to which a message has been sent
+ and for which we want to test message completion.
+ rrecv : string
+ discrete variable name + DirectionLabels + rank of the process
+ from which a message has been receive
+ and for which we want to test message completion.
+
+ """
+ if rsend is not None or rrecv is not None:
+ send_res = True
+ recv_res = True
+ if rsend is not None:
+ send_res = self._s_request[rsend].Test()
+ if rrecv is not None:
+ recv_res = self._r_request[rrecv].Test()
+ res = send_res and recv_res
+ return res
+ else:
+ return self.test_requests()
+
+
+class RedistributeInter(Redistribute):
+ """Operator to redistribute data from one communicator to another.
+ Source/target may be either a topology or a computational operator.
+ It implies mpi inter-communications.
+ """
+
+ @debug
+ def __init__(self, parent, source_id=None, target_id=None, **kwds):
+ """redistribute data from one communicator to another.
+ Source/target may be either a topology or a computational operator.
+ It implies mpi inter-communications.
+
+ Parameters
+ ----------
+ parent : MPI.COMM
+ mpi communicator that must owns all the
+ processes involved in source and target.
+ source_id, target_id : int
+ mpi task ids for the source/target.
+ Required if source/target is None
+ else infered from source/target.
+
+ See other required parameters in base class.
+ """
+ super(RedistributeInter, self).__init__(**kwds)
+
+ # parent communicator, that must contains all processes
+ # involved in source and target tasks.
+ self.parent = parent
+
+ # set source and targets ids.
+ # They must be known before setup.
+ # Either they can be infered from source and target
+ # or must be set in argument list, if either source
+ # or target is undefined on the current process.
+ if self._source is None:
+ assert source_id is not None
+
+ if self._target is None:
+ assert target_id is not None
+
+ self._source_id = source_id
+ self._target_id = target_id
+
+ # Set list of variables and domain.
+ self._set_variables()
+ # Set mpi related stuff
+ self._set_domain_and_tasks()
+
+ # Domain is set, we can check if we are on source or target
+ current_task = self.domain.current_task()
+ self._is_source = current_task == self._source_id
+ self._is_target = current_task == self._target_id
+ assert self._is_target or self._is_source
+ assert not (self._is_target and self._is_source)
+
+ nbprocs = len(self.domain.tasks_list())
+ msg = "Parent communicator size and number of procs "
+ msg += "in domain differ."
+ assert parent.Get_size() == nbprocs, msg
+
+ # the local topology. May be either source or target
+ # depending on the task of the current process.
+ self._topology = None
+
+ # dictionnary which maps rank with mpi derived type
+ # used for send/recv operations (send on source, recv on target ...)
+ self._transfer_types = None
+
+ # dictionnary which maps rank/field name with a
+ # send/recv request
+ self._requests = {}
+
+ @debug
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ # First of all, we need to get the current topology:
+ if self._is_source:
+ assert self._source is not None
+ self._topology = self._set_topology(self._source)
+ elif self._is_target:
+ assert self._target is not None
+ self._topology = self._set_topology(self._target)
+
+ # Now we can build the bridge (intercomm)
+ self.bridge = BridgeInter(self._topology, self.parent,
+ self._source_id, self._target_id)
+
+ # And get mpi derived types
+ self._transfer_types = self.bridge.transfer_types()
+
+ self._set_synchro()
+ self._is_uptodate = True
+
+ def _set_synchro(self):
+ """
+ Set who must wait for who ...
+ """
+ if self._is_source and isinstance(self._source, Computational):
+ # redistribute must wait for source if a variable of redistribute
+ # is an output from source.
+ for v in self.variables:
+ vout = v in self._source.output or False
+ if vout:
+ self.wait_for(self._source)
+ # And source must wait for redistribute
+ # if a variable of red. is an output from source.
+ self._source.wait_for(self)
+
+ if self._is_target and isinstance(self._target, Computational):
+ # target operator must wait for
+ # the end of this operator to apply.
+ self._run_till.append(self._target)
+
+ # Add this operator into wait list of
+ # operators listed in run_till
+ for op in self._run_till:
+ op.wait_for(self)
+
+ def add_run_till_op(self, op):
+ """Add an operator to the wait list"""
+ if self._is_target:
+ self._run_till.append(op)
+ op.wait_for(self)
+
+ @debug
+ @opapply
+ def apply(self, simulation=None):
+ # --- Standard send/recv ---
+ self._requests = {}
+
+ # basetag = self.mpi_params.rank + 1
+ # Comm used for send/receive operations
+ # It must contains all proc. of source topo and
+ # target topo.
+ refcomm = self.bridge.comm
+ # Map between rank and mpi types
+ # Loop over all required components of each variable
+ for v in self.variables:
+ rank = self._topology.comm.Get_rank()
+ for d in self._range_components(v):
+ v_name = v.name + DirectionLabels[d]
+ vtab = v.discrete_fields[self._topology].data[d]
+ for rk in self._transfer_types:
+ if self._is_target:
+ # Set reception
+ self._requests[v_name + str(rk)] = \
+ refcomm.Irecv([vtab[...], 1,
+ self._transfer_types[rk]],
+ source=rk, tag=rk)
+ if self._is_source:
+ self._requests[v_name + str(rk)] = \
+ refcomm.Issend([vtab[...], 1,
+ self._transfer_types[rk]],
+ dest=rk, tag=rank)
+ self._has_requests = True
+
+ def wait(self):
+ if self._has_requests:
+ for rk in self._requests:
+ self._requests[rk].Wait()
+ for v in self.variables:
+ for d in self._range_components(v):
+ vtab = v.discrete_fields[self._topology].data[d]
+ self._has_requests = False
+
+ def test_requests(self):
+ res = True
+ for rk in self._requests:
+ res = self._requests[rk].Test()
+ if not res:
+ return res
+
+
+class RedistributeOverlap(RedistributeIntra):
+ """A specific redistribute where source and target do not work with the same
+ group of mpi processes.
+ Requirements :
+ - work only on topologies, not on operators
+ - same global resolution for both topologies
+ - group from source topology and target topology MUST overlap.
+ """
+
+ @opsetup
+ def setup(self, rwork=None, iwork=None):
+ """
+ Check/set the list of variables to be distributed
+
+ What must be set at setup?
+ ---> the list of continuous variables to be distributed
+ ---> the bridge (one for all variables, which means
+ that all vars must have the same topology in source
+ and the same topology in target.
+ ---> the list of discrete variables for source and
+ for target.
+ """
+ if self._source is not None:
+ self._vsource = self._discrete_fields(self._source)
+ if self._target is not None:
+ self._vtarget = self._discrete_fields(self._target)
+
+ # We can create the bridge
+ self.bridge = BridgeOverlap(source=self._source, target=self._target,
+ comm_ref=self.mpi_params.comm)
+
+ # Build mpi derived types for send and receive operations.
+ # Shape of reference is the shape of source/target mesh
+ if self._source is not None:
+ self._send = self.bridge.send_types()
+ if self._target is not None:
+ self._receive = self.bridge.recv_types()
+
+ self._set_synchro()
+ self._is_uptodate = True
+
+ def _discrete_fields(self, topo):
+ """Return the dictionnary of discrete fields for topo
+ and the variables of this operator.
+
+ Parameters
+ ----------
+ topo : :class:`~hysop.core.mpi.topology.Cartesian`
+ """
+ assert isinstance(topo, Cartesian)
+ return {v: v.discretize(topo) for v in self.variables}
diff --git a/hysop/operator/reprojection.py b/hysop/old/operator.old/reprojection.py
similarity index 96%
rename from hysop/operator/reprojection.py
rename to hysop/old/operator.old/reprojection.py
index eb52b3b64696a76a8b97e01eef323c56f16af009..956f40ae6b07808582fee7e7ed2f95e3bcf45ef1 100644
--- a/hysop/operator/reprojection.py
+++ b/hysop/old/operator.old/reprojection.py
@@ -38,7 +38,7 @@ class Reprojection(Computational):
@opsetup
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
- self.discrete_op = RD(self.discreteFields[self.vorticity],
+ self.discrete_op = RD(self.discrete_fields[self.vorticity],
self.threshold,
self.frequency, rwork=rwork,
method=self.method)
diff --git a/hysop/operator/residual.py b/hysop/old/operator.old/residual.py
similarity index 92%
rename from hysop/operator/residual.py
rename to hysop/old/operator.old/residual.py
index 3eeee3530c037548dd0f3b6fe7eb73cf29ac2eb5..6ead744ede75fa500d7a1c447b809bf2a9451415 100644
--- a/hysop/operator/residual.py
+++ b/hysop/old/operator.old/residual.py
@@ -33,7 +33,7 @@ class Residual(Computational):
msg = 'The operator must be discretized '
msg += 'before any call to this function.'
raise RuntimeError(msg)
- wd = self.discreteFields[self.vorticity]
+ wd = self.discrete_fields[self.vorticity]
w_ind = wd.topology.mesh.compute_index
shape_w = wd[0][w_ind].shape
return {'rwork': [shape_w], 'iwork': None}
@@ -42,7 +42,7 @@ class Residual(Computational):
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
- self.discrete_op = ResD(self.discreteFields[self.vorticity],
+ self.discrete_op = ResD(self.discrete_fields[self.vorticity],
rwork=rwork)
# Initialization of w^(n-1) vorticity value
self.discrete_op.initialize_vortPrev()
diff --git a/hysop/operator/spectrum.py b/hysop/old/operator.old/spectrum.py
similarity index 51%
rename from hysop/operator/spectrum.py
rename to hysop/old/operator.old/spectrum.py
index 1b4f5c1b05df6221985040e76850cb880dc845a6..1e83b39713923bd3e71643bc709bcf326194be0d 100644
--- a/hysop/operator/spectrum.py
+++ b/hysop/old/operator.old/spectrum.py
@@ -1,5 +1,4 @@
-"""
-@file spectrum.py
+"""Compute the spectrum of a field (fftw based)
"""
from hysop.operator.computational import Computational
from hysop.operator.discrete.spectrum import FFTSpectrum
@@ -12,15 +11,17 @@ class Spectrum(Computational):
Fourier spectrum computation of a scalar field.
"""
- def __init__(self, field, prefix=None, **kwds):
+ def __init__(self, field, **kwds):
"""
- Constructor for Spectrum operator
- @param[in] field : field to compute
+
+ Parameters
+ ----------
+ field: :class:`~hysop.fields.continuous.Field`
+ the input field for which spectrum will be computed
"""
super(Spectrum, self).__init__(variables=[field], **kwds)
self.field = field
self.input = [field]
- self._prefix = prefix
def discretize(self):
super(Spectrum, self)._fftw_discretize()
@@ -28,7 +29,12 @@ class Spectrum(Computational):
@debug
@opsetup
def setup(self, rwork=None, iwork=None):
- self.discrete_op = FFTSpectrum(self.discreteFields[self.field],
- method=self.method,
- prefix=self._prefix)
+ self.discrete_op = FFTSpectrum(self.discrete_fields[self.field],
+ method=self.method)
+ nbc = self.discrete_op.res.size
+ self._set_io('spectrum', (1, 2 * nbc))
+ self.discrete_op.set_writer(self._writer)
self._is_uptodate = True
+
+ def get_work_properties(self):
+ return {'rwork': None, 'iwork': None}
diff --git a/hysop/operator/stretching.py b/hysop/old/operator.old/stretching.py
similarity index 66%
rename from hysop/operator/stretching.py
rename to hysop/old/operator.old/stretching.py
index 130d951b9d19569109ff083a6952ce4b2b5bd41b..94d36202a0969951f5f8a4007bb2f173ae25df5d 100755
--- a/hysop/operator/stretching.py
+++ b/hysop/old/operator.old/stretching.py
@@ -9,16 +9,14 @@ See also
"""
from hysop.constants import debug
-from hysop.methods_keys import TimeIntegrator, Formulation, \
- SpaceDiscretisation, Support
+from hysop.methods import TimeIntegrator, Formulation, \
+ SpaceDiscretization
+from hysop.numerics.finite_differences import FDC4
from hysop.operator.computational import Computational
from hysop.operator.continuous import opsetup
from hysop.operator.discrete.stretching import Conservative, GradUW
from hysop.operator.discrete.stretching import StretchingLinearized as SLD
-from hysop.gpu.gpu_stretching import GPUStretching
-
-import hysop.numerics.differential_operations as diff_op
-from hysop.numerics.finite_differences import FDC4
+from hysop.numerics.differential_operations import GradVxW, DivWV
from hysop.numerics.odesolvers import Euler
@@ -27,6 +25,7 @@ class Stretching(Computational):
"""
_authorized_methods = [FDC4]
+ _authorized_formulations = [Conservative, GradUW]
@debug
def __init__(self, velocity, vorticity, **kwds):
@@ -51,74 +50,63 @@ class Stretching(Computational):
# vorticity variable (vector)
self.vorticity = vorticity
# Numerical methods for time and space discretization
-
+
if self.method is None:
import hysop.default_methods as default
self.method = default.STRETCHING
- assert Formulation in self.method.keys()
- assert SpaceDiscretisation in self.method.keys()
- assert TimeIntegrator in self.method.keys()
+ assert Formulation in self.method.keys()
+ assert SpaceDiscretization in self.method.keys()
+ assert TimeIntegrator in self.method.keys()
msg = 'Stretching : unknown method for space discretization'
- assert self.method[SpaceDiscretisation] in self._authorized_methods,\
+ assert self.method[SpaceDiscretization] in self._authorized_methods,\
msg
-
- if Support in self.method.keys() and self.method[Support].lower().find('gpu')>=0:
- self.formulation = GPUStretching
- else:
- if self.method[Formulation] == 'GradUW':
- self.formulation = GradUW
- else:
- self.formulation = Conservative
-
+ # Formulation used for the stretching equation.
+ # Default = conservative form.
+ self.formulation = self.method[Formulation]
+ msg = 'Stretching error : unknown formulation.'
+ assert self.formulation in self._authorized_formulations, msg
self.input = [self.velocity, self.vorticity]
self.output = [self.vorticity]
def get_work_properties(self):
super(Stretching, self).get_work_properties()
-
# Get fields local shape.
- vd = self.discreteFields[self.velocity]
-
- if self.formulation is GPUStretching:
- #TODO
- pass
- else:
- # --> time-integrator required work space
- ti = self.method[TimeIntegrator]
- topo = vd.topology
- nbc = self.velocity.nb_components
- res = ti.get_work_properties(nbc, topo)
-
- # ---> differential operator work space
- if self.formulation is GradUW:
- dop = diff_op.GradVxW
- elif self.formulation is Conservative:
- dop = diff_op.DivWV
- res['rwork'] += dop.get_work_properties(topo)['rwork']
+ vd = self.discrete_fields[self.velocity]
+ # Collect info from numerical methods
+ # --> time-integrator required work space
+ ti = self.method[TimeIntegrator]
+ topo = vd.topology
+ nbc = self.velocity.nb_components
+ res = ti.get_work_properties(nbc, topo)
+ # ---> differential operator work space
+ if self.formulation is GradUW:
+ dop = GradVxW
+
+ elif self.formulation is Conservative:
+ dop = DivWV
+ res['rwork'] += dop.get_work_properties(topo)['rwork']
return res
@debug
def discretize(self):
- nbghosts = self.method[SpaceDiscretisation].ghosts_layer_size
+ nbghosts = self.method[SpaceDiscretization].ghosts_layer_size
super(Stretching, self)._standard_discretize(nbghosts)
@debug
@opsetup
def setup(self, rwork=None, iwork=None):
self.discrete_op =\
- self.formulation(velocity=self.discreteFields[self.velocity],
- vorticity=self.discreteFields[self.vorticity],
+ self.formulation(velocity=self.discrete_fields[self.velocity],
+ vorticity=self.discrete_fields[self.vorticity],
method=self.method, rwork=rwork, iwork=iwork)
self._is_uptodate = True
class StretchingLinearized(Stretching):
- """Solve the linearized stretching equation, i.e:
+ """Solve the linearized stretching equation
+
+ See details in :ref:`stretching`.
- \f{eqnarray*}
- \frac{\partial \omega}{\partial t} &=& (\om \cdot \nabla)u_b +
- (\om_b \cdot \nabla)u
- \f}
"""
@debug
def __init__(self, velocity_BF, vorticity_BF, **kwds):
@@ -153,7 +141,7 @@ class StretchingLinearized(Stretching):
@debug
def discretize(self):
- nbghosts = self.method[SpaceDiscretisation].ghosts_layer_size
+ nbghosts = self.method[SpaceDiscretization].ghosts_layer_size
self.usual_stretch.discretize()
super(StretchingLinearized, self)._standard_discretize(nbghosts)
@@ -168,9 +156,9 @@ class StretchingLinearized(Stretching):
method_lin = self.method.copy()
method_lin[TimeIntegrator] = Euler
self.discrete_op =\
- SLD(velocity=self.discreteFields[self.velocity],
- vorticity=self.discreteFields[self.vorticity],
- vorticity_BF=self.discreteFields[self.vorticity_BF],
+ SLD(velocity=self.discrete_fields[self.velocity],
+ vorticity=self.discrete_fields[self.vorticity],
+ vorticity_BF=self.discrete_fields[self.vorticity_BF],
usual_op=self.usual_stretch.discrete_op,
method=method_lin, rwork=rwork, iwork=iwork)
self._is_uptodate = True
diff --git a/hysop/old/operator.old/tests/__init__.py b/hysop/old/operator.old/tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/operator/tests/ref_files/penal2d_multi.xmf b/hysop/old/operator.old/tests/ref_files/penal2d_multi.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal2d_multi.xmf
rename to hysop/old/operator.old/tests/ref_files/penal2d_multi.xmf
diff --git a/hysop/operator/tests/ref_files/penal2d_multi_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal2d_multi_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal2d_multi_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal2d_multi_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal2d_porous.xmf b/hysop/old/operator.old/tests/ref_files/penal2d_porous.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal2d_porous.xmf
rename to hysop/old/operator.old/tests/ref_files/penal2d_porous.xmf
diff --git a/hysop/operator/tests/ref_files/penal2d_porous_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal2d_porous_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal2d_porous_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal2d_porous_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal2d_sphere.xmf b/hysop/old/operator.old/tests/ref_files/penal2d_sphere.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal2d_sphere.xmf
rename to hysop/old/operator.old/tests/ref_files/penal2d_sphere.xmf
diff --git a/hysop/operator/tests/ref_files/penal2d_sphere_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal2d_sphere_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal2d_sphere_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal2d_sphere_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal3d_multi.xmf b/hysop/old/operator.old/tests/ref_files/penal3d_multi.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_multi.xmf
rename to hysop/old/operator.old/tests/ref_files/penal3d_multi.xmf
diff --git a/hysop/operator/tests/ref_files/penal3d_multi_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal3d_multi_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_multi_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal3d_multi_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal3d_porous.xmf b/hysop/old/operator.old/tests/ref_files/penal3d_porous.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_porous.xmf
rename to hysop/old/operator.old/tests/ref_files/penal3d_porous.xmf
diff --git a/hysop/operator/tests/ref_files/penal3d_porous_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal3d_porous_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_porous_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal3d_porous_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal3d_porous_cyl.xmf b/hysop/old/operator.old/tests/ref_files/penal3d_porous_cyl.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_porous_cyl.xmf
rename to hysop/old/operator.old/tests/ref_files/penal3d_porous_cyl.xmf
diff --git a/hysop/operator/tests/ref_files/penal3d_porous_cyl_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal3d_porous_cyl_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_porous_cyl_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal3d_porous_cyl_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal3d_sphere.xmf b/hysop/old/operator.old/tests/ref_files/penal3d_sphere.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_sphere.xmf
rename to hysop/old/operator.old/tests/ref_files/penal3d_sphere.xmf
diff --git a/hysop/operator/tests/ref_files/penal3d_sphere_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal3d_sphere_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal3d_sphere_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal3d_sphere_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal_vort_2d_multi_sphere_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal_vort_2d_multi_sphere_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal_vort_2d_multi_sphere_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal_vort_2d_multi_sphere_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal_vort_2d_sphere.xmf b/hysop/old/operator.old/tests/ref_files/penal_vort_2d_sphere.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal_vort_2d_sphere.xmf
rename to hysop/old/operator.old/tests/ref_files/penal_vort_2d_sphere.xmf
diff --git a/hysop/operator/tests/ref_files/penal_vort_2d_sphere_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal_vort_2d_sphere_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal_vort_2d_sphere_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal_vort_2d_sphere_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal_vort_3d_multi_sphere_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal_vort_3d_multi_sphere_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal_vort_3d_multi_sphere_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal_vort_3d_multi_sphere_00000.h5
diff --git a/hysop/operator/tests/ref_files/penal_vort_3d_sphere.xmf b/hysop/old/operator.old/tests/ref_files/penal_vort_3d_sphere.xmf
similarity index 100%
rename from hysop/operator/tests/ref_files/penal_vort_3d_sphere.xmf
rename to hysop/old/operator.old/tests/ref_files/penal_vort_3d_sphere.xmf
diff --git a/hysop/operator/tests/ref_files/penal_vort_3d_sphere_00000.h5 b/hysop/old/operator.old/tests/ref_files/penal_vort_3d_sphere_00000.h5
similarity index 100%
rename from hysop/operator/tests/ref_files/penal_vort_3d_sphere_00000.h5
rename to hysop/old/operator.old/tests/ref_files/penal_vort_3d_sphere_00000.h5
diff --git a/hysop/old/operator.old/tests/test_absorption_bc.py b/hysop/old/operator.old/tests/test_absorption_bc.py
new file mode 100644
index 0000000000000000000000000000000000000000..8f97dd6c244ee6f982e361783404a2fa5724e12f
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_absorption_bc.py
@@ -0,0 +1,123 @@
+"""Test 'boundaries absorption' operator
+"""
+from hysop.operator.absorption_bc import AbsorptionBC
+from hysop import Box, Discretization, Field, VariableParameter,\
+ Simulation
+import numpy as np
+from hysop.domain.subsets import SubBox
+from hysop.operator.analytic import Analytic
+
+
+d2d = Discretization([33, ] * 2)
+d3d = Discretization([33, ] * 3)
+
+uinf = 10.
+
+
+def init_test(dim, discr, ext_filter, filter_func=None):
+ """Create fields and operator
+ """
+ dom = Box([1., ] * dim)
+ #topo = dom.create_topology(discr)
+ v = Field(dom, name='velo', is_vector=True)
+ w = Field(dom, name='vorti', is_vector=True)
+ wref = Field(v.domain, name='wref', is_vector=True)
+
+ topo = dom.create_topology(discr)
+ # Build and apply absorption operator on w
+ flowrate = VariableParameter(data=uinf)
+ x_range = [0.9, 1.]
+ op = AbsorptionBC(v, w, flowrate, x_range,
+ discretization=discr, filter_func=filter_func)
+ op.discretize()
+ op.setup()
+ wk_prop = op.get_work_properties()['rwork']
+ dop = op.discrete_op
+ assert np.prod(dop.absorption_box.mesh[topo].resolution) == wk_prop[0]
+
+ orig = [0.9, 0., 0.]
+ ll = [0.1, 1., 1.]
+ boxend = SubBox(origin=orig, length=ll, parent=dom)
+ ll = [0.9, 1., 1.]
+ boxend.discretize(topo)
+ v.randomize(topo)
+ vd = v.discretize(topo)
+ w.randomize(topo)
+ wref.copy(w, topo)
+ wdref = wref.discretize(topo)
+ wd = w.discretize(topo)
+
+ for d in xrange(dom.dimension):
+ assert np.allclose(wdref[d], wd[d])
+ op.apply()
+ # Apply filter on wref
+ if dop.absorption_box.on_proc[topo]:
+ ext_filter(wdref, vd, boxend, topo)
+ for d in xrange(dom.dimension):
+ assert np.allclose(wdref[d], wd[d])
+
+
+def apply_filter_default(res, velo, subbox, topo):
+ """Default values for the filter in the absorption box
+ """
+ xcend = subbox.mesh[topo].coords[0]
+ iend = subbox.ind[topo][0]
+ xb = xcend[0]
+ xe = xcend[-1]
+ xc = xb + (xe - xb) / 2.0
+ eps = 10.
+ form = np.tanh(eps * (xcend - xc))
+ absorption_filter = form - np.tanh(eps * (xe - xc))
+ coeff = 1.0 / (np.tanh(eps * (xb - xc)) - np.tanh(eps * (xe - xc)))
+ absorption_filter *= coeff
+ res[0][iend] *= absorption_filter
+ res[1][iend] *= absorption_filter
+ res[2][iend] *= absorption_filter
+ dfilter = eps * (1.0 - form ** 2)
+ dfilter *= coeff
+ res[1][iend] = res[1][iend] + (uinf - velo[2][iend]) * dfilter
+ res[2][iend] = res[2][iend] - (uinf - velo[1][iend]) * dfilter
+ return res
+
+
+def apply_user_filter(res, velo, subbox, topo):
+ """Linear filter
+ """
+ xcend = subbox.mesh[topo].coords[0]
+ iend = subbox.ind[topo][0]
+ xb = xcend[0]
+ xe = xcend[-1]
+ absorption_filter = xcend / (xb - xe) - 1. / (xb - xe)
+ res[0][iend] *= absorption_filter
+ res[1][iend] *= absorption_filter
+ res[2][iend] *= absorption_filter
+ dfilter = 1. / (xb - xe)
+ res[1][iend] = res[1][iend] + (uinf - velo[2][iend]) * dfilter
+ res[2][iend] = res[2][iend] - (uinf - velo[1][iend]) * dfilter
+ return res
+
+
+def test_default_filter_3d():
+ """Filter using default internal
+ filter
+ """
+ init_test(3, d3d, apply_filter_default)
+
+
+def user_filter(x):
+ """Linear filter, just for test"""
+ xb = x[0]
+ xe = x[-1]
+ return x / (xb - xe) - 1. / (xb - xe)
+
+
+def user_diff_filter(x):
+ """Linear filter, just for test"""
+ return 1. / (x[0] - x[-1])
+
+
+def test_user_filter_3d():
+ """Filter using external filter
+ """
+ filter_f = [user_filter, user_diff_filter]
+ init_test(3, d3d, apply_user_filter, filter_f)
diff --git a/hysop/operator/tests/test_adaptive_time_step.py b/hysop/old/operator.old/tests/test_adaptive_time_step.py
similarity index 98%
rename from hysop/operator/tests/test_adaptive_time_step.py
rename to hysop/old/operator.old/tests/test_adaptive_time_step.py
index c3b7c370979764a0ae96c66af5b0568530c98773..6ad31acd104ad744642830c9935982dabbeaeb3b 100755
--- a/hysop/operator/tests/test_adaptive_time_step.py
+++ b/hysop/old/operator.old/tests/test_adaptive_time_step.py
@@ -3,14 +3,14 @@ from hysop import Field, Box
from hysop.operator.adapt_timestep import AdaptiveTimeStep
from hysop.problem.simulation import Simulation
from hysop.tools.parameters import Discretization
-from hysop.mpi import main_comm, main_size
+from hysop.core.mpi import main_comm, main_size
import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.tools.misc import WorkSpaceTools
from hysop.numerics.tests.test_differential_operations import compute_vel,\
compute_vort, diag_grad_func_3d, compute_max, grad_v_func_3d, strain_f_3d
from math import pi
-from hysop.methods_keys import TimeIntegrator
+from hysop.methods import TimeIntegrator
sin = np.sin
cos = np.cos
diff --git a/hysop/old/operator.old/tests/test_advec_scales.py b/hysop/old/operator.old/tests/test_advec_scales.py
new file mode 100755
index 0000000000000000000000000000000000000000..d5d69ed4c164f52199d20d8206dc4ba72044eaa2
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_advec_scales.py
@@ -0,0 +1,218 @@
+"""Testing Scales advection operator.
+"""
+from __future__ import print_function
+import numpy as np
+from hysop.methods import TimeIntegrator, Interpolation,\
+ Remesh, Support, Splitting
+from hysop.methods import RK2, L2_1, L4_2, M8Prime, Linear
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.operator.advection import Advection, ScalesAdvection
+from hysop.problem.simulation import O2FULLHALF
+from hysop.problem.simulation import Simulation
+from hysop.testsenv import scales_failed
+from hysop.tools.parameters import Discretization
+d3d = Discretization([17, 17, 17])
+d3d_g = Discretization([17, 17, 17], [6, 6, 6])
+
+m1 = {TimeIntegrator: RK2, Interpolation: Linear, Remesh: L2_1,
+ Splitting: O2FULLHALF, Support: ''}
+m2 = {TimeIntegrator: RK2, Interpolation: Linear, Remesh: L4_2,
+ Splitting: O2FULLHALF, Support: ''}
+m3 = {TimeIntegrator: RK2, Interpolation: Linear, Remesh: M8Prime,
+ Splitting: O2FULLHALF, Support: ''}
+
+
+def run_advection(vector_field, method, mref=None, random_velocity=False):
+ """Create advection operator, ref operator
+ and fields, run scales and python advection,
+ compare results.
+
+ Parameters
+ ----------
+ vector_field: bool
+ True to advect a vector field, else scalar field.
+ method : dictionnary
+ Set scales remeshing type.
+ mref : dictionnary, optional
+ method for pure python advection. Default = m1
+ random_velocity: boolean
+ If True, randomize velocity values, else set it to 0.
+ """
+ box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
+ scal = Field(domain=box, name='Scalar', is_vector=vector_field)
+ scal_ref = Field(domain=box, name='Scalar_ref', is_vector=vector_field)
+ velo = Field(domain=box, name='Velocity',
+ formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
+ vectorize_formula=True)
+ advec = ScalesAdvection(velocity=velo,
+ advected_fields=scal,
+ discretization=d3d,
+ method=method)
+ if mref is None:
+ mref = m1
+ advec_py = Advection(velocity=velo,
+ advected_fields=scal_ref, discretization=d3d_g,
+ method=mref)
+ advec.discretize()
+ advec_py.discretize()
+ advec.setup()
+ advec_py.setup()
+ # Get and randomize discrete fields
+ topo = advec.advected_fields_topology()
+ topo_ref = advec_py.advected_fields_topology()
+
+ if random_velocity:
+ topo_velo = advec.velocity_topology()
+ vd = velo.randomize(topo_velo)
+ for d in xrange(velo.nb_components):
+ vd[d] /= 2 * topo_velo.mesh.resolution[d]
+ else:
+ assert (velo.norm(topo) == 0).all()
+ ic = topo.mesh.compute_index
+ icref = topo_ref.mesh.compute_index
+ print(icref)
+ print(ic)
+ scal_d = scal.randomize(topo)
+ scal_ref_d = scal.discretize(topo_ref)
+ for d in xrange(len(scal_d.data)):
+ scal_ref_d[d][icref] = scal_d[d][ic]
+ assert np.allclose(scal_ref_d.data[d][icref], scal_d.data[d][ic])
+ advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
+ advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
+ # compare values on grid (excluding ghosts)
+ # for d in xrange(len(scal_d.data)):
+ # assert np.allclose(scal_ref_d.data[d][icref], scal_d.data[d][ic])
+
+
+def run_advection_2(vector_field, method):
+ """Create advection operator,
+ fields, run and check results.
+
+ Parameters
+ ----------
+ vector_field: bool
+ True to advect a vector field, else scalar field.
+ method : dictionnary
+ Set scales remeshing type.
+ """
+ box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
+ scal = Field(domain=box, name='Scalar', is_vector=vector_field)
+ scal_ref = Field(domain=box, name='Scalar_ref', is_vector=vector_field)
+ velo = Field(domain=box, name='Velocity',
+ formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
+ vectorize_formula=True)
+ advec = ScalesAdvection(velocity=velo,
+ advected_fields=scal, discretization=d3d,
+ method=method)
+ advec.discretize()
+ advec.setup()
+ # Get and randomize discrete fields
+ topo = advec.advected_fields_topology()
+ assert (velo.norm(topo) == 0).all()
+ ic = topo.mesh.compute_index
+ scal_d = scal.randomize(topo)
+ scal_ref.copy(scal, topo)
+ scal_ref_d = scal.discretize(topo)
+ for d in xrange(len(scal_d.data)):
+ assert np.allclose(scal_ref_d.data[d][ic], scal_d.data[d][ic])
+ advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
+ # compare values on grid (excluding ghosts)
+ for d in xrange(len(scal_d.data)):
+ assert np.allclose(scal_ref_d.data[d][ic], scal_d.data[d][ic])
+
+
+@scales_failed
+def test_null_velocity_m4():
+ """Scalar field advection, null velocity, M4prime remesh
+ """
+ method = {Remesh: 'p_M4'}
+ run_advection_2(False, method)
+
+
+@scales_failed
+def test_null_velocity_vec_m4():
+ """Vector field advection, null velocity, M4prime remesh
+ """
+ method = {Remesh: 'p_M4'}
+ run_advection_2(True, method)
+
+
+@scales_failed
+def test_null_velocity_m6():
+ """Scalar field advection, null velocity, M6prime remesh
+ """
+ method = {Remesh: 'p_M6'}
+ run_advection_2(False, method)
+
+
+@scales_failed
+def test_null_velocity_vec_m6():
+ """Vector field advection, null velocity, M6prime remesh
+ """
+ method = {Remesh: 'p_M6'}
+ run_advection_2(True, method)
+
+
+@scales_failed
+def test_null_velocity_m8():
+ """Scalar field advection, null velocity, M6prime remesh
+ """
+ method = {Remesh: 'p_M8'}
+ run_advection_2(False, method)
+
+
+@scales_failed
+def test_null_velocity_vec_m8():
+ """Vector field advection, null velocity, M6prime remesh
+ """
+ method = {Remesh: 'p_M8'}
+ run_advection_2(True, method)
+
+
+@scales_failed
+def test_random_velocity_m4():
+ """Scalar field advection, random velocity, M4prime remesh
+ """
+ method = {Remesh: 'p_M4'}
+ run_advection(False, method, random_velocity=True)
+
+
+@scales_failed
+def test_random_velocity_vec_m4():
+ """Vector field advection, random velocity, M4prime remesh
+ """
+ method = {Remesh: 'p_M4'}
+ run_advection(True, method, random_velocity=True)
+
+
+@scales_failed
+def test_random_velocity_m6():
+ """Scalar field advection, random velocity, M6prime remesh
+ """
+ method = {Remesh: 'p_M6'}
+ run_advection(False, method, m2, random_velocity=True)
+
+
+@scales_failed
+def test_random_velocity_vec_m6():
+ """Vector field advection, random velocity, M6prime remesh
+ """
+ method = {Remesh: 'p_M6'}
+ run_advection(True, method, m2, random_velocity=True)
+
+
+@scales_failed
+def test_random_velocity_m8():
+ """Scalar field advection, random velocity, M8prime remesh
+ """
+ method = {Remesh: 'p_M8'}
+ run_advection(False, method, m3, random_velocity=True)
+
+
+@scales_failed
+def test_random_velocity_vec_m8():
+ """Vector field advection, random velocity, M8prime remesh
+ """
+ method = {Remesh: 'p_M8'}
+ run_advection(True, method, m3, random_velocity=True)
diff --git a/hysop/old/operator.old/tests/test_advection.py b/hysop/old/operator.old/tests/test_advection.py
new file mode 100644
index 0000000000000000000000000000000000000000..4b1d44ecf26ee8477a687cfcf252ae37a3359c92
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_advection.py
@@ -0,0 +1,199 @@
+"""Tests for non-gpu Advection"""
+
+from hysop.tools.parameters import Discretization
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.problem.simulation import Simulation
+from hysop.operator.advection import Advection
+from hysop.tools.numpywrappers import npw
+import numpy as np
+
+
+def find_min_work(velo, fields, topo):
+ """Get minimal space required for
+ internal buffers in advection
+ """
+ op = Advection(velocity=velo,
+ advected_fields=fields, discretization=topo)
+ op.discretize()
+ iwork = []
+ rwork = []
+ work_prop = op.get_work_properties()
+ if work_prop['rwork'] is not None:
+ for sh in work_prop['rwork']:
+ incr_sh = np.asarray(sh)
+ incr_sh[0] += 143
+ rwork.append(npw.zeros(incr_sh))
+
+ if work_prop['iwork'] is not None:
+ for sh in work_prop['iwork']:
+ incr_sh = np.asarray(sh)
+ incr_sh[0] += 1343
+ iwork.append(npw.int_zeros(sh))
+ return iwork, rwork
+
+g = 2
+d2d = Discretization([17, 17], [g, g])
+d3d = Discretization([17, 33, 29], [g, g, g])
+d2d_2 = Discretization([25, 17], [2, 2])
+d3d_2 = Discretization([25, 33, 29], [2, 2, 2])
+box_2d = Box(length=[2., 2.], origin=[-1., -1.])
+box_3d = Box(length=[2., 4., 1.], origin=[-1., -2., 0.])
+topo_2d = box_2d.create_topology(d2d, cutdir=[False, True])
+topo_3d = box_3d.create_topology(d3d, cutdir=[False, False, True])
+topo_2d_2 = box_2d.create_topology(d2d_2, cutdir=[False, True])
+topo_3d_2 = box_3d.create_topology(d3d_2, cutdir=[False, False, True])
+velo_2d = Field(domain=box_2d, name='Velocity2D',
+ formula=lambda x, y: (0., 0.), is_vector=True)
+velo_3d = Field(domain=box_3d, name='Velocity3D',
+ formula=lambda x, y: (0., 0., 0.), is_vector=True)
+scal_2d = Field(domain=box_2d, name='Scal2D')
+scal_3d = Field(domain=box_3d, name='Scal3D')
+scal_2d_2 = Field(domain=box_2d, name='Scal2D2')
+scal_3d_2 = Field(domain=box_3d, name='Scal3D2')
+global_iwork_2d, global_rwork_2d = find_min_work(velo_2d, scal_2d, topo_2d)
+global_iwork_3d, global_rwork_3d = find_min_work(velo_3d, scal_3d, topo_3d)
+simu = Simulation(start=0., end=0.1, nb_iter=1)
+
+
+def build_advection(velo, fields, discr, discr_fields=None,
+ rwork=None, iwork=None):
+ """declare, discretize and setup advection operator
+
+ Parameters
+ ----------
+
+ velo, fields : velocity field and list of advected fields
+ discr : chosen discretization for velocity
+ discr_fields : chosen discretization for advected_fields
+ if None == discr
+ rwork, iwork : pre-allocated work arrays
+ if None, let operator do the allocation job.
+
+ """
+ # Build and discretize advection
+ op = Advection(velocity=velo,
+ advected_fields=fields, discretization=discr,
+ discretization_fields=discr_fields)
+ op.discretize()
+ # checks
+ assert velo in op.input
+ assert velo not in op.output
+ if isinstance(fields, list):
+ for f in fields:
+ assert f in op.input
+ assert f in op.output
+ else:
+ assert fields in op.input
+ assert fields in op.output
+ assert len(op.discrete_op) == velo.domain.dimension
+ # iwork = None
+ # rwork = None
+ # if use_work:
+ # work_prop = op.get_work_properties()
+ # if work_prop['rwork'] is not None:
+ # rwork = []
+ # for sh in work_prop['rwork']:
+ # rwork.append(npw.zeros(sh))
+
+ # if work_prop['iwork'] is not None:
+ # rwork = []
+ # for sh in work_prop['iwork']:
+ # iwork.append(npw.zeros(sh))
+
+ # work_prop = op.get_work_properties()
+ op.setup(rwork, iwork)
+ dop = op.discrete_op[0]
+ rw0 = dop._rwork
+ iw0 = dop._iwork
+ for i in xrange(1, velo.domain.dimension):
+ dop = op.discrete_op[i]
+ rw = dop._rwork
+ iw = dop._iwork
+ assert len(rw) == len(rw0)
+ assert len(iw) == len(iw0)
+ for j in xrange(len(rw)):
+ assert npw.arrays_share_data(rw[j], rw0[j])
+ for j in xrange(len(iw)):
+ assert npw.arrays_share_data(iw[j], iw0[j])
+
+ return op
+
+
+def test_build_2d_1():
+ """single resolution build, 2d
+ """
+ build_advection(velo_2d, scal_2d, d2d)
+
+
+def test_build_2d_2():
+ """single resolution build, from topo, 2d"""
+ build_advection(velo_2d, [scal_2d, scal_2d_2], topo_2d)
+
+
+def test_build_2d_3():
+ """multi resolution build, 2d
+ """
+ build_advection(velo_2d, [scal_2d, scal_2d_2], d2d_2, d2d)
+
+
+def test_build_2d_4():
+ """multi resolution build, from topo, 2d"""
+ build_advection(velo_2d, scal_2d, topo_2d_2, topo_2d)
+
+
+def test_build_2d_5():
+ """multi resolution build, from topo, 2d, with work"""
+ op = build_advection(velo_2d, scal_2d, topo_2d_2, topo_2d,
+ rwork=global_rwork_2d, iwork=global_iwork_2d)
+ for i in xrange(velo_2d.domain.dimension):
+ dop = op.discrete_op[i]
+ rw = dop._rwork
+ iw = dop._iwork
+ for j in xrange(len(rw)):
+ assert npw.arrays_share_data(rw[j], global_rwork_2d[j])
+ for j in xrange(len(iw)):
+ assert npw.arrays_share_data(iw[j], global_iwork_2d[j])
+
+
+def test_build_3d_1():
+ """single resolution build, 3d
+ """
+ build_advection(velo_3d, scal_3d, d3d)
+
+
+def test_build_3d_2():
+ """single resolution build, from topo, 3d"""
+ build_advection(velo_3d, [scal_3d, scal_3d_2], topo_3d)
+
+
+def test_build_3d_3():
+ """multi resolution build, 3d
+ """
+ build_advection(velo_3d, [scal_3d, scal_3d_2], d3d_2, d3d)
+
+
+def test_build_3d_4():
+ """multi resolution build, from topo, 3d"""
+ build_advection(velo_3d, scal_3d, topo_3d_2, topo_3d)
+
+
+def test_build_3d_5():
+ """multi resolution build, from topo, 3d, with work"""
+ op = build_advection(velo_3d, scal_3d, topo_3d_2, topo_3d,
+ rwork=global_rwork_3d, iwork=global_iwork_3d)
+ for i in xrange(velo_3d.domain.dimension):
+ dop = op.discrete_op[i]
+ rw = dop._rwork
+ iw = dop._iwork
+ for j in xrange(len(rw)):
+ assert npw.arrays_share_data(rw[j], global_rwork_3d[j])
+ for j in xrange(len(iw)):
+ assert npw.arrays_share_data(iw[j], global_iwork_3d[j])
+
+
+def test_apply_2d():
+ """advection of a field ... at null velocity, 2d.
+ """
+ op = build_advection(velo_2d, scal_2d, d2d)
+ op.apply(simu)
diff --git a/hysop/old/operator.old/tests/test_analytic.py b/hysop/old/operator.old/tests/test_analytic.py
new file mode 100755
index 0000000000000000000000000000000000000000..99de42b0b2e6be35f6bfe5852d6546fb2ecab6d4
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_analytic.py
@@ -0,0 +1,162 @@
+"""Test initialization of fields with analytic formula
+"""
+from numpy import allclose
+from hysop.domain.box import Box
+from hysop.fields.continuous import Field
+from hysop.operator.analytic import Analytic
+from hysop.problem.simulation import Simulation
+from hysop.tools.parameters import Discretization
+from hysop.fields.tests.func_for_tests import func_scal_1, func_scal_2, \
+ func_vec_1, func_vec_2, func_vec_3, func_vec_4, func_vec_5, func_vec_6
+d3D = Discretization([33, 33, 33])
+d2D = Discretization([33, 33])
+L2D = [1., 1.]
+origin2D = [0., 0.]
+nbc = 4
+simu = Simulation(start=0., end=0.1, nb_iter=1)
+
+
+# Non-Vectorized and vectorized formulas for a scalar
+def test_analytical_op_1():
+ box = Box()
+ caf = Field(box, formula=func_scal_1, name='caf')
+ caf2 = Field(box, name='caf2', formula=func_scal_2, vectorize_formula=True)
+ op = Analytic(variables={caf: d3D})
+ op2 = Analytic(variables={caf2: d3D})
+ op.discretize()
+ op2.discretize()
+ op.setup()
+ op2.setup()
+ topo = op.discrete_fields[caf].topology
+ coords = topo.mesh.coords
+ ref = Field(box, name='ref')
+ refd = ref.discretize(topo)
+ cafd = caf.discrete_fields[topo]
+ cafd2 = caf2.discrete_fields[topo]
+ ids = id(cafd.data[0])
+ ids2 = id(cafd2.data[0])
+ op.apply(simu)
+ op2.apply(simu)
+ refd.data = func_scal_1(refd.data, *(coords + (simu.time,)))
+ assert allclose(cafd[0], refd.data[0])
+ assert id(cafd.data[0]) == ids
+ assert allclose(cafd2[0], refd.data[0])
+ assert id(cafd2.data[0]) == ids2
+
+
+# Non-Vectorized and vectorized formulas for a vector
+def test_analytical_op_3():
+ box = Box()
+ caf = Field(box, name='caf', formula=func_vec_1, is_vector=True)
+ caf2 = Field(box, name='caf', formula=func_vec_2,
+ vectorize_formula=True, is_vector=True)
+ op = Analytic(variables={caf: d3D})
+ op2 = Analytic(variables={caf2: d3D})
+ op.discretize()
+ op2.discretize()
+ op.setup()
+ op2.setup()
+ topo = op.discrete_fields[caf].topology
+ coords = topo.mesh.coords
+ ref = Field(box, is_vector=True, name='ref')
+ refd = ref.discretize(topo)
+ cafd = caf.discrete_fields[topo]
+ cafd2 = caf2.discrete_fields[topo]
+ ids = [0, ] * 3
+ ids2 = [0, ] * 3
+ for i in xrange(3):
+ ids[i] = id(cafd.data[i])
+ ids2[i] = id(cafd2.data[i])
+ op.apply(simu)
+ op2.apply(simu)
+ refd.data = func_vec_1(refd.data, *(coords + (simu.time,)))
+ for i in xrange(caf.nb_components):
+ assert allclose(cafd[i], refd.data[i])
+ assert id(cafd.data[i]) == ids[i]
+ assert allclose(cafd2[i], refd.data[i])
+ assert id(cafd2.data[i]) == ids2[i]
+
+
+# Non-Vectorized and vectorized formulas for a vector with extra-args
+def test_analytical_op_4():
+ box = Box()
+ caf = Field(box, formula=func_vec_3, is_vector=True, name='caf')
+ caf2 = Field(box, formula=func_vec_4, vectorize_formula=True,
+ name='caf2', is_vector=True)
+ op = Analytic(variables={caf: d3D})
+ op2 = Analytic(variables={caf2: d3D})
+ op.discretize()
+ op2.discretize()
+ op.setup()
+ op2.setup()
+ topo = op.discrete_fields[caf].topology
+ coords = topo.mesh.coords
+ ref = Field(box, name='ref', is_vector=True)
+ refd = ref.discretize(topo)
+ cafd = caf.discrete_fields[topo]
+ cafd2 = caf2.discrete_fields[topo]
+ ids = [0, ] * 3
+ ids2 = [0, ] * 3
+ for i in xrange(3):
+ ids[i] = id(cafd.data[i])
+ ids2[i] = id(cafd2.data[i])
+ theta = 3.
+ caf.set_formula_parameters(theta)
+ caf2.set_formula_parameters(theta)
+ op.apply(simu)
+ op2.apply(simu)
+ refd.data = func_vec_3(refd.data, *(coords + (simu.time, theta)))
+ for i in xrange(caf.nb_components):
+ assert allclose(cafd[i], refd.data[i])
+ assert id(cafd.data[i]) == ids[i]
+ assert allclose(cafd2[i], refd.data[i])
+ assert id(cafd2.data[i]) == ids2[i]
+
+
+# Non-Vectorized formula for a nbc components field with extra-args
+def test_analytical_op_5():
+ box = Box()
+ caf = Field(box, formula=func_vec_5, nb_components=nbc, name='caf')
+ op = Analytic(variables={caf: d3D})
+ op.discretize()
+ op.setup()
+ topo = op.discrete_fields[caf].topology
+ coords = topo.mesh.coords
+ ref = Field(box, nb_components=nbc, name='ref')
+ refd = ref.discretize(topo)
+ cafd = caf.discrete_fields[topo]
+ ids = [0, ] * nbc
+ for i in xrange(nbc):
+ ids[i] = id(cafd.data[i])
+ theta = 3.
+ caf.set_formula_parameters(theta)
+ op.apply(simu)
+ refd.data = func_vec_5(refd.data, *(coords + (simu.time, theta)))
+ for i in xrange(caf.nb_components):
+ assert allclose(cafd[i], refd.data[i])
+ assert id(cafd.data[i]) == ids[i]
+
+
+# Non-Vectorized formula for a nbc components field in 2D, with extra-args
+def test_analytical_op_6():
+ box = Box(dimension=2, length=L2D, origin=origin2D)
+ caf = Field(box, formula=func_vec_6, nb_components=nbc, name='caf')
+ op = Analytic(variables={caf: d2D})
+ op.discretize()
+ op.setup()
+ topo = op.discrete_fields[caf].topology
+ coords = topo.mesh.coords
+ ref = Field(box, nb_components=nbc, name='ref')
+ refd = ref.discretize(topo)
+ cafd = caf.discrete_fields[topo]
+ ids = [0, ] * nbc
+ for i in xrange(nbc):
+ ids[i] = id(cafd.data[i])
+ theta = 3.
+ caf.set_formula_parameters(theta)
+ op.apply(simu)
+ refd.data = func_vec_6(refd.data, *(coords + (simu.time, theta)))
+ for i in xrange(caf.nb_components):
+ assert allclose(cafd[i], refd.data[i])
+ assert id(cafd.data[i]) == ids[i]
+
diff --git a/hysop/old/operator.old/tests/test_custom.py b/hysop/old/operator.old/tests/test_custom.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f92c54ff6500b5c80c762ad72d6ef948ea10f1b
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_custom.py
@@ -0,0 +1,84 @@
+"""Test user-defined (custom) operator
+"""
+
+from hysop.operator.custom import Custom
+from hysop import Field, Discretization, Box, Simulation, IOParams, IO
+import numpy as np
+import os
+
+d2d = Discretization([33, 65], [2, 0])
+d3d = Discretization([33, 65, 33], [2, 0, 1])
+
+
+def func3d(sim, f_in, f_out, d=None):
+ """A test function, for a 3d domain,
+ no diagnostics
+ """
+ nbc = f_in[0].nb_components
+ for d in xrange(nbc):
+ f_out[0][d] = d * f_in[0][d] + + f_in[1][0] + np.cos(sim.time)
+
+
+def func3d_with_diag(sim, f_in, f_out, diagnostics):
+ """A test function, for a 3d domain,
+ no diagnostics
+ """
+ nbc = f_in[0].nb_components
+ for d in xrange(nbc):
+ f_out[0][d] = d * f_in[0][d] + f_in[1][0] + np.cos(sim.time)
+ diagnostics[0, 0] = sim.time
+ diagnostics[0, 1] = f_out[0].data[0].min()
+ diagnostics[0, 1] = f_out[0].data[0].max()
+
+
+def init_custom(dim, discr, func, do_write=False):
+ """Test build and apply, without
+ writer.
+ """
+ dom = Box(length=[1., ] * dim)
+ v1 = Field(name='v1', is_vector=True, domain=dom)
+ v2 = Field(name='v2', is_vector=False, domain=dom)
+ v3 = Field(name='v3', is_vector=True, domain=dom)
+ topo = dom.create_topology(discr)
+ v1.randomize(topo)
+ v2.randomize(topo)
+ if do_write:
+ iop = IOParams('/tmp/hysop_custom_test.dat', fileformat=IO.ASCII)
+ d_shape = (1, 3)
+ else:
+ iop = None
+ d_shape = None
+ op = Custom(in_fields=[v1, v2], out_fields=[v3],
+ variables=[v1, v2, v3], discretization=discr,
+ function=func, io_params=iop,
+ diagnostics_shape=d_shape)
+ op.discretize()
+ op.setup()
+ sim = Simulation(nb_iter=10)
+ sim.initialize()
+ nbc = v1.nb_components
+ vd1 = v1.discretize(topo)
+ vd2 = v2.discretize(topo)
+ vd3 = v3.discretize(topo)
+ while not sim.is_over:
+ op.apply(sim)
+ for d in xrange(nbc):
+ tmp1 = d * vd1[d] + + vd2[0] + np.cos(sim.time)
+ assert np.allclose(vd3[d], tmp1)
+ sim.advance()
+ if do_write:
+ assert os.path.isfile(iop.filename)
+
+
+def test_custom_op_1():
+ """Test build and apply, without
+ writer.
+ """
+ init_custom(3, d3d, func3d)
+
+
+def test_custom_op_2():
+ """Test build and apply, with
+ output in a file
+ """
+ init_custom(3, d3d, func3d_with_diag, True)
diff --git a/hysop/operator/tests/test_density.py b/hysop/old/operator.old/tests/test_density.py
similarity index 100%
rename from hysop/operator/tests/test_density.py
rename to hysop/old/operator.old/tests/test_density.py
diff --git a/hysop/operator/tests/test_diff_poisson_3D.py b/hysop/old/operator.old/tests/test_diff_poisson_3D.py
similarity index 81%
rename from hysop/operator/tests/test_diff_poisson_3D.py
rename to hysop/old/operator.old/tests/test_diff_poisson_3D.py
index 9dbea2debb24c60df61232202dd76a34a856b649..e406d2b4a6ef52f11a90bd2847047ee68e9fb1c2 100755
--- a/hysop/operator/tests/test_diff_poisson_3D.py
+++ b/hysop/old/operator.old/tests/test_diff_poisson_3D.py
@@ -1,9 +1,12 @@
-# -*- coding: utf-8 -*-
+"""Diffusion - Poisson sequence
+"""
import hysop as pp
from hysop.operator.poisson import Poisson
from hysop.operator.diffusion import Diffusion
from math import sqrt, pi, exp
from hysop.problem.simulation import Simulation
+from hysop import testsenv
+from hysop.tools.parameters import Discretization
def computeVel(x, y, z):
@@ -36,25 +39,27 @@ def computeVort(x, y, z):
return wx, wy, wz
-def test_Diff_Poisson():
+@testsenv.fftw_failed
+def test_diff_poisson():
+ """
+ """
# Parameters
nb = 33
boxLength = [1., 1., 1.]
boxMin = [0., 0., 0.]
- from hysop.tools.parameters import Discretization
d3D = Discretization([nb, nb, nb])
- ## Domain
+ # Domain
box = pp.Box(length=boxLength, origin=boxMin)
- ## Fields
+ # Fields
velo = pp.Field(domain=box, formula=computeVel,
name='Velocity', is_vector=True)
vorti = pp.Field(domain=box, formula=computeVort,
name='Vorticity', is_vector=True)
- ## FFT Diffusion operators and FFT Poisson solver
- diffusion = Diffusion(variables={vorti: d3D}, viscosity=0.002)
+ # FFT Diffusion operators and FFT Poisson solver
+ diffusion = Diffusion(vorticity=vorti, viscosity=0.002, discretization=d3D)
poisson = Poisson(velo, vorti, discretization=d3D)
diffusion.discretize()
diff --git a/hysop/operator/tests/test_differential.py b/hysop/old/operator.old/tests/test_differential.py
similarity index 79%
rename from hysop/operator/tests/test_differential.py
rename to hysop/old/operator.old/tests/test_differential.py
index 9eaa3895b537fd371434e01bcad3d3fd734697d3..3d5eca1f05ec78af3fb9d90d8844263271773255 100755
--- a/hysop/operator/tests/test_differential.py
+++ b/hysop/old/operator.old/tests/test_differential.py
@@ -4,17 +4,16 @@
import numpy as np
from hysop.domain.box import Box
from hysop.fields.continuous import Field
-import hysop.tools.numpywrappers as npw
-from hysop.methods_keys import SpaceDiscretisation
+from hysop.tools.numpywrappers import npw
+from hysop.methods import SpaceDiscretization
from hysop.methods import FDC4, FDC2
from hysop.operator.differential import Curl, Grad, DivAdvection
from hysop.tools.parameters import Discretization
-
+from hysop import testsenv
# Domain and topologies definitions
-
-nb = 65
import math
+nb = 65
Lx = Ly = Lz = 2. * math.pi
box1_3d = Box(length=[Lx, Ly, Lz], origin=[0., 0., 0.])
box1_2d = Box(length=[Lx, Ly], origin=[0., 0.])
@@ -91,6 +90,8 @@ def grad_velo_2d(res, x, y, t):
def check(op, ref_formula, topo, op_dim=3, order=4):
+ """Apply operator 'op' and compare its results with some references.
+ """
# Reference field
ref = Field(domain=topo.domain, formula=ref_formula, nb_components=op_dim,
name='reference')
@@ -100,7 +101,7 @@ def check(op, ref_formula, topo, op_dim=3, order=4):
result = op.outvar
velo.initialize(topo=topo)
op.apply()
- res_d = result.discreteFields[topo]
+ res_d = result.discrete_fields[topo]
# Compare results with reference
ind = topo.mesh.compute_index
@@ -116,6 +117,10 @@ def check(op, ref_formula, topo, op_dim=3, order=4):
def call_op(class_name, ref_formula, topo, use_work=False,
op_dim=3, method=None, order=4, vform=velocity_f):
+ """init and set an operator of type 'class_name'
+ and call check function on this operator.
+ """
+
# Velocity and result fields
velo = Field(domain=topo.domain, formula=vform, is_vector=True,
name='velo')
@@ -129,9 +134,10 @@ def call_op(class_name, ref_formula, topo, use_work=False,
if use_work:
work_prop = op.get_work_properties()['rwork']
work = []
- for l in xrange(len(work_prop)):
- shape = work_prop[l]
- work.append(npw.zeros(shape))
+ if work_prop is not None:
+ for l in xrange(len(work_prop)):
+ shape = work_prop[l]
+ work.append(npw.zeros(shape))
op.setup(rwork=work)
check(op, ref_formula, topo, op_dim, order)
@@ -139,6 +145,10 @@ def call_op(class_name, ref_formula, topo, use_work=False,
def call_op_fft(class_name, ref_formula, dom, discr,
op_dim=3, method=None, order=4, vform=velocity_f):
+ """init and set an operator of type 'class_name'
+ and call check function on this operator. FFTW method.
+ """
+
# Velocity and result fields
velo = Field(domain=dom, formula=vform, is_vector=True,
name='velo')
@@ -149,96 +159,102 @@ def call_op_fft(class_name, ref_formula, dom, discr,
op.discretize()
op.setup()
- topo = op.discreteFields[velo].topology
+ topo = op.discrete_fields[velo].topology
check(op, ref_formula, topo, op_dim, order)
def test_curl_fd_1():
- method = {SpaceDiscretisation: FDC4}
+ method = {SpaceDiscretization: FDC4}
call_op(Curl, vorticity_f, topo1_3d, method=method)
def test_curl_fd_2():
- method = {SpaceDiscretisation: FDC2}
+ method = {SpaceDiscretization: FDC2}
call_op(Curl, vorticity_f, topo1_3d, method=method, order=2)
def test_curl_fd_1_2d():
- method = {SpaceDiscretisation: FDC4}
+ method = {SpaceDiscretization: FDC4}
call_op(Curl, vorticity_f2d, topo1_2d, method=method,
op_dim=1, vform=velocity_f2d)
def test_curl_fd_3():
- method = {SpaceDiscretisation: FDC4}
+ method = {SpaceDiscretization: FDC4}
call_op(Curl, vorticity_f, topo3_3d, method=method)
def test_curl_fd_3_2d():
- method = {SpaceDiscretisation: FDC4}
+ method = {SpaceDiscretization: FDC4}
call_op(Curl, vorticity_f2d, topo3_2d, op_dim=1,
method=method, vform=velocity_f2d)
+def test_curl_fd_work():
+ method = {SpaceDiscretization: FDC4}
+ call_op(Curl, vorticity_f, topo3_3d, method=method, use_work=True)
+
+
+@testsenv.fftw_failed
def test_curl_fft_1():
- method = {SpaceDiscretisation: 'fftw'}
+ method = {SpaceDiscretization: 'fftw'}
d1_3d_nog = Discretization([nb, nb, nb])
call_op_fft(Curl, vorticity_f, box1_3d, d1_3d_nog, method=method, order=6)
# def test_curl_fft_1_2d():
-# method = {SpaceDiscretisation: 'fftw'}
+# method = {SpaceDiscretization: 'fftw'}
# d1_2d_nog = Discretization([nb, nb])
# call_op_fft(Curl, vorticity_f2d, box1_2d, d1_2d_nog, op_dim=1,
# method=method, order=6, vform=velocity_f2d)
#def test_curl_fft_ghosts():
-# from hysop.methods_keys import SpaceDiscretisation
+# from hysop.methods import SpaceDiscretization
# from hysop.operator.differential import Curl
-# method = {SpaceDiscretisation: 'fftw'}
+# method = {SpaceDiscretization: 'fftw'}
# call_op(Curl, vorticity_f, method=method, order=6, discretization=d3D)
# def test_curl_fft_2():
-# method = {SpaceDiscretisation: 'fftw'}
+# method = {SpaceDiscretization: 'fftw'}
# d2_3d_nog = Discretization([2 * nb, nb, nb])
# box2_3d = Box(length=[2. * Lx, Ly, Lz], origin=[0., 0., 0.])
# call_op_fft(Curl, vorticity_f, box2_3d, d2_3d_nog, method=method, order=6)
# def test_curl_fft_2_2d():
-# method = {SpaceDiscretisation: 'fftw'}
+# method = {SpaceDiscretization: 'fftw'}
# d2_2d_nog = Discretization([2 * nb, nb])
# box2_2d = Box(length=[2. * Lx, Ly], origin=[0., 0.])
# call_op_fft(Curl, vorticity_f, box2_2d, d2_2d_nog, method=method, order=6)
def test_grad_1():
- method = {SpaceDiscretisation: FDC2}
+ method = {SpaceDiscretization: FDC2}
call_op(Grad, grad_velo, topo1_3d, op_dim=9, method=method, order=2)
def test_grad_2():
- method = {SpaceDiscretisation: FDC4}
+ method = {SpaceDiscretization: FDC4}
call_op(Grad, grad_velo, topo1_3d, op_dim=9, method=method)
def test_grad_3():
- method = {SpaceDiscretisation: FDC2}
+ method = {SpaceDiscretization: FDC2}
call_op(Grad, grad_velo, topo3_3d, op_dim=9, method=method, order=2)
+def test_grad_3_work():
+ method = {SpaceDiscretization: FDC2}
+ call_op(Grad, grad_velo, topo3_3d, op_dim=9, method=method, order=2,
+ use_work=True)
+
+
def test_grad_3_2d():
- method = {SpaceDiscretisation: FDC4}
+ method = {SpaceDiscretization: FDC4}
call_op(Grad, grad_velo_2d, topo3_2d, op_dim=4, method=method,
vform=velocity_f2d)
-
-def test_curl_fd_work():
- method = {SpaceDiscretisation: FDC4}
- call_op(Curl, vorticity_f, topo3_3d, use_work=True, method=method)
-
-
def divadvection_func(res, x, y, z, t):
res[0][...] = - cos(z) * cos(z) * (cos(x) * cos(x) - sin(x) * sin(x)) - \
cos(z) * cos(z) * (cos(y) * cos(y) - sin(y) * sin(y))
@@ -246,5 +262,5 @@ def divadvection_func(res, x, y, z, t):
def test_div_advection():
- method = {SpaceDiscretisation: FDC4}
+ method = {SpaceDiscretization: FDC4}
call_op(DivAdvection, divadvection_func, topo3_3d, op_dim=1, method=method)
diff --git a/hysop/old/operator.old/tests/test_diffusion.py b/hysop/old/operator.old/tests/test_diffusion.py
new file mode 100755
index 0000000000000000000000000000000000000000..f933be0979870f0cabfcbed7bba7caafe4008299
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_diffusion.py
@@ -0,0 +1,94 @@
+"""Tests for diffusion and curl_diffusion operators.
+"""
+# -*- coding: utf-8 -*-
+
+import hysop as pp
+from hysop.operator.diffusion import Diffusion, CurlAndDiffusion
+from hysop.problem.simulation import Simulation
+from hysop.tools.parameters import Discretization
+import numpy as np
+from hysop.tools.numpywrappers import npw
+import math
+from hysop import testsenv
+from hysop.fields.tests.func_for_tests import v_TG, w_TG
+pi = math.pi
+sin = np.sin
+cos = np.cos
+# Physical Domain description
+dim = 3
+LL = 2 * pi * npw.ones((dim))
+cc = 2 * pi / LL
+d3D = Discretization([33, 33, 33])
+d2D = Discretization([33, 33])
+
+
+def computeVort2D(res, x, y, t):
+ # todo ...
+ res[0][...] = 4 * pi ** 2 * (cos(x * cc[0]) * sin(y * cc[1])) * \
+ (1. / LL[0] ** 2 + 1. / LL[1] ** 2)
+ return res
+
+
+@testsenv.fftw_failed
+def test_diffusion_3d():
+ """Vector field diffusion, 3d domain"""
+ dom = pp.Box(length=LL)
+ vorticity = pp.Field(domain=dom, formula=w_TG,
+ name='Vorticity', is_vector=True)
+ diff = Diffusion(viscosity=0.3, vorticity=vorticity, discretization=d3D)
+ diff.discretize()
+ diff.setup()
+ topo = diff.discrete_fields[vorticity].topology
+ simu = Simulation(end=0.1, time_step=0.01)
+ vorticity.initialize(topo=topo)
+ diff.apply(simu)
+ diff.finalize()
+
+
+@testsenv.fftw_failed
+def test_diffusion_2d():
+ """Vector field diffusion 2d domain"""
+ dom = pp.Box(length=LL[:2])
+ vorticity = pp.Field(domain=dom, formula=computeVort2D, name='Vorticity')
+ diff = Diffusion(viscosity=0.3, vorticity=vorticity, discretization=d2D)
+ diff.discretize()
+ diff.setup()
+ topo = diff.discrete_fields[vorticity].topology
+ simu = Simulation(end=0.1, time_step=0.01)
+ vorticity.initialize(topo=topo)
+ diff.apply(simu)
+ diff.finalize()
+
+
+@testsenv.fftw_failed
+def test_curl_and_diffusion_3d():
+ """Vector field diffusion, 3d domain"""
+ dom = pp.Box(length=LL)
+ vorticity_ref = pp.Field(domain=dom, name='Wref', formula=w_TG,
+ is_vector=True)
+ vorticity = pp.Field(domain=dom, name='Vorticity', is_vector=True)
+ velocity = pp.Field(domain=dom, name='Velocity', formula=v_TG,
+ is_vector=True)
+
+ diff_0 = Diffusion(viscosity=0.3, vorticity=vorticity_ref,
+ discretization=d3D)
+ diff_0.discretize()
+ diff_0.setup()
+ topo = diff_0.discrete_fields[vorticity_ref].topology
+ diff = CurlAndDiffusion(viscosity=0.3, velocity=velocity,
+ vorticity=vorticity, discretization=d3D)
+ diff.discretize()
+ diff.setup()
+
+ simu = Simulation(end=0.1, time_step=0.01)
+ vorticity_ref.initialize(topo=topo)
+ velocity.initialize(topo=topo)
+ simu.initialize()
+ wd = vorticity.discretize(topo).data
+ wd_ref = vorticity_ref.discretize(topo).data
+ diff_0.apply(simu)
+ diff.apply(simu)
+ for i in xrange(3):
+ assert np.allclose(wd[i], wd_ref[i])
+
+ diff_0.finalize()
diff --git a/hysop/operator/tests/test_drag_and_lift.py b/hysop/old/operator.old/tests/test_drag_and_lift.py
similarity index 99%
rename from hysop/operator/tests/test_drag_and_lift.py
rename to hysop/old/operator.old/tests/test_drag_and_lift.py
index aba51c89c416b1a6bfdf061f29249ee35d26b5d4..3b631e189d9ac14ebebb8be6a93980350a1cec6c 100755
--- a/hysop/operator/tests/test_drag_and_lift.py
+++ b/hysop/old/operator.old/tests/test_drag_and_lift.py
@@ -4,7 +4,7 @@ from hysop.operator.penalization import PenalizeVorticity
from hysop.problem.simulation import Simulation
from hysop.tools.parameters import Discretization
from hysop.tools.io_utils import IOParams, IO
-from hysop.mpi.topology import Cartesian
+from hysop.core.mpi.topology import Cartesian
import numpy as np
import os
from hysop import Field, Box
diff --git a/hysop/operator/tests/test_energy_enstrophy.py b/hysop/old/operator.old/tests/test_energy_enstrophy.py
similarity index 100%
rename from hysop/operator/tests/test_energy_enstrophy.py
rename to hysop/old/operator.old/tests/test_energy_enstrophy.py
diff --git a/hysop/old/operator.old/tests/test_hdf5_io.py b/hysop/old/operator.old/tests/test_hdf5_io.py
new file mode 100755
index 0000000000000000000000000000000000000000..927048c581083cafeaaf4c0d77102a5e11917d05
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_hdf5_io.py
@@ -0,0 +1,399 @@
+# -*- coding: utf-8 -*-
+"""Tests for reader/writer of fields in hdf5 format.
+"""
+
+from hysop import Box, Field
+import numpy as np
+import os
+from hysop.problem.simulation import Simulation
+from hysop.tools.parameters import Discretization
+from hysop.operator.hdf_io import HDF_Writer, HDF_Reader
+from hysop.tools.io_utils import IO, IOParams
+from hysop.core.mpi import main_rank, main_size
+from hysop.domain.subsets import SubBox
+from hysop.testsenv import postclean
+
+Lx = 2.
+nb = 65
+working_dir = os.getcwd() + '/test_hdf5/p' + str(main_size)
+#IO.set_default_path(os.getcwd() + '/test_hdf5/')
+if main_rank == 0:
+ print 'Set I/O default path to ', IO.default_path()
+
+cos = np.cos
+sin = np.sin
+
+
+def init1(dim):
+ # Domain (cubic)
+ dom = Box(length=[Lx] * dim, origin=[-1.] * dim)
+ # global resolution for the grid
+ resol = Discretization([nb] * dim, [2] * dim)
+ topo = dom.create_topology(discretization=resol)
+ return dom, topo
+
+
+def init2():
+ # Domain (not cubic)
+ dom = Box(length=[Lx, 2 * Lx, 3.9 * Lx], origin=[-1., 2., 3.9])
+ # global resolution for the grid
+ resol = Discretization([nb, 2 * nb, nb + 8], [2, 0, 1])
+ topo = dom.create_topology(discretization=resol)
+ return dom, topo
+
+
+def func3D(res, x, y, z, t):
+ res[0][...] = cos(t * x) + sin(y) + z
+ return res
+
+
+def vec3D(res, x, y, z, t):
+ res[0][...] = cos(t * x) + sin(y) + z + 0.2
+ res[1][...] = sin(t * x) + sin(y) + z + 0.3
+ res[2][...] = 3 * cos(2 * t * x) + sin(y) + y
+ return res
+
+
+def vort3D(res, x, y, z, t):
+ res[0][...] = 3 * cos(2 * t * x) + cos(y) + z
+ res[1][...] = sin(t * y) + x + 0.2
+ res[2][...] = 3 * cos(t) + sin(y) + z
+ return res
+
+
+@postclean(working_dir)
+def test_write_read_scalar_3D():
+ dom, topo = init1(3)
+ scal3D = Field(domain=dom, name='Scal3D')
+ scalRef = Field(domain=dom, formula=func3D, name='ScalRef3D')
+
+ filename = working_dir + '/testIO_scal'
+ iop = IOParams(filename, fileformat=IO.HDF5)
+ op = HDF_Writer(variables={scalRef: topo}, io_params=iop)
+ simu = Simulation(nb_iter=10)
+ op.discretize()
+ op.setup()
+ simu.initialize()
+
+ scalRef.initialize(simu.time, topo=topo)
+ op.apply(simu)
+
+ simu.advance()
+ simu.advance()
+ # Print scalRef for other iterations
+ op.apply(simu)
+ op.finalize()
+ fullpath = iop.filename
+ assert os.path.exists(fullpath + '.xmf')
+ assert os.path.exists(fullpath + '_00000.h5')
+ assert os.path.exists(fullpath + '_00002.h5')
+
+ # Reader
+ iop_read = IOParams(working_dir + '/testIO_scal_00002.h5',
+ fileformat=IO.HDF5)
+ reader = HDF_Reader(variables=[scal3D], discretization=topo,
+ io_params=iop_read,
+ var_names={scal3D: 'ScalRef3D_' + str(topo.get_id())})
+ reader.discretize()
+ reader.setup()
+ sc3d = scal3D.discretize(topo)
+ scref = scalRef.discretize(topo)
+ ind = topo.mesh.compute_index
+ for d in xrange(scal3D.nb_components):
+ sc3d.data[d][...] = 0.0
+ assert not np.allclose(scref.data[d][ind], sc3d.data[d][ind])
+ reader.apply()
+ reader.finalize()
+
+ for d in xrange(scal3D.nb_components):
+ assert np.allclose(scref.data[d][ind], sc3d.data[d][ind])
+
+
+@postclean(working_dir)
+def test_write_read_scalar_3D_defaults():
+ dom, topo = init1(3)
+ scal3D = Field(domain=dom, name='Scal3D')
+ scalRef = Field(domain=dom, formula=func3D, name='ScalRef3D')
+
+ # Write a scalar field, using default configuration for output
+ # names and location
+ op = HDF_Writer(variables={scalRef: topo})
+ simu = Simulation(nb_iter=3)
+ op.discretize()
+ op.setup()
+ scal3D.discretize(topo=topo)
+ scalRef.initialize(simu.time, topo=topo)
+ simu.initialize()
+ while not simu.is_over:
+ op.apply(simu)
+ simu.advance()
+
+ op.finalize()
+ filename = scalRef.name
+ fullpath = os.path.join(IO.default_path(), filename)
+
+ assert os.path.exists(fullpath + '.xmf')
+ assert os.path.exists(fullpath + '_00000.h5')
+ assert os.path.exists(fullpath + '_00001.h5')
+
+ sc3d = scal3D.discretize(topo)
+ scref = scalRef.discretize(topo)
+ ind = topo.mesh.compute_index
+ for d in xrange(scal3D.nb_components):
+ sc3d.data[d][...] = scref.data[d][...]
+ scref.data[d][...] = 0.0
+ # reinit ScalRef
+
+ # Read a scalar field, using default configuration for output
+ # names and location, with a given iteration number.
+ reader = HDF_Reader(variables={scalRef: topo},
+ restart=simu.current_iteration - 1)
+ reader.discretize()
+ reader.setup()
+ for d in xrange(scal3D.nb_components):
+ assert not np.allclose(scref.data[d][ind], sc3d.data[d][ind])
+ reader.apply()
+ reader.finalize()
+
+ for d in xrange(scal3D.nb_components):
+ assert np.allclose(scref.data[d][ind], sc3d.data[d][ind])
+
+@postclean(working_dir)
+def test_write_read_vectors_3D_defaults():
+ dom, topo = init2()
+ velo = Field(domain=dom, formula=vec3D, name='velo', is_vector=True)
+ vorti = Field(domain=dom, formula=vort3D, name='vorti', is_vector=True)
+
+ # Write a vector field, using default configuration for output
+ # names and location
+ op = HDF_Writer(variables={velo: topo, vorti: topo})
+ simu = Simulation(nb_iter=3)
+ op.discretize()
+ op.setup()
+ velo.initialize(simu.time, topo=topo)
+ vorti.initialize(simu.time, topo=topo)
+ simu.initialize()
+ while not simu.is_over:
+ op.apply(simu)
+ simu.advance()
+
+ op.finalize()
+ filename = ''
+ names = []
+ for var in op.input:
+ names.append(var.name)
+ names.sort()
+ for nn in names:
+ filename += nn + '_'
+ filename = filename[:-1]
+ fullpath = os.path.join(IO.default_path(), filename)
+
+ assert os.path.exists(fullpath + '.xmf')
+ assert os.path.exists(fullpath + '_00000.h5')
+ assert os.path.exists(fullpath + '_00001.h5')
+
+ v3d = velo.discretize(topo)
+ w3d = vorti.discretize(topo)
+ ind = topo.mesh.compute_index
+
+ # Copy current values of v3 and w3 into buff1 and buff2, for comparison
+ # after reader.apply, below.
+ buff1 = Field(domain=dom, name='buff1', is_vector=True)
+ buff2 = Field(domain=dom, name='buff2', is_vector=True)
+ b1 = buff1.discretize(topo=topo)
+ b2 = buff2.discretize(topo=topo)
+ for d in xrange(velo.nb_components):
+ b1.data[d][...] = v3d.data[d][...]
+ b2.data[d][...] = w3d.data[d][...]
+ # reset v3 and w3 to zero.
+ v3d.data[d][...] = 0.0
+ w3d.data[d][...] = 0.0
+
+ # Read vector fields, using default configuration for input
+ # names and location, with a given iteration number.
+ # If everything works fine, reader must read output from
+ # the writer above.
+ reader = HDF_Reader(variables={velo: topo, vorti: topo},
+ io_params=IOParams(filename),
+ restart=simu.current_iteration - 1)
+ reader.discretize()
+ reader.setup()
+ for d in xrange(v3d.nb_components):
+ assert not np.allclose(b1.data[d][ind], v3d.data[d][ind])
+ assert not np.allclose(b2.data[d][ind], w3d.data[d][ind])
+
+ reader.apply()
+ reader.finalize()
+ # Now, v3 and w3 (just read) must be equal to saved values in b1 and b2.
+ for d in xrange(v3d.nb_components):
+ assert np.allclose(b1.data[d][ind], v3d.data[d][ind])
+ assert np.allclose(b2.data[d][ind], w3d.data[d][ind])
+
+
+@postclean(working_dir)
+def test_write_read_vectors_3D():
+ dom, topo = init2()
+ velo = Field(domain=dom, formula=vec3D, name='velo', is_vector=True)
+ vorti = Field(domain=dom, formula=vort3D, name='vorti', is_vector=True)
+
+ # Write a vector field, using default for output location
+ # but with fixed names for datasets
+ filename = working_dir + '/testIO_vec'
+ iop = IOParams(filename, fileformat=IO.HDF5)
+ op = HDF_Writer(variables={velo: topo, vorti: topo},
+ var_names={velo: 'io_1', vorti: 'io_2'}, io_params=iop)
+ simu = Simulation(nb_iter=3)
+ op.discretize()
+ op.setup()
+
+ velo.initialize(simu.time, topo=topo)
+ vorti.initialize(simu.time, topo=topo)
+ simu.initialize()
+ while not simu.is_over:
+ op.apply(simu)
+ simu.advance()
+
+ op.finalize()
+
+ # filename = ''
+ # for v in op.input:
+ # filename += v.name
+ # filename += '_'
+ fullpath = iop.filename
+ assert os.path.exists(fullpath + '.xmf')
+ assert os.path.exists(fullpath + '_00000.h5')
+ assert os.path.exists(fullpath + '_00001.h5')
+
+ v3d = velo.discretize(topo)
+ w3d = vorti.discretize(topo)
+ ind = topo.mesh.compute_index
+
+ buff1 = Field(domain=dom, name='buff1', is_vector=True)
+ buff2 = Field(domain=dom, name='buff2', is_vector=True)
+
+ # Read vector fields, fixed filename, fixed dataset names.
+ iop_read = IOParams(working_dir + '/testIO_vec_00001.h5',
+ fileformat=IO.HDF5)
+ reader = HDF_Reader(variables={buff1: topo, buff2: topo},
+ io_params=iop_read,
+ var_names={buff1: 'io_2', buff2: 'io_1'})
+ reader.discretize()
+ reader.setup()
+ reader.apply()
+ reader.finalize()
+ b1 = buff1.discretize(topo)
+ b2 = buff2.discretize(topo)
+ for d in xrange(v3d.nb_components):
+ assert np.allclose(b2.data[d][ind], v3d.data[d][ind])
+ assert np.allclose(b1.data[d][ind], w3d.data[d][ind])
+
+
+@postclean(working_dir)
+def test_write_read_subset_1():
+ dom, topo = init2()
+ velo = Field(domain=dom, formula=vec3D, name='velo', is_vector=True)
+
+ # A subset of the current domain
+ from hysop.domain.subsets import SubBox
+ mybox = SubBox(origin=[-0.5, 2.3, 4.1], length=[Lx / 2, Lx / 3, Lx],
+ parent=dom)
+ # Write a vector field, using default for output location
+ # but with fixed names for datasets
+ op = HDF_Writer(variables={velo: topo}, var_names={velo: 'io_1'},
+ subset=mybox)
+ simu = Simulation(nb_iter=3)
+ op.discretize()
+ op.setup()
+ velo.initialize(simu.time, topo=topo)
+ simu.initialize()
+ while not simu.is_over:
+ op.apply(simu)
+ simu.advance()
+ op.finalize()
+
+ filename = ''
+ for v in op.input:
+ filename += v.name
+ filename += '_'
+ filename = filename[:-1]
+ fullpath = os.path.join(IO.default_path(), filename)
+
+ assert os.path.exists(fullpath + '.xmf')
+ assert os.path.exists(fullpath + '_00000.h5')
+ assert os.path.exists(fullpath + '_00001.h5')
+
+ v3d = velo.discretize(topo)
+ ind = topo.mesh.compute_index
+ indsubset = mybox.mesh[topo].compute_index
+
+ buff1 = Field(domain=dom, name='buff1', is_vector=True)
+
+ # Read vector fields, fixed filename, fixed dataset names.
+ iop = IOParams(filename + '_00000.h5', fileformat=IO.HDF5)
+ reader = HDF_Reader(variables={buff1: topo},
+ io_params=iop,
+ var_names={buff1: 'io_1'}, subset=mybox)
+ reader.discretize()
+ reader.setup()
+ reader.apply()
+ reader.finalize()
+ b1 = buff1.discretize(topo)
+ for d in xrange(v3d.nb_components):
+ assert not np.allclose(b1.data[d][ind], v3d.data[d][ind])
+ assert np.allclose(b1.data[d][indsubset], v3d.data[d][indsubset])
+
+
+@postclean(working_dir)
+def test_write_read_subset_2():
+ dom, topo = init2()
+ velo = Field(domain=dom, formula=vec3D, name='velo', is_vector=True)
+
+ # A subset of the current domain
+ # a plane ...
+ mybox = SubBox(origin=[-0.5, 2.3, 4.1], length=[Lx / 2, Lx / 3, 0.0],
+ parent=dom)
+ # Write a vector field, using default for output location
+ # but with fixed names for datasets
+ op = HDF_Writer(variables={velo: topo}, var_names={velo: 'io_1'},
+ subset=mybox)
+ simu = Simulation(nb_iter=3)
+ op.discretize()
+ op.setup()
+ velo.initialize(simu.time, topo=topo)
+ simu.initialize()
+ while not simu.is_over:
+ op.apply(simu)
+ simu.advance()
+ op.finalize()
+
+ filename = ''
+ for v in op.input:
+ filename += v.name
+ filename += '_'
+ filename = filename[:-1]
+ fullpath = os.path.join(IO.default_path(), filename)
+
+ assert os.path.exists(fullpath + '.xmf')
+ assert os.path.exists(fullpath + '_00000.h5')
+ assert os.path.exists(fullpath + '_00001.h5')
+
+ v3d = velo.discretize(topo)
+ ind = topo.mesh.compute_index
+ indsubset = mybox.mesh[topo].compute_index
+
+ buff1 = Field(domain=dom, name='buff1', is_vector=True)
+
+ # Read vector fields, fixed filename, fixed dataset names.
+ iop = IOParams(filename + '_00000.h5', fileformat=IO.HDF5)
+ reader = HDF_Reader(variables={buff1: topo},
+ io_params=iop,
+ var_names={buff1: 'io_1'}, subset=mybox)
+ reader.discretize()
+ reader.setup()
+ reader.apply()
+ reader.finalize()
+ b1 = buff1.discretize(topo)
+ for d in xrange(v3d.nb_components):
+ assert not np.allclose(b1.data[d][ind], v3d.data[d][ind])
+ assert np.allclose(b1.data[d][indsubset], v3d.data[d][indsubset])
+
diff --git a/hysop/operator/tests/test_multiphase_gradp.py b/hysop/old/operator.old/tests/test_multiphase_gradp.py
similarity index 91%
rename from hysop/operator/tests/test_multiphase_gradp.py
rename to hysop/old/operator.old/tests/test_multiphase_gradp.py
index d3e583c3ca297d6dc7680e3664f3c7a21b1a5de9..4a8684e85bf23a49f6af98f3bc482110e6c0ff33 100755
--- a/hysop/operator/tests/test_multiphase_gradp.py
+++ b/hysop/old/operator.old/tests/test_multiphase_gradp.py
@@ -5,9 +5,9 @@ from hysop.domain.box import Box
from hysop.fields.continuous import Field
from hysop.operator.multiphase_gradp import MultiphaseGradP
from hysop.numerics.finite_differences import FDC4, FDC2
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
-from hysop.methods_keys import Support, SpaceDiscretisation, ExtraArgs
+from hysop.methods import Support, SpaceDiscretization, ExtraArgs
from hysop.constants import HYSOP_REAL
pi, sin, cos = np.pi, np.sin, np.cos
@@ -58,15 +58,15 @@ def test_gradp():
discretization=d)
op.discretize()
op.setup()
- topo = op.discreteFields[velo].topology
+ topo = op.discrete_fields[velo].topology
compute_index = topo.mesh.compute_index
velo.initialize(topo=topo)
op.initialize_velocity()
res.initialize(topo=topo)
true_res.initialize(topo=topo)
op.apply(simu)
- d_res = res.discreteFields[topo]
- d_true_res = true_res.discreteFields[topo]
+ d_res = res.discrete_fields[topo]
+ d_true_res = true_res.discrete_fields[topo]
assert np.allclose(d_res[0][compute_index], d_true_res[0][compute_index], atol=8e-3)
assert np.allclose(d_res[1][compute_index], d_true_res[1][compute_index], atol=8e-3)
assert np.allclose(d_res[2][compute_index], d_true_res[2][compute_index])
diff --git a/hysop/operator/tests/test_multiresolution_filter.py b/hysop/old/operator.old/tests/test_multiresolution_filter.py
similarity index 90%
rename from hysop/operator/tests/test_multiresolution_filter.py
rename to hysop/old/operator.old/tests/test_multiresolution_filter.py
index 198d8ce4a2a4c9cb2c640dbcd0b5c98ba0948288..60b87513e4bf017b549f70f26dcabc67ff49ab3a 100755
--- a/hysop/operator/tests/test_multiresolution_filter.py
+++ b/hysop/old/operator.old/tests/test_multiresolution_filter.py
@@ -3,11 +3,11 @@ from hysop.tools.parameters import Discretization
from hysop.domain.box import Box
from hysop.fields.continuous import Field
from hysop.operator.multiresolution_filter import MultiresolutionFilter
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
-from hysop.methods_keys import Remesh
+from hysop.methods import Remesh
from hysop.methods import Rmsh_Linear, L2_1
-from hysop.mpi import main_size
+from hysop.core.mpi import main_size
L = [1., 1., 1.]
O = [0., 0., 0.]
@@ -45,12 +45,12 @@ def filter(d_fine, d_coarse, func, method, atol=1e-8, rtol=1e-5):
method=method)
op.discretize()
op.setup()
- topo_coarse = op.discreteFields[f].topology
- topo_fine = [t for t in f.discreteFields.keys()
+ topo_coarse = op.discrete_fields[f].topology
+ topo_fine = [t for t in f.discrete_fields.keys()
if not t is topo_coarse][0]
f.initialize(topo=topo_fine)
- # f_in = f.discreteFields[topo_fine]
- f_out = f.discreteFields[topo_coarse]
+ # f_in = f.discrete_fields[topo_fine]
+ f_out = f.discrete_fields[topo_coarse]
op.apply(simu)
valid = [npw.zeros(f_out[0].shape), ]
valid = func(valid, *topo_coarse.mesh.coords)
@@ -116,8 +116,9 @@ def test_L21_X():
b, e, err = filter(d_coarse=Discretization([n_middle, 5, 5],
ghosts=[2, 2, 2]),
d_fine=Discretization([n_large, 5, 5]),
- method={Remesh: L21, },
+ method={Remesh: L2_1, },
func=func_periodic_X)
+ print b, e, err
assert b, "max(|error|)=" + str(e) + " <= " + str(err)
@@ -125,7 +126,7 @@ def test_L21_Y():
b, e, err = filter(d_coarse=Discretization([5, n_middle, 5],
ghosts=[2, 2, 2]),
d_fine=Discretization([5, n_large, 5]),
- method={Remesh: L21, },
+ method={Remesh: L2_1, },
func=func_periodic_X)
assert b, "max(|error|)=" + str(e) + " <= " + str(err)
@@ -134,7 +135,7 @@ def test_L21_Z():
b, e, err = filter(d_coarse=Discretization([5, 5, n_middle],
ghosts=[2, 2, 2]),
d_fine=Discretization([5, 5, n_large]),
- method={Remesh: L21, },
+ method={Remesh: L2_1, },
func=func_periodic_X)
assert b, "max(|error|)=" + str(e) + " <= " + str(err)
@@ -179,11 +180,11 @@ def test_filter_linear():
method={Remesh: Rmsh_Linear, })
op.discretize()
op.setup()
- topo_coarse = op.discreteFields[f].topology
- topo_fine = [t for t in f.discreteFields.keys()
- if not t is topo_coarse][0]
+ topo_coarse = op.discrete_fields[f].topology
+ topo_fine = [t for t in f.discrete_fields.keys()
+ if t is not topo_coarse][0]
f.initialize(topo=topo_fine)
- f_out = f.discreteFields[topo_coarse]
+ f_out = f.discrete_fields[topo_coarse]
op.apply(simu)
valid = [npw.zeros(f_out[0].shape), ]
valid = func(valid, *topo_coarse.mesh.coords)
@@ -205,11 +206,11 @@ def test_filter_l2_1():
method={Remesh: L2_1, })
op.discretize()
op.setup()
- topo_coarse = op.discreteFields[f].topology
- topo_fine = [t for t in f.discreteFields.keys()
- if not t is topo_coarse][0]
+ topo_coarse = op.discrete_fields[f].topology
+ topo_fine = [t for t in f.discrete_fields.keys()
+ if t is not topo_coarse][0]
f.initialize(topo=topo_fine)
- f_out = f.discreteFields[topo_coarse]
+ f_out = f.discrete_fields[topo_coarse]
op.apply(simu)
valid = [npw.zeros(f_out[0].shape), ]
valid = func(valid, *topo_coarse.mesh.coords)
diff --git a/hysop/operator/tests/test_operators.py b/hysop/old/operator.old/tests/test_operators.py
similarity index 84%
rename from hysop/operator/tests/test_operators.py
rename to hysop/old/operator.old/tests/test_operators.py
index 1b184f29bd99d3faa2e2df79e48e613ebdbdb16e..e25b61b254a5c33b98473e93e1cefaea37c7a2bd 100644
--- a/hysop/operator/tests/test_operators.py
+++ b/hysop/old/operator.old/tests/test_operators.py
@@ -1,13 +1,11 @@
# -*- coding: utf-8 -*-
-"""
-@file test_operators.py
-tests for operators general interface
+"""tests for operators general interface
"""
-from hysop.mpi.tests.utils import create_multitask_context, CPU, GPU, OTHER
+from hysop.core.mpi.tests.utils import create_multitask_context, CPU, GPU, OTHER
from hysop.tools.parameters import Discretization
from hysop.operator.analytic import Analytic
-from hysop.mpi import main_size
+from hysop.core.mpi import main_size
import hysop as pp
r_ng = Discretization([33, ] * 3)
diff --git a/hysop/operator/tests/test_particle_advection.py b/hysop/old/operator.old/tests/test_particle_advection.py
similarity index 95%
rename from hysop/operator/tests/test_particle_advection.py
rename to hysop/old/operator.old/tests/test_particle_advection.py
index f753e4d4c8327c17bd6d9c995d14c726d435066f..6d5bfb3d1d7707bd7e39ad5ddf05538cc4ef9fd7 100755
--- a/hysop/operator/tests/test_particle_advection.py
+++ b/hysop/old/operator.old/tests/test_particle_advection.py
@@ -5,7 +5,7 @@ from hysop.fields.continuous import Field
from hysop.operator.advection import Advection
from hysop.problem.simulation import Simulation
from hysop.tools.parameters import Discretization
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import numpy as np
@@ -79,7 +79,7 @@ def setup_dict_3D():
def assertion(scal, advec):
advec.discretize()
advec.setup()
- scal_d = scal.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(
np.random.random(scal_d.data[0].shape))
scal_init = npw.copy(scal_d.data[0])
@@ -92,7 +92,7 @@ def assertion_vector2D(scal, advec):
advec.discretize()
advec.setup()
- scal_d = scal.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(
np.random.random(scal_d.data[0].shape))
scal_d.data[1][...] = npw.asrealarray(
@@ -111,7 +111,7 @@ def assertion_vector3D(scal, advec):
advec.discretize()
advec.setup()
- scal_d = scal.discreteFields.values()[0]
+ scal_d = scal.discrete_fields.values()[0]
scal_d.data[0][...] = npw.asrealarray(
np.random.random(scal_d.data[0].shape))
scal_d.data[1][...] = npw.asrealarray(np.random.random(
@@ -132,8 +132,8 @@ def assertion_list(scal, advec):
advec.discretize()
advec.setup()
- scal1_d = scal[0].discreteFields.values()[0]
- scal2_d = scal[1].discreteFields.values()[0]
+ scal1_d = scal[0].discrete_fields.values()[0]
+ scal2_d = scal[1].discrete_fields.values()[0]
scal1_d.data[0][...] = npw.asrealarray(
np.random.random(scal1_d.data[0].shape))
scal2_d.data[0][...] = npw.asrealarray(
diff --git a/hysop/operator/tests/test_penalization.py b/hysop/old/operator.old/tests/test_penalization.py
similarity index 99%
rename from hysop/operator/tests/test_penalization.py
rename to hysop/old/operator.old/tests/test_penalization.py
index 4aef8703b7a54cbc0364393a95bb2e224c173c61..5eeb11a90ea475c01fc28148be915bf111993725 100755
--- a/hysop/operator/tests/test_penalization.py
+++ b/hysop/old/operator.old/tests/test_penalization.py
@@ -5,8 +5,8 @@ from hysop.operator.penalization import Penalization, PenalizeVorticity
from hysop.problem.simulation import Simulation
from hysop.tools.parameters import Discretization
from hysop.tools.io_utils import IOParams
-from hysop.mpi.topology import Cartesian
-import hysop.tools.numpywrappers as npw
+from hysop.core.mpi.topology import Cartesian
+from hysop.tools.numpywrappers import npw
import numpy as np
import os
from hysop import Field, Box
diff --git a/hysop/old/operator.old/tests/test_poisson.py b/hysop/old/operator.old/tests/test_poisson.py
new file mode 100755
index 0000000000000000000000000000000000000000..6bd2718b8b49b5cf87c9407adbb3b75d955db9a7
--- /dev/null
+++ b/hysop/old/operator.old/tests/test_poisson.py
@@ -0,0 +1,308 @@
+# -*- coding: utf-8 -*-
+
+import hysop as pp
+from hysop.operator.poisson import Poisson
+from hysop.operator.analytic import Analytic
+from hysop.operator.reprojection import Reprojection
+from hysop.problem.simulation import Simulation
+from hysop.tools.parameters import Discretization
+from hysop.methods import SpaceDiscretization, \
+ GhostUpdate, Formulation
+import numpy as np
+from hysop.tools.numpywrappers import npw
+import math
+from hysop.domain.subsets import SubBox
+from hysop import testsenv
+
+
+pi = math.pi
+sin = np.sin
+cos = np.cos
+
+## Physical Domain description
+dim = 3
+LL = 2 * pi * npw.ones((dim))
+# formula to compute initial vorticity field
+coeff = 4 * pi ** 2 * (LL[1] ** 2 * LL[2] ** 2 + LL[0] ** 2 * LL[2] ** 2 +
+ LL[0] ** 2 * LL[1] ** 2) / (LL[0] ** 2 * LL[1] ** 2
+ * LL[2] ** 2)
+cc = 2 * pi / LL
+d3D = Discretization([33, 257, 257])
+d2D = Discretization([33, 33])
+uinf = 1.0
+
+
+def computeVort(res, x, y, z, t):
+ res[0][...] = coeff * sin(x * cc[0]) * sin(y * cc[1]) * cos(z * cc[2])
+ res[1][...] = coeff * cos(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])
+ res[2][...] = coeff * cos(x * cc[0]) * cos(y * cc[1]) * sin(z * cc[2])
+ return res
+
+def computePressure(res, x, y, z, t):
+ res[0][...] = -3.0 * sin(x * cc[0]) * cos(y * cc[1]) * cos(z * cc[2])
+ return res
+
+def computeRefPressure(res, x, y, z, t):
+ res[0][...] = sin(x * cc[0]) * cos(y * cc[1]) * cos(z * cc[2])
+ return res
+
+
+# ref. field
+def computeRef(res, x, y, z, t):
+ res[0][...] = -2. * pi / LL[1] * \
+ (cos(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
+ - 2. * pi / LL[2] * (cos(x * cc[0]) * sin(y * cc[1]) * cos(z * cc[2]))
+
+ res[1][...] = -2. * pi / LL[2] * \
+ (sin(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
+ + 2. * pi / LL[0] * (sin(x * cc[0]) * cos(y * cc[1]) * sin(z * cc[2]))
+
+ res[2][...] = -2. * pi / LL[0] * \
+ (sin(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
+ - 2. * pi / LL[1] * (sin(x * cc[0]) * cos(y * cc[1]) * cos(z * cc[2]))
+
+ return res
+
+
+# ref. field
+def computeRef_with_correction(res, x, y, z, t):
+ res[0][...] = -2. * pi / LL[1] * \
+ (cos(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
+ - 2. * pi / LL[2] * (cos(x * cc[0]) * sin(y * cc[1]) * cos(z * cc[2]))\
+ + uinf
+
+ res[1][...] = -2. * pi / LL[2] * \
+ (sin(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
+ + 2. * pi / LL[0] * (sin(x * cc[0]) * cos(y * cc[1]) * sin(z * cc[2]))
+
+ res[2][...] = -2. * pi / LL[0] * \
+ (sin(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
+ - 2. * pi / LL[1] * (sin(x * cc[0]) * cos(y * cc[1]) * cos(z * cc[2]))
+
+ return res
+
+
+def computeVort2D(res, x, y, t):
+ # todo ...
+ res[0][...] = 4 * pi ** 2 * (cos(x * cc[0]) * sin(y * cc[1])) * \
+ (1. / LL[0] ** 2 + 1. / LL[1] ** 2)
+ return res
+
+
+# ref. field
+def computeRef2D(res, x, y, t):
+ res[0][...] = 2. * pi / LL[1] * (cos(x * cc[0]) * cos(y * cc[1]))
+ res[1][...] = 2. * pi / LL[0] * (sin(x * cc[0]) * sin(y * cc[1]))
+
+ return res
+
+@testsenv.fftw_failed
+def test_Poisson_Pressure_3D():
+ dom = pp.Box(length=LL)
+
+ # Fields
+ ref = pp.Field(domain=dom, name='Ref')
+ pressure = pp.Field(domain=dom, formula=computePressure, name='Pressure')
+
+ # Definition of the Poisson operator
+ poisson = Poisson(pressure, pressure, discretization=d3D,
+ method={SpaceDiscretization: 'fftw',
+ GhostUpdate: True,
+ Formulation: 'pressure'})
+
+ poisson.discretize()
+ poisson.setup()
+ topo = poisson.discrete_fields[pressure].topology
+ # Analytic operator to compute the reference field
+ refOp = Analytic(variables={ref: topo}, formula=computeRefPressure)
+ simu = Simulation(nb_iter=10)
+ refOp.discretize()
+ refOp.setup()
+ pressure.initialize(topo=topo)
+ poisson.apply(simu)
+ refOp.apply(simu)
+ assert np.allclose(ref.norm(topo), pressure.norm(topo))
+ refD = ref.discretize(topo)
+ prsD = pressure.discretize(topo)
+ assert np.allclose(prsD[0], refD[0])
+ poisson.finalize()
+
+
+@testsenv.fftw_failed
+def test_Poisson3D():
+ dom = pp.Box(length=LL)
+
+ # Fields
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=computeVort,
+ name='Vorticity', is_vector=True)
+
+ # Definition of the Poisson operator
+ poisson = Poisson(velocity, vorticity, discretization=d3D)
+
+ poisson.discretize()
+ poisson.setup()
+ topo = poisson.discrete_fields[vorticity].topology
+ # Analytic operator to compute the reference field
+ ref = pp.Field(domain=dom, name='reference', is_vector=True)
+ refOp = Analytic(variables={ref: topo}, formula=computeRef)
+ simu = Simulation(nb_iter=10)
+ refOp.discretize()
+ refOp.setup()
+ vorticity.initialize(topo=topo)
+ poisson.apply(simu)
+ refOp.apply(simu)
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ refD = ref.discretize(topo)
+ vd = velocity.discretize(topo)
+ for i in range(dom.dimension):
+ assert np.allclose(vd[i], refD[i])
+ poisson.finalize()
+
+
+@testsenv.fftw_failed
+def test_Poisson2D():
+ dom = pp.Box(length=[2. * pi, 2. * pi], origin=[0., 0.])
+
+ # Fields
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=computeVort2D, name='Vorticity')
+
+ # Definition of the Poisson operator
+ poisson = Poisson(velocity, vorticity, discretization=d2D)
+
+ poisson.discretize()
+ poisson.setup()
+ topo = poisson.discrete_fields[vorticity].topology
+ # Analytic operator to compute the reference field
+ ref = pp.Field(domain=dom, name='reference', is_vector=True)
+ refOp = Analytic(variables={ref: topo}, formula=computeRef2D)
+ simu = Simulation(nb_iter=10)
+ refOp.discretize()
+ refOp.setup()
+ vorticity.initialize(topo=topo)
+ poisson.apply(simu)
+ refOp.apply(simu)
+
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ refD = ref.discretize(topo)
+ vd = velocity.discretize(topo)
+
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ for i in range(dom.dimension):
+ assert np.allclose(vd[i], refD[i])
+ poisson.finalize()
+
+
+@testsenv.fftw_failed
+def test_Poisson3D_correction():
+ dom = pp.Box(length=LL)
+
+ # Fields
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=computeVort,
+ name='Vorticity', is_vector=True)
+
+ # Definition of the Poisson operator
+ ref_rate = npw.zeros(3)
+ ref_rate[0] = uinf * LL[1] * LL[2]
+ rate = pp.VariableParameter(data=ref_rate)
+ poisson = Poisson(velocity, vorticity, discretization=d3D, flowrate=rate)
+
+ poisson.discretize()
+ poisson.setup()
+ topo = poisson.discrete_fields[vorticity].topology
+ # Analytic operator to compute the reference field
+ ref = pp.Field(domain=dom, name='reference', is_vector=True)
+ refOp = Analytic(variables={ref: topo}, formula=computeRef_with_correction)
+ simu = Simulation(nb_iter=10)
+ refOp.discretize()
+ refOp.setup()
+ vorticity.initialize(topo=topo)
+
+ poisson.apply(simu)
+ refOp.apply(simu)
+ refD = ref.discretize(topo)
+ vd = velocity.discretize(topo)
+ surf = SubBox(parent=dom, origin=dom.origin,
+ length=[0., LL[1], LL[2]])
+ surf.discretize(topo)
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ for i in range(dom.dimension):
+ assert np.allclose(vd[i], refD[i])
+ poisson.finalize()
+
+
+@testsenv.fftw_failed
+def test_Poisson3D_projection_1():
+ dom = pp.Box(length=LL)
+
+ # Fields
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=computeVort,
+ name='Vorticity', is_vector=True)
+
+ # Definition of the Poisson operator
+ poisson = Poisson(velocity, vorticity, discretization=d3D, projection=4)
+
+ poisson.discretize()
+ poisson.setup()
+ topo = poisson.discrete_fields[vorticity].topology
+ # Analytic operator to compute the reference field
+ ref = pp.Field(domain=dom, name='reference', is_vector=True)
+ refOp = Analytic(variables={ref: topo}, formula=computeRef)
+ simu = Simulation(nb_iter=10)
+ refOp.discretize()
+ refOp.setup()
+ vorticity.initialize(topo=topo)
+ poisson.apply(simu)
+ refOp.apply(simu)
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ refD = ref.discretize(topo)
+ vd = velocity.discretize(topo)
+
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ for i in range(dom.dimension):
+ assert np.allclose(vd[i], refD[i])
+
+ poisson.finalize()
+
+
+@testsenv.fftw_failed
+def test_Poisson3D_projection_2():
+ dom = pp.Box(length=LL)
+
+ # Fields
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=computeVort,
+ name='Vorticity', is_vector=True)
+ d3dG = Discretization([33, 33, 33], [2, 2, 2])
+ # Definition of the Poisson operator
+ proj = Reprojection(vorticity, threshold=0.05, frequency=4,
+ discretization=d3dG, io_params=True)
+
+ poisson = Poisson(velocity, vorticity, discretization=d3D,
+ projection=proj)
+ proj.discretize()
+ poisson.discretize()
+ poisson.setup()
+ proj.setup()
+ topo = poisson.discrete_fields[vorticity].topology
+ # Analytic operator to compute the reference field
+ ref = pp.Field(domain=dom, name='reference', is_vector=True)
+ refOp = Analytic(variables={ref: topo}, formula=computeRef)
+ simu = Simulation(nb_iter=10)
+ refOp.discretize()
+ refOp.setup()
+ vorticity.initialize(topo=topo)
+ poisson.apply(simu)
+ refOp.apply(simu)
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ refD = ref.discretize(topo)
+ vd = velocity.discretize(topo)
+
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ for i in range(dom.dimension):
+ assert np.allclose(vd[i], refD[i])
+ poisson.finalize()
diff --git a/hysop/operator/tests/test_redistribute.py b/hysop/old/operator.old/tests/test_redistribute.py
similarity index 98%
rename from hysop/operator/tests/test_redistribute.py
rename to hysop/old/operator.old/tests/test_redistribute.py
index 67198bc349353dafdf6d6a578210610ab31bfbec..2bd74cab090138a56e3d10636ddb2288b95aa7de 100755
--- a/hysop/operator/tests/test_redistribute.py
+++ b/hysop/old/operator.old/tests/test_redistribute.py
@@ -7,12 +7,12 @@ import numpy as np
import math
from hysop import Simulation
from hysop.operator.analytic import Analytic
-from hysop.mpi import main_comm, main_size
-from hysop.mpi.tests.utils import create_inter_topos, CPU, GPU, OTHER,\
+from hysop.core.mpi import main_comm, main_size
+from hysop.core.mpi.tests.utils import create_inter_topos, CPU, GPU, OTHER,\
create_multitask_context
from hysop.fields.tests.func_for_tests import v3d, v2d, v3dbis
from hysop.operators import EnergyEnstrophy
-from hysop.mpi.tests.test_bridge import create_subtopos
+from hysop.core.mpi.tests.test_bridge import create_subtopos
sin = np.sin
pi = math.pi
@@ -570,7 +570,7 @@ def test_distribute_inter_4():
assert np.allclose(wd.data[d][ind], vd.data[d][ind])
if dom_tasks.is_on_task(OTHER):
- assert topo not in velocity.discreteFields
+ assert topo not in velocity.discrete_fields
def test_distribute_inter_5():
diff --git a/hysop/operator/tests/test_reprojection.py b/hysop/old/operator.old/tests/test_reprojection.py
similarity index 100%
rename from hysop/operator/tests/test_reprojection.py
rename to hysop/old/operator.old/tests/test_reprojection.py
diff --git a/hysop/operator/tests/test_spectrum.py b/hysop/old/operator.old/tests/test_spectrum.py
similarity index 70%
rename from hysop/operator/tests/test_spectrum.py
rename to hysop/old/operator.old/tests/test_spectrum.py
index 7152e3f65633617b9937967645b80468e6ea26ed..274ebc4000121e20f8d4af22761c02020cb3ff64 100755
--- a/hysop/operator/tests/test_spectrum.py
+++ b/hysop/old/operator.old/tests/test_spectrum.py
@@ -1,23 +1,28 @@
+"""Test fftw spectrum computation
+"""
from hysop.domain.box import Box
from hysop.fields.continuous import Field
from hysop.operator.spectrum import Spectrum
from hysop.tools.parameters import Discretization
from hysop.problem.simulation import Simulation
-from hysop.operator.hdf_io import HDF_Writer
+from hysop import testsenv
import numpy as np
-from hysop.tools.io_utils import IO
pi = np.pi
sin = np.sin
cos = np.cos
def computeScal(res, x, y, z, t):
- res[0][...] = z * sin((3*pi*x)*(2*pi*y))
+ """test function, scalar input, 3D"""
+ res[0][...] = z * sin((3 * pi * x) * (2 * pi * y))
return res
+@testsenv.fftw_failed
def test_spectrum():
- dom = Box(origin=[0., 0., 0.], length=[1., 1., 1.])
+ """build/apply spectrum op
+ """
+ dom = Box()
field = Field(domain=dom, name='Field',
is_vector=False, formula=computeScal)
d3D = Discretization([257, 257, 257])
@@ -25,10 +30,8 @@ def test_spectrum():
op = Spectrum(field, discretization=d3D)
op.discretize()
op.setup()
- topo = op.discreteFields[field].topology
+ topo = op.discrete_fields[field].topology
field.initialize(topo=topo)
simu = Simulation(nb_iter=1)
simu.initialize()
op.apply(simu)
-
-
diff --git a/hysop/operator/tests/test_Stretching.py b/hysop/old/operator.old/tests/test_stretching.py
similarity index 60%
rename from hysop/operator/tests/test_Stretching.py
rename to hysop/old/operator.old/tests/test_stretching.py
index 3a0f89b2fed9091b517e316a9d4d795279cbb653..fc600acd338868683635da04c04ba17b594677fa 100755
--- a/hysop/operator/tests/test_Stretching.py
+++ b/hysop/old/operator.old/tests/test_stretching.py
@@ -3,10 +3,10 @@
"""
from hysop import Field, Box
import numpy as np
-from hysop.operator.stretching import Stretching, StretchingLinearized
+from hysop.operator.stretching import Stretching, StretchingLinearized, GradUW
from hysop.problem.simulation import Simulation
-from hysop.methods_keys import TimeIntegrator, Formulation,\
- SpaceDiscretisation
+from hysop.methods import TimeIntegrator, Formulation,\
+ SpaceDiscretization
from hysop.methods import RK3, FDC4
from hysop.tools.parameters import Discretization
from hysop.tools.misc import WorkSpaceTools
@@ -15,46 +15,13 @@ cos = np.cos
sin = np.sin
-def compute_vel(res, x, y, z, t):
- amodul = cos(pi * 1. / 3.)
- pix = pi * x
- piy = pi * y
- piz = pi * z
- pi2x = 2. * pix
- pi2y = 2. * piy
- pi2z = 2. * piz
- res[0][...] = 2. * sin(pix) * sin(pix) \
- * sin(pi2y) * sin(pi2z) * amodul
- res[1][...] = - sin(pi2x) * sin(piy) \
- * sin(piy) * sin(pi2z) * amodul
- res[2][...] = - sin(pi2x) * sin(piz) \
- * sin(piz) * sin(pi2y) * amodul
- return res
-
-
-def compute_vort(res, x, y, z, t):
- amodul = cos(pi * 1. / 3.)
- pix = pi * x
- piy = pi * y
- piz = pi * z
- pi2x = 2. * pix
- pi2y = 2. * piy
- pi2z = 2. * piz
- res[0][...] = 2. * pi * sin(pi2x) * amodul *\
- (- cos(pi2y) * sin(piz) * sin(piz) +
- sin(piy) * sin(piy) * cos(pi2z))
-
- res[1][...] = 2. * pi * sin(pi2y) * amodul *\
- (2. * cos(pi2z) * sin(pix) * sin(pix) +
- sin(piz) * sin(piz) * cos(pi2x))
-
- res[2][...] = -2. * pi * sin(pi2z) * amodul *\
- (cos(pi2x) * sin(piy) * sin(piy) +
- sin(pix) * sin(pix) * cos(pi2y))
+# 3d discretisation with size 2 ghosts layer
+d3d = Discretization([65, ] * 3, [2, ] * 3)
- return res
-def computeVelBF(res, x, y, z, t):
+def compute_vel(res, x, y, z, t):
+ """3d vector field
+ """
amodul = cos(pi * 1. / 3.)
pix = pi * x
piy = pi * y
@@ -71,7 +38,9 @@ def computeVelBF(res, x, y, z, t):
return res
-def computeVortBF(res, x, y, z, t):
+def compute_vort(res, x, y, z, t):
+ """3d vector field
+ """
amodul = cos(pi * 1. / 3.)
pix = pi * x
piy = pi * y
@@ -97,13 +66,8 @@ def computeVortBF(res, x, y, z, t):
def init(method=None, work=False):
"""Build, init, setup for operator
"""
- nb = 33
- box_length = [1., 1., 1.]
- box_min = [0., 0., 0.]
- nb_elem = Discretization([nb, nb, nb], [2, 2, 2])
-
# Domain
- box = Box(length=box_length, origin=box_min)
+ box = Box()
# Fields
velo = Field(
@@ -112,17 +76,22 @@ def init(method=None, work=False):
vorti = Field(
domain=box, formula=compute_vort,
name='Vorticity', is_vector=True)
- op = Stretching(velo, vorti, discretization=nb_elem, method=method)
+ # Stretching operator
+ op = Stretching(velo, vorti, discretization=d3d, method=method)
op.discretize()
rwork = None
if work:
+ # Find required size for internal work vector, if needed
wkp = op.get_work_properties()['rwork']
+ # Allocate work space
rwork = WorkSpaceTools.check_work_array(len(wkp), wkp[0])
- topo = op.discreteFields[velo].topology
- velo.initialize(topo=topo)
- vorti.initialize(topo=topo)
+ topo = op.discrete_fields[velo].topology
op.setup(rwork=rwork)
simulation = Simulation(start=0, end=1., time_step=0.05)
+ # initialize fields and simu
+ velo.initialize(topo=topo)
+ vorti.initialize(topo=topo)
+ simulation.initialize()
return op, simulation
@@ -130,13 +99,13 @@ def test_stretching():
"""Default case
"""
#method = {TimeIntegrator: RK3, Formulation: Conservative,
- # SpaceDiscretisation: FDC4}
+ # SpaceDiscretization: FDC4}
op, simu = init()
op.apply(simu)
def test_stretching_external_work():
- """User-defined work arrays
+ """Default setup but with user-defined work arrays
"""
op, simu = init(work=True)
op.apply(simu)
@@ -145,50 +114,66 @@ def test_stretching_external_work():
def test_stretching_graduw():
"""GradUW formulation
"""
- method = {TimeIntegrator: RK3, Formulation: "GradUW",
- SpaceDiscretisation: FDC4}
+ method = {TimeIntegrator: RK3, Formulation: GradUW,
+ SpaceDiscretization: FDC4}
op, simu = init(method=method)
op.apply(simu)
+# def test_compare_stretching():
+# """Run conservative and graduv form,
+# check if results are close enough
+# """
+# op1, simu = init()
+# op1.apply(simu)
+# method = {TimeIntegrator: RK3, Formulation: GradUW,
+# SpaceDiscretization: FDC4}
+# op2, simu = init(method=method)
+# op2.apply(simu)
+# w1 = op1.discrete_op.vorticity
+# w2 = op2.discrete_op.vorticity
+# h = w1.topology.mesh.space_step.max()
+# for d in xrange(op1.domain.dimension):
+# print np.abs((w1[d] - w2[d])).max()
+# assert np.allclose(w1[d], w2[d], atol=h ** 2)
+
+
def init_linearized(method=None, work=False):
- """Build, init, setup for operator
+ """Build, init, setup for linearized stretching
"""
- nb = 33
- box_length = [1., 1., 1.]
- box_min = [0., 0., 0.]
- nb_elem = Discretization([nb, nb, nb], [2, 2, 2])
-
# Domain
- box = Box(length=box_length, origin=box_min)
+ box = Box()
- # Fields
+ # Base fields:
+ velo_bf = Field(
+ domain=box, formula=compute_vel,
+ name='VelocityBF', is_vector=True)
+ vorti_bf = Field(
+ domain=box, formula=compute_vort,
+ name='VorticityBF', is_vector=True)
+ # Perturbations
velo = Field(
domain=box, formula=compute_vel,
name='Velocity', is_vector=True)
vorti = Field(
domain=box, formula=compute_vort,
name='Vorticity', is_vector=True)
- velo_bf = Field(
- domain=box, formula=computeVelBF,
- name='VelocityBF', is_vector=True)
- vorti_bf = Field(
- domain=box, formula=computeVortBF,
- name='VorticityBF', is_vector=True)
# Usual stretching operator
- stretch1 = Stretching(velo, vorti, discretization=nb_elem)
+ stretch1 = Stretching(velo, vorti, discretization=d3d)
+ # Linearized stretching
stretch2 = StretchingLinearized(velocity=velo, vorticity=vorti,
- velocity_BF=velo_bf,
- vorticity_BF=vorti_bf,
- discretization=nb_elem, method=method)
+ velocity_BF=velo_bf,
+ vorticity_BF=vorti_bf,
+ discretization=d3d, method=method)
stretch1.discretize()
stretch2.discretize()
rwork = None
if work:
wkp = stretch2.get_work_properties()['rwork']
rwork = WorkSpaceTools.check_work_array(len(wkp), wkp[0])
- topo = stretch1.discreteFields[velo].topology
+ topo = stretch1.discrete_fields[velo].topology
+ # initialize all fields
velo.initialize(topo=topo)
vorti.initialize(topo=topo)
velo_bf.initialize(topo=topo)
@@ -196,6 +181,7 @@ def init_linearized(method=None, work=False):
stretch1.setup()
stretch2.setup(rwork=rwork)
simulation = Simulation(start=0, end=1., time_step=0.05)
+ simulation.initialize()
return stretch1, stretch2, simulation
@@ -210,13 +196,7 @@ def test_stretching_linearized():
def test_stretching_external_work_graduv():
"""User-defined work arrays for GradUW formulation
"""
- method = {TimeIntegrator: RK3, Formulation: "GradUW",
- SpaceDiscretisation: FDC4}
+ method = {TimeIntegrator: RK3, Formulation: GradUW,
+ SpaceDiscretization: FDC4}
op, simu = init(work=True, method=method)
op.apply(simu)
-
-if __name__ == "__main__":
- test_stretching()
- test_stretching_external_work()
- test_stretching_graduw()
- test_stretching_external_work_graduv()
diff --git a/hysop/operator/tests/test_velocity_correction.py b/hysop/old/operator.old/tests/test_velocity_correction.py
similarity index 65%
rename from hysop/operator/tests/test_velocity_correction.py
rename to hysop/old/operator.old/tests/test_velocity_correction.py
index 7c883152045cf49aac2e72ee5bb5563b646294a7..aceed246ea90ac0173322c499a1b558a54f93b74 100755
--- a/hysop/operator/tests/test_velocity_correction.py
+++ b/hysop/old/operator.old/tests/test_velocity_correction.py
@@ -1,11 +1,12 @@
-# -*- coding: utf-8 -*-
-
+"""Test correction operator
+"""
import hysop as pp
from hysop.operator.velocity_correction import VelocityCorrection
from hysop.problem.simulation import Simulation
import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.tools.parameters import Discretization
+from hysop.fields.tests.func_for_tests import v_TG, v_TG_2d, w_TG, w_TG_2d
pi = np.pi
cos = np.cos
sin = np.sin
@@ -14,47 +15,21 @@ uinf = 1.0
tol = 1e-12
-## Function to compute TG velocity
-def computeVel(res, x, y, z, t):
- res[0][...] = sin(x) * cos(y) * cos(z)
- res[1][...] = - cos(x) * sin(y) * cos(z)
- res[2][...] = 0.
- return res
-
-
-## Function to compute reference vorticity
-def computeVort(res, x, y, z, t):
- res[0][...] = - cos(x) * sin(y) * sin(z)
- res[1][...] = - sin(x) * cos(y) * sin(z)
- res[2][...] = 2. * sin(x) * sin(y) * cos(z)
- return res
-
-
-## Function to compute TG velocity
-def computeVel2D(res, x, y, t):
- res[0][...] = sin(x) * cos(y)
- res[1][...] = - cos(x) * sin(y)
- return res
-
-
-## Function to compute reference vorticity
-def computeVort2D(res, x, y, t):
- res[0][...] = - cos(x) * sin(y)
- return res
-
-## Global resolution
+# Global resolution
g = 0
d2D = Discretization([33, 33], [g, g])
d3D = Discretization([33, 33, 33], [g, g, g])
-def test_velocity_correction_3D():
+def test_velocity_correction_3d():
+ """Apply velocity correction, 3d domain
+ """
# Domain
box = pp.Box(length=[2.0 * pi, pi, pi])
# Vector Fields
- velo = pp.Field(domain=box, formula=computeVel,
+ velo = pp.Field(domain=box, formula=v_TG,
name='Velocity', is_vector=True)
- vorti = pp.Field(domain=box, formula=computeVort,
+ vorti = pp.Field(domain=box, formula=w_TG,
name='Vorticity', is_vector=True)
# Usual Cartesian topology definition
@@ -80,17 +55,19 @@ def test_velocity_correction_3D():
assert (np.abs(flowrate - ref_rate) < tol).all()
-def test_velocity_correction_2D():
- ## Domain
+def test_velocity_correction_2d():
+ """Apply velocity correction, 2d domain
+ """
+ # Domain
box = pp.Box(length=[2.0 * pi, pi], origin=[0., 0.])
- ## Vector Fields
- velo = pp.Field(domain=box, formula=computeVel2D,
+ # Vector Fields
+ velo = pp.Field(domain=box, formula=v_TG_2d,
name='Velocity', is_vector=True)
- vorti = pp.Field(domain=box, formula=computeVort2D,
+ vorti = pp.Field(domain=box, formula=w_TG_2d,
name='Vorticity', is_vector=False)
- ## Usual Cartesian topology definition
+ # Usual Cartesian topology definition
topo = box.create_topology(discretization=d2D)
ref_rate = npw.zeros(2)
diff --git a/hysop/operator/velocity_correction.py b/hysop/old/operator.old/velocity_correction.py
similarity index 53%
rename from hysop/operator/velocity_correction.py
rename to hysop/old/operator.old/velocity_correction.py
index 9c863f19a7b0d8055930755eab411810a97f0222..18e1b38e0aac453d1372781a42a9faa80b4bf6ea 100755
--- a/hysop/operator/velocity_correction.py
+++ b/hysop/old/operator.old/velocity_correction.py
@@ -1,8 +1,9 @@
# -*- coding: utf-8 -*-
-"""
-@file operator/velocity_correction.py
+"""Operator used to shift velocity value
+ to fit with a required input flowrate.
+
+Check details in :ref:`velocity_correction` in HySoP user guide.
-Operator to shift velocity to fit with a required input flowrate.
"""
from hysop.constants import debug
@@ -13,44 +14,43 @@ from hysop.operator.continuous import opsetup
class VelocityCorrection(Computational):
- """
- The velocity field is corrected after solving the
+ """The velocity field is corrected after solving the
Poisson equation. For more details about calculations,
- see the "velocity_correction.pdf" explanations document
- in Docs.
+ see :ref:`velocity_correction` in HySoP user guide.
"""
@debug
def __init__(self, velocity, vorticity, req_flowrate, **kwds):
- """
- Corrects the values of the velocity field after
- solving Poisson equation in order to prescribe proper
- mean flow and ensure the desired inlet flowrate.
+ """Update velocity field (solution of Poisson equation)
+ in order to prescribe proper mean flow and ensure
+ the desired inlet flowrate.
- @param[in, out] velocity field to be corrected
- @param[in] vorticity field used to compute correction
- @param resolutions : grid resolutions of velocity and vorticity
- @param[in] req_flowrate : required value for the flowrate
- @param topo : a predefined topology to discretize velocity/vorticity
+ Parameters
+ ----------
+ velocity : :class:`~hysop.fields.continuous.Field`
+ in/out velocity continuous vector field.
+ vorticity : :class:`~hysop.fields.continuous.Field`
+ input vorticity vector field.
+ req_flowrate : a
+ :class:`~hysop.fields.variable_parameter.VariableParameter`
+ the desired inlet flowrate value
+ kwds : base class parameters
"""
assert 'variables' not in kwds, 'variables parameter is useless.'
- super(VelocityCorrection, self).__init__(variables=[velocity,
- vorticity], **kwds)
- ## velocity variable (vector)
+ super(VelocityCorrection, self).__init__(
+ variables=[velocity, vorticity], **kwds)
+ # velocity field
self.velocity = velocity
- ## velocity variable
+ # vorticity field
self.vorticity = vorticity
-
self.input = [self.velocity, self.vorticity]
self.output = [self.velocity]
- ## Expected value for the flow rate through input surface
+ # Expected value for the flow rate through input surface
self.req_flowrate = req_flowrate
dom = self.velocity.domain
+ # volume of control used to compute a reference for correction.
self.cb = ControlBox(origin=dom.origin, length=dom.length,
parent=dom)
- ## Extra parameters that may be required for discrete operator
- ## (at the time, only io_params)
- self.config = kwds
def discretize(self):
super(VelocityCorrection, self)._standard_discretize()
@@ -61,8 +61,8 @@ class VelocityCorrection(Computational):
def setup(self, rwork=None, iwork=None):
if not self._is_uptodate:
self.discrete_op =\
- VelocityCorrection_D(self.discreteFields[self.velocity],
- self.discreteFields[self.vorticity],
+ VelocityCorrection_D(self.discrete_fields[self.velocity],
+ self.discrete_fields[self.vorticity],
self.req_flowrate, self.cb, rwork=rwork,
iwork=iwork)
# Output setup
@@ -70,12 +70,11 @@ class VelocityCorrection(Computational):
self.discrete_op.set_writer(self._writer)
self._is_uptodate = True
- def computeCorrection(self):
- """
- Compute the required correction for the current state
+ def compute_correction(self):
+ """Compute the required correction for the current state
but do not apply it onto velocity.
"""
- self.discrete_op.computeCorrection()
+ self.discrete_op.compute_correction()
def get_work_properties(self):
return {'rwork': None, 'iwork': None}
diff --git a/hysop/problem/__init__.py b/hysop/old/problem.old/__init__.py
similarity index 100%
rename from hysop/problem/__init__.py
rename to hysop/old/problem.old/__init__.py
diff --git a/hysop/problem/navier_stokes.py b/hysop/old/problem.old/navier_stokes.py
similarity index 100%
rename from hysop/problem/navier_stokes.py
rename to hysop/old/problem.old/navier_stokes.py
diff --git a/hysop/problem/problem.py b/hysop/old/problem.old/problem.py
similarity index 98%
rename from hysop/problem/problem.py
rename to hysop/old/problem.old/problem.py
index 1cfce768a304b85828df67564742756ffec39ea6..a1c0b00acc9da9ff33eb03b5cf6a88234fb09a66 100644
--- a/hysop/problem/problem.py
+++ b/hysop/old/problem.old/problem.py
@@ -5,9 +5,9 @@ import cPickle
from hysop import __VERBOSE__, __GPU_ENABLED__
from hysop.operator.redistribute import Redistribute, RedistributeIntra
from hysop.tools.profiler import profile, Profiler
-from hysop.mpi import main_rank
+from hysop.core.mpi import main_rank
if __GPU_ENABLED__:
- from hysop.gpu.gpu_transfer import DataTransfer
+ from hysop.backend.device.opencl.gpu_transfer import DataTransfer
else:
DataTransfer = int
diff --git a/hysop/problem/problem_tasks.py b/hysop/old/problem.old/problem_tasks.py
similarity index 98%
rename from hysop/problem/problem_tasks.py
rename to hysop/old/problem.old/problem_tasks.py
index 1acbe8e93e16dc3050cb97526dfef63b3d33e9f1..9eaf8b9c19b07366a18b925806f44f7b816539d3 100644
--- a/hysop/problem/problem_tasks.py
+++ b/hysop/old/problem.old/problem_tasks.py
@@ -7,7 +7,7 @@ from hysop import __VERBOSE__
from hysop.problem.problem import Problem
from hysop.operator.redistribute import RedistributeInter, RedistributeIntra
from hysop.operator.redistribute import Redistribute
-from hysop.gpu.gpu_transfer import DataTransfer
+from hysop.backend.device.opencl.gpu_transfer import DataTransfer
from hysop.tools.profiler import profile
@@ -45,7 +45,7 @@ class ProblemTasks(Problem):
domain=domain, dumpFreq=dumpFreq, name=name)
self.tasks_list = tasks_list
if main_comm is None:
- from hysop.mpi import main_comm
+ from hysop.core.mpi import main_comm
self.main_comm = main_comm
self._main_rank = self.main_comm.Get_rank()
assert self.main_comm.Get_size() == len(self.tasks_list), \
diff --git a/hysop/problem/problem_with_GLRendering.py b/hysop/old/problem.old/problem_with_GLRendering.py
similarity index 92%
rename from hysop/problem/problem_with_GLRendering.py
rename to hysop/old/problem.old/problem_with_GLRendering.py
index 94c8854280cd0cbe6982c5d96b94bf3cf5b2730b..c8d254dd3e783413e44ff85224e2aa6a930b7270 100644
--- a/hysop/problem/problem_with_GLRendering.py
+++ b/hysop/old/problem.old/problem_with_GLRendering.py
@@ -1,10 +1,7 @@
-"""
-@file problem_with_GLRendering.py
-
-Extends Problem description to handel real time rendering wit OpenGL.
+"""Extend Problem description to handle real time rendering wit OpenGL.
"""
from hysop.constants import debug
-from hysop.mpi import main_rank
+from hysop.core.mpi import main_rank
from hysop.problem.problem import Problem
diff --git a/hysop/old/problem.old/tests/__init__.py b/hysop/old/problem.old/tests/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/problem/tests/test_simulation.py b/hysop/old/problem.old/tests/test_simulation.py
similarity index 99%
rename from hysop/problem/tests/test_simulation.py
rename to hysop/old/problem.old/tests/test_simulation.py
index 7528861ca48d16055ec5350dd2cc63516f272f59..876f099349c37dad0f954a86667c4ac83f661205 100755
--- a/hysop/problem/tests/test_simulation.py
+++ b/hysop/old/problem.old/tests/test_simulation.py
@@ -2,7 +2,7 @@
"""
from hysop.problem.simulation import Simulation, eps
from hysop.tools.io_utils import Writer, IOParams, IO
-from hysop.mpi import main_rank
+from hysop.core.mpi import main_rank
import numpy as np
diff --git a/hysop/problem/tests/test_transport.py b/hysop/old/problem.old/tests/test_transport.py
similarity index 94%
rename from hysop/problem/tests/test_transport.py
rename to hysop/old/problem.old/tests/test_transport.py
index 92d6f4302398b22dced50bb523e03d9b536e8ede..accb2f75d2101b67dd2cc18e50a5dcbac959e4f0 100644
--- a/hysop/problem/tests/test_transport.py
+++ b/hysop/old/problem.old/tests/test_transport.py
@@ -2,7 +2,7 @@
Testing transport problem.
"""
import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from math import sqrt, pi, cos
from hysop.domain.box import Box
from hysop.fields.continuous import Field
@@ -60,9 +60,9 @@ def assertion(dim, boxLength, boxMin, nbElem, finalTime, time_step,
time_step=time_step, max_iter=1)
pb = TransportProblem([advec], simu)
pb.setup()
- initial_scalar = npw.copy(scal.discreteFields.values()[0].data[0])
+ initial_scalar = npw.copy(scal.discrete_fields.values()[0].data[0])
pb.solve()
- return np.allclose(initial_scalar, scal.discreteFields.values()[0].data[0],
+ return np.allclose(initial_scalar, scal.discrete_fields.values()[0].data[0],
rtol, atol)
diff --git a/hysop/problem/transport.py b/hysop/old/problem.old/transport.py
similarity index 100%
rename from hysop/problem/transport.py
rename to hysop/old/problem.old/transport.py
diff --git a/hysop/operator/__init__.py b/hysop/operator/__init__.py
index 5fd789f846149728d69238261e3c35fc637070f3..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 100644
--- a/hysop/operator/__init__.py
+++ b/hysop/operator/__init__.py
@@ -1,3 +0,0 @@
-"""Package for operators (discrete and continuous) description
-
-"""
diff --git a/hysop/operator/advection.py b/hysop/operator/advection.py
deleted file mode 100644
index e73d8344c4f4d236f25022f2b370d588d2a2996a..0000000000000000000000000000000000000000
--- a/hysop/operator/advection.py
+++ /dev/null
@@ -1,639 +0,0 @@
-"""Advection of a field.
-
-See :ref:`advection` in user guide.
-"""
-from hysop import __VERBOSE__
-from hysop.constants import debug, S_DIR, ZDIR
-
-from hysop.operator.computational import Computational
-from hysop.operator.continuous import opsetup, opapply
-from hysop.operator.discrete.particle_advection_dir import ParticleAdvectionDir
-
-from hysop.mpi.topology import Cartesian
-from hysop.tools.parameters import Discretization
-from hysop.tools.misc import WorkSpaceTools
-from hysop.methods_keys import Support
-
-import hysop.tools.numpywrappers as npw
-import hysop.default_methods as default
-
-
-class Advection(Computational):
- """
- Advection of a field,
- \f{eqnarray*}
- X = Op(X,velocity)
- \f} for :
- \f{eqnarray*}
- \frac{\partial{X}}{\partial{t}} + velocity.\nabla X = 0
- \f}
- Note : we assume incompressible flow.
-
- Computations are performed within a dimensional splitting as folows:
- - 1st order:
- - X-dir, half time step
- - Y-dir, half time step
- - Z-dir, half time step
- - 2nd order:
- - X-dir, half time step
- - Y-dir, half time step
- - Z-dir, full time step
- - Y-dir, half time step
- - X-dir, half time step
- """
-
- @debug
- def __init__(self, velocity, discretization,
- advected_fields=None,
- variables=None,
- method=None,
- **kwds):
- """
- Advection of a set of fields for a given velocity.
-
- @param velocity :
- Continuous veolocity field used for advection.
- @param discretization : Cartesian or Discretization
- Discretization parameters for velocity and other fields specified in advected_fields.
- @param advected_fields : the list of continuous fields to be advected.
- It may be None or a single field (no list).
- If set to None, use variables to specify advected fields and their discretizations.
- @param variables: Can be used instead of advected_fields and discretization for advected fields.
- Dictionnary of continuous advected fields as keys and as discretization parameters as values.
- Thios should not contain the velocity.
- Discretization should still be given for velocity.
-
- Available implementations (changed by method[Support]):
- - 'scales' : Scales fortran routines (3d only, list of vector and/or scalar)
- - 'gpu' : OpenCL kernels (1d,2d,3d, list of scalar and/or vectors)
- - 'python' : Pure python (2d,3d, list of vector and/or scalar)
- Default support is 'python'.
- """
-
- # Get default support if method[Support] was not given
- if 'method' is None:
- method=default.ADVECTION.copy()
- else:
- if Support not in method:
- msg="method given but method[Support] has not been set!"
- msg+="\nAvailable implementations are 'scales', 'python' and 'gpu'."
- raise ValueError(msg)
-
- # Velocity must always be given
- # Discretization must always be given as well, at least for velocity
- if velocity is None:
- raise ValueError('Velocity is None.')
- if discretization is None:
- raise ValueError('Discretization is None.')
- self.velocity = velocity
-
- # Advected fields can be given either in advected_fields or
- # within the variables keyword along with their discretization parameters
- if (advected_fields is not None):
- if not isinstance(advected_fields,list):
- msg='Advected fields should be a list!'
- raise ValueError(msg)
- if variables is not None:
- msg='The variables keyword should not be used when using'
- msg+=' the advected_fields argument.'
- raise ValueError(msg)
-
- if isinstance(advected_fields, list):
- self.advected_fields = advected_fields
- else:
- self.advected_fields = [advected_fields]
-
- variables = advected_fields+[velocity]
-
- elif variables is not None:
- # In that case, variables must contain only advected fields
- # along with their discretization parameters.
- if not isinstance(variables,dict):
- raise ValueError(msg)
- msg = 'Variables should be a dictionnary.'
- variables = variables.copy()
- self.advected_fields = variables.keys()
- variables[velocity] = discretization
- discretization = None
- else:
- msg = 'Neither advected_fields nor variables has been set.'
- raise ValueError(msg)
-
- if self.velocity in self.advected_fields:
- raise ValueError('Velocity has been given in advected fields.')
-
- super(Advection, self).__init__(variables=variables,
- discretization=discretization,
- method=method,
- **kwds)
- self.input = self.advected_fields + [self.velocity]
- self.output = self.advected_fields
-
-
- # Find which solver is used for advection among Scales, pure-python and GPU-like.
- # Set corresponding _init, _setup, _apply and _discretize functions.
-
- support = method[Support]
- self._is_scales = (support is 'scales')
- self._is_gpu = (support is 'gpu')
- self._is_python = (support is 'python')
-
- self._init = None
- self._setup = None
- self._apply = None
- self._dicretize = None
-
- if self._is_scales:
- # ---- Scales advection (Fortran implementation) ----
- self._init = self._init_scales
- self._discretize = self._discretize_scales
- self._setup = self._setup_scales
- self._apply = self._apply_scales
- elif self._is_gpu:
- # ---- GPU advection (OpenCL implementation) ----
- self._init = self._init_gpu
- self._discretize = self._splitting_discretize
- self._setup = self._splitting_setup
- self._apply = self._splitting_apply
- elif self._is_python:
- # ---- Pure python advection (numpy implementation) ----
- self._init = self._init_python
- self._discretize = self._splitting_discretize
- self._setup = self._splitting_setup
- self._apply = self._splitting_apply
- else:
- msg="Unknown advection method support '{}'.".format(support)
- msg+="\nAvailable supports are 'scales', 'python' and 'gpu'."
- raise ValueError(msg)
-
- self._is_splitted = (self._is_python or self._is_gpu)
- if self._is_splitted:
- self._ParticleAdvectionDir = None
- self._advec_dir = []
-
- msg='Function configuration error!'
- if (self._init is None) or (self._setup is None) \
- or (self._apply is None) or (self._discretize is None):
- raise RuntimeError(msg)
-
- # Initialize target solver
- self._init()
-
- self._is_discretized = False
- self._is_uptodate = False
-
-
- def discretize(self):
- """
- Discretisation (create topologies and discretize fields)
- """
- if self._is_discretized:
- return
-
- self._discretize()
- self._check_topologies()
-
- self._is_discretized = True
-
- def _check_topologies(self):
- advected_discrete_fields = [self.discrete_fields[f]
- for f in self.advected_fields]
- toporef = advected_discrete_fields[0].topology
-
- msg = 'All advected fields must have the same topology.'
- for f in advected_discrete_fields:
- if f.topology != toporef:
- raise RuntimeError(msg)
-
-
- def get_work_properties(self):
- """
- Return the length of working arrays lists required
- for the discrete operator.
- @return shapes, shape of the arrays:
- shapes['rwork'] == list of shapes for real arrays,
- shapes['iwork'] == list of shapes for int arrays.
- len(shapes['...'] gives the number of required arrays.
- """
- if not self._is_discretized:
- msg = 'The operator must be discretized '
- msg += 'before any call to this function.'
- raise RuntimeError(msg)
-
- if self._is_scales:
- return {'rwork': None, 'iwork': None}
- elif self._is_splitted:
- if len(self._advec_dir)==0:
- raise ValueError('_advec_dir has not been correctly initialized.')
-
- ad0wp = self._advec_dir[0].get_work_properties()
- for ad in self._advec_dir:
- if ad.get_work_properties() != ad0wp:
- msg='ParticleAdvectionDir work properties mismatch! Cannot share works.'
- raise NotImplementedError(msg)
- return ad0wp
- else:
- raise NotImplementedError('Not implemented yet.')
-
- @opsetup
- def setup(self, rwork=None, iwork=None):
- if self._is_uptodate:
- return
- self._setup(rwork=rwork, iwork=iwork)
- self._is_uptodate = True
-
- @debug
- @opapply
- def apply(self, simulation=None, **extra_params):
- """
- Apply this operator to its variables.
- @param simulation : object that describes the simulation
- parameters (time, time step, iteration number ...), see
- hysop.problem.simulation.Simulation for details.
- """
- if (simulation is None):
- raise ValueError('Simulation is None!')
- self._apply(simulation=simulation, **extra_params)
-
- @debug
- def finalize(self):
- """
- Memory cleaning.
- """
- if self._is_scales:
- Computational.finalize(self)
- elif self._is_splitted:
- for dop in self._advec_dir:
- dop.finalize()
- else:
- raise NotImplementedError('Not implemented yet!')
-
-
- def get_profiling_info(self):
- if self._is_uptodate:
- if self._is_scales:
- self.profiler += self.discrete_op.profiler
- elif self._is_splitted:
- for dop in self._advec_dir:
- self.profiler += dop.profiler
- else:
- raise NotImplementedError('Not implemented yet!')
-
- def __str__(self):
- """
- Common printings for operators
- """
- short_name = str(self.__class__).rpartition('.')[-1][0:-2]
- if self._is_scales:
- super(Advection, self).__str__()
- else:
- for i in xrange(self.domain.dimension):
- if self._advec_dir[i].discrete_op is not None:
- s = str(self.advec_dir[i].discrete_op)
- else:
- s = short_name + " operator. Not discretised."
- return s + "\n"
-
-
-# Solver specific functions
- def _init_gpu(self):
- assert self._is_gpu
- from hysop.gpu.static_gpu_particle_advection_dir import StaticGPUParticleAdvectionDir
- self._ParticleAdvectionDir = StaticGPUParticleAdvectionDir
-
- def _init_python(self):
- assert self._is_python
- from hysop.operator.discrete.particle_advection_dir import PythonParticleAdvectionDir
- self._ParticleAdvectionDir = PythonParticleAdvectionDir
-
- #TODO check and fix python implementation
- raise NotImplementedError('Python implementation should be checked!')
-
-
- def _splitting_discretize(self):
- """
- GPU or pure-python discretization
- """
- assert self._is_splitted
-
- # check if ParticleAdvectionDir has been correctly set during init
- if self._ParticleAdvectionDir is None:
- raise ValueError('_ParticleAdvectionDir has not been set!')
-
- # discretize fields
- self._standard_discretize()
-
- # extract discrete fields
- discrete_fields = self.discrete_fields
- dvelo = discrete_fields[self.velocity]
- advected_dfields = [discrete_fields[f] for f in self.advected_fields]
-
- # create all directional discrete ParticleAdvectionDir operators
- dim = self.domain.dimension
- self._advec_dir = [None]*dim
- for i in xrange(dim):
- self._advec_dir[i] = self._ParticleAdvectionDir(
- velocity=dvelo,
- advected_fields=advected_dfields,
- direction=i,
- method=self.method)
-
- op0 = self._advec_dir[0]
- if not isinstance(op0, ParticleAdvectionDir):
- msg='hysop.operator.discrete.ParticleAdvectionDir is not a base of '
- msg+='{}.'.format(op0.__class__.__name__)
- raise ValueError(msg)
-
-
- def _splitting_setup(self, rwork=None, iwork=None):
- """
- Local allocation of work arrays,
- In case of splitting they are common to all _advec_dir operators.
- """
- assert self._is_splitted
-
- ops = self._advec_dir
- if rwork is None:
- rwork = WorkSpaceTools.find_common_workspace(ops,'rwork')
- if iwork is None:
- iwork = WorkSpaceTools.find_common_workspace(ops,'iwork')
-
- # Work arrays are common between all directions
- # of advection.
- for i in xrange(self.domain.dimension):
- self._advec_dir[i].setup(rwork=rwork, iwork=iwork)
-
- if __VERBOSE__ and self._is_gpu:
- self._print_device_allocations()
-
- def _splitting_apply(self,simulation,**extra_params):
- assert self._is_splitted
-
- directions = self._advec_dir[0].step_directions()
- for step_id,step_dir in enumerate(directions):
- self._advec_dir[step_dir].apply(simulation,step_id=step_id,**extra_params)
-
- def _print_device_allocations(self):
- assert self._is_gpu
- cl_env = self._advec_dir[0].cl_env
-
- device_id = cl_env._device_id
- device_name = cl_env.device.name
- gpu_comm = cl_env.gpu_comm
- gpu_rank = gpu_comm.Get_rank()
-
- s = ''
- if gpu_rank == 0:
- s += '=== OpenCL buffers allocated'
- s += ' on device {}: {} ===\n'.format(device_id, device_name)
- s += 'Global memory used:\n'
-
- gmem = 0
- for i,ad in enumerate(self._advec_dir):
- g_mem_d = gpu_comm.allreduce(ad.size_global_alloc)
- if gpu_rank == 0:
- s += " Advection" + S_DIR[i] + ": {0:9d}".format(g_mem_d)
- s += " Bytes ({0:5d} MB)\n".format(g_mem_d / (1024 ** 2))
- gmem += g_mem_d
-
- if gpu_rank == 0:
- s += " Total : {0:9d}".format(gmem)
- s += " Bytes ({0:5d} MB)\n".format(gmem / (1024 ** 2))
- s += "Local memory used:\n"
-
- lmem = 0
- for i,ad in enumerate(self._advec_dir):
- l_mem_d = gpu_comm.allreduce(ad.size_local_alloc)
- if gpu_rank == 0:
- s += " Advection" + S_DIR[i] + ": {0:9d}".format(l_mem_d)
- s += " Bytes ({0:5d} MB)\n".format(l_mem_d / (1024 ** 2))
- lmem += l_mem_d
-
- if gpu_rank ==0:
- s += " Total : {0:9d}".format(lmem)
- s += " Bytes ({0:5d} MB)\n".format(lmem / (1024 ** 2))
- print s
-
-
- # def _setup_python(self, rwork=None, iwork=None):
- # setup for advection in each direction
- # self._setup_advec_dir(rwork, iwork)
- # set splitting parameters (depends on method)
- # self._configure_splitting()
- # configure gpu
- # if self.method[Support].find('gpu') >= 0:
- # self._configure_gpu()
- # self._is_uptodate = True
-
- # def _configure_splitting(self):
- # dimension = self.domain.dimension
- # if self.method[Splitting] == 'o2_FullHalf':
- # Half timestep in all directions
- # [self.splitting.append((i, 0.5))
- # for i in xrange(dimension)]
- # [self.splitting.append((dimension - 1 - i, 0.5))
- # for i in xrange(dimension)]
- # elif self.method[Splitting] == 'o1':
- # [self.splitting.append((i, 1.)) for i in xrange(dimension)]
- # elif self.method[Splitting] == 'x_only':
- # self.splitting.append((0, 1.))
- # elif self.method[Splitting] == 'y_only':
- # self.splitting.append((1, 1.))
- # elif self.method[Splitting] == 'z_only':
- # self.splitting.append((2, 1.))
- # elif self.method[Splitting] == 'o2':
- # Half timestep in all directions but last
- # [self.splitting.append((i, 0.5))
- # for i in xrange(dimension - 1)]
- # self.splitting.append((dimension - 1, 1.))
- # [self.splitting.append((dimension - 2 - i, 0.5))
- # for i in xrange(dimension - 1)]
- # else:
- # raise ValueError('Unknown splitting configuration:' +
- # self.method[Splitting])
-
-
-
- def _init_scales(self):
- #TODO fix this implementation
- raise NotImplementedError('This implementation should be checked!')
-
- if not self.domain.dimension == 3:
- raise ValueError("Scales Advection not implemented in 2D.")
- # Default splitting = Strang
- if Splitting not in self.method.keys():
- self.method[Splitting] = 'strang'
-
- @debug
- def _discretize_scales(self):
- """
- Discretization (create topologies and discretize fields)
- when using SCALES fortran routines (3d only, list of vector
- and/or scalar)
- - 'p_O2' : order 4 method, corrected to allow large CFL number,
- untagged particles
- - 'p_O4' : order 4 method, corrected to allow large CFL number,
- untagged particles
- - 'p_L2' : limited and corrected lambda 2
- - 'p_M4' : Lambda_2,1 (=M'4) 4 point formula
- - 'p_M6' (default) : Lambda_4,2 (=M'6) 6 point formula
- - 'p_M8' : M8prime formula
- - 'p_44' : Lambda_4,4 formula
- - 'p_64' : Lambda_6,4 formula
- - 'p_66' : Lambda_6,6 formula
- - 'p_84' : Lambda_8,4 formula
- """
- assert self._is_scales
- # - Extract order form self.method (default p_M6) -
- order, splitting = self.scales_parameters()
-
- # Check if topos need to be created
- build_topos = self._check_variables()
- from hysop.f2hysop import scales2py as scales
-
- # Scales, single resolution
- if self._single_topo:
- if build_topos:
- # In that case, self._discretization must be
- # a Discretization object, used for all fields.
- # We use it to initialize scales solver
- topo = self._create_scales_topo(self._discretization,
- order, splitting)
- for v in self.variables:
- self.variables[v] = topo
- else:
- # In that case, self._discretization must be
- # a Cartesian object, used for all fields.
- # We use it to initialize scales solver
- assert isinstance(self._discretization, Cartesian)
- topo = self._discretization
- msg = 'input topology is not compliant with scales.'
- #assert topo.dimension == 1, msg
- msg = 'Ghosts points not yet implemented for scales operators.'
- assert (topo.mesh.discretization.ghosts == 0).all(), msg
-
- nbcells = topo.mesh.discretization.resolution - 1
- topodims = topo.shape
- scalesres, global_start = \
- scales.init_advection_solver(nbcells,
- self.domain.length,
- npw.asintarray(topodims),
- self._mpis.comm.py2f(),
- order=order,
- dim_split=splitting)
-
- assert (topo.shape == topodims).all()
- assert (topo.mesh.resolution == scalesres).all()
- assert (topo.mesh.start() == global_start).all()
-
- msg = 'Scales Advection not yet implemented with ghosts points.'
- assert (topo.ghosts() == 0).all(), msg
-
- # Scales, multi-resolution
- else:
- if build_topos[self.velocity]:
- # Resolution used for velocity
- v_resol = self.variables[self.velocity].resolution - 1
-
- else:
- topo = self.variables[self.velocity]
- v_resol = topo.mesh.discretization.resolution
-
- vbuild = [v for v in self.variables if build_topos[v]]
- for v in vbuild:
- self.variables[v] = self._create_scales_topo(
- self.variables[v], order, splitting)
-
- topo = self.variables.values()[0]
- self._check_scales_topo(topo, order, splitting)
-
- # Init multiscale in scales
- scales.init_multiscale(v_resol[0], v_resol[1], v_resol[2],
- self.method[MultiScale])
-
- # All topos are built, we can discretize fields.
- self._discretize_vars()
-
- def scales_parameters(self):
- """
- Return the name of the particular method used in scales
- and the type of splitting.
- """
- order = None
- for o in ['p_O2', 'p_O4', 'p_L2',
- 'p_M4', 'p_M6', 'p_M8',
- 'p_44', 'p_64', 'p_66', 'p_84']:
- if self.method[Scales].find(o) >= 0:
- order = o
- if order is None:
- print ('Unknown advection method, turn to default (p_M6).')
- order = 'p_M6'
-
- # - Extract splitting form self.method (default strang) -
- splitting = 'strang'
- for s in ['classic', 'strang', 'particle']:
- if self.method[Splitting].find(s) >= 0:
- splitting = s
-
- return order, splitting
-
-
- def _create_scales_topo(self, d3d, order, splitting):
- from hysop.f2hysop import scales2py as scales
- comm = self._mpis.comm
- topodims = [1, 1, comm.Get_size()]
- msg = 'Wrong type for parameter discretization (at init).' + str(self._discretization)
- assert isinstance(d3d, Discretization), msg
- nbcells = d3d.resolution - 1
- scalesres, global_start = \
- scales.init_advection_solver(nbcells,
- self.domain.length,
- npw.asintarray(topodims),
- comm.py2f(),
- order=order,
- dim_split=splitting)
- # Create the topo (plane, cut through ZDIR)
- return self.domain.create_plane_topology_from_mesh(
- global_start=global_start, localres=scalesres,
- discretization=d3d, cdir=ZDIR)
-
- def _check_scales_topo(self, toporef, order, splitting):
- from hysop.f2hysop import scales2py as scales
- # In that case, self._discretization must be
- # a Cartesian object, used for all fields.
- # We use it to initialize scales solver
- comm = self._mpis.comm
- #topodims = [1, 1, comm.Get_size()]
- nbcells = toporef.mesh.discretization.resolution - 1
-
- scalesres, global_start = \
- scales.init_advection_solver(nbcells, self.domain.length,
- npw.asintarray(toporef.shape),
- comm.py2f(),
- order=order, dim_split=splitting)
- for v in self.variables:
- topo = self.variables[v]
- assert isinstance(topo, Cartesian), str(topo)
- #assert (topo.shape == topodims).all(), \
- # str(topo.shape) + ' != ' + str(topodims)
- assert not self._single_topo or (topo.mesh.resolution == scalesres).all(), \
- str(topo.mesh.resolution) + ' != ' + str(scalesres)
- assert not self._single_topo or (topo.mesh.start() == global_start).all(), \
- str(topo.mesh.start()) + ' != ' + str(global_start)
-
- def _setup_scales(self, rwork=None, iwork=None):
-
- advected_discrete_fields = [self.discreteFields[f]
- for f in self.advected_fields]
- # - Create the discrete_op from the
- # list of discrete fields -
- from hysop.operator.discrete.scales_advection import \
- ScalesAdvection
- self.discrete_op = ScalesAdvection(
- self.discreteFields[self.velocity],
- advected_discrete_fields, method=self.method,
- rwork=rwork, iwork=iwork,
- **self.config)
- self._is_uptodate = True
-
-
diff --git a/hysop/operator/advection_dir.py b/hysop/operator/advection_dir.py
deleted file mode 100644
index 2fa908e21befbb281b44ec03c8c7d24d67e56c01..0000000000000000000000000000000000000000
--- a/hysop/operator/advection_dir.py
+++ /dev/null
@@ -1,246 +0,0 @@
-"""
-@file advectionDir.py
-
-Advection of a field in a single direction.
-"""
-from hysop.constants import debug, S_DIR
-from hysop.methods_keys import Support, MultiScale, \
- TimeIntegrator, Interpolation
-from hysop.numerics.remeshing import L2_1, L4_2, L4_4, Remeshing, Linear
-from hysop.operator.computational import Computational
-# To get default method values for advection:
-import hysop.default_methods as default
-import numpy as np
-from hysop.operator.continuous import opsetup, opapply
-
-
-class AdvectionDir(Computational):
- """
- Advection of a field,
- \f{eqnarray*}
- X = Op(X,velocity)
- \f} for :
- \f{eqnarray*}
- \frac{\partial{X}}{\partial{t}} + velocity.\nabla X = 0
- \f}
- Note : we assume incompressible flow.
-
- Computations are performed in a given direction.
- """
-
- @debug
- def __init__(self, velocity, direction, advected_fields=None,
- name_suffix='', **kwds):
- ## Get the other arguments to pass to the discrete operators
- self._kwds = kwds.copy()
- self._kwds.pop('discretization')
- ## Transport velocity
- self.velocity = velocity
- if 'variables' in kwds:
- self._kwds.pop('variables')
- kw = kwds.copy()
- kw['variables'] = kwds['variables'].copy()
- # In that case, variables must contains only the advected fields
- # with their discretization param.
- # Velocity must always be given outside variables, with its
- # own discretization.
- assert advected_fields is None, 'too many input arguments.'
- self.advected_fields = kwds['variables'].keys()
- kw['variables'][self.velocity] = kwds['discretization']
- kw.pop('discretization')
- super(AdvectionDir, self).__init__(**kw)
- else:
- v = [self.velocity]
- if isinstance(advected_fields, list):
- self.advected_fields = advected_fields
- else:
- self.advected_fields = [advected_fields]
- v += self.advected_fields
- super(AdvectionDir, self).__init__(variables=v, **kwds)
-
- # Set default method, if required
- if self.method is None:
- self.method = default.ADVECTION
- self.output = self.advected_fields
- self.input = [var for var in self.variables]
-
- from hysop.methods_keys import Splitting
- if Splitting not in self.method.keys():
- self.method[Splitting] = 'o2'
- self.name += name_suffix + S_DIR[direction]
-
- ## direction to advect
- self.direction = direction
-
- ## Fields on particles
- self.particle_fields = None
-
- ## Positions of the particles
- self.particle_positions = None
-
- @debug
- def discretize(self):
- if self._is_discretized:
- return
-
- build_topos = self._check_variables()
-
- # Check if multiscale is available
- if not self._single_topo:
- if self.method[Support].find('gpu') < 0:
- raise ValueError("Multiscale advection is not yet supported "
- "in pure Python, use Scales or GPU.")
-
- ## Default topology cutdir for parallel advection
- cutdir = [False] * self.domain.dimension
- cutdir[-1] = True
-
- if self._single_topo:
- # One topo for all fields ...
- self.method[MultiScale] = None
- if build_topos:
- topo = self.domain.create_topology(
- discretization=self._discretization, cutdir=cutdir)
- for v in self.variables:
- self.variables[v] = topo
- else:
- # Topo is already built, just check if it is 1D
- topo = self.variables.values()[0]
- msg = str(topo.cutdir) + ' != ' + str(cutdir)
- assert (topo.cutdir == cutdir).all(), msg
-
- else:
- # ... or one topo for each field.
- for v in self.variables:
- if build_topos[v]:
- topo = self.domain.create_topology(
- discretization=self.variables[v], cutdir=cutdir)
- self.variables[v] = topo
- build_topos[v] = False
- # compute velocity minimal ghost layer size
- self._check_ghost_layer(build_topos)
-
- # All topos are built, we can discretize fields.
- self._discretize_vars()
-
- self._is_discretized = True
-
- def _check_ghost_layer(self, build_topos):
- """
- Only meaningful if fields have different resolutions.
- Check/set interpolation method for multiscale and
- set ghost layer size, if required.
- """
- # Set method to default if unknown
- if MultiScale not in self.method.keys():
- self.method[MultiScale] = L2_1
-
- mscale = self.method[MultiScale]
- if mscale == Linear:
- min_ghosts = 1
- elif mscale == L2_1:
- min_ghosts = 2
- elif mscale == L4_2 or mscale == L4_4:
- min_ghosts = 3
- else:
- raise ValueError("Unknown multiscale method")
-
- # Topo or resolution associated with velocity
- discr_v = self.variables[self.velocity]
- if build_topos[self.velocity]:
- # discr_v = Discretization
- ghosts_v = discr_v.ghosts
- else:
- # discr_v = Cartesian
- ghosts_v = discr_v.ghosts()
- msg = 'Ghost layer required for velocity. Size min = '
- msg += str(min_ghosts) + " (" + str(ghosts_v) + " given)"
- assert (ghosts_v >= min_ghosts).all(), msg
-
- @opsetup
- def setup(self, rwork=None, iwork=None):
- # select discretization of the advected fields
- advected_discrete_fields = [self.discreteFields[v]
- for v in self.variables
- if v is not self.velocity]
- # GPU advection ...
- if self.method[Support].find('gpu') >= 0:
- topo_shape = advected_discrete_fields[0].topology.shape
- if topo_shape[self.direction] == 1:
- from hysop.gpu.gpu_particle_advection \
- import GPUParticleAdvection as advec
- else:
- from hysop.gpu.multi_gpu_particle_advection \
- import MultiGPUParticleAdvection as advec
- else:
- # pure-python advection
- from hysop.operator.discrete.particle_advection \
- import ParticleAdvection as advec
-
- self.discrete_op = advec(
- velocity=self.discreteFields[self.velocity],
- fields_on_grid=advected_discrete_fields,
- direction=self.direction,
- rwork=rwork, iwork=iwork,
- **self._kwds)
-
- self._is_uptodate = True
-
- def get_work_properties(self):
- """
- Work vector for advection in one dir :
-
- [ interp , part_positions, fields_on_particles]
- interp part is used also for remesh and time-integrator.
- """
- assert self._is_discretized
-
- # Shape of reference comes from fields, not from velocity
- advected_discrete_fields = [self.discreteFields[v]
- for v in self.variables
- if v is not self.velocity]
- topo = advected_discrete_fields[0].topology
- # number of components of the rhs (time integration)
- rhs_size = 1
-
- if self.method[Support].find('gpu') < 0:
- # -- pure python advection --
- # work array shape depends on the time integrator
- # interpolation scheme and remeshing scheme
- ti_work = self.method[TimeIntegrator].get_work_properties(
- rhs_size, topo)
- ti_rwork_length = len(ti_work['rwork'])
- iw_prop = self.method[Interpolation].get_work_properties(topo)
- rw_prop = Remeshing.get_work_properties(topo)
- interp_iwork_length = len(iw_prop['iwork'])
- interp_rwork_length = len(iw_prop['rwork'])
- remesh_iwork_length = len(rw_prop['iwork'])
- remesh_rwork_length = len(rw_prop['rwork'])
- iwork_length = max(interp_iwork_length, remesh_iwork_length)
- rwork_length = max(ti_rwork_length + interp_rwork_length,
- remesh_rwork_length)
- else:
- # -- GPU advection --
- # no work array
- iwork_length, rwork_length = 0, 0
-
- memshape = advected_discrete_fields[0].topology.mesh.resolution
- rwork_length += np.sum([f.nb_components for f in self.advected_fields])
- if self.method[Support].find('gpu') < 0 or \
- self.method[Support].find('gpu_2k') >= 0:
- rwork_length += 1 # work array for position
- memsize = np.prod(topo.mesh.resolution)
- return {'rwork': [memshape] * rwork_length,
- 'iwork': [memshape] * iwork_length}
-
- @debug
- @opapply
- def apply(self, simulation=None, dtCoeff=1.0, split_id=0, old_dir=0):
- """
- Apply this operator to its variables.
- @param simulation : object that describes the simulation
- parameters (time, time step, iteration number ...), see
- hysop.problem.simulation.Simulation for details.
- """
- self.discrete_op.apply(simulation,
- dtCoeff, split_id, old_dir)
diff --git a/hysop/operator/analytic.py b/hysop/operator/analytic.py
index 9e3cf0c179ac01ca4c7b59090299efe19597c9ff..1d14831dac07db0943f783dc07fad50fb082cef9 100644
--- a/hysop/operator/analytic.py
+++ b/hysop/operator/analytic.py
@@ -1,63 +1,97 @@
+"""Initialize fields on a grid, with a user-defined function
"""
-@file operator/analytic.py
-Initialize fields on a grid, with a user-defined function
-"""
-from hysop.constants import debug
-from hysop.operator.continuous import opsetup, opapply
-from hysop.operator.computational import Computational
-from hysop.methods_keys import Support
-
+from hysop.constants import Backend
+from hysop.core.graph.computational_operator import ComputationalGraphOperator
+from hysop.core.graph.graph import ready
+from hysop.tools.types import check_instance
+from hysop import Field, TopologyDescriptor
+from hysop.tools.decorators import debug
-class Analytic(Computational):
+class Analytic(ComputationalGraphOperator):
"""
Applies an analytic formula, given by user, on its fields.
"""
@debug
- def __init__(self, formula=None, vectorize_formula=False, **kwds):
- """
- Operator to apply a user-defined formula onto a list of fields.
- @param formula : the formula to be applied
- @param vectorize_formula : true if formula must be vectorized (numpy),
- default = false.
+ def __init__(self, variables, formula=None,
+ vectorize_formula=False, **kwds):
+ """ Apply a user-defined formula onto a list of fields.
+
+ Parameters
+ ----------
+ formula : python function
+ the formula to be applied
+ vectorize_formula : boolean, optional
+ true if formula must be vectorized (numpy), default = false.
+
+ Notes
+ -----
+ This can be used to initialize multiple fields at once.
+ see :ref:`analytical_operator` for details on
+ the authorized signature for input formula or check
+ test_analytic.py
"""
- super(Analytic, self).__init__(**kwds)
- isGPU = False
- if 'method' in kwds.keys() and Support in kwds['method'].keys():
- isGPU = kwds['method'][Support].find('gpu') >= 0
- if formula is not None:
- ## A formula applied to all variables of this operator
- self.formula = formula
+
+ check_instance(variables, dict, keys=Field, values=TopologyDescriptor)
+
+ input_vars = None
+ output_vars = variables
+
+ for (var,topo) in variables.iteritems():
+ if topo.backend != Backend.HOST:
+ raise ValueError('Analytic only has support for the Host backend yet.')
+
+ super(Analytic, self).__init__(input_vars=input_vars, output_vars=output_vars,
+ **kwds)
+
+
+ # A formula applied to all variables of this operator
+ # on correspoding topologies.
+ self.formula = formula
+ if (formula is not None):
for v in self.variables:
v.set_formula(formula, vectorize_formula)
- elif not isGPU:
- vref = self.variables.keys()[0]
- assert vref.formula is not None
- self.formula = vref.formula
- # Only one formula allowed per operator
+ else:
for v in self.variables:
- assert v.formula is self.formula
+ assert (v.formula is not None)
- self.output = self.variables
+ @debug
+ def initialize(self, **kwds):
+ super(Analytic,self).initialize(**kwds)
+
+ @debug
def discretize(self):
- super(Analytic, self)._standard_discretize()
+ super(Analytic,self).discretize()
- @opsetup
- def setup(self, rwork=None, iwork=None):
- self._is_uptodate = True
+ @debug
+ def get_work_properties(self):
+ return None
+
+ @debug
+ def setup(self, work=None):
+ super(Analytic,self).setup(work=work)
@debug
- @opapply
- def apply(self, simulation=None):
+ @ready
+ def apply(self, simulation=None, **kargs):
assert simulation is not None, \
"Missing simulation value for computation."
- for v in self.variables:
- topo = self.discreteFields[v].topology
- v.initialize(time=simulation.time, topo=topo)
+ for (var,topo) in self.variables.iteritems():
+ var.initialize(time=simulation.time, topo=topo)
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return True
- def get_profiling_info(self):
- pass
-
- def get_work_properties(self):
- return {'rwork': None, 'iwork': None}
+ @classmethod
+ def supports_mpi(cls):
+ return True
+
+ def available_methods(self):
+ return {}
+ def default_method(self):
+ return {}
+ def handle_method(self, method):
+ super(Analytic,self).handle_method(method)
+
diff --git a/hysop/operator/custom.py b/hysop/operator/custom.py
deleted file mode 100644
index 669c9fa6fdc549f5f4e8a2df6e12edeae618fef8..0000000000000000000000000000000000000000
--- a/hysop/operator/custom.py
+++ /dev/null
@@ -1,53 +0,0 @@
-"""
-@file custom.py
-"""
-from hysop.operator.computational import Computational
-from hysop.operator.discrete.custom import CustomMonitor as CM
-from hysop.operator.discrete.custom import CustomOp as CO
-from hysop.operator.continuous import opsetup
-
-
-class CustomOp(Computational):
- def __init__(self, in_fields, out_fields, function, **kwds):
- super(CustomOp, self).__init__(**kwds)
- self.function = function
- self.input = in_fields
- self.output = out_fields
-
- @opsetup
- def setup(self, rwork=None, iwork=None):
- if not self._is_uptodate:
- self.discretize()
- self.discrete_op = CO(
- [self.discreteFields[f] for f in self.input],
- [self.discreteFields[f] for f in self.output],
- self.function,
- variables=self.discreteFields.values())
- self._is_uptodate = True
-
- def get_work_properties(self):
- super(CustomOp,self).get_work_properties()
- #TODO
-
-
-class CustomMonitor(Computational):
- def __init__(self, function, res_shape=1, **kwds):
- super(CustomMonitor, self).__init__(**kwds)
- self.function = function
- self.res_shape = res_shape
- self.input = self.variables
-
- @opsetup
- def setup(self, rwork=None, iwork=None):
- if not self._is_uptodate:
- self.discretize()
- self.discrete_op = CM(self.function, self.res_shape,
- variables=self.discreteFields.values())
- # Output setup
- self._set_io(self.function.__name__, (1, 1 + self.res_shape))
- self.discrete_op.set_writer(self._writer)
- self._is_uptodate = True
-
- def get_work_properties(self):
- super(CustomMonitor,self).get_work_properties()
- #TODO
diff --git a/hysop/operator/diffusion.py b/hysop/operator/diffusion.py
index c72f695649d31fab4e7888d420da892ce7a93d92..b918b81fcc504c638685bfec2eccbe3b14d7c701 100644
--- a/hysop/operator/diffusion.py
+++ b/hysop/operator/diffusion.py
@@ -1,84 +1,78 @@
-# -*- coding: utf-8 -*-
-"""
-@file diffusion.py
-
-Operator for diffusion problem.
"""
-from hysop.operator.computational import Computational
-from hysop.operator.discrete.diffusion_fft import DiffusionFFT
-from hysop.constants import debug
-from hysop.operator.continuous import opsetup
-from hysop.methods_keys import SpaceDiscretisation
-import hysop.default_methods as default
-from hysop import __FFTW_ENABLED__
+@file advection_dir.py
+Directional advection operator generator.
+"""
+from hysop.constants import Implementation
+from hysop.tools.types import check_instance
+from hysop.tools.enum import EnumFactory
+from hysop.tools.decorators import debug
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+from hysop.core.graph.computational_node_frontend import ComputationalGraphNodeFrontend
+from hysop.backend.host.fortran.operator.diffusion import DiffusionFFTW
-class Diffusion(Computational):
+class Diffusion(ComputationalGraphNodeFrontend):
"""
- Diffusion operator
- \f{eqnarray*}
- \omega = Op(\omega)
- \f} with :
- \f{eqnarray*}
- \frac{\partial \omega}{\partial t} &=& \nu\Delta\omega
- \f}
+ Interface the poisson solver.
+ Available implementations are: FFTW
"""
+
+ __implementations = {
+ Implementation.FORTRAN: DiffusionFFTW
+ }
+ @classmethod
+ def implementations(cls):
+ return cls.__implementations
+
+ @classmethod
+ def default_implementation(cls):
+ return Implementation.FORTRAN
+
@debug
- def __init__(self, viscosity, vorticity=None, **kwds):
+ def __init__(self, input_field, variables, viscosity,
+ output_field=None, implementation=None, base_kwds=None, **kwds):
"""
- Constructor for the diffusion operator.
- @param[in,out] vorticity : vorticity field. If None, it must be passed
- through variables argument
- @param[in] viscosity : viscosity of the considered medium.
- """
- if vorticity is not None:
- super(Diffusion, self).__init__(variables=[vorticity], **kwds)
- else:
- super(Diffusion, self).__init__(**kwds)
-
- # The only available method at the time is fftw
- if self.method is None:
- self.method = default.DIFFUSION
- ## input/output field, solution of the problem
- if vorticity is not None:
- self.vorticity = vorticity
- else:
- self.vorticity = self.variables.keys()[0]
- ## viscosity
- self.viscosity = viscosity
+ Initialize a Poisson operator frontend.
+ Solves dF/dt = viscosity * Laplacian(F)
+
+ Parameters
+ ----------
+ input_field: field
+ input field that should be diffused
+ output_field: field, optional, defaults to none
+ output field that should be diffused.
+ if none this will be set to input_field.
+ variables: dict
+ dictionary of fields as keys and topologies as values.
+ viscosity: scalar or Field
+ Warning: implementations may only offer scalar viscosity.
+ implementation: Implementation, optional, defaults to None
+ target implementation, should be contained in available_implementations().
+ If None, implementation will be set to default_implementation().
+ base_kwds: dict, optional, defaults to None
+ Base class keywords arguments.
+ If None, an empty dict will be passed.
+ kwds:
+ Keywords arguments that will be passed towards implementation
+ poisson operator __init__.
- self.kwds = kwds
-
- self.input = [self.vorticity]
- self.output = [self.vorticity]
-
- def discretize(self):
- if self.method[SpaceDiscretisation] is 'fftw' and __FFTW_ENABLED__:
- super(Diffusion, self)._fftw_discretize()
- elif self.method[SpaceDiscretisation] is 'fd':
- super(Diffusion, self)._standard_discretize()
- else:
- raise AttributeError("Method not yet implemented.")
+ Notes
+ -----
+ A diffusion operator implementation should at least support
+ the following __init__ attributes:
+ input_field, output_field, variables, viscosity
+ """
+ output_field = output_field or input_field
+ base_kwds = base_kwds or dict()
- @debug
- @opsetup
- def setup(self, rwork=None, iwork=None):
- if self.method[SpaceDiscretisation] is 'fftw':
- self.discrete_op = DiffusionFFT(
- self.discreteFields[self.vorticity], self.viscosity,
- method=self.method)
- elif self.method[SpaceDiscretisation] is 'fd':
- from hysop.gpu.gpu_diffusion import GPUDiffusion
- kw = self.kwds.copy()
- if 'discretization' in kw.keys():
- kw.pop('discretization')
- self.discrete_op = GPUDiffusion(
- self.discreteFields[self.vorticity],
- viscosity=self.viscosity,
- **kw)
- self._is_uptodate = True
+ check_instance(input_field, Field)
+ check_instance(output_field, Field)
+ check_instance(variables, dict, keys=Field, values=CartesianDescriptors)
+ check_instance(base_kwds, dict, keys=str)
- def get_work_properties(self):
- return {'rwork': None, 'iwork': None}
+ super(Diffusion, self).__init__(input_field=input_field, output_field=output_field,
+ variables=variables, viscosity=viscosity, implementation=implementation, base_kwds=base_kwds,
+ **kwds)
diff --git a/hysop/operator/directional/__init__.py b/hysop/operator/directional/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/hysop/operator/directional/advection_dir.py b/hysop/operator/directional/advection_dir.py
new file mode 100644
index 0000000000000000000000000000000000000000..7c15bd4035a25cab755c2c481cfe5a4fd09a326e
--- /dev/null
+++ b/hysop/operator/directional/advection_dir.py
@@ -0,0 +1,98 @@
+"""
+@file advection_dir.py
+Directional advection frontends (operator generator).
+"""
+
+import itertools as it
+from hysop.constants import DirectionLabels, Implementation
+from hysop.tools.types import check_instance, to_tuple, to_list
+from hysop.tools.decorators import debug
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology import Topology
+from hysop.operator.directional.directional import DirectionalOperatorFrontend
+
+from hysop.backend.device.opencl.operators import OpenClDirectionalAdvection
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+
+
+class DirectionalAdvection(DirectionalOperatorFrontend):
+ """
+ Interface for particular advection and remeshing method of a list
+ of fields in a given direction.
+
+ Available implementations are:
+ *OpenCL
+ """
+
+ __implementations = {
+ Implementation.OPENCL_CODEGEN: OpenClDirectionalAdvection
+ }
+
+ @classmethod
+ def implementations(cls):
+ return cls.__implementations
+
+ @classmethod
+ def default_implementation(cls):
+ return Implementation.OPENCL_CODEGEN
+
+ @debug
+ def __init__(self, velocity, advected_fields, variables,
+ advected_fields_out=None,
+ implementation=None,
+ base_kwds=None,
+ **kwds):
+ """
+ Initialize a DirectionalAdvectionFrontend.
+
+ Parameters
+ ----------
+ velocity: Field
+ continuous velocity field (all components)
+ advected_fields: Field or array like of Fields
+ instance or list of continuous fields to be advected.
+ advected_fields_out: Field or array like of Field, optional, defaults to None
+ advection output, if set to None, advection is done inplace
+ on a per variable basis.
+ variables: dict
+ Dictionary of continuous fields as keys and topologies as values.
+ implementation: implementation, optional, defaults to None
+ target implementation, should be contained in available_implementations().
+ If None, implementation will be set to default_implementation().
+ base_kwds: dict, optional, defaults to None
+ Base class keywords arguments.
+ If None, an empty dict will be passed.
+ kwds:
+ Extra parameters passed to generated directional operators.
+
+ Notes
+ -----
+ An implementation should at least support the following __init__ parameters:
+ velocity, advected_fields, advected_fields_out, variables
+ direction, splitting_dim
+ Extra keywords parameters are passed through kwds.
+ """
+ advected_fields = to_list(advected_fields)
+ assert len(set(advected_fields))==len(advected_fields)
+
+ if (advected_fields_out is None):
+ advected_fields_out = advected_fields
+ else:
+ advected_fields_out = to_list(advected_fields_out)
+ assert len(advected_fields)==len(advected_fields_out)
+ assert len(set(advected_fields_out))==len(advected_fields_out)
+ for i,field in enumerate(advected_fields_out):
+ if (field is None):
+ advected_fields_out[i] = advected_fields[i]
+
+ base_kwds = base_kwds or dict()
+
+ check_instance(velocity, Field)
+ check_instance(advected_fields, list, values=Field)
+ check_instance(advected_fields_out, list, values=Field)
+ check_instance(variables, dict, keys=Field, values=CartesianDescriptors)
+ check_instance(base_kwds, dict, keys=str)
+
+ super(DirectionalAdvection, self).__init__(velocity=velocity,
+ advected_fields=advected_fields, advected_fields_out=advected_fields_out,
+ variables=variables, implementation=implementation, base_kwds=base_kwds, **kwds)
diff --git a/hysop/operator/directional/all.py b/hysop/operator/directional/all.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbf1017454d306d77c4ced39590aa449c7ca810d
--- /dev/null
+++ b/hysop/operator/directional/all.py
@@ -0,0 +1,3 @@
+
+from hysop.operator.directional.advection_dir import DirectionalAdvection
+
diff --git a/hysop/operator/directional/directional.py b/hysop/operator/directional/directional.py
new file mode 100644
index 0000000000000000000000000000000000000000..a20ea7de41f4ad2c3b8dee975f21ac5f5d75e743
--- /dev/null
+++ b/hysop/operator/directional/directional.py
@@ -0,0 +1,202 @@
+
+from abc import ABCMeta, abstractmethod
+from hysop.tools.types import check_instance
+from hysop.tools.decorators import debug
+from hysop.constants import Implementation, DirectionLabels
+from hysop.core.graph.graph import generated, not_implemented
+from hysop.core.graph.node_generator import ComputationalGraphNodeGenerator
+
+class DirectionalOperator(ComputationalGraphNodeGenerator):
+ """
+ Simple ComputationalGraphNodeGenerator to generate an operator in
+ multiple directions.
+ """
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, operator, base_kwds, **op_kwds):
+ """
+ Initialize a DirectionalOperator.
+
+ Parameters
+ ----------
+ operator: ComputationalGraphNodeGenerator or ComputationalGraphNode
+ operator class to be built in each direction.
+ operator.__init__ should accept all extra keywords
+ arguments op_kwds + 'direction' + 'splitting_dim' + 'name'
+ base_kwds: dict, optional, defaults to None
+ Base class keywords arguments.
+ If None, an empty dict will be passed.
+ op_kwds:
+ Keywords arguments that will be passed towards operator.__init__
+ during a call to _generate. In addition to those arguments,
+ direction and splitting_dim will also be passed.
+ If name is present in op_kwds, generated names will be
+ op_kwds['name'] + '_' + DirectionLabels[dir]
+ else:
+ self.__class__.__name__ + '_' + DirectionLabels[dir]
+ """
+ super(DirectionalOperator,self).__init__(**base_kwds)
+ self._splitting_dim = None
+ self._operator = operator
+ self._op_kwds = op_kwds
+
+ @debug
+ def _generate(self, splitting_dim):
+ """
+ Generate splitting_dim operators in each direction.
+ """
+ assert not self.nodes
+
+ kwds = self._op_kwds
+ if 'name' in kwds:
+ basename = kwds.pop('name')
+ else:
+ basename = self.__class__.__name__
+
+ kargs = {}
+ kargs.update(kwds)
+ kargs['splitting_dim'] = splitting_dim
+
+ nodes = []
+ for i in xrange(splitting_dim):
+ kargs['direction']=i
+ kargs['name'] = '{}_{}'.format(basename, DirectionLabels[i])
+ try:
+ op = self._operator(**kargs)
+ nodes.append(op)
+ except:
+ sargs = ['*{} = {}'.format(k,v.__class__)
+ for (k,v) in kargs.iteritems()]
+ msg = 'FATAL ERROR during {}.generate():\n'
+ msg += ' => failed to call {}.__init__()\n with the following keywords:'
+ msg += '\n '+'\n '.join(sargs)
+ msg = msg.format(self.__class__, self._operator)
+ print '\n{}\n'.format(msg)
+ raise
+ self._splitting_dim = splitting_dim
+ return nodes
+
+ @generated
+ def splitting_dimension(self):
+ """
+ Returns the splitting dimension used to generate this DirectionalOperator.
+ """
+ return self._splitting_dim
+
+ @generated
+ def get_direction(self, i):
+ """
+ Retrieve operator in direction i.
+ """
+ max_op = len(self.nodes)
+ if (i<0) or (i>= max_op):
+ msg='Requested direction is out of bounds (i={}, max_op={}).'
+ msg=msg.format(i, max_op)
+ raise ValueError(msg)
+ return self.nodes[i]
+
+
+class DirectionalOperatorFrontend(DirectionalOperator):
+ """
+ Frontend facility for directional operators that provide
+ multiple implementation implementations.
+ """
+
+ __metaclass__ = ABCMeta
+
+ @debug
+ def __init__(self, implementation=None, base_kwds=None, **op_kwds):
+ """
+ Initialize a DirectionalOperatorFrontend.
+
+ Parameters
+ ----------
+ implementation: Implementation, optional, defaults to None
+ target implementation, should be contained in available_implementations().
+ If None, implementation will be set to default_implementation().
+ base_kwds: dict, optional, defaults to None
+ Base class keywords arguments.
+ If None, an empty dict will be passed.
+ op_kwds:
+ Keywords arguments that will be passed towards implementation implemention
+ __init__ during a call to _generate.
+ In addition to those arguments, direction and splitting_dim will
+ also be passed.
+
+ Attributes
+ ----------
+ implementation: Implementation
+ the implementation implementation
+ """
+
+ base_kwds = base_kwds or dict()
+
+ check_instance(implementation, Implementation, allow_none=True)
+ check_instance(base_kwds, dict, keys=str)
+
+ operator = self._get_implementation(implementation)
+
+ super(DirectionalOperatorFrontend,self).__init__(operator=operator, base_kwds=base_kwds, **op_kwds)
+ self.implementation = implementation
+
+ def _get_implementation(self, implementation):
+ """
+ Make some checks and return the operator implementation corresponding
+ to chosen implementation.
+ """
+ default_implementation = self.default_implementation()
+ available_implementations = self.available_implementations()
+
+ if not isinstance(default_implementation, Implementation):
+ raise TypeError('default_implementation is not a instance of hysop.implementation.Implementation.')
+ for b in available_implementations:
+ if not isinstance(b, Implementation):
+ msg='{} is not a instance of hysop.implementation.Implementation.'
+ msg=msg.format(b)
+ raise TypeError(msg)
+
+ if default_implementation not in available_implementations:
+ raise ValueError('default_implementation is not contained in available_implementations.')
+
+ if implementation is None:
+ implementation = default_implementation
+ elif implementation not in available_implementations:
+ simplementations=[]
+ simplementations.append('-{} (default)'.format(default_implementation))
+ for b in available_implementations:
+ if b!=default_implementation:
+ simplementations.append('-{}'.format(b))
+
+ msg = 'Specified implementation \'{}\' is not an available implementation, '
+ msg+= 'available implementations are:\n {}'
+ msg=msg.format(implementation, '\n '.join(implementations))
+ raise ValueError(msg)
+
+ return self.implementations()[implementation]
+
+ @classmethod
+ @not_implemented
+ def implementations(cls):
+ """
+ Should return all implementations as a dictionnary.
+ Keys are Implementation instances and values are either ComputationalGraphNode
+ or ComputationalGraphNodeGenerator.
+ """
+ pass
+
+ @classmethod
+ @not_implemented
+ def default_implementation(cls):
+ """
+ Return the default Implementation, should be compatible with available_implementations.
+ """
+ pass
+
+ @classmethod
+ def available_implementations(cls):
+ """
+ Return all available implementations.
+ """
+ return cls.implementations().keys()
+
diff --git a/hysop/operator/directional/stretching_dir.py b/hysop/operator/directional/stretching_dir.py
new file mode 100644
index 0000000000000000000000000000000000000000..070dc15409cd002bd6f3e2b1fce7dac9da7b1174
--- /dev/null
+++ b/hysop/operator/directional/stretching_dir.py
@@ -0,0 +1,84 @@
+
+"""
+@file advection_dir.py
+Directional advection operator generator.
+"""
+import itertools as it
+from hysop.constants import DirectionLabels, Implementation
+from hysop.tools.types import check_instance, to_tuple
+from hysop.tools.decorators import debug
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+from hysop.operator.directional.directional import DirectionalOperatorFrontend
+
+from hysop.backend.device.opencl.operators import OpenClDirectionalStretching
+
+class DirectionalStretching(DirectionalOperatorFrontend):
+ """
+ Interface for vorticity stretching in a given direction.
+
+ Available implementations are:
+ *OpenCL
+ """
+
+ __implementations = {
+ Implementation.OPENCL_STATIC: OpenClDirectionalStretching
+ }
+
+ @classmethod
+ def implementations(cls):
+ return cls.__implementations
+
+ @classmethod
+ def default_implementation(cls):
+ return Implementation.OPENCL_STATIC
+
+ @debug
+ def __init__(self, velocity, vorticity, variables, vorticity_out=None,
+ implementation=None, base_kwds=None, **kargs):
+ """
+ Initialize a directional advection operator.
+
+ Parameters
+ ----------
+ velocity: Field
+ Continuous velocity field.
+ vorticity: Field
+ Continuous vorticicty field.
+ vorticity_out: Field, optional, defaults to None.
+ Continuous vorticicty output field.
+ If None this is set to vorticity input.
+ variables:
+ Dictionary of continuous fields as keys and topologies as values
+ implementation: Implementation, optional, defaults to None
+ target implementation, should be contained in available_implementations().
+ If None, implementation will be set to default_implementation().
+ base_kwds: dict, optional, defaults to None
+ Base class keywords arguments.
+ If None, an empty dict will be passed.
+ kwds:
+ Extra parameters passed to generated directional operators.
+
+ Notes
+ -----
+ An implementation should at least support the following __init__ parameters:
+ velocity, vorticity, vorticity_out, variables
+ direction, splitting_dim
+ Extra keywords parameters are passed through kwds.
+ """
+
+ vorticity_out = vorticity_out or vorticity
+
+ check_instance(velocity, Field)
+ check_instance(vorticity, Field)
+ check_instance(vorticity_out, Field)
+ check_instance(variables, dict, keys=Field, values=CartesianDescriptors)
+
+ assert vorticity.domain.dimension==3
+ assert vorticity_out.domain.dimension==3
+ assert velocity.domain.dimension==3
+
+ super(DirectionalStretching, self).__init__(velocity=velocity,
+ vorticity=vorticity, vorticity_out=vorticity_out, variables=variables,
+ implementation=implementation, base_kwds=base_kwds, **kargs)
+
diff --git a/hysop/operator/discrete/__init__.py b/hysop/operator/discrete/__init__.py
deleted file mode 100644
index 70f15434bdf7ca63593af802292c2fbb54364f1c..0000000000000000000000000000000000000000
--- a/hysop/operator/discrete/__init__.py
+++ /dev/null
@@ -1,24 +0,0 @@
-## @package hysop.operator.discrete
-# Discrete operators classes.
-#
-# A DiscreteOperator is an object that represents the discretisation of a
-# continuous operator for a specific given method and of its variables for
-# some resolutions.
-#
-# Example: if we want to perform the advection of a scalar at
-# velocity v using scales with M4 remesh, we define the following continuous
-# operator :
-#\code
-# nbElem = [65, 65, 65]
-# advec = Advection(velo, scal,
-# resolutions={velo: nbElem,
-# scal: nbElem},
-# method = 'scales, p_M4',)
-# ...
-# advec.setup()
-# ...
-# advec.apply()
-# \endcode
-#
-# setup call will result in the creation of a ScalesAdvection operator
-# and apply will perform a call to scale's solver.
diff --git a/hysop/operator/discrete/absorption_BC.py b/hysop/operator/discrete/absorption_BC.py
deleted file mode 100755
index 16f9b98b35c95ec1397014e278466d5b44565c1a..0000000000000000000000000000000000000000
--- a/hysop/operator/discrete/absorption_BC.py
+++ /dev/null
@@ -1,132 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-@file operator/discrete/absorption_BC.py
-
-Operator to kill the vorticity at the outlet boundary
-(i.e. removal of the periodic BC in the flow direction
-by vorticity absorption in order to set the far field
-velocity to u_inf at the inlet)
-"""
-
-from hysop.constants import debug, np
-from hysop.operator.discrete.discrete import DiscreteOperator
-from hysop.fields.variable_parameter import VariableParameter
-from hysop.tools.profiler import profile
-import hysop.tools.numpywrappers as npw
-from hysop.constants import XDIR, YDIR, ZDIR
-
-
-class AbsorptionBC_D(DiscreteOperator):
- """
- The periodic boundary condition is modified at the outlet
- in the flow direction in order to discard
- in the downstream region the eddies coming
- periodically from the outlet.
- The vorticity absorption conserves div(omega)=0.
- The far field velocity is set to u_inf at the inlet.
- """
-
- @debug
- def __init__(self, velocity, vorticity, req_flowrate,
- x_coords_absorp, cb, **kwds):
- """
- @param[in] velocity field
- @param[in, out] vorticity field to absorbe
- @param[in] req_flowrate : required value for the flowrate
- (used to set the u_inf velocity value at the inlet)
- @param x_coords_absorp : array containing the x-coordinates delimitating
- the absorption domain ([x_beginning, x_end])
- @param cb : control box for inlet surface computation
- """
- assert 'variables' not in kwds, 'variables parameter is useless.'
- super(AbsorptionBC_D, self).__init__(
- variables=[velocity, vorticity], **kwds)
- ## velocity discrete field
- self.velocity = velocity
- ## vorticity discrete field
- self.vorticity = vorticity
- ## domain dimension
- self.dim = self.velocity.domain.dimension
- # If 2D problem, vorticity must be a scalar
- if self.dim == 2:
- assert self.vorticity.nb_components == 1
- assert (self.dim >= 2),\
- "Wrong problem dimension: only 2D and 3D cases are implemented."
-
- self.input = self.variables
- self.output = [self.vorticity]
- ## A reference topology
- self.topo = self.vorticity.topology
- ## Volume of control
- self.cb = cb
- self.cb.discretize(self.topo)
- # A reference surface, i.e. input surface for flow in x direction
- self._in_surf = cb.surf[XDIR]
-
- sdirs = self._in_surf.t_dir
- # Compute 1./ds and 1./dv ...
- cb_length = self.cb.real_length[self.topo]
- self._inv_ds = 1. / npw.prod(cb_length[sdirs])
- self._inv_dvol = 1. / npw.prod(cb_length)
- ## Expected value for the flow rate through self.surfRef
- self.req_flowrate = req_flowrate
- assert isinstance(self.req_flowrate, VariableParameter),\
- "the required flowrate must be a VariableParameter object."
- self.req_flowrate_val = None
- ## x-coordinates delimitating the absorption band at the outlet
- self.x_coords_absorp = x_coords_absorp
-
- ## setup for the absorption filter definition
- self.xb = self.x_coords_absorp[0]
- self.xe = self.x_coords_absorp[1]
- self.xc = self.xb + (self.xe - self.xb) / 2.0
- self.eps = 10.0
- self.coeff = 1.0 / (np.tanh(self.eps * (self.xb - self.xc)) -
- np.tanh(self.eps * (self.xe - self.xc)))
- self.coords = self.topo.mesh.coords
-
- @debug
- @profile
- def apply(self, simulation=None):
- # the required flowrate value is updated (depending on time)
- self.req_flowrate.update(simulation)
- # \warning : the flow rate value is divided by area of input surf.
- self.req_flowrate_val = self.req_flowrate[self.req_flowrate.name] \
- * self._inv_ds
-
- # Definition of the filter function (for smooth vorticity absorption)
- self._filter = npw.ones_like(self.vorticity.data[0])
- indFilter = np.where(np.logical_and(self.coords[0][:,0,0] >= self.xb,
- self.coords[0][:,0,0] <= self.xe))
-# indFilterZero = np.where(self.coords[0][:,0,0] > self.xe)
- FiltFormula = np.tanh(self.eps * (self.coords[0][indFilter] -
- self.xc))
- FiltFormula -= np.tanh(self.eps * (self.xe - self.xc))
- FiltFormula *= self.coeff
- self._filter[indFilter,:,:] = FiltFormula
-# self._filter[indFilterZero] = 0.0
-
- # Beginning of divergence free vorticity absorption
- # for non-periodic inlet BC
- for d in xrange(self.vorticity.nb_components):
- self.vorticity[d][...] *= self._filter[...]
-
- # Definition of the X-derivative of the filter function
- self._filter = npw.zeros_like(self.vorticity.data[0])
- indFilter = np.where(np.logical_and(self.coords[0][:,0,0] >= self.xb,
- self.coords[0][:,0,0] <= self.xe))
- FiltFormula = self.eps * (1.0 - np.tanh(self.eps *
- (self.coords[0][indFilter] -
- self.xc)) ** 2)
- FiltFormula *= self.coeff
- self._filter[indFilter] = FiltFormula
-
- # End of divergence free vorticity absorption for non-periodic inlet BC
- self.vorticity.data[YDIR][...] += (- self._filter[...] *
- self.velocity[ZDIR][...]) + \
- (self._filter[...] *
- self.req_flowrate_val[ZDIR])
- self.vorticity.data[ZDIR][...] += (self._filter[...] *
- self.velocity[YDIR][...]) - \
- (self._filter[...] *
- self.req_flowrate_val[YDIR])
diff --git a/hysop/operator/discrete/curlAndDiffusion_fft.py b/hysop/operator/discrete/curlAndDiffusion_fft.py
deleted file mode 100644
index d8828c7fd1e5c6769737938358f7c09c5a3352f4..0000000000000000000000000000000000000000
--- a/hysop/operator/discrete/curlAndDiffusion_fft.py
+++ /dev/null
@@ -1,117 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-@file diffusion_fft.py
-Discrete Diffusion operator using FFTW (fortran)
-"""
-try:
- from hysop.f2hysop import fftw2py
-except ImportError:
- from hysop.fakef2py import fftw2py
-from hysop.operator.discrete.discrete import DiscreteOperator
-from hysop.constants import debug
-from hysop.tools.profiler import profile
-
-
-class DiffusionFFT(DiscreteOperator):
- """
- Discretized Poisson operator based on FFTW.
- See details in hysop.operator.diffusion.
-
- """
- @debug
- def __init__(self, vorticity, viscosity, method=None):
- """
- Constructor.
- @param[in,out] vorticity : discretisation of the field \f$ \omega \f$.
- @param[in] viscosity : \f$\nu\f$, viscosity of the considered medium.
- """
-
- DiscreteOperator.__init__(self, [vorticity], method,
- name="Diffusion FFT")
- ## Velocity.
- self.velocity = velocity
- ## Vorticity.
- self.vorticity = vorticity
- ## Viscosity.
- self.viscosity = viscosity
- ## Boolean : pure vort diffusion or curl(u) + vort diffusion.
- self.with_curl = with_curl
-
- @debug
- @profile
- def apply(self, simulation):
-
- if (self.vorticity.dimension == 2):
-
- if self.with_curl:
- raise ValueError("Not yet implemented")
-
- else:
- self.vorticity.data = \
- fftw2py.solve_diffusion_2d(self.viscosity * dt,
- self.vorticity.data)
-
- elif (self.vorticity.dimension == 3):
-
- if self.with_curl:
- self.vorticity.data[0], self.vorticity.data[1],\
- self.vorticity.data[2] = \
- fftw2py.solve_curl_diffusion_3d(self.viscosity * dt,
- self.velocity.data[0],
- self.velocity.data[1],
- self.velocity.data[2],
- self.vorticity.data[0],
- self.vorticity.data[1],
- self.vorticity.data[2])
-
- else:
- self.vorticity.data[0], self.vorticity.data[1],\
- self.vorticity.data[2] = \
- fftw2py.solve_diffusion_3d(self.viscosity * dt,
- self.vorticity.data[0],
- self.vorticity.data[1],
- self.vorticity.data[2])
-
- else:
- raise ValueError("invalid problem dimension")
-# ind0a = self.topology.mesh.local_start[0]
-# ind0b = self.topology.mesh.local_end[0] + 1
-# ind1a = self.topology.mesh.local_start[1]
-# ind1b = self.topology.mesh.local_end[1] + 1
-# ind2a = self.topology.mesh.local_start[2]
-# ind2b = self.topology.mesh.local_end[2] + 1
-
-# vorticityNoG = [npw.zeros((self.resolution - 2 * self.ghosts))
-# for d in xrange(self.dim)]
-# velocityNoG = [nwp.zeros((self.resolution - 2 * self.ghosts))
-# for d in xrange(self.dim)]
-# for i in xrange(self.dim):
-# vorticityNoG[i][...] = self.vorticity[i][ind0a:ind0b,
-# ind1a:ind1b, ind2a:ind2b]
-# velocityNoG[i][...] = self.velocity[i][ind0a:ind0b,
-# ind1a:ind1b, ind2a:ind2b]
-
-# # Curl + Vorticity diffusion
-## vorticityNoG[0][...], vorticityNoG[1][...], vorticityNoG[2][...] = \
-## fftw2py.solve_curl_diffusion_3d(self.viscosity * dt,
-## velocityNoG[0][...],
-## velocityNoG[1][...],
-## velocityNoG[2][...],
-## vorticityNoG[0][...],
-## vorticityNoG[1][...],
-## vorticityNoG[2][...])
-
-# # Pure Vorticity diffusion
-# vorticityNoG[0][...], vorticityNoG[1][...], vorticityNoG[2][...] = \
-# fftw2py.solve_diffusion_3d(self.viscosity * dt,
-# vorticityNoG[0][...],
-# vorticityNoG[1][...],
-# vorticityNoG[2][...])
-
-# for i in xrange(self.dim):
-# self.vorticity[i][ind0a:ind0b, ind1a:ind1b, ind2a:ind2b] = \
-# vorticityNoG[i][...]
-
- def __str__(self):
- s = "Diffusion_d (DiscreteOperator). " + DiscreteOperator.__str__(self)
- return s
diff --git a/hysop/operator/discrete/custom.py b/hysop/operator/discrete/custom.py
deleted file mode 100644
index 20b6aa4daf32ae48f394566a99509914fca27823..0000000000000000000000000000000000000000
--- a/hysop/operator/discrete/custom.py
+++ /dev/null
@@ -1,28 +0,0 @@
-from hysop.operator.discrete.discrete import DiscreteOperator
-
-
-class CustomOp(DiscreteOperator):
- def __init__(self, in_fields, out_fields, function, **kwds):
- super(CustomOp, self).__init__(**kwds)
- self.function = function
- self._in_fields = in_fields
- self._out_fields = out_fields
-
- def apply(self, simulation):
- self.function(simulation, self._in_fields, self._out_fields)
-
-
-class CustomMonitor(DiscreteOperator):
- def __init__(self, function, res_shape=1, **kwds):
- super(CustomMonitor, self).__init__(**kwds)
- self.function = function
- self.res_shape = res_shape
-
- def apply(self, simulation=None):
- ite = simulation.current_iteration
- values = self.function(simulation,
- self.variables)
- if self._writer is not None and self._writer.do_write(ite):
- self._writer.buffer[0, 0] = simulation.time
- self._writer.buffer[0, 1:] = values
- self._writer.write()
diff --git a/hysop/operator/discrete/diffusion_fft.py b/hysop/operator/discrete/diffusion_fft.py
deleted file mode 100644
index daa409eeb5fece5ba305d5a3fb861d89398252d0..0000000000000000000000000000000000000000
--- a/hysop/operator/discrete/diffusion_fft.py
+++ /dev/null
@@ -1,73 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-@file diffusion_fft.py
-Discrete Diffusion operator using FFTW (fortran)
-"""
-try:
- from hysop.f2hysop import fftw2py
-except ImportError:
- from hysop.fakef2py import fftw2py
-from hysop.operator.discrete.discrete import DiscreteOperator
-from hysop.constants import debug
-from hysop.tools.profiler import profile
-
-
-class DiffusionFFT(DiscreteOperator):
- """
- Discretized Poisson operator based on FFTW.
- See details in hysop.operator.diffusion.
-
- """
- @debug
- def __init__(self, vorticity, viscosity, **kwds):
- """
- Constructor.
- @param[in,out] vorticity : discretisation of the field \f$ \omega \f$.
- @param[in] viscosity : \f$\nu\f$, viscosity of the considered medium.
- """
- ## Discretisation of the solution field
- self.vorticity = vorticity
- ## Viscosity.
- self.viscosity = viscosity
-
- if self.vorticity.dimension == 1:
- raise AttributeError("1D case not yet implemented.")
- # Base class initialisation
- assert 'variables' not in kwds, 'variables parameter is useless.'
- super(DiffusionFFT, self).__init__(variables=[vorticity],
- **kwds)
- self.input = [self.vorticity]
- self.output = [self.vorticity]
-
- @debug
- @profile
- def apply(self, simulation=None):
- assert simulation is not None, \
- "Missing dt value for diffusion computation."
- dt = simulation.time_step
- ghosts = self.vorticity.topology.ghosts()
-
- if self.vorticity.dimension == 2:
- self.vorticity.data = fftw2py.solve_diffusion_2d(
- self.viscosity * dt, self.vorticity.data, ghosts)
-
- elif self.vorticity.dimension == 3:
- self.vorticity.data[0], self.vorticity.data[1],\
- self.vorticity.data[2] = \
- fftw2py.solve_diffusion_3d(self.viscosity * dt,
- self.vorticity.data[0],
- self.vorticity.data[1],
- self.vorticity.data[2],
- ghosts)
-
- else:
- raise ValueError("invalid problem dimension")
-
- def finalize(self):
- """
- Clean memory (fftw plans and so on)
- """
- pass
- # TODO : fix bug that occurs when several finalize
- # of fft operators are called.
- # fftw2py.clean_fftw_solver(self.vorticity.dimension)
diff --git a/hysop/operator/discrete/spectrum.py b/hysop/operator/discrete/spectrum.py
deleted file mode 100755
index defda637093bb1f59baf41de513731f898a10fb9..0000000000000000000000000000000000000000
--- a/hysop/operator/discrete/spectrum.py
+++ /dev/null
@@ -1,84 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-@file spectrum.py
-Discrete Spectrum operator using FFTW (fortran)
-"""
-try:
- from hysop.f2hysop import fftw2py
-except ImportError:
- from hysop.fakef2py import fftw2py
-from hysop.operator.discrete.discrete import DiscreteOperator
-from hysop.constants import debug, np, HYSOP_MPI_REAL
-from hysop.tools.profiler import profile
-from hysop.tools.io_utils import IO
-import hysop.tools.numpywrappers as npw
-from hysop.mpi import MPI
-import os
-
-
-class FFTSpectrum(DiscreteOperator):
- """
- Discretized Spectrum operator based on FFTW.
-
- """
- @debug
- def __init__(self, field, prefix=None, **kwds):
- """
- Constructor.
- @param[in] vorticity : field to compute.
- """
- # Discretisation of the input field
- self.field = field
-
- if self.field.nb_components > 1:
- raise AttributeError("Vector case not yet implemented.")
- # Base class initialisation
- assert 'variables' not in kwds, 'variables parameter is useless.'
- super(FFTSpectrum, self).__init__(variables=[field],
- **kwds)
- self.input = [self.field]
- l = np.min(self.field.topology.mesh.discretization.resolution)
- self._tmp = npw.zeros(((l - 1) / 2, ))
- self._kx = npw.zeros(((l - 1) / 2, ))
- self.res = npw.zeros(((l - 1) / 2, ))
- self._prefix = "spectrum" if prefix is None else prefix
- IO.check_dir(os.path.join(IO.default_path(),
- self._prefix + "_00000.dat"))
-
- @debug
- @profile
- def apply(self, simulation=None):
- assert simulation is not None, \
- "Missing dt value for diffusion computation."
- ite = simulation.current_iteration
- ghosts = self.field.topology.ghosts()
- if self.field.dimension == 3:
- fftw2py.spectrum_3d(self.field.data[0],
- self._tmp, self._kx,
- ghosts, np.min(self.domain.length))
- if self.field.topology.size == 1:
- self.res[...] = self._tmp
- else:
- self.field.topology.comm.Reduce(
- [self._tmp, self.res.shape[0], HYSOP_MPI_REAL],
- [self.res, self.res.shape[0], HYSOP_MPI_REAL],
- op=MPI.SUM, root=0)
- if self.field.topology.rank == 0:
- _file = open(os.path.join(
- IO.default_path(),
- self._prefix + "_{0:05d}.dat".format(ite)), 'w')
- for i in xrange(self.res.shape[0]):
- _file.write("{0} {1}\n".format(
- self._kx[i], self.res[i]))
- _file.close()
- else:
- raise ValueError("invalid problem dimension")
-
- def finalize(self):
- """
- Clean memory (fftw plans and so on)
- """
- pass
- # TODO : fix bug that occurs when several finalize
- # of fft operators are called.
- # fftw2py.clean_fftw_solver(self.vorticity.dimension)
diff --git a/hysop/operator/hdf_io.py b/hysop/operator/hdf_io.py
index 5ccd13a733b416de127a16a47d918480665a22d2..4a2e2671913b8b46a50041a548dd2605965a8dd8 100755
--- a/hysop/operator/hdf_io.py
+++ b/hysop/operator/hdf_io.py
@@ -7,36 +7,30 @@
* :class:`~HDF_IO` abstract interface for hdf io classes
"""
-from hysop.constants import S_DIR, debug, HYSOP_REAL
-from hysop.operator.computational import Computational
-from hysop.operator.continuous import opapply, opsetup
-import hysop.tools.numpywrappers as npw
-from hysop.tools.io_utils import IO, IOParams, XMF
from abc import ABCMeta, abstractmethod
+from hysop.deps import h5py
+from hysop.core.graph.graph import discretized
+from hysop.constants import DirectionLabels, HYSOP_REAL
+from hysop.tools.decorators import debug
+from hysop.tools.types import check_instance
+from hysop.tools.numpywrappers import npw
+from hysop.tools.io_utils import IO, IOParams, XMF
+from hysop.core.graph.computational_graph import ComputationalGraphOperator
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology_descriptor import TopologyDescriptor
+from hysop.domain.subsets import Subset
-try:
- import h5py
-except ImportError as h5py_error:
- h5py = None
- msg_err = 'Warning, h5py not found, you may not be able to'
- msg_err += ' use hdf5 I/O functionnalities.'
- print msg_err
-
-from hysop.tools.profiler import profile
-
-
-class HDF_IO(Computational):
+class HDF_IO(ComputationalGraphOperator):
"""Abstract interface to read/write from/to hdf files, for
hysop fields.
"""
__metaclass__ = ABCMeta
- def __init__(self, var_names=None, subset=None, **kwds):
+ def __init__(self, var_names=None, subset=None, **kargs):
"""Read/write some fields data from/into hdf/xmdf files.
Parallel io.
-
Parameters
----------
var_names : a dictionnary, optional
@@ -59,16 +53,17 @@ class HDF_IO(Computational):
into velo/vorti.
"""
- super(HDF_IO, self).__init__(**kwds)
+
+ check_instance(var_names, dict, keys=Field, values=str, allow_none=True)
+ check_instance(subset, Subset, allow_none=True)
+
+ super(HDF_IO, self).__init__(**kargs)
if h5py is None:
print ('You try to use HDF5 reader but h5py module ',)
print ('has not been found on your system.', )
raise h5py_error
- self.input = self.variables
- self.output = self.variables
-
# If no filename is given, set it to
# the concatenation of variables'names.
if self.io_params is None:
@@ -79,7 +74,7 @@ class HDF_IO(Computational):
# to another.
name = ''
names = []
- for var in self.input:
+ for var in self.variables.keys():
names.append(var.name)
names.sort()
for nn in names:
@@ -104,14 +99,18 @@ class HDF_IO(Computational):
# Value = discrete field
self.dataset = {}
# Get hdf file name. Depends on read/write process. Must be
- # defined in HDF_READER or _WRITER init.
+ # defined in HDF_READER or HDF_WRITER init.
self._get_filename = lambda i=None: None
# File Object that holds hdf file
self._hdf_file = None
+ def initialize(self, **kwds):
+ super(HDF_IO, self).initialize(**kwds)
+
def discretize(self):
- super(HDF_IO, self)._standard_discretize()
- assert self._single_topo, 'Multi-resolution case is not allowed.'
+ if not self.initialized:
+ self.initialize()
+ super(HDF_IO, self).discretize()
self.topology = self.variables.values()[0]
# Discretize the subset, if required
@@ -133,21 +132,21 @@ class HDF_IO(Computational):
sl.reverse()
self._sl = tuple(sl)
- @opsetup
- def setup(self, rwork=None, iwork=None):
+ def setup(self, work=None):
+ super(HDF_IO, self).setup(work=work)
# No list of hdf dataset names provided by user ...
if self.var_names is None:
# Get field names and initialize dataset dict.
- for df in self.discreteFields.values():
+ for df in self.discrete_fields.values():
for d in xrange(df.nb_components):
- name = df.name + S_DIR[d]
+ name = df.name + '_' + DirectionLabels[d]
self.dataset[name] = df.data[d]
else:
for var in self.var_names:
# Discrete field associated to var
var_d = var.discretize(self.topology)
for d in xrange(var_d.nb_components):
- name = self.var_names[var] + S_DIR[d]
+ name = self.var_names[var] + '_' + DirectionLabels[d]
self.dataset[name] = var_d.data[d]
def open_hdf(self, count, mode):
@@ -162,22 +161,29 @@ class HDF_IO(Computational):
return compression
- @abstractmethod
- @opapply
- def apply(self, simulation=None):
- """
- Abstract interface to read/write process
- """
-
def get_work_properties(self):
- return {'rwork': None, 'iwork': None}
+ return None
+
+ @classmethod
+ def supports_multiple_topologies(cls):
+ return False
+ @classmethod
+ def supports_mpi(cls):
+ return True
+
+ def available_methods(self):
+ return {}
+ def default_method(self):
+ return {}
+ def handle_method(self, method):
+ super(HDF_IO,self).handle_method(method)
class HDF_Writer(HDF_IO):
"""
Print field(s) values on a given topo, in HDF5 format.
"""
- def __init__(self, xmfalways=True, **kwds):
+ def __init__(self, variables, xmfalways=True, **kargs):
"""
Write some fields data into hdf/xmdf files.
Parallel writings.
@@ -188,9 +194,16 @@ class HDF_Writer(HDF_IO):
true if xmf output must be done every time
an hdf5 file is created (i.e. at each time step),
default=True
- kwds : base class arguments
+ kargs : base class arguments
"""
- super(HDF_Writer, self).__init__(**kwds)
+
+ check_instance(variables, dict, keys=Field, values=TopologyDescriptor)
+
+ input_vars = variables
+ output_vars = None
+
+ super(HDF_Writer, self).__init__(input_vars=input_vars, output_vars=output_vars,
+ **kargs)
# count the number of calls
self._count = 0
@@ -217,9 +230,7 @@ class HDF_Writer(HDF_IO):
return self.io_params.filename + "_{0:05d}".format(i) + '.h5'
@debug
- @profile
- @opapply
- def apply(self, simulation=None):
+ def apply(self, simulation=None, **kargs):
if simulation is None:
raise ValueError("Missing simulation value for monitoring.")
ite = simulation.current_iteration
@@ -231,7 +242,7 @@ class HDF_Writer(HDF_IO):
"""Create and fill the xdmf file
"""
- if self._mpis.rank == self.io_params.io_leader:
+ if self.mpi_params.rank == self.io_params.io_leader:
f = open(self.io_params.filename + '.xmf', 'w')
f.write("<?xml version=\"1.0\" ?>\n")
f.write("<!DOCTYPE Xdmf SYSTEM \"Xdmf.dtd\">\n")
@@ -295,7 +306,7 @@ class HDF_Reader(HDF_IO):
"""
Parallel reading of hdf/xdmf files to fill some fields in.
"""
- def __init__(self, restart=None, **kwds):
+ def __init__(self, variables, restart=None, **kargs):
"""Read some fields data from hdf/xmdf files.
Parallel readings.
@@ -304,14 +315,19 @@ class HDF_Reader(HDF_IO):
restart : int, optional
number of a specific iteration to be read, default=None,
i.e. read first iteration.
- kwds : base class arguments
+ kargs : base class arguments
Notes: restart corresponds to the number which appears in
the hdf file name, corresponding to the number of the
iteration where writing occured.
See examples in tests_hdf_io.py
"""
- super(HDF_Reader, self).__init__(**kwds)
+
+ input_vars = None
+ output_vars = variables
+
+ super(HDF_Reader, self).__init__(input_vars=input_vars, output_vars=output_vars,
+ **kargs)
self.restart = restart
if self.restart is not None:
# filename = prefix_N, N = counter value
@@ -321,9 +337,7 @@ class HDF_Reader(HDF_IO):
self._get_filename = lambda i=None: self.io_params.filename
@debug
- @profile
- @opapply
- def apply(self, simulation=None):
+ def apply(self, simulation=None, **kargs):
# Read HDF file
self.open_hdf(count=self.restart, mode='r')
@@ -343,11 +357,11 @@ class HDF_Reader(HDF_IO):
self._hdf_file = None
# Do we need a CPU->GPU transfer here?
+ @discretized
def dataset_names(self):
"""Return the list of available names for datasets in
the required file.
"""
- assert self._is_discretized, 'a call to discretize() is required.'
if self._hdf_file is None:
self.open_hdf(count=self.restart, mode='r')
return self._hdf_file.keys()
diff --git a/hysop/operator/poisson.py b/hysop/operator/poisson.py
index 324ed1168d074be0c8756d0d46475c910af00daa..ee12c8b1faeef08443b4ceff1eb0a6f3f7a13173 100644
--- a/hysop/operator/poisson.py
+++ b/hysop/operator/poisson.py
@@ -1,137 +1,103 @@
-# -*- coding: utf-8 -*-
-"""Poisson problem.
+
+"""
+@file poisson.py
+Poisson solver frontend.
"""
-from hysop.operator.computational import Computational
-from hysop.operator.discrete.poisson_fft import PoissonFFT
-from hysop.constants import debug
-from hysop.operator.velocity_correction import VelocityCorrection
-from hysop.operator.reprojection import Reprojection
-from hysop.methods_keys import SpaceDiscretisation, Formulation
-from hysop.operator.continuous import opsetup
-import hysop.default_methods as default
-from hysop import __FFTW_ENABLED__
+from hysop.constants import Implementation
+from hysop.tools.types import check_instance
+from hysop.tools.enum import EnumFactory
+from hysop.tools.decorators import debug
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology_descriptor import CartesianDescriptors
+from hysop.core.graph.computational_node_frontend import ComputationalGraphNodeFrontend
+from hysop.backend.host.fortran.operator.poisson import PoissonFFTW
-class Poisson(Computational):
+class Poisson(ComputationalGraphNodeFrontend):
"""
- \f{eqnarray*}
- v = Op(\omega)
- \f} with :
- \f{eqnarray*}
- \Delta \phi &=& -\omega \\
- v &=& \nabla \times \phi
- \f}
+ Interface the poisson solver.
+ Available implementations are:
+ *FORTRAN (fftw based solver)
"""
-
+
+ __implementations = {
+ Implementation.FORTRAN: PoissonFFTW
+ }
+
+ @classmethod
+ def implementations(cls):
+ return cls.__implementations
+
+ @classmethod
+ def default_implementation(cls):
+ return Implementation.FORTRAN
+
@debug
- def __init__(self, output_field, input_field, flowrate=None,
- projection=None, **kwds):
+ def __init__(self, velocity, vorticity, variables,
+ implementation=None, base_kwds=None, **kwds):
"""
- Constructor for the Poisson problem.
-
- @param[out] output_field : solution field
- @param[in] input_field : rhs field
- @param[in] flowrate : a flow rate value (through input_field surf,
- normal to xdir) used to compute a correction of the solution field.
- Default = 0 (no correction). See hysop.operator.output_field_correction.
- @param projection : if None, no projection. Else:
- - either the value of the frequency of reprojection, never update.
- - or a tuple = (frequency, threshold).
- In that case, a criterion
- depending on the input_field will be computed at each time step, if
- criterion > threshold, then frequency projection is active.
-
- Note about method:
- - SpaceDiscretisation == fftw
- - Formulation = 'velocity' or 'pressure'
- velocity : laplacian(phi) = -w and v = nabla X psi, in = vorticity, out = velo
- pressure : laplacian(p) = -nabla.(u.nabla u, in = velo, out = pressure
+ Initialize a Poisson operator frontend.
+
+ Parameters
+ ----------
+ velocity: Field
+ output continuous velocity field (all components)
+ vorticity: Field
+ input continuous vorticity field (all components)
+ variables: dict
+ dictionary of fields as keys and topologies as values.
+ implementation: Implementation, optional, defaults to None
+ target implementation, should be contained in available_implementations().
+ If None, implementation will be set to default_implementation().
+ base_kwds: dict, optional, defaults to None
+ Base class keywords arguments.
+ If None, an empty dict will be passed.
+ kwds:
+ Keywords arguments that will be passed towards implementation
+ poisson operator __init__.
+
+ Notes
+ -----
+ *Equations:
+ laplacian(psi) = -W
+ U = rot(psi)
+
+ in = W (vorticity)
+ out = U (velocity)
+
+ * About dimensions:
+ - if velocity is a 2D vector field, vorticity should have only one component Wx.
+ - if velocity is a 3D vector field, vortcitiy should have three components (Wx,Wy,Wz).
+
+ A Poisson operator implementation should at least support
+ the following __init__ attributes: velocity, vorticity, variables
"""
- # Warning : for fftw all variables must have
- # the same resolution.
- assert 'variables' not in kwds, 'variables parameter is useless.'
- super(Poisson, self).__init__(variables=[output_field, input_field],
- **kwds)
- ## solution of the problem
- self.output_field = output_field
- ## -(right-hand side)
- self.input_field = input_field
- if self.method is None:
- self.method = default.POISSON
-
- if self.method[SpaceDiscretisation] is not 'fftw':
- raise AttributeError("Method not yet implemented.")
-
- # Deterlination of the Poisson equation formulation :
- # Velo Poisson eq or Pressure Poisson eq
- self.formulation = None
- if self.method[Formulation] is not 'velocity':
- self.formulation = self.method[Formulation]
-
- self.input = [self.input_field]
- self.output = [self.output_field]
- if flowrate is not None:
- self.withCorrection = True
- self._flowrate = flowrate
- else:
- self.withCorrection = False
- self.correction = None
- self.projection = projection
- self._config = kwds
-
- if projection is not None:
- self.output.append(self.input_field)
-
- def discretize(self):
- # Poisson solver based on fftw
- if self.method[SpaceDiscretisation] is 'fftw' and __FFTW_ENABLED__:
- super(Poisson, self)._fftw_discretize()
- if self.withCorrection:
- toporef = self.discreteFields[self.output_field].topology
- if 'discretization' in self._config:
- self._config['discretization'] = toporef
- self.correction = VelocityCorrection(
- self.output_field, self.input_field,
- req_flowrate=self._flowrate, **self._config)
- self.correction.discretize()
-
- if isinstance(self.projection, tuple):
- freq = self.projection[0]
- threshold = self.projection[1]
- self.projection = Reprojection(self.input_field,
- threshold, freq,
- **self._config)
- self.projection.discretize()
- else:
- raise AttributeError("Method not implemented.")
-
- @debug
- @opsetup
- def setup(self, rwork=None, iwork=None):
- # Activate correction, if required
- if self.withCorrection:
- self.correction.setup()
- cd = self.correction.discrete_op
- else:
- cd = None
-
- # Activate projection, if required
- if isinstance(self.projection, Reprojection):
- # Projection frequency is updated at each
- # time step, and depends on the input_field
- self.projection.setup(rwork=rwork)
- projection_discr = self.projection.discrete_op
- else:
- projection_discr = self.projection
-
- self.discrete_op = PoissonFFT(self.discreteFields[self.output_field],
- self.discreteFields[self.input_field],
- correction=cd,
- rwork=rwork, iwork=iwork,
- projection=projection_discr,
- formulation=self.formulation)
-
- self._is_uptodate = True
-
- def get_work_properties(self):
- return {'rwork': None, 'iwork': None}
+ base_kwds = base_kwds or dict()
+
+ check_instance(velocity, Field)
+ check_instance(vorticity, Field)
+ check_instance(variables, dict, keys=Field, values=CartesianDescriptors)
+ check_instance(base_kwds, dict, keys=str)
+
+ dim = velocity.domain.dimension
+ vcomp = velocity.nb_components
+ wcomp = vorticity.nb_components
+
+ if (velocity.domain != vorticity.domain):
+ msg = 'Velocity and vorticity do not share the same domain.'
+ raise ValueError(msg)
+ if dim not in [2,3]:
+ msg='Velocity dimension should be 2 or 3, got a {}D vector field.'.format(dim)
+ raise ValueError(msg)
+ if (vcomp != dim):
+ msg = 'Velocity is a {}D vector field but has {} components.'
+ msg=msg.format(dim,vcomp)
+ if (dim==2) and (wcomp!=1):
+ msg='Vorticity component mistmach, got {} components but expected 1.'.format(wcomp)
+ raise RuntimeError(msg)
+ if (dim==3) and (wcomp!=3):
+ msg='Vorticity component mistmach, got {} components but expected 3.'.format(wcomp)
+ raise RuntimeError(msg)
+
+ super(Poisson, self).__init__(velocity=velocity, vorticity=vorticity,
+ variables=variables, base_kwds=base_kwds, implementation=implementation, **kwds)
diff --git a/hysop/operator/redistribute.py b/hysop/operator/redistribute.py
index bf21b5eb2139e339e2615c74097ae5d7d9469eb0..e63fecd76e2a882de23fe85fa227723bb17ae110 100644
--- a/hysop/operator/redistribute.py
+++ b/hysop/operator/redistribute.py
@@ -2,649 +2,167 @@
`.. currentmodule : hysop.operator.redistribute
-* :class:`~RedistributeIntra` for topologies/operators defined
- inside the same mpi communicator
-* :class:`~RedistributeInter` for topologies/operators defined
- on two different mpi communicator
-* :class:`~RedistributeOverlap` for topologies defined
- inside the same mpi parent communicator and
- with a different number of processes
-* :class:`~Redistribute` abstract base class
-
+* :class:`~Redistribute` generate the optimal set of RedistributeOperator instances
+ for one or multiple variables given candidate source topolgies and one output topology.
"""
-from hysop.operator.continuous import Operator
from abc import ABCMeta, abstractmethod
-from hysop.mpi.topology import Cartesian
-from hysop.operator.computational import Computational
-from hysop.operator.continuous import opsetup, opapply
-from hysop.mpi.bridge import Bridge, BridgeOverlap, BridgeInter
-from hysop.constants import S_DIR, debug
-
-
-class Redistribute(Operator):
- """Abstract interface to redistribute operators
+from hysop.constants import DirectionLabels
+from hysop.tools.types import check_instance, to_set
+from hysop.tools.decorators import debug
+from hysop.fields.continuous import Field
+from hysop.core.mpi.topology import Topology, Cartesian
+from hysop.core.mpi.redistribute import RedistributeOperator, RedistributeIntra
+from hysop.core.graph.node_generator import ComputationalGraphNodeGenerator
+
+class Redistribute(ComputationalGraphNodeGenerator):
+ """Interface to generate redistribute operators.
"""
-
- __metaclass__ = ABCMeta
-
- def __init__(self, source, target, component=None,
- run_till=None, **kwds):
- """
- Parameters
- ----------
- source, target: :class:`~hysop.mpi.topology.Cartesian` or
- :class:`~hysop.operator.computational.Computational
- topologies or operators that own the source mesh and targeted mesh
- component: int
- which component of the field must be distributed (default = all)
- run_till: list of :class:`~hysop.operator.computational.Computational
- operators that must wait for the completion of this redistribute
- before any apply.
-
- """
- # Base class initialisation
- super(Redistribute, self).__init__(**kwds)
-
- # Object (may be an operator or a topology) which handles the
- # fields to be transfered
- self._source = source
- # Object (may an operator or a topology) which handles the fields
- # to be filled in from source.
- self._target = target
-
- self.component = component
- if component is None:
- # All components are considered
- self._range_components = lambda v: xrange(v.nb_components)
- else:
- # Only the given component is considered
- assert self.component >= 0, 'component value must be positive.'
- self._range_components = lambda v: (self.component)
-
- # Bridge between topology of source and topology of target
- self.bridge = None
- # True if some MPI operations are running for the current operator.
- self._has_requests = False
- # Which operator must wait for this one before
- # any computation
- # Exp : run_till = op1 means that op1 will
- # wait for the end of this operator before
- # op1 starts its apply.
- if run_till is None:
- run_till = []
-
- assert isinstance(run_till, list)
- self._run_till = run_till
-
- @abstractmethod
- def setup(self, rwork=None, iwork=None):
- """
- Check/set the list of variables to be distributed
-
- What must be set at setup?
- ---> the list of continuous variables to be distributed
- ---> the bridge (one for all variables, which means
- that all vars must have the same topology in source
- and the same topology in target.
- ---> the list of discrete variables for source and
- for target.
- """
- assert self.domain is not None
- for v in self.variables:
- assert v.domain is self.domain
- super(Redistribute, self).setup(rwork, iwork)
-
- def _check_operator(self, op):
- """ ensure op properties:
- * check if op is really a computational operator
- * discretize op
- * check if all required variables (if any) belong to op
-
- Parameters
- ----------
- op : :class:`~hysop.operator.computational.Computational
- :param: op : a computational operator
-
- """
- assert isinstance(op, Computational)
- op.discretize()
- msg = 'The variables to be distributed '
- msg += 'do not belong to the input operator.'
- if len(self.variables) > 0:
- assert all(v in op.variables for v in self.variables), msg
-
- def _set_variables(self):
- """
- Check/set the list of variables proceed by the current operator.
- """
- # Set list of variables.
- # It depends on :
- # - the type of source/target : Cartesian, Computational or None
- # - the args variables : a list of variables or None
- # Possible cases:
- # - if source or target is None --> variables is required
- # - if source and target are Cartesian --> variables is required
- # - in all other cases, variables is optional.
- # If variables are not set at init,
- # they must be infered from source/target operators.
- has_var = len(self.variables) > 0
- vlist = (v for v in self.variables)
-
- if self._source is None or self._target is None:
- assert len(self.variables) > 0
- self.variables = [v for v in vlist]
- else:
- source_is_topo = isinstance(self._source, Cartesian)
- target_is_topo = isinstance(self._target, Cartesian)
-
- # both source and target are topologies. Variables required.
- if source_is_topo and target_is_topo:
- msg = 'Redistribute, a list of variables is required at init.'
- assert has_var, msg
- self.variables = [v for v in vlist]
-
- elif not source_is_topo and not target_is_topo:
- # both source and target are operators
- # --> intersection of their variables
- vsource = self._source.variables
- vtarget = self._target.variables
- if not has_var:
- vlist = (v for v in vsource if v in vtarget)
- self.variables = [v for v in vlist]
-
- elif source_is_topo:
- # source = topo, target = operator
- vtarget = self._target.variables
- if not has_var:
- vlist = (v for v in vtarget)
- self.variables = [v for v in vlist]
-
- else:
- # source = operator, target = topo
- vsource = self._source.variables
- if not has_var:
- vlist = (v for v in vsource)
- self.variables = [v for v in vlist]
-
- assert len(self.variables) > 0
-
- # Variables is converted to a dict to be coherent with
- # computational operators ...
- self.variables = {key: None for key in self.variables}
-
- # All variables must have the same domain
- self.domain = self.variables.keys()[0].domain
- for v in self.variables:
- assert v.domain is self.domain
-
- def _set_topology(self, current):
- """This function check if current is valid, fits with self.variables
- and get its topology to set self._topology.
-
- Parameters
- ----------
- current : :class:`~hysop.mpi.topology.Cartesian` or
- :class:`~hysop.mpi.operator.computational.Computational`
-
- """
- if isinstance(current, Cartesian):
- result = current
- for v in self.variables:
- v.discretize(result)
- elif isinstance(current, Computational):
- self._check_operator(current)
- vref = self.variables.keys()[0]
- vcurrent = current.variables
- result = vcurrent[vref]
- # We ensure that all vars have
- # the same topo in target/target.
- for v in (v for v in self.variables if v is not vref):
- assert vcurrent[v] is result
- else:
- msg = "the source/target is neither an operator or a topology."
- raise AttributeError(msg)
- assert result.task_id() == self.domain.current_task()
- return result
-
- def computation_time(self):
- pass
-
-
-class RedistributeIntra(Redistribute):
- """Data transfer between two operators/topologies.
- Source and target must:
- - be defined on the same communicator
- - work on the same number of mpi process
- - work with the same global resolution
+
+ __redistribute_operators = {
+ 0: RedistributeIntra,
+ #1: RedistributeInter,
+ #2: RedistributeOverlap,
+ }
+ """
+ Implemented redistribute operators,
+ keys are operator priority (smaller value has more priority),
+ values are classes that inerit
+ hysop.core.mpi.redistribute.RedistributeOperator
"""
- def __init__(self, **kwds):
- """Data transfer between two operators/topologies defined on the
- same communicator
-
- Source and target must:
- * be defined on the same communicator
- * work on the same number of mpi process
- * work with the same global resolution
- """
-
- # Base class initialisation
- super(RedistributeIntra, self).__init__(**kwds)
-
- # Warning : comm from io_params will be used as
- # reference for all mpi communication of this operator.
- # --> rank computed in refcomm
- # --> source and target must work inside refcomm
- # If io_params is None, refcomm will COMM_WORLD.
-
- # Dictionnary of discrete fields to be sent
- self._vsource = {}
- # Dictionnary of discrete fields to be overwritten
- self._vtarget = {}
-
- # dictionnary which maps rank with mpi derived type
- # for send operations
- self._send = {}
- # dictionnay which maps rank with mpi derived type
- # for send operations
- self._receive = {}
- # dictionnary which map rank/field name with a
- # receive request
- self._r_request = None
- # dictionnary which map rank/field name with a
- # send request
- self._s_request = None
-
- # Set list of variables and the domain.
- self._set_variables()
- # Set mpi related stuff
- self._set_domain_and_tasks()
-
- @opsetup
- def setup(self, rwork=None, iwork=None):
- # At setup, source and topo must be either
- # a hysop.mpi.topology.Cartesian or
- # a computational operator.
-
- msg = 'Redistribute error : undefined source of target.'
- assert self._source is not None and self._target is not None, msg
-
- t_source = self._set_topology(self._source)
- t_target = self._set_topology(self._target)
-
- source_res = t_source.mesh.discretization.resolution
- target_res = t_target.mesh.discretization.resolution
- msg = 'Redistribute error: source and target must '
- msg += 'have the same global resolution.'
- assert (source_res == target_res).all(), msg
-
- # Set the dictionnaries of source/target variables
- self._vsource = {v: v.discretize(t_source)
- for v in self.variables}
- self._vtarget = {v: v.discretize(t_target)
- for v in self.variables}
-
- # We can create the bridge
- self.bridge = Bridge(t_source, t_target)
+ for cls in __redistribute_operators.values():
+ assert issubclass(cls, RedistributeOperator)
- # Shape of reference is the shape of source/target mesh
- self._send = self.bridge.send_types()
- self._receive = self.bridge.recv_types()
- self._set_synchro()
- self._is_uptodate = True
- def _set_synchro(self):
- """
- Set who must wait for who ...
+ def __init__(self, variables, source_topos, target_topo, components=None,
+ name=None, **kwds):
"""
- # Check input operators
- if isinstance(self._source, Computational):
- # redistribute must wait for source if a variable of redistribute
- # is an output from source.
- for v in self.variables:
- vout = v in self._source.output or False
- if vout:
- self.wait_for(self._source)
- # And source must wait for redistribute
- # if a variable of red. is an output from source.
- self._source.wait_for(self)
-
- if isinstance(self._target, Computational):
- # target operator must wait for
- # the end of this operator to apply.
- self._run_till.append(self._target)
-
- # Add this operator into wait list of
- # operators listed in run_till
- for op in self._run_till:
- op.wait_for(self)
-
- self._is_uptodate = True
-
- def add_run_till_op(self, op):
- """Add an operator to the wait list"""
- self._run_till.append(op)
- op.wait_for(self)
-
- @opapply
- def apply(self, simulation=None):
- # Try different way to send vars?
- # - Buffered : copy all data into a buffer and send/recv
- # - Standard : one send/recv per component
- # --- Standard send/recv ---
- br = self.bridge
-
- # reset send/recv requests
- self._r_request = {}
- self._s_request = {}
-
- basetag = self._mpis.rank + 1
- # Comm used for send/receive operations
- # It must contains all proc. of source topo and
- # target topo.
- refcomm = self.bridge.comm
- # Loop over all required components of each variable
- for v in self.variables:
- for d in self._range_components(v):
- v_name = v.name + S_DIR[d]
-
- # Deal with local copies of data
- if br.has_local_inter():
- vTo = self._vtarget[v].data[d]
- vFrom = self._vsource[v].data[d]
- vTo[br.local_target_ind()] = vFrom[br.local_source_ind()]
-
- # Transfers to other mpi processes
- for rk in self._receive:
- recvtag = basetag * 989 + (rk + 1) * 99 + (d + 1) * 88
- mpi_type = self._receive[rk]
- vTo = self._vtarget[v].data[d]
- self._r_request[v_name + str(rk)] = \
- refcomm.Irecv([vTo, 1, mpi_type],
- source=rk, tag=recvtag)
- self._has_requests = True
- for rk in self._send:
- sendtag = (rk + 1) * 989 + basetag * 99 + (d + 1) * 88
- mpi_type = self._send[rk]
- vFrom = self._vsource[v].data[d]
- self._s_request[v_name + str(rk)] = \
- refcomm.Issend([vFrom, 1, mpi_type],
- dest=rk, tag=sendtag)
- self._has_requests = True
-
- def wait(self):
- if self._has_requests:
- for rk in self._r_request:
- self._r_request[rk].Wait()
- for rk in self._s_request:
- self._s_request[rk].Wait()
- self._has_requests = False
-
- def test_requests(self):
- res = True
- for rk in self._r_request.keys():
- res = self._r_request[rk].Test()
- if not res:
- return res
- for rk in self._s_request.keys():
- res = self._s_request[rk].Test()
- if not res:
- return res
-
- def test_single_request(self, rsend=None, rrecv=None):
- """if neither rsend or rrecv is given return
- True if all communication request are complete
- else check for sending to rsend or receiving from rrecv.
- Process ranks should be those in parent_comm.
-
Parameters
----------
- rsend : string
- discrete variable name + S_DIR + rank of the process
- to which a message has been sent
- and for which we want to test message completion.
- rrecv : string
- discrete variable name + S_DIR + rank of the process
- from which a message has been receive
- and for which we want to test message completion.
-
- """
- if rsend is not None or rrecv is not None:
- send_res = True
- recv_res = True
- if rsend is not None:
- send_res = self._s_request[rsend].Test()
- if rrecv is not None:
- recv_res = self._r_request[rrecv].Test()
- res = send_res and recv_res
- return res
+ variables: :class:`~hysop.field.continuous.Field` or array like of continuous fields.
+ the continuous variables to be distributed
+ source_topos: :class:`~hysop.core.mpi.topology.Topology` or array like of topologies, or dict(field, topologies)
+ candidate source mesh topologies (for each field the optimal source topology will be choosed)
+ target_topo: :class:`~hysop.core.mpi.topology.Topology` or dict(Field, Topology)
+ target mesh topology for all variables (or per variable if a dictionnary is passed)
+ components: None, int or array like of ints or dict(Field,components)
+ which component of the fields must be distributed (default = all components)
+
+ """
+ assert 'source_topo' not in kwds
+
+ super(Redistribute,self).__init__(name=name)
+
+ # format variables to a set of variables
+ variables = to_set(variables)
+ check_instance(variables, set, values=Field)
+
+ # format source topos to a dict(Field, set(Topology))
+ if isinstance(source_topos, dict):
+ for k,v in source_topos:
+ if not isinstance(v,set):
+ source_topos[k] = to_set(v)
else:
- return self.test_requests()
-
-
-class RedistributeInter(Redistribute):
- """Operator to redistribute data from one communicator to another.
- Source/target may be either a topology or a computational operator.
- It implies mpi inter-communications.
- """
-
- @debug
- def __init__(self, parent, source_id=None, target_id=None, **kwds):
- """redistribute data from one communicator to another.
- Source/target may be either a topology or a computational operator.
- It implies mpi inter-communications.
-
- Parameters
- ----------
- parent : MPI.COMM
- mpi communicator that must owns all the
- processes involved in source and target.
- source_id, target_id : int
- mpi task ids for the source/target.
- Required if source/target is None
- else infered from source/target.
-
- See other required parameters in base class.
- """
- super(RedistributeInter, self).__init__(**kwds)
-
- # parent communicator, that must contains all processes
- # involved in source and target tasks.
- self.parent = parent
-
- # set source and targets ids.
- # They must be known before setup.
- # Either they can be infered from source and target
- # or must be set in argument list, if either source
- # or target is undefined on the current process.
- if self._source is None:
- assert source_id is not None
-
- if self._target is None:
- assert target_id is not None
-
- self._source_id = source_id
- self._target_id = target_id
-
- # Set list of variables and domain.
- self._set_variables()
- # Set mpi related stuff
- self._set_domain_and_tasks()
-
- # Domain is set, we can check if we are on source or target
- current_task = self.domain.current_task()
- self._is_source = current_task == self._source_id
- self._is_target = current_task == self._target_id
- assert self._is_target or self._is_source
- assert not (self._is_target and self._is_source)
-
- nbprocs = len(self.domain.tasks_list())
- msg = "Parent communicator size and number of procs "
- msg += "in domain differ."
- assert parent.Get_size() == nbprocs, msg
-
- # the local topology. May be either source or target
- # depending on the task of the current process.
- self._topology = None
-
- # dictionnary which maps rank with mpi derived type
- # used for send/recv operations (send on source, recv on target ...)
- self._transfer_types = None
-
- # dictionnary which maps rank/field name with a
- # send/recv request
- self._requests = {}
-
- @debug
- @opsetup
- def setup(self, rwork=None, iwork=None):
- # First of all, we need to get the current topology:
- if self._is_source:
- assert self._source is not None
- self._topology = self._set_topology(self._source)
- elif self._is_target:
- assert self._target is not None
- self._topology = self._set_topology(self._target)
-
- # Now we can build the bridge (intercomm)
- self.bridge = BridgeInter(self._topology, self.parent,
- self._source_id, self._target_id)
-
- # And get mpi derived types
- self._transfer_types = self.bridge.transfer_types()
-
- self._set_synchro()
- self._is_uptodate = True
-
- def _set_synchro(self):
- """
- Set who must wait for who ...
- """
- if self._is_source and isinstance(self._source, Computational):
- # redistribute must wait for source if a variable of redistribute
- # is an output from source.
- for v in self.variables:
- vout = v in self._source.output or False
- if vout:
- self.wait_for(self._source)
- # And source must wait for redistribute
- # if a variable of red. is an output from source.
- self._source.wait_for(self)
-
- if self._is_target and isinstance(self._target, Computational):
- # target operator must wait for
- # the end of this operator to apply.
- self._run_till.append(self._target)
-
- # Add this operator into wait list of
- # operators listed in run_till
- for op in self._run_till:
- op.wait_for(self)
-
- def add_run_till_op(self, op):
- """Add an operator to the wait list"""
- if self._is_target:
- self._run_till.append(op)
- op.wait_for(self)
-
+ source_topos = to_set(source_topos)
+ source_topos = dict(zip(variables, (source_topos,)*len(variables)))
+
+ check_instance(source_topos, dict, keys=Field, values=set)
+ for v in source_topos.values():
+ check_instance(v, set, values=Topology)
+
+ # format target_topo to a dict(Field, Topology)
+ if not isinstance(target_topo, dict):
+ check_instance(target_topo, Topology)
+ target_topo = dict(zip(variables, (target_topo,)*len(variables)))
+ check_instance(target_topo, dict, keys=Field, values=Topology)
+
+ # format components to a dict(Field, set(int)|None)
+ if not isinstance(components, dict):
+ if components is not None:
+ components = to_set(components)
+ components = dict(zip(variables, (components,)*len(variables)))
+ check_instance(components, dict, keys=Field)
+ for v in components.values():
+ check_instance(v, set, values=int, allow_none=True)
+
+ self._variables = variables
+ self._source_topos = source_topos
+ self._target_topo = target_topo
+ self._components = components
+ self._name = name
+ self._kwds = kwds
+
@debug
- @opapply
- def apply(self, simulation=None):
- # --- Standard send/recv ---
- self._requests = {}
-
- # basetag = self._mpis.rank + 1
- # Comm used for send/receive operations
- # It must contains all proc. of source topo and
- # target topo.
- refcomm = self.bridge.comm
- # Map between rank and mpi types
- # Loop over all required components of each variable
- for v in self.variables:
- rank = self._topology.comm.Get_rank()
- for d in self._range_components(v):
- v_name = v.name + S_DIR[d]
- vtab = v.discreteFields[self._topology].data[d]
- for rk in self._transfer_types:
- if self._is_target:
- # Set reception
- self._requests[v_name + str(rk)] = \
- refcomm.Irecv([vtab[...], 1,
- self._transfer_types[rk]],
- source=rk, tag=rk)
- if self._is_source:
- self._requests[v_name + str(rk)] = \
- refcomm.Issend([vtab[...], 1,
- self._transfer_types[rk]],
- dest=rk, tag=rank)
- self._has_requests = True
-
- def wait(self):
- if self._has_requests:
- for rk in self._requests:
- self._requests[rk].Wait()
- for v in self.variables:
- for d in self._range_components(v):
- vtab = v.discreteFields[self._topology].data[d]
- self._has_requests = False
-
- def test_requests(self):
- res = True
- for rk in self._requests:
- res = self._requests[rk].Test()
- if not res:
- return res
-
-
-class RedistributeOverlap(RedistributeIntra):
- """A specific redistribute where source and target do not work with the same
- group of mpi processes.
- Requirements :
- - work only on topologies, not on operators
- - same global resolution for both topologies
- - group from source topology and target topology MUST overlap.
- """
-
- @opsetup
- def setup(self, rwork=None, iwork=None):
- """
- Check/set the list of variables to be distributed
-
- What must be set at setup?
- ---> the list of continuous variables to be distributed
- ---> the bridge (one for all variables, which means
- that all vars must have the same topology in source
- and the same topology in target.
- ---> the list of discrete variables for source and
- for target.
- """
- if self._source is not None:
- self._vsource = self._discrete_fields(self._source)
- if self._target is not None:
- self._vtarget = self._discrete_fields(self._target)
-
- # We can create the bridge
- self.bridge = BridgeOverlap(source=self._source, target=self._target,
- comm_ref=self._mpis.comm)
-
- # Build mpi derived types for send and receive operations.
- # Shape of reference is the shape of source/target mesh
- if self._source is not None:
- self._send = self.bridge.send_types()
- if self._target is not None:
- self._receive = self.bridge.recv_types()
-
- self._set_synchro()
- self._is_uptodate = True
-
- def _discrete_fields(self, topo):
- """Return the dictionnary of discrete fields for topo
- and the variables of this operator.
-
- Parameters
- ----------
- topo : :class:`~hysop.mpi.topology.Cartesian`
- """
- assert isinstance(topo, Cartesian)
- return {v: v.discretize(topo) for v in self.variables}
+ def _generate(self):
+ nodes = []
+ for var in self._variables:
+ source_topos = self._source_topos[var]
+ target_topo = self._target_topo[var]
+ components = self._components[var]
+ kwds = self._kwds.copy()
+
+ if (self._name is not None):
+ name = self._name + '_{}'.format(var.name)
+ name += ''.join([DirectionLabels[i] for i in sorted(components)]).lower()
+ kwds['name'] = name
+
+ # if source topology is destination topology there is nothing to be done
+ if target_topo in source_topos:
+ continue
+
+ # else we find the most suitable source topology
+ node = Redistribute._select_redistribute(variable=var, source_topos=source_topos,
+ target_topo=target_topo, components=components, **kwds)
+ nodes.append(node)
+ return nodes
+
+ @staticmethod
+ def _select_redistribute(variable, source_topos, target_topo, components, **kwds):
+ assert target_topo not in source_topos
+ best_redis = None
+ for source_topo in source_topos:
+ redis = Redistribute._get_compatible_redistribute(variable, source_topo, target_topo, components,
+ **kwds)
+ best_redis = Redistribute._select_best_operator(best_redis, redis)
+
+ if (best_redis is None):
+ msg='Failed to find a suitable redistribute operator for variables {} '
+ msg+='between sources topologies and destination topology.\n'
+ msg=msg.format(variable.name)
+ for i,st in enumerate(source_topos):
+ msg+= '\n::CANDIDATE SOURCE TOPOLOGY {}::\n'.format(i)
+ msg+=str(st)
+ msg+='\n::DESTINATION TOPOLOGY::\n'+str(target_topo)
+ msg+='\n'
+
+ raise RuntimeError(msg)
+ return best_redis
+
+ @staticmethod
+ def _select_best_operator(lhs, rhs):
+ # select highest priority operator when there are more
+ # than one candidate source topology
+ if (lhs is None):
+ return rhs
+ if (rhs is None):
+ return lhs
+ check_instance(lhs, RedistributeOperator)
+ check_instance(rhs, RedistributeOperator)
+ lhs_priority = Redistribute.__redistribute_operators[lhs]
+ rhs_priority = Redistribute.__redistribute_operators[rhs]
+ if (lhs_priority<=rhs_priority):
+ return lhs
+ else:
+ return rhs
+
+ @staticmethod
+ def _get_compatible_redistribute(variable, source_topo, target_topo, components, **kwds):
+ # look from highest prority operator to smallest priority operators
+ # if nothing is found return None
+ for priority in sorted(Redistribute.__redistribute_operators.keys()):
+ cls = Redistribute.__redistribute_operators[priority]
+ if cls.can_redistribute(source_topo=source_topo, target_topo=target_topo):
+ return cls(variable=variable, source_topo=source_topo,
+ target_topo=target_topo, components=components, **kwds)
+ return None
diff --git a/hysop/operator/tests/test_advec_scales.py b/hysop/operator/tests/test_advec_scales.py
deleted file mode 100755
index c81900e7ec7a81599b1f5af9fb51a315a4c4110f..0000000000000000000000000000000000000000
--- a/hysop/operator/tests/test_advec_scales.py
+++ /dev/null
@@ -1,472 +0,0 @@
-"""
-Testing Scales advection operator.
-"""
-import numpy as np
-from hysop.methods_keys import Scales, TimeIntegrator, Interpolation,\
- Remesh, Support, Splitting
-from hysop.methods import RK2, L2_1, L4_2, M8Prime, Linear
-from hysop.domain.box import Box
-from hysop.fields.continuous import Field
-from hysop.operator.advection import Advection
-from hysop.problem.simulation import Simulation
-import hysop.tools.numpywrappers as npw
-
-from hysop.tools.parameters import Discretization
-d3d = Discretization([17, 17, 17])
-
-
-def test_nullVelocity_m4():
- """Basic test with random velocity. Using M4prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar')
- scal_ref = Field(domain=box, name='Scalar_ref')
- velo = Field(domain=box, name='Velocity',
- formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
- vectorize_formula=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M4'})
- advec_py = Advection(velo, scal_ref, discretization=d3d,
- method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: L2_1,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- topo = scal_d.topology
- assert (velo.norm(topo) == 0).all()
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
- print (np.max(np.abs(scal_ref_d.data[0] - scal_d.data[0])))
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0])
-
-
-def test_nullVelocity_vec_m4():
- """Basic test with random velocity and vector field. Using M4prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar', is_vector=True)
- scal_ref = Field(domain=box, name='Scalar_ref', is_vector=True)
- velo = Field(domain=box, name='Velocity',
- formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
- vectorize_formula=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M4'})
- advec_py = Advection(velo, scal_ref, discretization=d3d,
- method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: L2_1,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape))
- scal_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- scal_ref_d.data[1][...] = scal_d.data[1][...]
- scal_ref_d.data[2][...] = scal_d.data[2][...]
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0])
- assert np.allclose(scal_ref_d.data[1], scal_d.data[1])
- assert np.allclose(scal_ref_d.data[2], scal_d.data[2])
-
-
-def test_nullVelocity_m6():
- """Basic test with null velocity. Using M6prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar')
- velo = Field(domain=box, name='Velocity',
- formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
- vectorize_formula=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M6'}
- )
- advec.discretize()
- advec.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_d.data[0][...] = np.asarray(np.random.random(scal_d.data[0].shape))
- scal_init = npw.copy(scal_d.data[0])
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_init, scal_d.data[0])
-
-
-def test_nullVelocity_vec_m6():
- """Basic test with null velocity and vector field. Using M6prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar', is_vector=True)
- velo = Field(domain=box, name='Velocity',
- formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
- vectorize_formula=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M6'}
- )
- advec.discretize()
- advec.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape))
- scal_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape))
- scal_init0 = npw.copy(scal_d.data[0])
- scal_init1 = npw.copy(scal_d.data[1])
- scal_init2 = npw.copy(scal_d.data[2])
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_init0, scal_d.data[0])
- assert np.allclose(scal_init1, scal_d.data[1])
- assert np.allclose(scal_init2, scal_d.data[2])
-
-
-def test_nullVelocity_m8():
- """Basic test with random velocity. Using M4prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar')
- scal_ref = Field(domain=box, name='Scalar_ref')
- velo = Field(domain=box, name='Velocity',
- formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
- vectorize_formula=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M8'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d, method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: M8Prime,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
- topo = advec.discreteFields[velo].topology
- scal_d = scal.discreteFields[topo]
- scal_ref_d = scal_ref.discreteFields[topo]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_ref_d.data[0][...] = scal_d.data[0]
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0])
-
-
-def test_nullVelocity_vec_m8():
- """Basic test with random velocity and vector field. Using M4prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar', is_vector=True)
- scal_ref = Field(domain=box, name='Scalar_ref', is_vector=True)
- velo = Field(domain=box, name='Velocity',
- formula=lambda x, y, z, t: (0., 0., 0.), is_vector=True,
- vectorize_formula=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M8'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d, method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: M8Prime,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
- topo = scal_d.topology
- assert (velo.norm(topo) == 0).all()
- for i in xrange(box.dimension):
- scal_d.data[i][...] = \
- npw.asrealarray(np.random.random(scal_d.data[i].shape))
- scal_ref_d.data[i][...] = scal_d.data[i][...]
-
- advec.apply(Simulation(start=0., end=0.075, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.075, nb_iter=1))
-
- for i in xrange(box.dimension):
- assert np.allclose(scal_ref_d.data[i], scal_d.data[i])
-
-
-def _randomVelocity_m4():
- """Basic test with random velocity. Using M4prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar')
- scal_ref = Field(domain=box, name='Scalar_ref')
- velo = Field(domain=box, name='Velocity', is_vector=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M4'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d, method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: L2_1,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- velo_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[0])
- velo_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[1])
- velo_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[1])
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0])
-
-
-def _randomVelocity_vec_m4():
- """Basic test with random velocity vector Field. Using M4prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar', is_vector=True)
- scal_ref = Field(domain=box, name='Scalar_ref', is_vector=True)
- velo = Field(domain=box, name='Velocity', is_vector=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M4'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d, method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: L2_1,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape))
- scal_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- scal_ref_d.data[1][...] = scal_d.data[1][...]
- scal_ref_d.data[2][...] = scal_d.data[2][...]
- velo_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[0])
- velo_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape)) / (2. * scal_d.resolution[1])
- velo_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape)) / (2. * scal_d.resolution[1])
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0])
- assert np.allclose(scal_ref_d.data[1], scal_d.data[1])
- assert np.allclose(scal_ref_d.data[2], scal_d.data[2])
-
-
-def test_randomVelocity_m6():
- """Basic test with random velocity. Using M6prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar')
- scal_ref = Field(domain=box, name='Scalar_ref')
- velo = Field(domain=box, name='Velocity', is_vector=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M6'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d, method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: L4_2,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- velo_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[0])
- velo_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[1])
- velo_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[1])
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0])
-
-
-def test_randomVelocity_vec_m6():
- """Basic test with random velocity vector Field. Using M6prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar', is_vector=True)
- scal_ref = Field(domain=box, name='Scalar_ref', is_vector=True)
- velo = Field(domain=box, name='Velocity', is_vector=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M6'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d, method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: L4_2,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape))
- scal_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- scal_ref_d.data[1][...] = scal_d.data[1][...]
- scal_ref_d.data[2][...] = scal_d.data[2][...]
- velo_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[0])
- velo_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape)) / (2. * scal_d.resolution[1])
- velo_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape)) / (2. * scal_d.resolution[1])
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0])
- assert np.allclose(scal_ref_d.data[1], scal_d.data[1])
- assert np.allclose(scal_ref_d.data[2], scal_d.data[2])
-
-
-def test_randomVelocity_m8():
- """Basic test with random velocity. Using M8prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar')
- scal_ref = Field(domain=box, name='Scalar_ref')
- velo = Field(domain=box, name='Velocity', is_vector=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M8'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d,
- method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: M8Prime,
- Splitting: 'o2_FullHalf',
- Support: ''}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- velo_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[0])
- velo_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[1])
- velo_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[1])
-
- advec.apply(Simulation(start=0., end=0.1, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.1, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0], atol=1e-07)
-
-
-def test_randomVelocity_vec_m8():
- """Basic test with random velocity vector Field. Using M8prime"""
- box = Box(length=[1., 1., 1.], origin=[0., 0., 0.])
- scal = Field(domain=box, name='Scalar', is_vector=True)
- scal_ref = Field(domain=box, name='Scalar_ref', is_vector=True)
- velo = Field(domain=box, name='Velocity', is_vector=True)
- advec = Advection(velo, scal, discretization=d3d, method={Scales: 'p_M8'}
- )
- advec_py = Advection(velo, scal_ref, discretization=d3d,
- method={TimeIntegrator: RK2,
- Interpolation: Linear,
- Remesh: M8Prime,
- Support: '',
- Splitting: 'o2_FullHalf'}
- )
- advec.discretize()
- advec_py.discretize()
- advec.setup()
- advec_py.setup()
-
- scal_d = scal.discreteFields.values()[0]
- scal_ref_d = scal_ref.discreteFields.values()[0]
- velo_d = velo.discreteFields.values()[0]
-
- scal_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape))
- scal_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape))
- scal_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape))
- scal_ref_d.data[0][...] = scal_d.data[0][...]
- scal_ref_d.data[1][...] = scal_d.data[1][...]
- scal_ref_d.data[2][...] = scal_d.data[2][...]
- velo_d.data[0][...] = npw.asrealarray(
- np.random.random(scal_d.data[0].shape)) / (2. * scal_d.resolution[0])
- velo_d.data[1][...] = npw.asrealarray(
- np.random.random(scal_d.data[1].shape)) / (2. * scal_d.resolution[1])
- velo_d.data[2][...] = npw.asrealarray(
- np.random.random(scal_d.data[2].shape)) / (2. * scal_d.resolution[1])
-
- advec.apply(Simulation(start=0., end=0.01, nb_iter=1))
- advec_py.apply(Simulation(start=0., end=0.01, nb_iter=1))
-
- assert np.allclose(scal_ref_d.data[0], scal_d.data[0], atol=1e-07)
- assert np.allclose(scal_ref_d.data[1], scal_d.data[1], atol=1e-07)
- assert np.allclose(scal_ref_d.data[2], scal_d.data[2], atol=1e-07)
diff --git a/hysop/operator/tests/test_analytic.py b/hysop/operator/tests/test_analytic.py
index 6d9678e6a6fa8bc6521f946e1b3fdae01d488ad6..6aa85e0870d15239d384a0a9781d67d475441d9c 100755
--- a/hysop/operator/tests/test_analytic.py
+++ b/hysop/operator/tests/test_analytic.py
@@ -4,12 +4,12 @@ from numpy import allclose
from hysop.domain.box import Box
from hysop.fields.continuous import Field
from hysop.operator.analytic import Analytic
-from hysop.problem.simulation import Simulation
+from hysop import Simulation, Cartesian
from hysop.tools.parameters import Discretization
from hysop.fields.tests.func_for_tests import func_scal_1, func_scal_2, \
func_vec_1, func_vec_2, func_vec_3, func_vec_4, func_vec_5, func_vec_6
-d3D = Discretization([33, 33, 33])
-d2D = Discretization([33, 33])
+d3d = Discretization([17, 17, 17])
+d2d = Discretization([17, 17])
L2D = [1., 1.]
origin2D = [0., 0.]
nbc = 4
@@ -21,18 +21,20 @@ def test_analytical_op_1():
box = Box()
caf = Field(box, formula=func_scal_1, name='caf')
caf2 = Field(box, name='caf2', formula=func_scal_2, vectorize_formula=True)
- op = Analytic(variables={caf: d3D})
- op2 = Analytic(variables={caf2: d3D})
+ topo = Cartesian(box, d3d)
+ op = Analytic(variables={caf: topo})
+ op2 = Analytic(variables={caf2: topo})
+ op.initialize()
+ op2.initialize()
op.discretize()
op2.discretize()
op.setup()
op2.setup()
- topo = op.discreteFields[caf].topology
coords = topo.mesh.coords
ref = Field(box, name='ref')
refd = ref.discretize(topo)
- cafd = caf.discreteFields[topo]
- cafd2 = caf2.discreteFields[topo]
+ cafd = caf.discrete_fields[topo]
+ cafd2 = caf2.discrete_fields[topo]
ids = id(cafd.data[0])
ids2 = id(cafd2.data[0])
op.apply(simu)
@@ -50,18 +52,20 @@ def test_analytical_op_3():
caf = Field(box, name='caf', formula=func_vec_1, is_vector=True)
caf2 = Field(box, name='caf', formula=func_vec_2,
vectorize_formula=True, is_vector=True)
- op = Analytic(variables={caf: d3D})
- op2 = Analytic(variables={caf2: d3D})
+ topo = Cartesian(box, d3d)
+ op = Analytic(variables={caf: topo})
+ op2 = Analytic(variables={caf2: topo})
+ op.initialize()
+ op2.initialize()
op.discretize()
op2.discretize()
op.setup()
op2.setup()
- topo = op.discreteFields[caf].topology
coords = topo.mesh.coords
ref = Field(box, is_vector=True, name='ref')
refd = ref.discretize(topo)
- cafd = caf.discreteFields[topo]
- cafd2 = caf2.discreteFields[topo]
+ cafd = caf.discrete_fields[topo]
+ cafd2 = caf2.discrete_fields[topo]
ids = [0, ] * 3
ids2 = [0, ] * 3
for i in xrange(3):
@@ -83,18 +87,20 @@ def test_analytical_op_4():
caf = Field(box, formula=func_vec_3, is_vector=True, name='caf')
caf2 = Field(box, formula=func_vec_4, vectorize_formula=True,
name='caf2', is_vector=True)
- op = Analytic(variables={caf: d3D})
- op2 = Analytic(variables={caf2: d3D})
+ topo = Cartesian(box, d3d)
+ op = Analytic(variables={caf: topo})
+ op2 = Analytic(variables={caf2: topo})
+ op.initialize()
+ op2.initialize()
op.discretize()
op2.discretize()
op.setup()
op2.setup()
- topo = op.discreteFields[caf].topology
coords = topo.mesh.coords
ref = Field(box, name='ref', is_vector=True)
refd = ref.discretize(topo)
- cafd = caf.discreteFields[topo]
- cafd2 = caf2.discreteFields[topo]
+ cafd = caf.discrete_fields[topo]
+ cafd2 = caf2.discrete_fields[topo]
ids = [0, ] * 3
ids2 = [0, ] * 3
for i in xrange(3):
@@ -117,14 +123,15 @@ def test_analytical_op_4():
def test_analytical_op_5():
box = Box()
caf = Field(box, formula=func_vec_5, nb_components=nbc, name='caf')
- op = Analytic(variables={caf: d3D})
+ topo = Cartesian(box, d3d)
+ op = Analytic(variables={caf: topo})
+ op.initialize()
op.discretize()
op.setup()
- topo = op.discreteFields[caf].topology
coords = topo.mesh.coords
ref = Field(box, nb_components=nbc, name='ref')
refd = ref.discretize(topo)
- cafd = caf.discreteFields[topo]
+ cafd = caf.discrete_fields[topo]
ids = [0, ] * nbc
for i in xrange(nbc):
ids[i] = id(cafd.data[i])
@@ -140,15 +147,16 @@ def test_analytical_op_5():
# Non-Vectorized formula for a nbc components field in 2D, with extra-args
def test_analytical_op_6():
box = Box(dimension=2, length=L2D, origin=origin2D)
+ topo = Cartesian(box, d2d)
caf = Field(box, formula=func_vec_6, nb_components=nbc, name='caf')
- op = Analytic(variables={caf: d2D})
+ op = Analytic(variables={caf: topo})
+ op.initialize()
op.discretize()
op.setup()
- topo = op.discreteFields[caf].topology
coords = topo.mesh.coords
ref = Field(box, nb_components=nbc, name='ref')
refd = ref.discretize(topo)
- cafd = caf.discreteFields[topo]
+ cafd = caf.discrete_fields[topo]
ids = [0, ] * nbc
for i in xrange(nbc):
ids[i] = id(cafd.data[i])
@@ -157,6 +165,6 @@ def test_analytical_op_6():
op.apply(simu)
refd.data = func_vec_6(refd.data, *(coords + (simu.time, theta)))
for i in xrange(caf.nb_components):
- assert allclose(cafd[i], refd.data[i])
assert id(cafd.data[i]) == ids[i]
+ assert allclose(cafd[i], refd.data[i])
diff --git a/hysop/operator/tests/test_diffusion.py b/hysop/operator/tests/test_diffusion.py
index 6473a8b5d9ba226f8e7ba1717ff72fa2cf2335a6..64205d83abd93892b2c734d9efe7bf2c51c4e283 100755
--- a/hysop/operator/tests/test_diffusion.py
+++ b/hysop/operator/tests/test_diffusion.py
@@ -1,86 +1,64 @@
-# -*- coding: utf-8 -*-
+"""Tests for diffusion and curl_diffusion operators.
+"""
+from hysop import Simulation, Box, Discretization, Field, testsenv, Cartesian
+from hysop.deps import np, math
+from hysop.tools.numpywrappers import npw
+from hysop.operators import Diffusion
+from hysop.fields.tests.func_for_tests import v_TG, w_TG
+from hysop.backend.host.fortran.operator.diffusion import DiffusionFFTW as Diffusion
-import hysop as pp
-from hysop.operator.diffusion import Diffusion
-from hysop.problem.simulation import Simulation
-from hysop.tools.parameters import Discretization
-import numpy as np
-import hysop.tools.numpywrappers as npw
-import math
pi = math.pi
sin = np.sin
cos = np.cos
-## Physical Domain description
+
+# Physical Domain description
dim = 3
LL = 2 * pi * npw.ones((dim))
cc = 2 * pi / LL
-d3D = Discretization([33, 33, 33])
-d2D = Discretization([33, 33])
-
-
-def computeVort(res, x, y, z, t):
- res[0][...] = sin(x * cc[0]) * sin(y * cc[1]) * cos(z * cc[2])
- res[1][...] = cos(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])
- res[2][...] = cos(x * cc[0]) * cos(y * cc[1]) * sin(z * cc[2])
- return res
+d2d = Discretization([33, 33])
+d3d = Discretization([33, 33, 33])
def computeVort2D(res, x, y, t):
- # todo ...
res[0][...] = 4 * pi ** 2 * (cos(x * cc[0]) * sin(y * cc[1])) * \
(1. / LL[0] ** 2 + 1. / LL[1] ** 2)
return res
-
-def test_Diffusion3D():
- dom = pp.Box(length=LL)
-
- # Fields
- vorticity = pp.Field(domain=dom, formula=computeVort,
+@testsenv.fftw_failed
+def test_diffusion_3d():
+ """Vector field diffusion, 3d domain"""
+ dom = Box(length=LL)
+ topo = Cartesian(dom, d3d)
+ vorticity = Field(domain=dom, formula=w_TG,
name='Vorticity', is_vector=True)
-
- # Definition of the Poisson operator
- diff = Diffusion(viscosity=0.3, vorticity=vorticity, discretization=d3D)
+ diff = Diffusion(viscosity=0.3, input_field=vorticity, output_field=vorticity,
+ variables={vorticity: topo})
+ diff.initialize()
diff.discretize()
diff.setup()
- topo = diff.discreteFields[vorticity].topology
- simu = Simulation(nb_iter=10)
+ simu = Simulation(end=0.1, time_step=0.01)
vorticity.initialize(topo=topo)
diff.apply(simu)
- diff.finalize()
-
-
-def test_Diffusion3D_2():
- dom = pp.Box(length=LL)
-
- # Fields
- vorticity = pp.Field(domain=dom, formula=computeVort,
- name='Vorticity', is_vector=True)
-
- # Definition of the Poisson operator
- diff = Diffusion(viscosity=0.3, variables={vorticity: d3D})
+ diff.finalize(clean_fftw_solver=True)
+
+
+@testsenv.fftw_failed
+def test_diffusion_2d():
+ """Vector field diffusion 2d domain"""
+ dom = Box(length=LL[:2])
+ topo = Cartesian(dom, d2d)
+ vorticity = Field(domain=dom, formula=computeVort2D, name='Vorticity')
+ diff = Diffusion(viscosity=0.3, input_field=vorticity, output_field=vorticity,
+ variables={vorticity: topo})
+ diff.initialize()
diff.discretize()
diff.setup()
- topo = diff.discreteFields[vorticity].topology
- simu = Simulation(nb_iter=10)
+ simu = Simulation(end=0.1, time_step=0.01)
vorticity.initialize(topo=topo)
diff.apply(simu)
- diff.finalize()
-
-
-def test_Diffusion2D():
- dom = pp.Box(length=LL[:2])
-
- # Fields
- vorticity = pp.Field(domain=dom, formula=computeVort2D, name='Vorticity')
+ diff.finalize(clean_fftw_solver=True)
- # Definition of the Poisson operator
- diff = Diffusion(viscosity=0.3, vorticity=vorticity, discretization=d2D)
- diff.discretize()
- diff.setup()
- topo = diff.discreteFields[vorticity].topology
- simu = Simulation(nb_iter=10)
- vorticity.initialize(topo=topo)
- diff.apply(simu)
- diff.finalize()
+if __name__ == '__main__':
+ test_diffusion_2d()
+ test_diffusion_3d()
diff --git a/hysop/operator/tests/test_hdf5_io.py b/hysop/operator/tests/test_hdf5_io.py
index 199ee817bed96cbe2a83fa079e844da36a09ad12..7f080128dbc2b349c7467d7a0650e513216a6a98 100755
--- a/hysop/operator/tests/test_hdf5_io.py
+++ b/hysop/operator/tests/test_hdf5_io.py
@@ -5,11 +5,11 @@
from hysop import Box, Field
import numpy as np
import os
-from hysop.problem.simulation import Simulation
+from hysop import Simulation
from hysop.tools.parameters import Discretization
from hysop.operator.hdf_io import HDF_Writer, HDF_Reader
from hysop.tools.io_utils import IO, IOParams
-from hysop.mpi import main_rank, main_size
+from hysop.core.mpi import main_rank, main_size
from hysop.domain.subsets import SubBox
from hysop.testsenv import postclean
@@ -71,6 +71,7 @@ def test_write_read_scalar_3D():
iop = IOParams(filename, fileformat=IO.HDF5)
op = HDF_Writer(variables={scalRef: topo}, io_params=iop)
simu = Simulation(nb_iter=10)
+ op.initialize()
op.discretize()
op.setup()
simu.initialize()
@@ -91,9 +92,10 @@ def test_write_read_scalar_3D():
# Reader
iop_read = IOParams(working_dir + '/testIO_scal_00002.h5',
fileformat=IO.HDF5)
- reader = HDF_Reader(variables=[scal3D], discretization=topo,
+ reader = HDF_Reader(variables={scal3D:topo},
io_params=iop_read,
var_names={scal3D: 'ScalRef3D_' + str(topo.get_id())})
+ reader.initialize()
reader.discretize()
reader.setup()
sc3d = scal3D.discretize(topo)
@@ -119,6 +121,7 @@ def test_write_read_scalar_3D_defaults():
# names and location
op = HDF_Writer(variables={scalRef: topo})
simu = Simulation(nb_iter=3)
+ op.initialize()
op.discretize()
op.setup()
scal3D.discretize(topo=topo)
@@ -148,6 +151,7 @@ def test_write_read_scalar_3D_defaults():
# names and location, with a given iteration number.
reader = HDF_Reader(variables={scalRef: topo},
restart=simu.current_iteration - 1)
+ reader.initialize()
reader.discretize()
reader.setup()
for d in xrange(scal3D.nb_components):
@@ -168,6 +172,7 @@ def test_write_read_vectors_3D_defaults():
# names and location
op = HDF_Writer(variables={velo: topo, vorti: topo})
simu = Simulation(nb_iter=3)
+ op.initialize()
op.discretize()
op.setup()
velo.initialize(simu.time, topo=topo)
@@ -180,7 +185,7 @@ def test_write_read_vectors_3D_defaults():
op.finalize()
filename = ''
names = []
- for var in op.input:
+ for var in op.input_vars.keys():
names.append(var.name)
names.sort()
for nn in names:
@@ -216,6 +221,7 @@ def test_write_read_vectors_3D_defaults():
reader = HDF_Reader(variables={velo: topo, vorti: topo},
io_params=IOParams(filename),
restart=simu.current_iteration - 1)
+ reader.initialize()
reader.discretize()
reader.setup()
for d in xrange(v3d.nb_components):
@@ -243,6 +249,7 @@ def test_write_read_vectors_3D():
op = HDF_Writer(variables={velo: topo, vorti: topo},
var_names={velo: 'io_1', vorti: 'io_2'}, io_params=iop)
simu = Simulation(nb_iter=3)
+ op.initialize()
op.discretize()
op.setup()
@@ -255,10 +262,6 @@ def test_write_read_vectors_3D():
op.finalize()
- # filename = ''
- # for v in op.input:
- # filename += v.name
- # filename += '_'
fullpath = iop.filename
assert os.path.exists(fullpath + '.xmf')
assert os.path.exists(fullpath + '_00000.h5')
@@ -277,6 +280,7 @@ def test_write_read_vectors_3D():
reader = HDF_Reader(variables={buff1: topo, buff2: topo},
io_params=iop_read,
var_names={buff1: 'io_2', buff2: 'io_1'})
+ reader.initialize()
reader.discretize()
reader.setup()
reader.apply()
@@ -302,6 +306,7 @@ def test_write_read_subset_1():
op = HDF_Writer(variables={velo: topo}, var_names={velo: 'io_1'},
subset=mybox)
simu = Simulation(nb_iter=3)
+ op.initialize()
op.discretize()
op.setup()
velo.initialize(simu.time, topo=topo)
@@ -312,7 +317,7 @@ def test_write_read_subset_1():
op.finalize()
filename = ''
- for v in op.input:
+ for v in op.input_vars.keys():
filename += v.name
filename += '_'
filename = filename[:-1]
@@ -333,6 +338,7 @@ def test_write_read_subset_1():
reader = HDF_Reader(variables={buff1: topo},
io_params=iop,
var_names={buff1: 'io_1'}, subset=mybox)
+ reader.initialize()
reader.discretize()
reader.setup()
reader.apply()
@@ -357,6 +363,7 @@ def test_write_read_subset_2():
op = HDF_Writer(variables={velo: topo}, var_names={velo: 'io_1'},
subset=mybox)
simu = Simulation(nb_iter=3)
+ op.initialize()
op.discretize()
op.setup()
velo.initialize(simu.time, topo=topo)
@@ -367,7 +374,7 @@ def test_write_read_subset_2():
op.finalize()
filename = ''
- for v in op.input:
+ for v in op.input_vars.keys():
filename += v.name
filename += '_'
filename = filename[:-1]
@@ -388,6 +395,7 @@ def test_write_read_subset_2():
reader = HDF_Reader(variables={buff1: topo},
io_params=iop,
var_names={buff1: 'io_1'}, subset=mybox)
+ reader.initialize()
reader.discretize()
reader.setup()
reader.apply()
diff --git a/hysop/operator/tests/test_poisson.py b/hysop/operator/tests/test_poisson.py
old mode 100755
new mode 100644
index 97eb83cf7cf5dfb6f21b3ba2abe123196e1697a5..5b25b0762ae93d68007b37c04d0b1b8f026c7713
--- a/hysop/operator/tests/test_poisson.py
+++ b/hysop/operator/tests/test_poisson.py
@@ -1,54 +1,51 @@
# -*- coding: utf-8 -*-
import hysop as pp
-from hysop.operator.poisson import Poisson
+from hysop.constants import FieldProjection
+from hysop.operator.poisson import PoissonFFTW
from hysop.operator.analytic import Analytic
-from hysop.operator.reprojection import Reprojection
-from hysop.problem.simulation import Simulation
+from hysop import Simulation
from hysop.tools.parameters import Discretization
-from hysop.methods_keys import SpaceDiscretisation, \
- GhostUpdate, Formulation
import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
import math
from hysop.domain.subsets import SubBox
-from hysop import testsenv
+from hysop import testsenv, Cartesian
-
-pi = math.pi
+pi = math.pi
sin = np.sin
cos = np.cos
## Physical Domain description
dim = 3
LL = 2 * pi * npw.ones((dim))
-# formula to compute initial vorticity field
-coeff = 4 * pi ** 2 * (LL[1] ** 2 * LL[2] ** 2 + LL[0] ** 2 * LL[2] ** 2 +
- LL[0] ** 2 * LL[1] ** 2) / (LL[0] ** 2 * LL[1] ** 2
- * LL[2] ** 2)
+
cc = 2 * pi / LL
-d3D = Discretization([33, 257, 257])
-d2D = Discretization([33, 33])
+d3d = Discretization([33, 257, 257])
+d2d = Discretization([33, 33])
uinf = 1.0
+# 2D reference and vorticity fields
+def compute_ref2D(res, x, y, t):
+ res[0][...] = 2. * pi / LL[1] * (cos(x * cc[0]) * cos(y * cc[1]))
+ res[1][...] = 2. * pi / LL[0] * (sin(x * cc[0]) * sin(y * cc[1]))
+ return res
+def compute_vort2D(res, x, y, t):
+ res[0][...] = 4 * pi ** 2 * (cos(x * cc[0]) * sin(y * cc[1])) * \
+ (1. / LL[0] ** 2 + 1. / LL[1] ** 2)
+ return res
-def computeVort(res, x, y, z, t):
+# 3D reference and vorticity fields
+coeff = 4 * pi ** 2 * (LL[1] ** 2 * LL[2] ** 2 + LL[0] ** 2 * LL[2] ** 2 +
+ LL[0] ** 2 * LL[1] ** 2) / (LL[0] ** 2 * LL[1] ** 2
+ * LL[2] ** 2)
+def compute_vort3D(res, x, y, z, t):
res[0][...] = coeff * sin(x * cc[0]) * sin(y * cc[1]) * cos(z * cc[2])
res[1][...] = coeff * cos(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])
res[2][...] = coeff * cos(x * cc[0]) * cos(y * cc[1]) * sin(z * cc[2])
return res
-def computePressure(res, x, y, z, t):
- res[0][...] = -3.0 * sin(x * cc[0]) * cos(y * cc[1]) * cos(z * cc[2])
- return res
-
-def computeRefPressure(res, x, y, z, t):
- res[0][...] = sin(x * cc[0]) * cos(y * cc[1]) * cos(z * cc[2])
- return res
-
-
-# ref. field
-def computeRef(res, x, y, z, t):
+def compute_ref3D(res, x, y, z, t):
res[0][...] = -2. * pi / LL[1] * \
(cos(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
- 2. * pi / LL[2] * (cos(x * cc[0]) * sin(y * cc[1]) * cos(z * cc[2]))
@@ -64,125 +61,31 @@ def computeRef(res, x, y, z, t):
return res
-# ref. field
-def computeRef_with_correction(res, x, y, z, t):
- res[0][...] = -2. * pi / LL[1] * \
- (cos(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
- - 2. * pi / LL[2] * (cos(x * cc[0]) * sin(y * cc[1]) * cos(z * cc[2]))\
- + uinf
-
- res[1][...] = -2. * pi / LL[2] * \
- (sin(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
- + 2. * pi / LL[0] * (sin(x * cc[0]) * cos(y * cc[1]) * sin(z * cc[2]))
-
- res[2][...] = -2. * pi / LL[0] * \
- (sin(x * cc[0]) * sin(y * cc[1]) * sin(z * cc[2])) \
- - 2. * pi / LL[1] * (sin(x * cc[0]) * cos(y * cc[1]) * cos(z * cc[2]))
-
- return res
-
-
-def computeVort2D(res, x, y, t):
- # todo ...
- res[0][...] = 4 * pi ** 2 * (cos(x * cc[0]) * sin(y * cc[1])) * \
- (1. / LL[0] ** 2 + 1. / LL[1] ** 2)
- return res
-
-
-# ref. field
-def computeRef2D(res, x, y, t):
- res[0][...] = 2. * pi / LL[1] * (cos(x * cc[0]) * cos(y * cc[1]))
- res[1][...] = 2. * pi / LL[0] * (sin(x * cc[0]) * sin(y * cc[1]))
-
- return res
-
-@testsenv.fftw_failed
-def test_Poisson_Pressure_3D():
- dom = pp.Box(length=LL)
-
- # Fields
- ref = pp.Field(domain=dom, name='Ref')
- pressure = pp.Field(domain=dom, formula=computePressure, name='Pressure')
-
- # Definition of the Poisson operator
- poisson = Poisson(pressure, pressure, discretization=d3D,
- method={SpaceDiscretisation: 'fftw',
- GhostUpdate: True,
- Formulation: 'pressure'})
-
- poisson.discretize()
- poisson.setup()
- topo = poisson.discreteFields[pressure].topology
- # Analytic operator to compute the reference field
- refOp = Analytic(variables={ref: topo}, formula=computeRefPressure)
- simu = Simulation(nb_iter=10)
- refOp.discretize()
- refOp.setup()
- pressure.initialize(topo=topo)
- poisson.apply(simu)
- refOp.apply(simu)
- assert np.allclose(ref.norm(topo), pressure.norm(topo))
- refD = ref.discretize(topo)
- prsD = pressure.discretize(topo)
- assert np.allclose(prsD[0], refD[0])
- poisson.finalize()
-
-
-@testsenv.fftw_failed
-def test_Poisson3D():
- dom = pp.Box(length=LL)
-
- # Fields
- velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
- vorticity = pp.Field(domain=dom, formula=computeVort,
- name='Vorticity', is_vector=True)
-
- # Definition of the Poisson operator
- poisson = Poisson(velocity, vorticity, discretization=d3D)
-
- poisson.discretize()
- poisson.setup()
- topo = poisson.discreteFields[vorticity].topology
- # Analytic operator to compute the reference field
- ref = pp.Field(domain=dom, name='reference', is_vector=True)
- refOp = Analytic(variables={ref: topo}, formula=computeRef)
- simu = Simulation(nb_iter=10)
- refOp.discretize()
- refOp.setup()
- vorticity.initialize(topo=topo)
- poisson.apply(simu)
- refOp.apply(simu)
- assert np.allclose(ref.norm(topo), velocity.norm(topo))
- refD = ref.discretize(topo)
- vd = velocity.discretize(topo)
- for i in range(dom.dimension):
- assert np.allclose(vd[i], refD[i])
- poisson.finalize()
-
-
@testsenv.fftw_failed
def test_Poisson2D():
dom = pp.Box(length=[2. * pi, 2. * pi], origin=[0., 0.])
+ topo = Cartesian(dom, d2d)
# Fields
- velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
- vorticity = pp.Field(domain=dom, formula=computeVort2D, name='Vorticity')
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=compute_vort2D, name='Vorticity')
- # Definition of the Poisson operator
- poisson = Poisson(velocity, vorticity, discretization=d2D)
+ # Definition of the Poisson operator
+ poisson = PoissonFFTW(velocity, vorticity, topology=topo)
+ poisson.initialize()
poisson.discretize()
poisson.setup()
- topo = poisson.discreteFields[vorticity].topology
# Analytic operator to compute the reference field
ref = pp.Field(domain=dom, name='reference', is_vector=True)
- refOp = Analytic(variables={ref: topo}, formula=computeRef2D)
+ ref_op = Analytic(variables={ref: topo}, formula=compute_ref2D)
simu = Simulation(nb_iter=10)
- refOp.discretize()
- refOp.setup()
+ ref_op.initialize()
+ ref_op.discretize()
+ ref_op.setup()
vorticity.initialize(topo=topo)
poisson.apply(simu)
- refOp.apply(simu)
+ ref_op.apply(simu)
assert np.allclose(ref.norm(topo), velocity.norm(topo))
refD = ref.discretize(topo)
@@ -191,118 +94,81 @@ def test_Poisson2D():
assert np.allclose(ref.norm(topo), velocity.norm(topo))
for i in range(dom.dimension):
assert np.allclose(vd[i], refD[i])
- poisson.finalize()
-
+ poisson.finalize(clean_fftw_solver=True)
@testsenv.fftw_failed
-def test_Poisson3D_correction():
+def test_Poisson3D():
dom = pp.Box(length=LL)
+ topo = Cartesian(dom, d3d)
# Fields
- velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
- vorticity = pp.Field(domain=dom, formula=computeVort,
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=compute_vort3D,
name='Vorticity', is_vector=True)
# Definition of the Poisson operator
- ref_rate = npw.zeros(3)
- ref_rate[0] = uinf * LL[1] * LL[2]
- rate = pp.VariableParameter(data=ref_rate)
- poisson = Poisson(velocity, vorticity, discretization=d3D, flowrate=rate)
-
+ poisson = PoissonFFTW(velocity, vorticity, topology=topo)
+ poisson.initialize()
poisson.discretize()
poisson.setup()
- topo = poisson.discreteFields[vorticity].topology
- # Analytic operator to compute the reference field
- ref = pp.Field(domain=dom, name='reference', is_vector=True)
- refOp = Analytic(variables={ref: topo}, formula=computeRef_with_correction)
- simu = Simulation(nb_iter=10)
- refOp.discretize()
- refOp.setup()
- vorticity.initialize(topo=topo)
-
- poisson.apply(simu)
- refOp.apply(simu)
- refD = ref.discretize(topo)
- vd = velocity.discretize(topo)
- surf = SubBox(parent=dom, origin=dom.origin,
- length=[0., LL[1], LL[2]])
- surf.discretize(topo)
- assert np.allclose(ref.norm(topo), velocity.norm(topo))
- assert np.allclose(ref.norm(topo), velocity.norm(topo))
- for i in range(dom.dimension):
- assert np.allclose(vd[i], refD[i])
- poisson.finalize()
-
-
-@testsenv.fftw_failed
-def test_Poisson3D_projection_1():
- dom = pp.Box(length=LL)
- # Fields
- velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
- vorticity = pp.Field(domain=dom, formula=computeVort,
- name='Vorticity', is_vector=True)
-
- # Definition of the Poisson operator
- poisson = Poisson(velocity, vorticity, discretization=d3D, projection=4)
-
- poisson.discretize()
- poisson.setup()
- topo = poisson.discreteFields[vorticity].topology
# Analytic operator to compute the reference field
ref = pp.Field(domain=dom, name='reference', is_vector=True)
- refOp = Analytic(variables={ref: topo}, formula=computeRef)
+ ref_op = Analytic(variables={ref: topo}, formula=compute_ref3D)
simu = Simulation(nb_iter=10)
- refOp.discretize()
- refOp.setup()
+ ref_op.initialize()
+ ref_op.discretize()
+ ref_op.setup()
vorticity.initialize(topo=topo)
poisson.apply(simu)
- refOp.apply(simu)
+ ref_op.apply(simu)
assert np.allclose(ref.norm(topo), velocity.norm(topo))
refD = ref.discretize(topo)
vd = velocity.discretize(topo)
-
- assert np.allclose(ref.norm(topo), velocity.norm(topo))
for i in range(dom.dimension):
assert np.allclose(vd[i], refD[i])
-
- poisson.finalize()
-
+ poisson.finalize(clean_fftw_solver=True)
@testsenv.fftw_failed
-def test_Poisson3D_projection_2():
+def test_Poisson3D_projection():
+ #/!\ projected values are not tested, only execution flow
dom = pp.Box(length=LL)
+ topo = Cartesian(dom, d3d)
# Fields
- velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
- vorticity = pp.Field(domain=dom, formula=computeVort,
+ velocity = pp.Field(domain=dom, is_vector=True, name='Velocity')
+ vorticity = pp.Field(domain=dom, formula=compute_vort3D,
name='Vorticity', is_vector=True)
- d3dG = Discretization([33, 33, 33], [2, 2, 2])
- # Definition of the Poisson operator
- proj = Reprojection(vorticity, threshold=0.05, frequency=4,
- discretization=d3dG, io_params=True)
-
- poisson = Poisson(velocity, vorticity, discretization=d3D,
- projection=proj)
- proj.discretize()
- poisson.discretize()
- poisson.setup()
- proj.setup()
- topo = poisson.discreteFields[vorticity].topology
+
# Analytic operator to compute the reference field
ref = pp.Field(domain=dom, name='reference', is_vector=True)
- refOp = Analytic(variables={ref: topo}, formula=computeRef)
+ ref_op = Analytic(variables={ref: topo}, formula=compute_ref3D)
simu = Simulation(nb_iter=10)
- refOp.discretize()
- refOp.setup()
- vorticity.initialize(topo=topo)
- poisson.apply(simu)
- refOp.apply(simu)
- assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ ref_op.initialize()
+ ref_op.discretize()
+ ref_op.setup()
+ ref_op.apply(simu)
refD = ref.discretize(topo)
- vd = velocity.discretize(topo)
- assert np.allclose(ref.norm(topo), velocity.norm(topo))
- for i in range(dom.dimension):
- assert np.allclose(vd[i], refD[i])
- poisson.finalize()
+ # Definition of the Poisson operator
+ for projection in [FieldProjection.EVERY_STEP, 1]:
+ poisson = PoissonFFTW(velocity, vorticity, topology=topo,
+ method={FieldProjection: projection})
+ poisson.initialize()
+ poisson.discretize()
+ poisson.setup()
+
+ vorticity.initialize(topo=topo)
+ poisson.apply(simu)
+
+ assert np.allclose(ref.norm(topo), velocity.norm(topo))
+ vd = velocity.discretize(topo)
+ for i in range(dom.dimension):
+ assert np.allclose(vd[i], refD[i])
+ poisson.finalize(clean_fftw_solver=True)
+
+
+if __name__=='__main__':
+ test_Poisson2D()
+ test_Poisson3D()
+ test_Poisson3D_projection()
diff --git a/hysop/operators.py b/hysop/operators.py
index 9dfb7a2ebdacc4e8c8f664cf85540036ed9c2753..d81e53f29b43156379185c7fca46f6819419cdaa 100644
--- a/hysop/operators.py
+++ b/hysop/operators.py
@@ -1,29 +1,14 @@
-"""Shortcuts for operators import
+"""
+Shortcuts for operators import
Allows things like:
-
-from hysop.operators import Advection
+from hysop.operators import DirectionalAdvection
"""
-import hysop.operator.stretching
-import hysop.operator.differential
-import hysop.operator.analytic
-import hysop.operator.penalization
-import hysop.operator.drag_and_lift
-import hysop.operator.hdf_io
-import hysop.operator.poisson
-import hysop.operator.advection
-import hysop.operator.energy_enstrophy
-Stretching = hysop.operator.stretching.Stretching
-Curl = hysop.operator.differential.Curl
-Grad = hysop.operator.differential.Grad
-DivAdvection = hysop.operator.differential.DivAdvection
-Analytic = hysop.operator.analytic.Analytic
-Penalization = hysop.operator.penalization.Penalization
-PenalizeVorticity = hysop.operator.penalization.PenalizeVorticity
-MomentumForces = hysop.operator.drag_and_lift.MomentumForces
-NocaForces = hysop.operator.drag_and_lift.NocaForces
-HDF_Reader = hysop.operator.hdf_io.HDF_Reader
-HDF_Writer = hysop.operator.hdf_io.HDF_Writer
-Poisson = hysop.operator.poisson.Poisson
-Advection = hysop.operator.advection.Advection
-EnergyEnstrophy = hysop.operator.energy_enstrophy.EnergyEnstrophy
+
+from hysop.operator.poisson import Poisson
+from hysop.operator.diffusion import Diffusion
+from hysop.operator.redistribute import Redistribute
+from hysop.operator.analytic import Analytic
+from hysop.operator.hdf_io import HDF_Writer, HDF_Reader
+from hysop.operator.directional.advection_dir import DirectionalAdvection
+from hysop.operator.directional.stretching_dir import DirectionalStretching
diff --git a/hysop/problem.py b/hysop/problem.py
new file mode 100644
index 0000000000000000000000000000000000000000..745b13316327134d048bc1c9fd8ed5c2f27cc889
--- /dev/null
+++ b/hysop/problem.py
@@ -0,0 +1,43 @@
+
+from hysop import vprint
+from hysop.tools.decorators import debug
+from hysop.core.graph.computational_graph import ComputationalGraph
+
+class Problem(ComputationalGraph):
+
+ def __init__(self, name=None, method=None):
+ super(Problem,self).__init__(name=name, method=method)
+
+ @debug
+ def insert(self, *ops):
+ self.push_nodes(*ops)
+
+ @debug
+ def build(self):
+ vprint('\nInitializing problem...')
+ self.initialize(outputs_are_inputs=True, topgraph_method=None)
+ vprint('\nDiscretizing problem...')
+ self.discretize()
+ vprint('\nGetting work properties...')
+ work = self.get_work_properties()
+ vprint('\nAllocating work...')
+ work.allocate()
+ vprint('\nSetting up problem...')
+ self.setup(work)
+
+ @debug
+ def solve(self, simu, **kargs):
+ vprint('\nSolving problem...')
+ simu.initialize()
+ while not simu.is_over:
+ vprint()
+ simu.print_state()
+ self.apply(simulation=simu, **kargs)
+ simu.advance()
+ simu.finalize()
+
+ @debug
+ def finalize(self):
+ vprint('\nFinalizing problem...')
+ super(Problem,self).finalize()
+
diff --git a/hysop/f2py/scales2py.f90 b/hysop/scales_f/scales2py.f90
similarity index 83%
rename from hysop/f2py/scales2py.f90
rename to hysop/scales_f/scales2py.f90
index c021618b45a1f723b4ea2176bf7e22036df5956b..165c071c14b68ab7be6a0e20576d73bd5d72524f 100755
--- a/hysop/f2py/scales2py.f90
+++ b/hysop/scales_f/scales2py.f90
@@ -6,8 +6,7 @@ use advec, only : advec_init,advec_step,advec_step_Inter_basic,advec_step_Inter_
use advec_vect, only : advec_step_Vect,advec_step_Inter_basic_Vect
use interpolation_velo, only : interpol_init
use mpi
-use hysopparam
-
+use precision
implicit none
@@ -23,14 +22,14 @@ contains
subroutine init_advection_solver(ncells,lengths,topodims,main_comm,datashape,offset,dim,order,dim_split)
integer, intent(in) :: dim
integer, dimension(dim),intent(in) :: ncells
- real(pk),dimension(dim), intent(in) :: lengths
+ real(wp),dimension(dim), intent(in) :: lengths
integer, dimension(dim), intent(in) :: topodims
integer, intent(in) :: main_comm
- integer(ik), dimension(dim), intent(out) :: datashape
- integer(ik), dimension(dim), intent(out) :: offset
+ integer(ip), dimension(dim), intent(out) :: datashape
+ integer(ip), dimension(dim), intent(out) :: offset
character(len=*), optional, intent(in) :: order, dim_split
- !! real(pk), optional, intent(out) :: stab_coeff
- real(pk) :: stab_coeff
+ !! real(wp), optional, intent(out) :: stab_coeff
+ real(wp) :: stab_coeff
!f2py integer optional , depend(ncells) :: dim=len(ncells)
!f2py intent(hide) dim
!f2py character(*) optional, intent(in) :: order = 'p_O2'
@@ -88,12 +87,12 @@ contains
!! @param[in,out] scal 3d scalar field which is advected
subroutine solve_advection(dt,vx,vy,vz,scal)
- real(pk), intent(in) :: dt
- real(pk), dimension(:,:,:), intent(in) :: vx, vy, vz
- real(pk), dimension(size(vx,1),size(vx,2),size(vx,3)), intent(inout) :: scal
- !f2py real(pk) intent(in,out), depend(size(vx,1)) :: scal
+ real(wp), intent(in) :: dt
+ real(wp), dimension(:,:,:), intent(in) :: vx, vy, vz
+ real(wp), dimension(size(vx,1),size(vx,2),size(vx,3)), intent(inout) :: scal
+ !f2py real(wp) intent(in,out), depend(size(vx,1)) :: scal
- real(pk) :: t0
+ real(wp) :: t0
t0 = MPI_Wtime()
call advec_step(dt,vx,vy,vz,scal)
@@ -110,12 +109,12 @@ contains
!! @param[in,out] cz 3d scalar field which is advected
subroutine solve_advection_vect(dt,vx,vy,vz,cx,cy,cz)
- real(pk), intent(in) :: dt
- real(pk), dimension(:,:,:), intent(in) :: vx, vy, vz
- real(pk), dimension(size(vx,1),size(vx,2),size(vx,3)), intent(inout) :: cx,cy,cz
- !f2py real(pk) intent(in,out), depend(size(vx,1)) :: cx
- !f2py real(pk) intent(in,out), depend(size(vx,1)) :: cy
- !f2py real(pk) intent(in,out), depend(size(vx,1)) :: cz
+ real(wp), intent(in) :: dt
+ real(wp), dimension(:,:,:), intent(in) :: vx, vy, vz
+ real(wp), dimension(size(vx,1),size(vx,2),size(vx,3)), intent(inout) :: cx,cy,cz
+ !f2py real(wp) intent(in,out), depend(size(vx,1)) :: cx
+ !f2py real(wp) intent(in,out), depend(size(vx,1)) :: cy
+ !f2py real(wp) intent(in,out), depend(size(vx,1)) :: cz
real(8) :: t0
@@ -134,9 +133,9 @@ contains
subroutine solve_advection_inter_basic(dt, Vx, Vy, Vz, scal)
! Input/Output
- real(pk), intent(in) :: dt
- real(pk), dimension(:,:,:), intent(in) :: Vx, Vy, Vz
- real(pk), dimension(:,:,:), intent(inout) :: scal
+ real(wp), intent(in) :: dt
+ real(wp), dimension(:,:,:), intent(in) :: Vx, Vy, Vz
+ real(wp), dimension(:,:,:), intent(inout) :: scal
!f2py intent(in,out) :: scal
call advec_step_Inter_basic(dt, Vx, Vy, Vz, scal)
@@ -154,9 +153,9 @@ contains
subroutine solve_advection_inter_basic_vec(dt, Vx, Vy, Vz, cx, cy, cz)
! Input/Output
- real(pk), intent(in) :: dt
- real(pk), dimension(:,:,:), intent(in) :: Vx, Vy, Vz
- real(pk), dimension(:,:,:), intent(inout) :: cx,cy,cz
+ real(wp), intent(in) :: dt
+ real(wp), dimension(:,:,:), intent(in) :: Vx, Vy, Vz
+ real(wp), dimension(:,:,:), intent(inout) :: cx,cy,cz
!f2py intent(in,out) :: cx
!f2py intent(in,out) :: cy
!f2py intent(in,out) :: cz
diff --git a/hysop/f2py/scales2py.pyf b/hysop/scales_f/scales2py.pyf
similarity index 57%
rename from hysop/f2py/scales2py.pyf
rename to hysop/scales_f/scales2py.pyf
index 584336cfac437a80667dccfa9dcc3cf15bcf2e87..d47582692be664ff51ae6838b391016281e914f5 100644
--- a/hysop/f2py/scales2py.pyf
+++ b/hysop/scales_f/scales2py.pyf
@@ -7,14 +7,14 @@ module scales2py ! in scales2py.f90
use cart_topology, only: cart_rank,coord,n_proc,discretisation_set_mesh_velo,cart_create,set_group_size,discretisation_create
use advec_vect, only: advec_step_vect,advec_step_inter_basic_vect
use mpi
- use hysopparam
+ use precision
subroutine init_advection_solver(ncells,lengths,topodims,main_comm,datashape,offset,dim,order,dim_split) ! in scales2py.f90:scales2py
integer dimension(dim),intent(in) :: ncells
- real(kind=pk) dimension(dim),intent(in),depend(dim) :: lengths
+ real(kind=wp) dimension(dim),intent(in),depend(dim) :: lengths
integer dimension(dim),intent(in),depend(dim) :: topodims
integer intent(in) :: main_comm
- integer(kind=ik) dimension(dim),intent(out),depend(dim) :: datashape
- integer(kind=ik) dimension(dim),intent(out),depend(dim) :: offset
+ integer(kind=ip) dimension(dim),intent(out),depend(dim) :: datashape
+ integer(kind=ip) dimension(dim),intent(out),depend(dim) :: offset
integer, optional,intent(hide),depend(ncells) :: dim=len(ncells)
character*(*), optional,intent(in) :: order='p_o2'
character*(*), optional,intent(in) :: dim_split
@@ -26,36 +26,36 @@ module scales2py ! in scales2py.f90
character*(*), optional,intent(in) :: formula
end subroutine init_multiscale
subroutine solve_advection(dt,vx,vy,vz,scal) ! in scales2py.f90:scales2py
- real(kind=pk) intent(in) :: dt
- real(kind=pk) dimension(:,:,:),intent(in) :: vx
- real(kind=pk) dimension(:,:,:),intent(in) :: vy
- real(kind=pk) dimension(:,:,:),intent(in) :: vz
- real(kind=pk) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: scal
+ real(kind=wp) intent(in) :: dt
+ real(kind=wp) dimension(:,:,:),intent(in) :: vx
+ real(kind=wp) dimension(:,:,:),intent(in) :: vy
+ real(kind=wp) dimension(:,:,:),intent(in) :: vz
+ real(kind=wp) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: scal
end subroutine solve_advection
subroutine solve_advection_vect(dt,vx,vy,vz,cx,cy,cz) ! in scales2py.f90:scales2py
- real(kind=pk) intent(in) :: dt
- real(kind=pk) dimension(:,:,:),intent(in) :: vx
- real(kind=pk) dimension(:,:,:),intent(in) :: vy
- real(kind=pk) dimension(:,:,:),intent(in) :: vz
- real(kind=pk) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: cx
- real(kind=pk) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: cy
- real(kind=pk) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: cz
+ real(kind=wp) intent(in) :: dt
+ real(kind=wp) dimension(:,:,:),intent(in) :: vx
+ real(kind=wp) dimension(:,:,:),intent(in) :: vy
+ real(kind=wp) dimension(:,:,:),intent(in) :: vz
+ real(kind=wp) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: cx
+ real(kind=wp) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: cy
+ real(kind=wp) dimension(size(vx,1),size(vx,2),size(vx,3)),intent(in,out),depend(size(vx,1)) :: cz
end subroutine solve_advection_vect
subroutine solve_advection_inter_basic(dt,vx,vy,vz,scal) ! in scales2py.f90:scales2py
- real(kind=pk) intent(in) :: dt
- real(kind=pk) dimension(:,:,:),intent(in) :: vx
- real(kind=pk) dimension(:,:,:),intent(in) :: vy
- real(kind=pk) dimension(:,:,:),intent(in) :: vz
- real(kind=pk) dimension(:,:,:),intent(in,out) :: scal
+ real(kind=wp) intent(in) :: dt
+ real(kind=wp) dimension(:,:,:),intent(in) :: vx
+ real(kind=wp) dimension(:,:,:),intent(in) :: vy
+ real(kind=wp) dimension(:,:,:),intent(in) :: vz
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: scal
end subroutine solve_advection_inter_basic
subroutine solve_advection_inter_basic_vec(dt,vx,vy,vz,cx,cy,cz) ! in scales2py.f90:scales2py
- real(kind=pk) intent(in) :: dt
- real(kind=pk) dimension(:,:,:),intent(in) :: vx
- real(kind=pk) dimension(:,:,:),intent(in) :: vy
- real(kind=pk) dimension(:,:,:),intent(in) :: vz
- real(kind=pk) dimension(:,:,:),intent(in,out) :: cx
- real(kind=pk) dimension(:,:,:),intent(in,out) :: cy
- real(kind=pk) dimension(:,:,:),intent(in,out) :: cz
+ real(kind=wp) intent(in) :: dt
+ real(kind=wp) dimension(:,:,:),intent(in) :: vx
+ real(kind=wp) dimension(:,:,:),intent(in) :: vy
+ real(kind=wp) dimension(:,:,:),intent(in) :: vz
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: cx
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: cy
+ real(kind=wp) dimension(:,:,:),intent(in,out) :: cz
end subroutine solve_advection_inter_basic_vec
end module scales2py
diff --git a/hysop/problem/simulation.py b/hysop/simulation.py
similarity index 94%
rename from hysop/problem/simulation.py
rename to hysop/simulation.py
index dea2196c18b2018fe72589ec9bb5811631353a7c..451e7f289d5a685592ea2d5c385a73fee48606da 100644
--- a/hysop/problem/simulation.py
+++ b/hysop/simulation.py
@@ -28,8 +28,8 @@ Usage
io.apply(s)
"""
-import sys
from abc import ABCMeta, abstractmethod
+from hysop.deps import sys
eps = sys.float_info.epsilon
"""Machine epsilon, used to compare times."""
@@ -92,8 +92,9 @@ class Simulation(object):
msg += ' are given, time step input will be ignored.\n'
msg += '------------------------------------------------\n'
- if nb_iter is not None and time_step is not None:
- print (msg)
+ if (nb_iter is not None) and (time_step is not None):
+ from hysop import vprint
+ vprint(msg)
self.time_step = (self.end - self.start) / self.nb_iter
elif time_step is not None:
# Simulation time step
@@ -173,21 +174,6 @@ class Simulation(object):
"""
self.time_step = dt
- def print_state(self):
- """Print current simulation parameters
- """
- msg = "== Iteration : {0:3d}, from t = {1:6.5} to t = {2:6.5f} =="
- print (msg.format(self.current_iteration, self.tk, self.time))
-
- def __str__(self):
- s = "Simulation parameters : "
- s += "from " + str(self.start) + ' to ' + str(self.end)
- s += ', time step : ' + str(self.time_step)
- s += ', current time : ' + str(self.time) + ', iteration number : '
- s += str(self.current_iteration) + ', max number of iterations : '
- s += str(self.max_iter)
- return s
-
def initialize(self):
"""(Re)set simulation to initial values
--> back to iteration 0 and ready to run.
@@ -202,19 +188,26 @@ class Simulation(object):
self._is_ready = True
self._next_is_last = False
- def set_split(self, split_id, split):
- self.split_id = split_id
- self.sub_step = split[1] * self.time_step
- self.current_dir = split[0]
-
- def next_split(self):
- self.old_dir = self.current_dir
-
def finalize(self):
"""Use this function when you need to call an hdf i/o operator
after the end of the time-loop.
"""
self.is_over = True
self.current_iteration = -1
+
+ def print_state(self):
+ """Print current simulation parameters
+ """
+ msg = "== Iteration : {0:3d}, from t = {1:6.5} to t = {2:6.5f} =="
+ from hysop import vprint
+ vprint(msg.format(self.current_iteration, self.tk, self.time))
+ def __str__(self):
+ s = "Simulation parameters : "
+ s += "from " + str(self.start) + ' to ' + str(self.end)
+ s += ', time step : ' + str(self.time_step)
+ s += ', current time : ' + str(self.time) + ', iteration number : '
+ s += str(self.current_iteration) + ', max number of iterations : '
+ s += str(self.max_iter)
+ return s
diff --git a/hysop/testsenv.py b/hysop/testsenv.py
old mode 100755
new mode 100644
index d677d10b6f9a4f683be40e80ad074720636ea57d..6473bdf4c0a8643db14a6af4df5312c1286af4cc
--- a/hysop/testsenv.py
+++ b/hysop/testsenv.py
@@ -1,11 +1,13 @@
"""Set some functions and variables useful to run tests.
"""
-from hysop import __FFTW_ENABLED__, __SCALES_ENABLED__
+
+import os
import pytest
import shutil
+
+from hysop import __FFTW_ENABLED__, __SCALES_ENABLED__, __ENABLE_LONG_TESTS__
from hysop.tools.io_utils import IO
-from hysop.mpi import main_rank
-import os
+from hysop.core.mpi import main_rank
# accept failing tests when fft is not enabled
if __FFTW_ENABLED__:
@@ -13,7 +15,6 @@ if __FFTW_ENABLED__:
"""For fftw tests that must not fail
"""
return f
-
else:
fftw_failed = pytest.mark.xfail
@@ -24,10 +25,45 @@ if __SCALES_ENABLED__:
"""For scales tests that must not fail
"""
return f
-
else:
scales_failed = pytest.mark.xfail
+# accept failing tests when opencl is not present
+from hysop.backend import __HAS_OPENCL_BACKEND__
+if __HAS_OPENCL_BACKEND__:
+ from hysop.backend.device.opencl import cl
+ from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+ def opencl_failed(f):
+ """For opencl tests that must not fail
+ """
+ return f
+
+ def iter_clenv(**kargs):
+ """Iterate over all platforms and device and yield OpenClEnvironments.
+ If __ENABLE_LONG_TESTS__ is False, just yield default clenv."""
+ if __ENABLE_LONG_TESTS__:
+ envs = []
+ for i,plat in enumerate(cl.get_platforms()):
+ for j,dev in enumerate(plat.get_devices()):
+ env = get_or_create_opencl_env(platform_id=i, device_id=j, **kargs)
+ assert env not in envs
+ envs.append(env)
+ yield env
+ else:
+ yield get_or_create_opencl_env(**kargs)
+else:
+ opencl_failed = pytest.mark.xfail
+ iter_clenv = None
+
+from hysop.backend import __HAS_CUDA_BACKEND__
+if __HAS_CUDA_BACKEND__:
+ def cuda_failed(f):
+ """For cuda tests that must not fail
+ """
+ return f
+else:
+ cuda_failed = pytest.mark.xfail
+
hysop_failed = pytest.mark.xfail
"""Use this decorator for tests that must fail"""
diff --git a/hysop/tools/callback.py b/hysop/tools/callback.py
new file mode 100644
index 0000000000000000000000000000000000000000..b7bd848a5c783f80533b6f18c59d529eea5ca840
--- /dev/null
+++ b/hysop/tools/callback.py
@@ -0,0 +1,481 @@
+import numpy as np
+from hysop.tools.units import unit2str, time2str, bytes2str, bdw2str
+from hysop.backend.device.codegen.base.statistics import WorkStatistics
+
+def _to_list(e):
+ if isinstance(e,list):
+ return e
+ elif isinstance(e,tuple) or isinstance(e,set):
+ return list(e)
+ elif isinstance(e,np.ndarray):
+ return e.tolist()
+ else:
+ return [e]
+
+
+
+class TimerInterface(object):
+ def __init__(self,**kargs):
+ super(TimerInterface,self).__init__(**kargs)
+ self.state = None
+ self.min = None
+ self.max = None
+ self.nruns = 0
+ self.data = []
+
+ def mean(self):
+ if self.nruns==0:
+ return None
+ else:
+ return sum(self.data)/float(self.nruns)
+
+ def total(self):
+ if self.nruns==0:
+ return 0
+ else:
+ return sum(self.data)
+
+ def status(self):
+ if self.state is None: #waiting 1st run
+ return 'W'
+ elif self.state < 0: #running
+ return 'R'
+ else: #sleeping
+ return 'S'
+
+ def register_timing(self,timing):
+ if self.min is None:
+ self.min = timing
+ elif timing < self.min:
+ self.min = timing
+
+ if self.max is None:
+ self.max = timing
+ elif timing > self.max:
+ self.max = timing
+
+ self.nruns += 1
+ self.data.append(timing)
+
+ def __str__(self):
+ return '({}) nruns={:4d}, min={}, max={}, mean={}, total={}' \
+ .format(self.status(), self.nruns,
+ time2str(self.min), time2str(self.max),
+ time2str(self.mean()), time2str(self.total()))
+
+ @staticmethod
+ def _as_group(groupname,tasks,tic_callbacks=[],tac_callbacks=[]):
+ return TimingGroup(name=groupname,tasks=tasks,
+ tic_callbacks=tic_callbacks,tac_callbacks=tac_callbacks)
+
+
+class MemInterface(TimerInterface):
+ def __init__(self,membytes,**kargs):
+ super(MemInterface,self).__init__(**kargs)
+ self.membytes=membytes
+ self.min_bandwidth = None
+ self.max_bandwidth = None
+ self.bandwidth = []
+ def register_timing(self,timing):
+ super(MemInterface,self).register_timing(timing)
+
+ bdw = self.membytes / float(timing)
+ if self.min_bandwidth is None:
+ self.min_bandwidth = bdw
+ elif bdw < self.min_bandwidth:
+ self.min_bandwidth = bdw
+
+ if self.max_bandwidth is None:
+ self.max_bandwidth = bdw
+ elif bdw > self.max_bandwidth:
+ self.max_bandwidth = bdw
+ self.bandwidth.append(bdw)
+
+ def mean_bandwidth(self):
+ if self.nruns==0:
+ return None
+ else:
+ return sum(self.bandwidth)/float(self.nruns)
+
+ def total_mem_moved(self):
+ return self.nruns * self.membytes
+
+ def __str__(self):
+ s = '\n{:15s} min_bdw={}, max_bdw={}, mean_bdw={}, total_mem_moved={}'.format(
+ '',
+ bdw2str(self.min_bandwidth), bdw2str(self.max_bandwidth),
+ bdw2str(self.mean_bandwidth()),
+ bytes2str(self.total_mem_moved()))
+ return TimerInterface.__str__(self) + s
+
+class MemcpyInterface(MemInterface):
+ def __init__(self,membytes,**kargs):
+ super(MemcpyInterface,self).__init__(membytes=membytes,**kargs)
+
+ def __str__(self):
+ s = '\n{:15s} min_bdw={}, max_bdw={}, mean_bdw={}, total_mem_moved={}'.format(
+ '',
+ bdw2str(2*self.min_bandwidth), bdw2str(2*self.max_bandwidth),
+ bdw2str(2*self.mean_bandwidth()),
+ bytes2str(self.total_mem_moved()))
+ return TimerInterface.__str__(self) + s
+
+class ComputeInterface(MemInterface):
+ def __init__(self,total_work,per_work_statistic,ftype='float',**kargs):
+ if not isinstance(per_work_statistic, WorkStatistics):
+ raise ValueError('per_work_statistic is not a WorkStatistics')
+ if total_work<1:
+ raise ValueError('total_work < 1.')
+
+ membytes = total_work*per_work_statistic.global_mem_transactions()
+ super(ComputeInterface, self).__init__(membytes=membytes,**kargs)
+
+ self.ftype = ftype
+ self.total_work = total_work
+ self.per_work_statistic = per_work_statistic
+ self.total_work_statistic = WorkStatistics()
+
+ def register_timing(self,timing):
+ super(ComputeInterface,self).register_timing(timing)
+ self.total_work_statistic += self.total_work*self.per_work_statistic
+
+ def stats_per_second(self):
+ if self.nruns==0:
+ return None
+ else:
+ return self.total_work_statistic.compute_timed_statistics(self.total())
+
+ def __str__(self):
+
+ s=''
+
+ timed_stats = self.stats_per_second()
+ if (timed_stats is not None):
+
+ if self.ftype=='float':
+ float_op_category = 'FLOPS (FP32)'
+ float_op_factor=1.0
+ elif self.ftype == 'double':
+ float_op_category = 'FLOPS (FP64)'
+ float_op_factor=0.5
+ elif self.ftype == 'half':
+ float_op_category = 'FLOPS (FP16)'
+ float_op_factor=2.0
+ else:
+ raise ValueError()
+ flops = timed_stats.ops_per_category()['FLOPS']
+ flops *= float_op_factor
+
+ opi = flops/timed_stats.global_mem_transactions()
+
+ if timed_stats.global_mem_throughput()>0:
+ s += ' throughput={}'.format(bdw2str(timed_stats.global_mem_throughput()))
+ if timed_stats.global_mem_throughput() < timed_stats.total_mem_throughput():
+ s+= ' (tot={})'.format(bdw2str(timed_stats.total_mem_throughput()))
+ s += ' OPI={}'.format(unit2str(opi,'FLOP/B',decimal=True,rounded=2))
+ for (op_category, ops_per_second) in timed_stats.ops_per_second().iteritems():
+ if op_category!='FLOPS':
+ s += ' {}'.format(unit2str(ops_per_second,op_category,decimal=True,rounded=2))
+ else:
+ s += ' {}'.format(unit2str(ops_per_second*float_op_factor,float_op_category,decimal=True,rounded=2))
+
+ return TimerInterface.__str__(self) + s
+
+
+class CallbackTask(object):
+ def __init__(self,name,tic_callbacks=[],tac_callbacks=[], **kargs):
+ super(CallbackTask, self).__init__(**kargs)
+ self.name = name
+ self.tic_callbacks = []
+ self.tac_callbacks = []
+ self.register_callbacks(tic_callbacks,tac_callbacks)
+ def tic(self,**kargs):
+ self._on_tic(**kargs)
+ for cb in self.tic_callbacks:
+ cb(self,**kargs)
+ def tac(self,**kargs):
+ self._on_tac(**kargs)
+ for cb in self.tac_callbacks:
+ cb(self,**kargs)
+ def register_callbacks(self,tic_callbacks=[],tac_callbacks=[]):
+ tic_callbacks = _to_list(tic_callbacks)
+ tac_callbacks = _to_list(tac_callbacks)
+ for cb in tic_callbacks:
+ if cb not in self.tic_callbacks:
+ self.tic_callbacks.append(cb)
+ for cb in tac_callbacks:
+ if cb not in self.tac_callbacks:
+ self.tac_callbacks.append(cb)
+
+ def _on_tic(self,**kargs):
+ msg='_on_tic not implemented in class {}.'.format(self.__class__.__name__)
+ raise NotImplementedError(msg)
+ def _on_tac(self,**kargs):
+ msg='_on_tac not implemented in class {}.'.format(self.__class__.__name__)
+ raise NotImplementedError(msg)
+ def __str__(self):
+ msg='__str__ not implemented in class {}.'.format(self.__class__.__name__)
+ raise NotImplementedError(msg)
+
+ def report(self,offset):
+ return self.offset_str(offset) + '{:15s}'.format(self.name)
+
+ @staticmethod
+ def offset_str(count):
+ return ' '*count
+ @staticmethod
+ def format(s,count):
+ return s.replace('\n','\n '+CallbackTask.offset_str(count))
+
+class CallbackGroup(CallbackTask):
+ def __init__(self,name,tasks,**kargs):
+ super(CallbackGroup,self).__init__(name,**kargs)
+ self.tasks = tasks
+ self.ticked = np.zeros(shape=(len(tasks),), dtype=bool)
+ self.tacked = self.ticked.copy()
+
+ taskid = {}
+ for i,task in enumerate(tasks):
+ taskid[task.name] = i
+ self._taskid = taskid
+
+ self._check()
+ def _on_task_tic(task,**args):
+ tid = self.taskid(task)
+ self.ticked[tid] = True
+ if self.ticked.all():
+ super(CallbackGroup,self).tic(**args)
+
+ def _on_task_tac(task,**args):
+ tid = self.taskid(task)
+ self.tacked[tid] = True
+ if self.tacked.all():
+ super(CallbackGroup,self).tac(**args)
+ self.ticked[:] = False
+ self.tacked[:] = False
+
+ for task in tasks:
+ task.register_callbacks(tic_callbacks=_on_task_tic,tac_callbacks=_on_task_tac)
+
+ def _check(self):
+ if len(self.tasks)==0:
+ raise ValueError('Empty task list!')
+ def taskid(self,task):
+ return self._taskid[task.name]
+
+ def tic(self,**kargs):
+ raise RuntimeError('CallbackGroup.tic() should not be called explicitely.')
+ def tac(self,**kargs):
+ raise RuntimeError('CallbackGroup.tac() should never be called explicitely.')
+
+ def report(self,offset=0):
+ s = ''
+ s += '{}{}'.format(self.offset_str(offset), self.name)
+ tasks = sorted(self.tasks, key=lambda x:x.total(), reverse=True)
+ for task in tasks:
+ s += '\n'+task.report(offset+1)
+ s += '\n{}{:15s} {}'.format(self.offset_str(offset+1),'total:',
+ self.__str__())
+ return s
+
+ @classmethod
+ def _as_group(cls,groupname,tasks,tic_callbacks=[],tac_callbacks=[],**kargs):
+ return self.__class__(name=groupname,tasks=tasks,
+ tic_callbacks=tic_callbacks,tac_callbacks=tac_callbacks,
+ **kargs)
+
+
+class TimingGroup(CallbackGroup, TimerInterface):
+ def __init__(self,**kargs):
+ super(TimingGroup,self).__init__(**kargs)
+ self._check()
+
+ def _check(self):
+ for task in self.tasks:
+ if not isinstance(task,TimerInterface):
+ msg='{} is not an instance of TimerInteface, \
+ got {} instead.'.format(task.name,task.__class__.__name__)
+ raise ValueError(msg)
+ elif not isinstance(task,CallbackTask):
+ msg='{} is not an instance of CallbackTask, \
+ got {} instead.'.format(task.name,task.__class__.__name__)
+ raise ValueError(msg)
+
+ def _on_tic(self,**kargs):
+ pass
+ def _on_tac(self,**kargs):
+
+ total = 0
+ for task in self.tasks:
+ total += task.data[-1]
+
+ if self.min is None:
+ self.min=total
+ else:
+ self.min = min(self.min,total)
+
+ if self.max is None:
+ self.max=total
+ else:
+ self.max = max(self.max,total)
+
+ self.nruns += 1
+ self.data.append(total)
+
+ def __str__(self):
+ return TimerInterface.__str__(self)
+
+class TimingTask(CallbackTask,TimerInterface):
+ def __init__(self,**kargs):
+ super(TimingTask,self).__init__(**kargs)
+
+ def report(self,offset=0):
+ return '{} {}'.format(CallbackTask.report(self,offset), TimerInterface.__str__(self))
+ def __str__(self):
+ return self.report()
+
+class MemcpyTask(CallbackTask,MemcpyInterface):
+ def __init__(self,MPI,**kargs):
+ super(MemcpyTask,self).__init__(**kargs)
+ self.MPI=MPI
+
+ def report(self,offset=0):
+ return '{} {}'.format(
+ CallbackTask.report(self,offset),
+ self.format(MemcpyInterface.__str__(self),offset))
+ def __str__(self):
+ return self.report()
+ def _on_tic(self,**kargs):
+ self.state = -self.MPI.Wtime()
+ def _on_tac(self,**kargs):
+ self.state += self.MPI.Wtime()
+ self.register_timing(self.state)
+
+class ComputeTask(CallbackTask,ComputeInterface):
+ def __init__(self,MPI,**kargs):
+ super(ComputeTask,self).__init__(**kargs)
+ self.MPI=MPI
+
+ def report(self,offset=0):
+ return '{} {}'.format(
+ CallbackTask.report(self,offset),
+ self.format(ComputeInterface.__str__(self),offset))
+ def __str__(self):
+ return self.report()
+ def _on_tic(self,**kargs):
+ self.state = -self.MPI.Wtime()
+ def _on_tac(self,**kargs):
+ self.state += self.MPI.Wtime()
+ self.register_timing(self.state)
+
+
+class MPITimingTask(TimingTask):
+ def __init__(self,MPI,**kargs):
+ super(MPITimingTask,self).__init__(**kargs)
+ self.MPI = MPI
+ def _on_tic(self,**kargs):
+ self.state = -self.MPI.Wtime()
+ def _on_tac(self,**kargs):
+ self.state += self.MPI.Wtime()
+ self.register_timing(self.state)
+
+class CallbackProfiler(object):
+ def __init__(self,MPI):
+ self._MPI = MPI
+ self.tasks = {}
+ self.groups = {}
+ self._tasks_in_group = set()
+
+ def tic(self,target,**kargs):
+ self._check_registered(target)[target].tic(**kargs)
+ def tac(self,target,**kargs):
+ self._check_registered(target)[target].tac(**kargs)
+
+ def register_tasks(self,tasks, tic_callbacks=[], tac_callbacks=[],**kargs):
+ tasks = _to_list(tasks)
+ for task in tasks:
+ if isinstance(task,CallbackTask):
+ taskname = task.name
+ self._check_not_registered(taskname)
+ else:
+ taskname = task
+ if taskname in self.tasks:
+ task = self.tasks[task]
+ elif 'per_work_statistic' in kargs:
+ task = ComputeTask(MPI=self._MPI,name=taskname,**kargs)
+ elif 'membytes' in kargs:
+ task = MemcpyTask(MPI=self._MPI,name=taskname,**kargs)
+ else:
+ task = MPITimingTask(MPI=self._MPI,name=taskname,**kargs)
+ task.register_callbacks(tic_callbacks,tac_callbacks)
+ self.tasks[taskname] = task
+
+ def register_group(self,groupname, tasknames,
+ tic_callbacks=[], tac_callbacks=[]):
+ if groupname in self.groups:
+ source = set(tasknames)
+ target = set([task.name for task in self.groups[groupname].tasks])
+ if source != target:
+ msg = 'Group {} was already registered!'.format(groupname)
+ raise RuntimeError(msg)
+ else:
+ # just update callbacks
+ self.groups[groupname].register_callbacks(tic_callbacks,tac_callbacks)
+ else:
+ tasks = []
+ for taskname in tasknames:
+ if taskname in self.registered_targets():
+ tasks.append(self._check_registered(taskname)[taskname])
+ self._tasks_in_group.update([taskname])
+ group = tasks[0]._as_group(groupname,tasks,tic_callbacks,tac_callbacks)
+ group.register_callbacks(tic_callbacks,tac_callbacks)
+ self.groups[groupname] = group
+
+ def registered_targets(self):
+ return self.groups.keys() + self.tasks.keys()
+
+ def register_callbacks(self,target,tic_callbacks=[],tac_callbacks=[]):
+ dic = self._check_registered(target)
+ dic[target].register_callbacks(tic=tic_callbacks,tac=tac_callbacks)
+
+ def has_tasks(self):
+ return bool(self.tasks)
+ def has_groups(self):
+ return bool(self.groups)
+
+ def _check_registered(self,target):
+ if target not in self.registered_targets():
+ msg='{} is not registered as a task or a group.'.format(target)
+ raise ValueError(msg)
+ return self.groups if (target in self.groups.keys()) else self.tasks
+ def _check_not_registered(self,target):
+ if target in self.registered_targets():
+ msg='Target {} was already registered!'.format(target)
+ raise ValueError(msg)
+
+ def report(self,mode='recursive'):
+ s = '=== Callback Profiler Report ==='
+ if mode=='all':
+ if self.has_tasks():
+ s += '\n ::Individual tasks::'
+ for taskname,task in self.tasks.iteritems():
+ s += '\n'+task.report(1)
+ if self.has_groups():
+ s += '\n ::Group tasks::'
+ for taskname,task in self.groups.iteritems():
+ s += '\n'+task.report(1)
+ elif mode =='recursive':
+ if self.has_groups():
+ groups = sorted(self.groups.values(), key=lambda x:x.total(), reverse=True)
+ for group in groups:
+ s += '\n'+group.report(1)
+ if self.has_tasks():
+ individual_tasknames = set(self.tasks.keys()).difference(self._tasks_in_group)
+ tasknames = sorted(individual_tasknames, key=lambda x:self.tasks[x].total(), reverse=True)
+ for taskname in tasknames:
+ task = self.tasks[taskname]
+ s += '\n'+task.report(1)
+ return s
+
+ def __str__(self):
+ return self.report()
diff --git a/hysop/tools/contexts.py b/hysop/tools/contexts.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c4fd9c932354afaf80c09fc0d5db8c4b2ca7b6b
--- /dev/null
+++ b/hysop/tools/contexts.py
@@ -0,0 +1,21 @@
+
+import numpy as np
+import time
+from contextlib import contextmanager
+
+@contextmanager
+def printoptions(*args, **kwargs):
+ original = np.get_printoptions()
+ np.set_printoptions(*args, **kwargs)
+ yield
+ np.set_printoptions(**original)
+
+class Timer:
+ def __enter__(self, factor=1):
+ self.start = time.clock()
+ self.factor = factor
+ return self
+
+ def __exit__(self, *args):
+ self.end = time.clock()
+ self.interval = (self.end - self.start)*self.factor
diff --git a/hysop/tools/decorators.py b/hysop/tools/decorators.py
new file mode 100644
index 0000000000000000000000000000000000000000..1631b72fceb0dab17a59081a64122a38e68426b0
--- /dev/null
+++ b/hysop/tools/decorators.py
@@ -0,0 +1,153 @@
+
+from functools import wraps as _wraps
+from hysop.constants import __DEBUG__, HYSOP_ROOT, __VERBOSE__
+from hysop.deps import inspect, types
+from hysop.tools.sys_utils import SysUtils
+
+def wraps(f):
+ """
+ Like functools.wraps but keep trace of the original wrapped function
+ in the '__wrapped__' attribute. This is usefull to trace functions
+ calls origin. See hysop.tools.decorators.debug
+ """
+ if not hasattr(f, '__wrapped__'):
+ setattr(f, '__wrapped__', f)
+ wrapper_assignments=['__module__', '__name__', '__doc__', '__wrapped__']
+ g = _wraps(f, wrapper_assignments)
+ return g
+
+def static_vars(**kwargs):
+ """
+ Attach a static variable local to decorated function.
+ """
+ def decorate(f):
+ for k in kwargs:
+ setattr(f, k, kwargs[k])
+ return f
+ return decorate
+
+
+@static_vars(call_depth=-1)
+def debug(f):
+ """
+ Debug decorator
+ Usage: @debug before function definition you want to debug
+ If verbose is set to True: prints filename and line of function definition
+ Else: only print depth of call and function name
+ """
+ verbose=False #__VERBOSE__
+
+ if __DEBUG__:
+ @wraps(f)
+ def decorator(*args, **kw):
+ debug.call_depth += 1
+
+ cls = None
+ fw = f
+ if isinstance(f, types.FunctionType) and hasattr(args[0],'__class__'):
+ cls = args[0].__class__
+ if hasattr(f, '__wrapped__'):
+ fw = f.__wrapped__
+ for _cls in inspect.getmro(cls)[::-1]:
+ if hasattr(_cls, fw.__name__):
+ _f = getattr(_cls, fw.__name__)
+ if hasattr(_f, '__wrapped__'):
+ _f = _f.__wrapped__
+ if _f is fw:
+ cls = _cls
+ break
+ cls = cls.__name__
+ if hasattr(args[0], 'name'):
+ cls+='({})'.format(args[0].name)
+
+ print '{}{}{}{}{}()'.format('{}:'.format(fw.__code__.co_filename.replace(HYSOP_ROOT, 'hysop')) if verbose else '',
+ '{} '.format(fw.__code__.co_firstlineno) if verbose else '',
+ '>'*debug.call_depth if not verbose else '',
+ '{}::'.format(cls) if (cls is not None) else '',
+ fw.__name__),
+ if 'name' in kw:
+ print 'with name {}.'.format(kw['name']),
+
+ if f.__name__ is '__new__':
+ fullclassname = args[0].__mro__[0].__module__ + '.'
+ fullclassname += args[0].__mro__[0].__name__
+ print '=> instanciate :', fullclassname,
+ print
+
+ # Calling f
+ ret = f(*args, **kw)
+
+ debug.call_depth -= 1
+ if debug.call_depth==-1:
+ print
+
+ return ret
+
+ return decorator
+ else:
+ #define empty debug decorator:
+ return f
+
+def requires_cmd(*args):
+ """
+ Raise a RuntimeError if given executable names are not found
+ in system PATH.
+ """
+ def decorate(func):
+ for cmd in args:
+ if not SysUtils.cmd_exists(cmd):
+ msg='Function {} requires executable {} to be present '
+ msg+='on your system.'
+ msg=msg.format(func.__name__, cmd)
+ raise RuntimeError(msg)
+ return func
+ return decorate
+
+def not_implemented(f):
+ """
+ Raise an NotImplementedError with an explicit message
+ if the decorated function is called.
+ This can be used to define virtual static/class methods or
+ to declare that a feature has not been implemented yet.
+ """
+ fname = f.__name__
+ @wraps(f)
+ def wrapper(*args, **kargs):
+ args = list(args) + kargs.values()
+ if len(args)>0:
+ arg0 = args[0]
+ if isinstance(arg0,type): # @classmethod
+ cls = arg0.__name__
+ msg = '{}.{}() has not been implemented.'.format(cls,fname)
+ else: # instance method
+ self = arg0
+ cls = self.__class__.__name__
+ try:
+ name = self.name
+ msg = '{}.{}() has not been implemented (in node \'{}\').'
+ msg = msg.format(cls,fname,name)
+ except:
+ msg = '{}.{}() has not been implemented.'
+ msg = msg.format(cls,fname)
+ else: # @staticmethod without arguments
+ msg = '{}() has not been implemented yet.'.format(fname)
+ raise NotImplementedError(msg)
+ return wrapper
+
+def required_property(f):
+ @wraps(f)
+ def decorator(*args, **kargs):
+ msg='Property corresponding to getter {}() has not been correctly set up in class {}.'
+ msg=msg.format(f.__name__, args[0].__class__)
+ raise RuntimeError(msg)
+ return decorator
+
+def optional_property(f):
+ @wraps(f)
+ def decorator(*args, **kargs):
+ msg=('Property corresponding to getter {}() is optional and '
+ +'has not been set up in class {}.')
+ msg=msg.format(f.__name__, args[0].__class__)
+ raise RuntimeError(msg)
+ return decorator
+
diff --git a/hysop/tools/enum.py b/hysop/tools/enum.py
index 8a1e100e1b88be756e39166ff0300337af4b6795..dfd0c06af8a7303697bcc1794b14e6d83c19374e 100644
--- a/hysop/tools/enum.py
+++ b/hysop/tools/enum.py
@@ -1,23 +1,34 @@
"""Tool to create enums compatible with C (32 bit signed integers)
* :class:`~EnumFactory`
-
"""
-
import numpy as np
-
-
+import keyword, re
+
registered_enums = {}
+
+class _EnumInstanceGenerator(object):
+ # pickle instance generator
+ def __call__(self, enum_name, enum_field):
+ if enum_name not in registered_enums:
+ msg='Pickle: trying to create an instance of {} but '
+ msg+='this enum has not been registered yet.'
+ msg=msg.format(enum_name)
+ raise RuntimeError(msg)
+ enum_cls = registered_enums[enum_name]
+ assert enum_field in enum_cls.fields().keys()
+ return enum_cls(enum_field)
+
class EnumFactory(object):
"""
- Static class with utilities to create enums.
+ Class with utilities to create enums.
"""
-
- class StaticMetaEnum(type):
+
+ class MetaEnum(type):
pass
@staticmethod
- def create(name, fields, dtype=np.int32):
+ def create(name, fields, dtype=np.int32, base=object):
"""Create a static enum with corresponding dtype.
Parameters
@@ -25,50 +36,101 @@ class EnumFactory(object):
name : str
Type name of the enumeration.
fields: dict or list
- Dictionary of enum fields. If this is a list, the first element will the value 0.
+ Dictionary of enum fields as string and corresponding values.
+ If this is a list, the first element will the value 0 and so on.
dtype: np.int32, np.int64, np.uint32, np.uint64
Underlying storage type for enum values. For C compatibility use np.int32.
+ For C++ you can use any of signed or unsigned integer or long integer.
Returns
-------
generated_enum
- An enum based on input fields and dtype.
+ An enum *class* based on input fields and dtype.
Examples
--------
-
- fields = {'X':0, 'Y':1, 'Z':2}
+ fields = {'X':0, 'Y':1, 'Z':42}
TestEnum = EnumFactory.create('Test', fields)
- print TestEnum.dtype
+
+ X = TestEnum()
+ Y = TestEnum('Y')
+ Z = TestEnum.Z
+ print TestEnum.dtype
print TestEnum.fields()
print TestEnum['X'], TestEnum['Y'], TestEnum['Z']
- print TestEnum.X, TestEnum.Y, TestEnum.Z
print TestEnum.rfields()
- print TestEnum[0], TestEnum[1], TestEnum[2]
+ print TestEnum[0], TestEnum[1], TestEnum[42]
+ print
+ print TestEnum.X, TestEnum.Y, TestEnum.Z
+ print X, Y, Z
+ print
+ print X.__class__.__name__
+ print X.value(), X()
+ print X.svalue(), str(X)
+ print repr(X)
See Also
-------
- Generate corresponding enum C or C++ code with `hysop.codegen.base.enum_codegen.EnumCodeGenerator`.
+ Generate corresponding enum C or C++ code with
+ `hysop.backend.device.codegen.base.enum_codegen.EnumCodeGenerator`.
"""
- if name in registered_enums.keys():
- msg="Enum '{}' was already created!".format(name)
+ if not fields:
+ msg='fields should contain at least one entry, got {}.'
+ msg=msg.format(fields)
raise ValueError(msg)
- if not isinstance(fields, dict):
+
+ if isinstance(fields, dict):
+ if len(set(fields.values())) != len(fields.values()):
+ msg = 'Field values collision: {}.'.format(fields)
+ raise ValueError(msg)
+ elif isinstance(fields, (list, set, tuple)):
+ if len(set(fields)) != len(fields):
+ msg = 'Field names collision: {}.'.format(fields)
+ raise ValueError(msg)
fields = dict(zip(fields, xrange(len(fields))))
- if len(set(fields.values())) != len(fields.values()):
- msg = 'Field values collision: {}.'.format(fields.values())
- raise ValueError(msg)
+ else:
+ msg='fields have to be of type list,set,tuple or dict but got {}.'
+ msg=msg.format(fields.__class__.__name__)
+ raise TypeError(msg)
+
+ if name in registered_enums.keys():
+ enum = registered_enums[name]
+ if any( [(f not in fields) for f in enum.fields().keys()] ):
+ msg='Enum \'{}\' was already created with different entries:'
+ msg+='\n\tregistered enum: {}\n\tnew values: {}'
+ msg=msg.format(name, enum.fields().keys(), fields.keys())
+ raise ValueError(msg)
+ elif any([ fields[k] != v for (k,v) in enum.fields().iteritems()]):
+ msg='Enum \'{}\' was already created with different values:'
+ msg+='\n\tregistered enum: {}\n\tnew values: {}'
+ msg=msg.format(name, enum.fields(), fields)
+ raise ValueError(msg)
+ elif enum.dtype != dtype:
+ msg="Enum '{}' was already created with different dtype!"
+ msg+='\n\tregistered enum dtype: {}\n\tnew dtype: {}'
+ msg=msg.format(name, enum.dtype, dtype)
+ raise ValueError(msg)
+ else:
+ return enum
+
for k in fields.keys():
if not isinstance(k, str):
- return ValueError('Enum keys should be strings, got {}.'.format(k))
- if k=='':
- return ValueError('Field name is empty!')
- if ' ' in k:
- return ValueError("No space are allowed in field names, got '{}'.".format(k))
+ msg='Enum keys should be strings, got {} of type {}.'
+ msg=msg.format(k,k.__class__.__name__)
+ raise TypeError(msg)
+ if keyword.iskeyword(k):
+ msg='Enum entry ({}) cannot be a python keyword.'
+ msg=msg.format(k)
+ raise ValueError(msg)
+ if not re.match('[_A-Za-z][_a-zA-Z0-9]*$',k):
+ msg='Enum entry ({}) has to be a valid python identifier.'
+ msg=msg.format(k)
+ raise ValueError(msg)
+
fields = dict(zip(fields.keys(), np.asarray(fields.values()).astype(dtype)))
rfields = dict(zip(fields.values(), fields.keys()))
@@ -76,81 +138,135 @@ class EnumFactory(object):
return cls._fields
def __rfields(cls):
return cls._rfields
- def __entries(cls):
- return cls._entries
+
def __getitem__(cls,val):
if isinstance(val,str) and (val in cls._fields.keys()):
return cls._fields[val]
elif (isinstance(val,int) or isinstance(val,dtype)) and (val in cls._rfields.keys()):
- return cls._rfields[val]
+ return getattr(cls, cls._rfields[val])
else:
raise RuntimeError('Unknown entry {} of type {}.'.format(val, type(val)))
+ def __str__(cls):
+ return name
+ def __repr__(cls):
+ return name
- def __value(cls,val):
- if val not in cls.entries():
- raise RuntimeError('Unknown entry {} of type {}.'.format(val, type(val)))
- if val in cls._fields.keys():
+ def __value(cls,field):
+ if field in cls._fields.keys():
return cls.dtype(cls._fields[val])
else:
- return cls.dtype(val)
+ raise RuntimeError('Unknown field {} of type {}.'.format(val, type(val)))
def __svalue(cls,val):
- if val not in cls.entries():
- raise RuntimeError('Unknown entry {} of type {}.'.format(val, type(val)))
if val in cls._rfields.keys():
return cls._rfields[val]
else:
- return val
+ raise RuntimeError('Unknown value {} of type {}.'.format(val, type(val)))
def __variable(cls,name,typegen,val=None,**kwds):
- from hysop.codegen.base.variables import CodegenVariable, dtype_to_ctype
+ from hysop.backend.device.codegen.base.variables import CodegenVariable, \
+ dtype_to_ctype
if val is None:
val = cls.fields().values()[0]
value = cls.value(val)
svalue = cls.svalue(val)
- return CodegenVariable(name=name,typegen=typegen,ctype=dtype_to_ctype(cls.dtype),value=value,svalue=svalue,**kwds)
+ return CodegenVariable(name=name,typegen=typegen,ctype=dtype_to_ctype(cls.dtype),
+ value=value,svalue=svalue,**kwds)
+ def __array_variable(cls,name,typegen,vals,**kwds):
+ from hysop.backend.device.codegen.base.variables import CodegenArray, \
+ dtype_to_ctype
+ assert vals is not None
+ size = len(vals)
+ value = [getattr(cls,cls.svalue(v)) if isinstance(v, (int,long))
+ else v for v in vals]
+ svalue = [cls.svalue(v) if isinstance(v, (int,long)) else str(v) for v in vals]
+ return CodegenArray(name=name,typegen=typegen,ctype=dtype_to_ctype(cls.dtype),
+ value=value,svalue=svalue,dim=1,**kwds)
mcls_dic = {'name':name,
'dtype':dtype,
'_fields':fields,
'_rfields':rfields,
- '_entries':set(fields.keys()).union(set(rfields.keys())),
'fields':__fields,
'rfields':__rfields,
- 'entries':__entries,
'value':__value,
'svalue':__svalue,
'variable':__variable,
+ 'array_variable':__array_variable,
- '__getitem__':__getitem__}
- mcls_dic.update(fields)
- mcls = type(name+'MetaEnum', (EnumFactory.StaticMetaEnum,), mcls_dic)
+ '__getitem__':__getitem__,
+ '__str__':__str__,
+ '__repr__':__repr__}
+ mcls = type(name+'MetaEnum', (EnumFactory.MetaEnum,), mcls_dic)
- class StaticEnum(object):
+ class Enum(base):
__metaclass__=mcls
- def __init__(self):
- raise RuntimeError('An enum should not be instanciated!')
+ def __init__(self, field=sorted(fields.keys())[0]):
+ assert isinstance(field, str) and len(field)>0
+ self._field = field
+ self._value = self.__class__.dtype(self.__class__._fields[field])
+
+ def svalue(self):
+ return self._field
+ def value(self):
+ return self._value
+ def __call__(self):
+ return self.value()
+
+ def __str__(self):
+ return self.svalue()
+ def __repr__(self):
+ return '{}({})'.format(self.svalue(),self.value())
+
+ def __eq__(self, other):
+ assert isinstance(other, self.__class__)
+ return self._value == other._value
+ def __ne__(self, other):
+ assert isinstance(other, self.__class__)
+ return self._value != other._value
+
+ #pickling
+ def __reduce__(self):
+ return (_EnumInstanceGenerator(), (name, self._field))
- generated_enum = type(name+'Enum', (StaticEnum,), {})
- registered_enums[name] = generated_enum
+ generated_enum = type(name+'Enum', (Enum,), {})
+ _all = []
+ for k,v in fields.iteritems():
+ instance = generated_enum(field=k)
+ setattr(mcls, k, instance)
+ _all.append(instance)
+ setattr(generated_enum,'all',_all)
+ registered_enums[name] = generated_enum
return generated_enum
if __name__ == '__main__':
- fields = ['X','Y','Z']
+ fields = {'X':0,'Y':1,'Z':42}
TestEnum = EnumFactory.create('Test', fields)
+ X = TestEnum()
+ Y = TestEnum('Y')
+ Z = TestEnum.Z
+
+ print type(TestEnum)
print TestEnum.__class__
- print TestEnum.dtype
+ print TestEnum.__class__.__name__
print
print TestEnum.fields()
print TestEnum['X'], TestEnum['Y'], TestEnum['Z']
- print TestEnum.X, TestEnum.Y, TestEnum.Z
print
print TestEnum.rfields()
- print TestEnum[0], TestEnum[1], TestEnum[2]
+ print TestEnum[0], TestEnum[1], TestEnum[42]
+ print
+ print TestEnum.X, TestEnum.Y, TestEnum.Z
+ print X, Y, Z
+ print
+ print X.__class__.__name__
+ print X.value(), X()
+ print X.svalue(), str(X)
+ print repr(X), repr(Y), repr(Z)
print
- print TestEnum.entries()
+ print TestEnum.dtype, type(X.value())
diff --git a/hysop/tools/handle.py b/hysop/tools/handle.py
new file mode 100644
index 0000000000000000000000000000000000000000..d62048d741fb17e18cafaf8b262acb92db78e7f8
--- /dev/null
+++ b/hysop/tools/handle.py
@@ -0,0 +1,58 @@
+
+from hysop.deps import ABCMeta
+from hysop.tools.decorators import not_implemented
+
+class Handle(object):
+ """
+ Generic class to encapsulate various objects ('handles').
+ """
+
+ __metaclass__ = ABCMeta
+
+ @classmethod
+ @not_implemented
+ def handle_cls(cls):
+ """
+ Returns the wrapped python type.
+ """
+ pass
+
+ @classmethod
+ @not_implemented
+ def wrap(cls, handle, **kargs):
+ """
+ Build a wrapped instance of handle.
+ """
+ pass
+
+ def __init__(self, handle, **kargs):
+ """
+ Build a Handle from a handle instance.
+
+ Raise ValueError if given handle is None.
+ Raise TypeError if given handle does not match targetted
+ handle type.
+ """
+ super(Handle,self).__init__(**kargs)
+
+ cls = self.__class__
+ handle_cls = cls.handle_cls()
+
+ if (handle is None):
+ msg = 'Handle cannot be None.'
+ raise ValueError(msg)
+
+ if not isinstance(handle, handle_cls):
+ msg='Handle is not a {} but a {}.'
+ msg=msg.format(handle_cls, handle.__class__)
+ raise TypeError(msg)
+
+ self._cls = cls
+ self._handle = handle
+
+ def handle(self):
+ """
+ Return encapsulated handle instance.
+ """
+ return self._handle
+
diff --git a/hysop/tools/hash.py b/hysop/tools/hash.py
new file mode 100644
index 0000000000000000000000000000000000000000..0d44ab8a0e3e35e6f93f39f62cb572a2b7ea4267
--- /dev/null
+++ b/hysop/tools/hash.py
@@ -0,0 +1,22 @@
+
+from hysop.deps import np, hashlib
+
+def hash_communicator(comm, h=None):
+ from hysop.core.mpi import processor_hash
+ phashes = comm.allgather(processor_hash)
+ s = '{}[{}]'.format(comm.Get_size(),
+ ','.join(str(phash) for phash in phashes))
+ if h is not None:
+ h.update(s)
+ else:
+ return s
+
+def hash_nd_array(array, h=None):
+ if h is None:
+ h = hashlib.sha1()
+ h.update(array.view(np.uint8))
+ return h.hexdigest()
+
+def hash_id(obj, length=4):
+ return hashlib.sha1(str(id(obj))).hexdigest()[:length]
+
diff --git a/hysop/tools/io_utils.py b/hysop/tools/io_utils.py
index f508dfb791b7be5f566182233012fae75d597f6b..eef68e9df7ddeb8d9fc9a3a8ccd377678cdd3ece 100755
--- a/hysop/tools/io_utils.py
+++ b/hysop/tools/io_utils.py
@@ -8,16 +8,14 @@
* :class:`~XMF`, tools to prepare/write xmf files.
"""
-import os
+import os, h5py
import scitools.filetable as ft
-import hysop.tools.numpywrappers as npw
+from collections import namedtuple
from inspect import getouterframes, currentframe
-import hysop.mpi as mpi
from re import findall
+
from hysop.tools.parameters import MPIParams
-from collections import namedtuple
-from hysop.constants import S_DIR
-import h5py
+import hysop.core.mpi as mpi
class IO(object):
@@ -196,7 +194,7 @@ class IO(object):
"""
val = field_name + '_' + str(topo.get_id())
if direction is not None:
- val += S_DIR[direction]
+ val += DirectionLabels[direction]
return val
@staticmethod
@@ -327,11 +325,11 @@ class Writer(object):
else:
msg = 'wrong type for mpi_params arg.'
assert isinstance(mpi_params, MPIParams), msg
- self._mpis = mpi_params
+ self.mpi_params = mpi_params
# check if output dir exists, create it if not.
IO.check_dir(self.io_params.filename, self.io_params.io_leader,
- self._mpis.comm)
+ self.mpi_params.comm)
# Shape of the output buffer (must be a 2D numpy array)
if buffshape is None:
@@ -341,6 +339,7 @@ class Writer(object):
'2D shape required : set arg buffshape as a 2D tuple: (x,y)'
# The buffer (numpy array) that will be printed to a file
+ from hysop.tools.numpywrappers import npw
self.buffer = npw.zeros(self._buffshape)
" buffer used to save printed data"
@@ -358,8 +357,8 @@ class Writer(object):
# Force synchro to be sure that all output dirs
# have been created.
- self._mpis.comm.barrier()
- if self._mpis.rank == self.io_params.io_leader:
+ self.mpi_params.comm.barrier()
+ if self.mpi_params.rank == self.io_params.io_leader:
self._file = open(self.io_params.filename, 'w')
def do_write(self, ite):
@@ -373,7 +372,7 @@ class Writer(object):
"""
num = ite + 1 # Number of iterations done
- rk = self._mpis.rank
+ rk = self.mpi_params.rank
return rk == self.io_params.io_leader and \
(num % self.io_params.frequency) == 0
@@ -389,12 +388,12 @@ class Writer(object):
def finalize(self):
"""close, if required"""
- if self._mpis.rank == self.io_params.io_leader:
+ if self.mpi_params.rank == self.io_params.io_leader:
if not self._file.closed:
self._file.close()
def __str__(self):
- if self._mpis.rank == self.io_params.io_leader:
+ if self.mpi_params.rank == self.io_params.io_leader:
s = ' === Writer === \n'
s += ' - filename = ' + self.io_params.filename
s += '\n - buffshape = ' + str(self._buffshape)
@@ -427,7 +426,7 @@ class XMF(object):
Parameters
-----------
- topo : :class:`hysop.mpi.topology.Cartesian`
+ topo : :class:`hysop.core.mpi.topology.Cartesian`
used as reference to define local and global meshes in xdmf file.
dataset_names : list
all datasets names
diff --git a/hysop/tools/misc.py b/hysop/tools/misc.py
index 1781bafdd41ca6a5c3d6e3d66b74cf06bdf6ac76..341f3d37440bba10fb36d10eeb6df6f60e274897 100644
--- a/hysop/tools/misc.py
+++ b/hysop/tools/misc.py
@@ -7,10 +7,40 @@
"""
-import numpy as np
-import hysop.tools.numpywrappers as npw
+from hysop.deps import inspect, np, functools, operator
from hysop.constants import HYSOP_REAL, HYSOP_INTEGER
+def prod(values, neutral=1):
+ """
+ Like sum but for products.
+ """
+ return functools.reduce(operator.mul, values, neutral)
+
+def get_default_args(func):
+ """
+ returns a dictionary of arg_name:default_values for the input function.
+ """
+ args, varargs, keywords, defaults = inspect.getargspec(func)
+ if defaults is None:
+ return dict()
+ else:
+ return dict(zip(args[-len(defaults):], defaults))
+
+def get_argnames(func):
+ """
+ returns arguments name and possible varargs.
+ """
+ argnames,varargs,_,_ = inspect.getargspec(func)
+ return argnames, varargs
+
+def args2kargs(func, args):
+ argnames,_,_,_ = inspect.getargspec(func)
+ return dict(zip(argnames, args))
+
+def kargs2args(func, kargs, remove=[]):
+ argnames,_,_,_ = inspect.getargspec(func)
+ return tuple([kargs[a] for a in argnames if a not in remove])
+
class Utils(object):
"""tools to handle array and slices.
@@ -25,6 +55,24 @@ class Utils(object):
def argsort(seq):
return sorted(range(len(seq)), key=seq.__getitem__)
+ @staticmethod
+ def upper_pow2(x):
+ def _upper_pow2(x):
+ if x<0:
+ raise RuntimeError('x<0')
+ i=0
+ k=2**i
+ while k<x:
+ i+=1
+ k*=2
+ return k
+
+ if np.isscalar(x):
+ return _upper_pow2(x)
+ else:
+ return np.asarray([_upper_pow2(_x) for _x in x])
+
+
@staticmethod
def array_to_dict(inarray):
"""
@@ -104,6 +152,7 @@ class WorkSpaceTools(object):
between several operators thanks to the numpy reshape function.
"""
+ from hysop.tools.numpywrappers import npw
result = []
# print subshape, len(subshape), np.prod(subshape[0])
if isinstance(subshape, list):
@@ -157,6 +206,7 @@ class WorkSpaceTools(object):
@staticmethod
def find_common_workspace(operators, array_type='rwork'):
+ from hysop.tools.numpywrappers import npw
"""Allocate a list of common workspaces able to work
with some given operators
diff --git a/hysop/tools/numerics.py b/hysop/tools/numerics.py
new file mode 100644
index 0000000000000000000000000000000000000000..f140a95cb109a450c23b0c30b69e398329413756
--- /dev/null
+++ b/hysop/tools/numerics.py
@@ -0,0 +1,129 @@
+
+from hysop.constants import HYSOP_REAL, HYSOP_INTEGER, HYSOP_INDEX, HYSOP_BOOL, HYSOP_COMPLEX
+from hysop.deps import np, gmp
+from gmpy2 import mpq,mpz,mpfr,f2q
+
+MPQ = mpq(0).__class__
+MPZ = mpz(0).__class__
+MPFR = mpfr(0).__class__
+F2Q = f2q(0).__class__
+
+def _mpqize(x):
+ if isinstance(x, int) or isinstance(x, long):
+ return mpq(x,1)
+ elif isinstance(x, float):
+ return f2q(x)
+ else:
+ return mpq(str(x))
+mpqize = np.vectorize(_mpqize)
+
+def get_dtype(x):
+ if isinstance(x, np.dtype):
+ return x.type
+ elif hasattr(x, 'dtype'):
+ if callable(x.dtype):
+ return x.dtype
+ elif x.dtype.__class__.__name__ == 'getset_descriptor': # dtype.type has a dtype field...
+ return x
+ else:
+ return x.dtype
+ elif isinstance(x, int) or isinstance(x, long):
+ return np.int64
+ elif isinstance(x, float):
+ return np.float64
+ elif isinstance(x, complex):
+ return np.complex128
+ elif (x is None):
+ return None
+ else:
+ msg='Unknown type in get_dtype (got {}).'
+ msg=msg.format(x.__class__)
+ raise TypeError(msg)
+
+def is_fp(x):
+ types=(np.float16, np.float32, np.float64, np.longdouble)
+ return (get_dtype(x) in types)
+
+def is_signed(x):
+ types = (np.int8, np.int16, np.int32, np.int64)
+ return (get_dtype(x) in types)
+
+def is_unsigned(x):
+ types = (np.bool, np.uint8, np.uint16, np.uint32, np.uint64)
+ return (get_dtype(x) in types)
+
+def is_integer(x):
+ return is_signed(x) or is_unsigned(x)
+
+def is_complex(x):
+ types = (np.complex64, np.complex128, np.clongdouble)
+ return (get_dtype(x) in types)
+
+def match_dtype(x, dtype):
+ xtype = get_dtype(x)
+ if isinstance(dtype,str):
+ if dtype=='f':
+ return np.promote_types(xtype,np.float16)
+ elif dtype=='i':
+ return np.promote_types(xtype,np.int8)
+ elif dtype=='u':
+ return np.promote_types(xtype,np.uint8)
+ elif dtype=='b':
+ return np.promote_types(xtype,HYSOP_BOOL)
+ elif dtype=='c':
+ return np.promote_types(xtype,np.complex64)
+ elif (xtype is None):
+ return dtype
+ elif (dtype is None):
+ return xtype
+ else:
+ return dtype
+ #return np.promote_types(xtype,dtype)
+
+def match_float_type(x):
+ return match_dtype(x,'f')
+
+def match_signed_type(x):
+ return match_dtype(x,'i')
+
+def match_unsigned_type(x):
+ return match_dtype(x,'i')
+
+def match_complex_type(x):
+ return match_dtype(x,'c')
+
+def match_bool_type(x):
+ return match_dtype(x,'b')
+
+def complex_to_float_dtype(dtype):
+ dtype = get_dtype(dtype)
+ assert is_complex(dtype)
+ if dtype == np.complex64:
+ return np.float32
+ elif dtype == np.complex128:
+ return np.float64
+ elif dtype == np.clongdouble:
+ return np.longdouble
+ else:
+ msg=msg.format(dtype)
+ msg='Unknown complex type {}.'
+ raise RuntimeError(msg)
+
+def float_to_complex_dtype(dtype):
+ dtype = get_dtype(dtype)
+ assert is_fp(dtype), '{} is not a float'.format(dtype)
+ if dtype==np.float32:
+ return np.complex64
+ elif dtype==np.float64:
+ return np.complex128
+ elif dtype==np.longdouble:
+ return np.clongdouble
+ else:
+ msg='Unknown float type {}.'
+ msg=msg.format(dtype)
+ raise RuntimeError(msg)
+
+def find_common_dtype(*args):
+ dtypes = [ get_dtype(arg) for arg in args ]
+ return np.find_common_type([], dtypes)
+
diff --git a/hysop/tools/numpywrappers.py b/hysop/tools/numpywrappers.py
index b31e7100ccc2a0366a6d4db70e85d3e4b154bf33..9e72bc6b0d6cf13a97bef278d4b41b9ad4f0b913 100644
--- a/hysop/tools/numpywrappers.py
+++ b/hysop/tools/numpywrappers.py
@@ -1,249 +1,98 @@
-# -*- coding: utf-8 -*-
-"""Interface to numpy arrays, with hysop predifined types for int, real ...
-
-Those functions are useful to enforce hysop predefined types in numpy arrays
-and to keep hysop predefined data layout.
"""
-from hysop.constants import HYSOP_REAL, ORDER, HYSOP_INTEGER,\
- HYSOP_DIM
-import numpy as np
-import scitools.filetable as ft
-bool = np.bool
-
-
-def zeros(shape, dtype=HYSOP_REAL):
- """
- Wrapper to numpy.zeros, force order to hysop.constants.ORDER
- """
- return np.zeros(shape, dtype=dtype, order=ORDER)
-
-
-def ones(shape, dtype=HYSOP_REAL):
- """
- Wrapper to numpy.ones, force order to hysop.constants.ORDER
- """
- return np.ones(shape, dtype=dtype, order=ORDER)
-
-
-def zeros_like(tab):
- """
- Wrapper to numpy.zeros_like, force order to hysop.constants.ORDER
- """
- return np.zeros_like(tab, dtype=tab.dtype, order=ORDER)
-
-
-def ones_like(tab):
- """
- Wrapper to numpy.ones_like, force order to hysop.constants.ORDER
- """
- return np.ones_like(tab, dtype=tab.dtype, order=ORDER)
-
-
-def reshape(tab, shape):
- """
- Wrapper to numpy.reshape, force order to hysop.constants.ORDER
- """
- return np.reshape(tab, shape, order=ORDER)
-
-
-def realempty(tab):
- """
- Wrapper to numpy.empty, force order to hysop.constants.ORDER
- """
- return np.empty(tab, dtype=HYSOP_REAL, order=ORDER)
-
-
-def empty_like(tab):
- """
- Wrapper to numpy.empty_like, force order to hysop.constants.ORDER
- """
- return np.empty_like(tab, dtype=tab.dtype, order=ORDER)
-
-
-def copy(tab):
- """
- Wrapper to numpy.copy, ensure the same ordering in copy.
- """
- return tab.copy(order='A')
-
-
-def asarray(tab):
- """
- Wrapper to numpy.asarray, force order to hysop.constants.ORDER
- """
- return np.asarray(tab, order=ORDER, dtype=tab.dtype)
-
-
-def asrealarray(tab):
- """
- Wrapper to numpy.asarray, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_REAL
- """
- return np.asarray(tab, order=ORDER, dtype=HYSOP_REAL)
-
-
-def const_realarray(tab):
- """
- Wrapper to numpy.asarray, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_REAL.
- Forbid any later change in the content of the array.
- """
- tmp = np.asarray(tab, order=ORDER, dtype=HYSOP_REAL)
- tmp.flags.writeable = False
- return tmp
-
-
-def const_dimarray(tab):
- """
- Wrapper to numpy.asarray, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_DIM.
- Forbid any later change in the content of the array.
- """
- tmp = np.asarray(tab, order=ORDER, dtype=HYSOP_DIM)
- tmp.flags.writeable = False
- return tmp
-
-
-def asintarray(tab):
- """
- Wrapper to numpy.asarray, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_INTEGER.
- """
- return np.asarray(tab, order=ORDER, dtype=HYSOP_INTEGER)
-
-
-def int_zeros(shape):
- """
- Wrapper to numpy.zeros, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_INTEGER.
- """
- return np.zeros(shape, order=ORDER, dtype=HYSOP_INTEGER)
-
-
-def int_ones(shape):
- """
- Wrapper to numpy.ones, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_INTEGER.
- """
- return np.ones(shape, order=ORDER, dtype=HYSOP_INTEGER)
-
-
-def asdimarray(tab):
- """
- Wrapper to numpy.asarray, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_DIM.
- """
- return np.asarray(tab, order=ORDER, dtype=HYSOP_DIM)
-
-
-def asboolarray(tab):
- """
- Wrapper to numpy.asarray, force order to hysop.constants.ORDER
- and type to np.bool.
- """
- return np.asarray(tab, order=ORDER, dtype=np.bool)
-
-
-def dim_ones(shape):
- """
- Wrapper to numpy.ones, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_INTEGER.
- """
- return np.ones(shape, order=ORDER, dtype=HYSOP_DIM)
+Interface to numpy arrays, with hysop predifined types for int, real ...
+Those functions are useful to enforce hysop predefined types in numpy arrays.
+"""
-def dim_zeros(shape):
- """
- Wrapper to numpy.ones, force order to hysop.constants.ORDER
- and type to hysop.constants.HYSOP_DIM.
- """
- return np.zeros(shape, order=ORDER, dtype=HYSOP_DIM)
+from hysop.constants import HYSOP_REAL, HYSOP_COMPLEX, HYSOP_ORDER
+from hysop.constants import HYSOP_INTEGER, HYSOP_INDEX, HYSOP_DIM, HYSOP_BOOL
+from hysop.deps import np as npw
-def equal(a, b):
- """compare two arrays and ensure data types are the same.
- """
- msg = 'You try to compare two values of different '
- msg += 'types : ' + str(np.asarray(a).dtype) + 'and '
- msg += str(np.asarray(b).dtype) + '.'
- assert np.asarray(a).dtype == np.asarray(b).dtype, msg
- return np.equal(a, b)
+##########################
+### EXTRA HYSOP METHODS ##
+def __generate_hysop_type_functions():
+
+ functions = {
-def abs(tab):
+ 'as{type}array':
+'''
+def __hysop_array_generated_method(a, order=HYSOP_ORDER, **kargs):
"""
- Wrapper to numpy.abs, force order to hysop.constants.ORDER
+ Convert the input to an array of dtype HYSOP_{TYPE}.
"""
- return np.abs(tab, order=ORDER, dtype=tab.dtype)
-
-
-def real_sum(tab):
+ dtype = HYSOP_{TYPE}
+ return npw.asarray(a=a, dtype=dtype, order=order, **kargs)
+''',
+ '{type}_prod':
+'''
+def __hysop_array_generated_method(a, axis=None, out=None, **kargs):
"""
- Wrapper to numpy.sum, force type to hysop.constants.HYSOP_REAL.
+ Sum of array elements over a given axis.
"""
- return np.sum(tab, dtype=HYSOP_REAL)
-
-
-def prod(tab, dtype=HYSOP_REAL):
+ dtype = HYSOP_{TYPE}
+ return npw.prod(a=a,axis=axis,out=out,dtype=dtype,**kargs)
+''',
+ '{type}_sum':
+'''
+def __hysop_array_generated_method(a, axis=None, out=None, **kargs):
"""
- Wrapper to numpy.prod
+ Sum of array elements over a given axis.
"""
- return np.prod(tab, dtype=dtype)
+ dtype = HYSOP_{TYPE}
+ return npw.sum(a=a,axis=axis,out=out,dtype=dtype,**kargs)
+''',
-
-def add(a, b, c, dtype=HYSOP_REAL):
+ '{type}_empty':
+'''
+def __hysop_array_generated_method(shape, order=HYSOP_ORDER, **kargs):
"""
- Wrapper to numpy.add
+ Return a new array of given shape and type, without initializing entries.
"""
- return np.add(a, b, c, dtype=dtype)
-
+ dtype = HYSOP_{TYPE}
+ return npw.empty(shape=shape, dtype=dtype, order=order, **kargs)
+''',
-def write_to_file(fname, data, mode='a'):
+ '{type}_ones':
+'''
+def __hysop_array_generated_method(shape, order=HYSOP_ORDER, **kargs):
"""
- write data (numpy array) to file fname
+ Return a new array of given shape filled with ones of type HYSOP_{TYPE}.
"""
- fout = open(fname, mode)
- ft.write(fout, data)
- fout.close()
-
-
-def lock(tab):
+ dtype = HYSOP_{TYPE}
+ return npw.ones(shape=shape, order=order, dtype=dtype, **kargs)
+''',
+
+ '{type}_zeros':
+'''
+def __hysop_array_generated_method(shape, order=HYSOP_ORDER, **kargs):
"""
- Set tab as a non-writeable array
+ Return a new array of given shape, filled with zeros of type HYSOP_{TYPE}.
"""
- tab.flags.writeable = False
-
+ dtype = HYSOP_{TYPE}
+ return npw.zeros(shape=shape, order=order, dtype=dtype, **kargs)
+''',
-def unlock(tab):
+ '{type}_full':
+'''
+def __hysop_array_generated_method(shape, fill_value, order=HYSOP_ORDER, **kargs):
"""
- set tab as a writeable array
+ Return a new array of given shape, filled with fill_value of type HYSOP_{TYPE}.
"""
- tab.flags.writeable = True
+ dtype = HYSOP_{TYPE}
+ return npw.full(shape=shape, fill_value=fill_value, order=order, dtype=dtype, **kargs)
+'''
+}
+
+ hysop_types = ['real', 'complex', 'integer', 'index', 'dim', 'bool']
+ for ht in hysop_types:
+ for fname, fdefinition in functions.iteritems():
+ fname = fname.format(type=ht, TYPE=ht.upper())
+ fdef = fdefinition.format(type=ht, TYPE=ht.upper())
+ exec(fdef)
+ setattr(npw, fname, __hysop_array_generated_method)
-def random(shape):
- """Return an array filled with random values, of type HYSOP_REAL
+__generate_hysop_type_functions()
- Parameters
- ----------
- shape : tuple
- shape of the array
- """
- return asrealarray(np.random.random(shape))
-
-
-# Some useful functions, from http://ipython-books.github.io/featured-01/
-def get_data_base(arr):
- """For a given Numpy array, finds the
- base array that "owns" the actual data."""
- base = arr
- while isinstance(base.base, np.ndarray):
- base = base.base
- return base
-
-
-def arrays_share_data(x, y):
- """Returns true if x and y arrays share the same
- memory location
- """
- return get_data_base(x) is get_data_base(y)
diff --git a/hysop/tools/parameters.py b/hysop/tools/parameters.py
index 1d3f0a80178a7aa9be82bc9bb2326ec3f0dfe85b..33d4749f1ccd7340b6392abf8afa9d9638015c0e 100755
--- a/hysop/tools/parameters.py
+++ b/hysop/tools/parameters.py
@@ -8,18 +8,18 @@
"""
from collections import namedtuple
-from hysop.mpi import main_comm, main_rank, MPI
-from hysop.constants import DEFAULT_TASK_ID
-import hysop.tools.numpywrappers as npw
+from hysop.deps import hashlib
+from hysop.tools.hash import hash_communicator
+from hysop.core.mpi import main_comm, main_rank, MPI
+from hysop.constants import HYSOP_DEFAULT_TASK_ID
-
-class MPIParams(namedtuple('MPIParams', ['comm', 'task_id',
+class MPIParams(namedtuple('MPIParams', ['comm', 'size', 'task_id',
'rank', 'on_task'])):
"""
Struct to save mpi parameters :
- comm : parent mpi communicator (default = main_comm)
- task_id : id of the task that owns this object
- (default = DEFAULT_TASK_ID)
+ (default = HYSOP_DEFAULT_TASK_ID)
- rank of the current process in comm
- on_task : true if the task_id of the object corresponds
to the task_id of the current process.
@@ -38,15 +38,32 @@ class MPIParams(namedtuple('MPIParams', ['comm', 'task_id',
and tell if the current operator belongs to the current process
mpi task.
"""
- def __new__(cls, comm=main_comm, task_id=DEFAULT_TASK_ID,
+ def __new__(cls, comm=main_comm, task_id=HYSOP_DEFAULT_TASK_ID,
rank=main_rank, on_task=True):
if comm != MPI.COMM_NULL:
rank = comm.Get_rank()
+ size = comm.Get_size()
else:
rank = MPI.UNDEFINED
- return super(MPIParams, cls).__new__(cls, comm, task_id,
+ return super(MPIParams, cls).__new__(cls, comm, size, task_id,
rank, on_task)
+ def __eq__(self, other):
+ if self.__class__ != other.__class__:
+ return NotImplemented
+ eq = (self.task_id == other.task_id)
+ eq &= (self.on_task == other.on_task)
+ eq &= (self.comm is other.comm)
+ return eq
+
+ def __ne__(self, other):
+ return not self.__eq__(other)
+
+ def __hash__(self):
+ h = hashlib.sha1()
+ h.update(str(self.task_id))
+ h.update(str(self.on_task))
+ return hash(h.hexdigest()) ^ id(self.comm)
class Discretization(namedtuple("Discretization", ['resolution', 'ghosts'])):
"""
@@ -56,20 +73,21 @@ class Discretization(namedtuple("Discretization", ['resolution', 'ghosts'])):
or array. Default = None.
"""
def __new__(cls, resolution, ghosts=None):
+ from hysop.tools.numpywrappers import npw
resolution = npw.asdimarray(resolution)
if ghosts is not None:
- ghosts = npw.asintarray(ghosts)
+ ghosts = npw.asintegerarray(ghosts)
msg = 'Dimensions of resolution and ghosts parameters'
msg += ' are not complient.'
assert ghosts.size == resolution.size, msg
assert all(ghosts >= 0)
else:
- ghosts = npw.int_zeros(resolution.size)
+ ghosts = npw.integer_zeros(resolution.size)
return super(Discretization, cls).__new__(cls, resolution, ghosts)
def __eq__(self, other):
if self.__class__ != other.__class__:
- return False
+ return NotImplemented
return (self.resolution == other.resolution).all() and\
(self.ghosts == other.ghosts).all()
@@ -78,3 +96,16 @@ class Discretization(namedtuple("Discretization", ['resolution', 'ghosts'])):
if result is NotImplemented:
return result
return not result
+
+ def __str__(self):
+ s = 'discretization:'
+ s+= '\n *resolution: {}'.format(self.resolution)
+ s+= '\n *ghosts: {}'.format(self.ghosts)
+ return s
+
+ def __hash__(self):
+ from hysop.deps import hashlib, np
+ h = hashlib.sha1()
+ h.update(self.resolution.view(np.uint8))
+ h.update(self.ghosts.view(np.uint8))
+ return hash(h.hexdigest())
diff --git a/hysop/tools/problem2dot.py b/hysop/tools/problem2dot.py
index a052a2f97ee497430108e089637c044d80eb1f15..fb5f112c6d702fe7f980a16e3f1259f5809a65bc 100644
--- a/hysop/tools/problem2dot.py
+++ b/hysop/tools/problem2dot.py
@@ -3,7 +3,7 @@
"""
from hysop.operator.advection import Advection
from hysop.operator.redistribute import Redistribute, RedistributeInter
-from hysop.mpi import main_rank
+from hysop.core.mpi import main_rank
import pydot
colors = [
"#dc322f",
diff --git a/hysop/tools/profiler.py b/hysop/tools/profiler.py
index 11fee02cde070936e33ceb6e9414d37d61baad5b..219306570db0c6c0f177493c893f9f45a5f465fe 100644
--- a/hysop/tools/profiler.py
+++ b/hysop/tools/profiler.py
@@ -1,9 +1,9 @@
"""Tools to collect time profiling information
for hysop classes.
"""
-from hysop.mpi import Wtime as ftime
-from hysop.mpi import main_rank
-import hysop.tools.numpywrappers as npw
+from hysop.core.mpi import Wtime as ftime
+from hysop.core.mpi import main_rank
+from hysop.tools.numpywrappers import npw
import numpy as np
diff --git a/hysop/tools/string_utils.py b/hysop/tools/string_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..5805986538ea081c59126507ad2f7cc58f79c36e
--- /dev/null
+++ b/hysop/tools/string_utils.py
@@ -0,0 +1,21 @@
+import re
+
+def camel2snake(string):
+ """
+ Convert a string from camel case to snake case.
+ """
+ s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', string)
+ return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()
+
+def prepend(string, prefix):
+ """
+ Append prefix after each line return in string.
+ """
+ lines=[]
+ for s in string.split('\n'):
+ if s:
+ lines.append(prefix+s)
+ else:
+ lines.append(s)
+ return '\n'.join(lines)
+
diff --git a/hysop/tools/sympy_utils.py b/hysop/tools/sympy_utils.py
index 143183631dd154aa47077c8207c4106bfdd221f3..02b57d8c220cd753ec3b5fff6915a605059cdea4 100644
--- a/hysop/tools/sympy_utils.py
+++ b/hysop/tools/sympy_utils.py
@@ -1,16 +1,15 @@
-import operator
-import numpy as np
-import sympy as sm
-
-subscript_decimals = ['\u208{}'.format(i).decode('unicode-escape') for i in xrange(10)]
-subscript_signs = [u'\u208a',u'\u208b']
-subscript_parenthesis = [u'\u208d', u'\u208e']
-
-def prod(it,init=1):
- return reduce(operator.mul, it, init)
+from hysop.deps import np, sm, copy
+
+# unicode subscripts for decimal numbers, signs and parenthesis
+dec = ['\u208{}'.format(i).decode('unicode-escape') for i in xrange(10)]
+sign = [u'\u208a',u'\u208b']
+parenthesis = [u'\u208d', u'\u208e']
def subscript(i,with_sign=False):
+ """
+ Generate an unicode subscript of value i, sign can be enforced.
+ """
decimals = '0123456789'
snumber = str(i)
if with_sign:
@@ -20,31 +19,45 @@ def subscript(i,with_sign=False):
out = u''
for s in snumber:
if s in decimals:
- out += subscript_decimals[int(s)]
+ out += dec[int(s)]
elif s=='+':
- out += subscript_signs[0]
+ out += sign[0]
elif s=='-':
- out += subscript_signs[1]
+ out += sign[1]
else:
out += s
return out
def subscripts(ids,sep,with_sign=False,with_parenthesis=False,prefix=''):
+ """
+ Generate a unicode tuple subscript separated by sep,
+ with or without parenthesis, prefix, and sign.
+ """
if with_parenthesis:
return u'{}{}{}{}'.format(prefix,parenthesis[0],sep.join([subscript(i,with_sign) for i in ids]),parenthesis[1])
else:
return u'{}{}'.format(prefix,sep.join([subscript(i,with_sign) for i in ids]))
-def tensor_symbol(prefix,shape,mask=None,origin=None,sep=None,with_parenthesis=False,force_sign=False):
- origin = np.asarray(origin) if origin is not None else np.asarray([0]*len(shape))
+def tensor_symbol(prefix,shape,origin=None,mask=None,
+ sep=None,with_parenthesis=False,force_sign=False):
+ """
+ Generate a np.ndarray of sympy.Symbol.
+ Each of the symbol has given prefix and subscripts are
+ taken from specified origin if specified or else in matrix/tensor notation.
+ Other parameters handles subscripts style, see the subscripts() function.
+
+ It also returns all generated Symbols as a list.
+ """
+ origin = origin if origin is not None else np.asarray([0]*len(shape))
sep = sep if sep is not None else u','
with_sign = force_sign or ((origin>0).any() and len(shape)>1)
tensor = np.empty(shape=shape,dtype=object)
for idx in np.ndindex(*shape):
- ids = idx-origin
- sname = subscripts(ids,sep,with_sign=with_sign,with_parenthesis=with_parenthesis,prefix=prefix)
- if mask is None or mask[idx]:
+ if (mask is None) or mask[idx]:
+ ids = idx-origin
+ sname = subscripts(ids,sep,with_sign=with_sign,
+ with_parenthesis=with_parenthesis,prefix=prefix)
tensor[idx] = sm.Symbol(sname.encode('utf-8'), real=True)
else:
tensor[idx] = 0
@@ -52,30 +65,82 @@ def tensor_symbol(prefix,shape,mask=None,origin=None,sep=None,with_parenthesis=F
return tensor, tensor_vars
def tensor_xreplace(tensor,vars):
+ """
+ Performs an xreplace and all tensor (np.ndarray) elements.
+ """
T = tensor.copy()
for idx in np.ndindex(*tensor.shape):
symbol = tensor[idx]
- try:
+ if isinstance(symbol,sm.Expr):
if (symbol in vars.keys()):
T[idx] = vars[symbol]
elif (symbol.name in vars.keys()):
T[idx] = vars[symbol.name]
- except:
- pass
return T
-def factor_split(expr,variables,include_vars=False):
+
+def non_eval_xreplace(expr, rule):
+ """
+ Duplicate of sympy's xreplace but with non-evaluate statement included.
+ """
+ if expr in rule:
+ return rule[expr]
+ elif rule:
+ args = []
+ altered = False
+ for a in expr.args:
+ try:
+ new_a = non_eval_xreplace(a, rule)
+ except AttributeError:
+ new_a = a
+ if new_a != a:
+ altered = True
+ args.append(new_a)
+ args = tuple(args)
+ if altered:
+ return expr.func(*args, evaluate=False)
+ return expr
+
+# Convert powers to mult. in polynomial expressions V
+# Example: x^3 -> x*x*x
+def remove_pows(expr):
+ """
+ Convert pows to multiplications: x^3 -> x*x*x
+ """
+ pows = list(expr.atoms(sm.Pow))
+ repl = [sm.Mul(*[b]*e,evaluate=False) for b,e in [i.as_base_exp() for i in pows]]
+ e = non_eval_xreplace(expr,dict(zip(pows,repl)))
+ return e
+
+def evalf_str(x,n,literal='',significant=True):
+ """
+ Call evalf on x up to n-th decimal and removes zeros
+ if significant is set.
+ """
+ x = x.evalf(n).__str__()
+ if significant:
+ i=len(x)
+ while i>1 and x[i-1] == '0':
+ i-=1
+ if i>1:
+ x = x[:i+1]
+ return x+literal
+
+def factor_split(expr,variables,constant_var=None,include_var=False,init=0,_factor=True,_handle_const=True):
+ """
+ Factorize and split expresssion.
+ """
expr = expr.expand()
factors = {}
for var in variables:
- factors[var] = 0
+ factors[var] = init
for arg in expr.args:
I = arg.atoms(sm.Symbol).intersection(variables)
if len(I)==0:
continue
elif len(I)==1:
var = I.pop()
- if not include_vars:
+ if not include_var:
arg = arg.xreplace({var:1})
factors[var] += arg
else:
@@ -83,6 +148,11 @@ def factor_split(expr,variables,include_vars=False):
return factors
def build_eqs_from_dicts(d0,d1):
+ """
+ Build equations from two dictionnaries (lhs and rhs).
+ ie. rhs-lhs = 0
+ For keys that are only present in one dictionary, the other operand is set to 0.
+ """
treated = []
eqs = []
for k in d0.keys():
@@ -101,17 +171,12 @@ def build_eqs_from_dicts(d0,d1):
eqs.append(de)
return eqs
-def recurse_expression_tree(op,expr):
+def recurse_expression_tree(op, expr):
+ """
+ Recurse through sympy expression tree and apply op on each subexpression.
+ """
op(expr)
if isinstance(expr, sm.Expr):
- for e in expr.args:
- recurse_expression_tree(op,e)
+ for arg in expr.args:
+ recurse_expression_tree(op, arg)
-
-if __name__ == '__main__':
- tensor, _ = tensor_symbol('T',(2,4),(0,0))
- print tensor
- print
-
- tensor, _ = tensor_symbol('P',(3,3),(1,1))
- print tensor
diff --git a/hysop/tools/sys_utils.py b/hysop/tools/sys_utils.py
index 0767cf2bb2e2c5972f03f46111599acfd428021f..00f146fff21a03cc76da5ee4b1ce0fcb3aa65287 100755
--- a/hysop/tools/sys_utils.py
+++ b/hysop/tools/sys_utils.py
@@ -1,7 +1,6 @@
"""Tools related to global config.
"""
-import sys
-
+import sys, os
class SysUtils(object):
"""
@@ -25,3 +24,13 @@ class SysUtils(object):
used.
"""
return hasattr(sys, 'ps1') or hasattr(sys, 'ipcompleter')
+
+ @staticmethod
+ def cmd_exists(cmd):
+ """
+ Returns True if cmd exists.
+ """
+ return any(
+ os.access(os.path.join(path, cmd), os.X_OK)
+ for path in os.environ["PATH"].split(os.pathsep)
+ )
diff --git a/hysop/tools/tests/test_profiler.py b/hysop/tools/tests/test_profiler.py
index 370b88969202fda28fde5c104df6fe4b5a8b6cc7..bca3f0a6d93d8e70fc5a25a7508d04a92da5e2f1 100755
--- a/hysop/tools/tests/test_profiler.py
+++ b/hysop/tools/tests/test_profiler.py
@@ -1,7 +1,7 @@
"""Unitary tests for hysop.tools.profiler module
"""
from hysop.tools.profiler import Profiler, profile, FProfiler, ftime
-from hysop.mpi import main_comm
+from hysop.core.mpi import main_comm
class A_class(object):
diff --git a/hysop/tools/tests/test_work_arrays.py b/hysop/tools/tests/test_work_arrays.py
index e6f79b488f125435c6fc44051c7cf36959f47809..3b7f9ddf2063aaecfedb64b4199843219e8ebe4c 100644
--- a/hysop/tools/tests/test_work_arrays.py
+++ b/hysop/tools/tests/test_work_arrays.py
@@ -7,7 +7,7 @@ import numpy as np
from hysop import Field, Box
from hysop.operators import Stretching, EnergyEnstrophy, Curl
from hysop.tools.misc import WorkSpaceTools
-import hysop.tools.numpywrappers as npw
+from hysop.tools.numpywrappers import npw
from hysop.constants import HYSOP_REAL, HYSOP_INTEGER
cos = np.cos
diff --git a/hysop/tools/types.py b/hysop/tools/types.py
new file mode 100644
index 0000000000000000000000000000000000000000..02db6b0bba4855f107f4f77126edf951b50fcb68
--- /dev/null
+++ b/hysop/tools/types.py
@@ -0,0 +1,108 @@
+
+from hysop.deps import np
+
+class InstanceOf(object):
+ def __init__(self, cls):
+ assert isinstance(cls,type)
+ self.cls = cls
+ def match_instance(self, obj):
+ return isinstance(obj,self.cls)
+ def __str__(self):
+ return 'InstanceOf({})'.format(self.cls.__name__)
+
+def check_instance(val, cls, allow_none=False, **kargs):
+ """
+ raise a TypeError if val is not an instance of cls.
+ specialized for some types.
+ """
+ if (val is None):
+ if allow_none:
+ return
+ else:
+ raise ValueError('value cannot be None.')
+
+ allcls=to_tuple(cls)
+
+ if not any((isinstance(val, cls) for cls in allcls)):
+ msg = 'Expected a {} but got a value of class {}.'
+ msg = msg.format(cls.__name__, val.__class__.__name__)
+ raise TypeError(msg)
+ if cls in [list,tuple,set] and ('values' in kargs):
+ val_cls = kargs.pop('values')
+ for v in val:
+ if not isinstance(v,val_cls):
+ msg='Value contained in given {} is not an instance of {}.'
+ msg=msg.format(cls.__name__, val_cls.__name__)
+ raise TypeError(msg)
+ if cls in [dict]:
+ if 'keys' in kargs:
+ key_cls = kargs.pop('keys')
+ for k,v in val.iteritems():
+ if not isinstance(k,key_cls):
+ msg='Key contained in {} is not an instance of {}, got {}.'
+ msg=msg.format(cls.__name__, key_cls.__name__, k.__class__)
+ raise TypeError(msg)
+ if 'values' in kargs:
+ val_cls = kargs.pop('values')
+ for k,v in val.iteritems():
+ if not isinstance(v,val_cls):
+ if hasattr(k, 'name'):
+ key=k.name
+ msg='Value contained in {} at key \'{}\' is not an instance of {}, got {}.'
+ msg=msg.format(cls.__name__, k, val_cls, v.__class__)
+ raise TypeError(msg)
+ if kargs:
+ raise RuntimeError('Some arguments were not used ({}).'.format(kargs))
+
+
+
+def to_tuple(arg):
+ if isinstance(arg, tuple):
+ return arg
+ elif isinstance(arg, list) or isinstance(arg,set):
+ return tuple(arg)
+ elif isinstance(arg, np.ndarray):
+ return tuple(x for x in arg)
+ else:
+ return (arg,)
+
+def to_list(arg):
+ if isinstance(arg, list):
+ return arg
+ elif isinstance(arg, tuple) or isinstance(arg,set):
+ return list(arg)
+ elif isinstance(arg, np.ndarray):
+ return arg.tolist()
+ else:
+ return [arg]
+
+def to_set(arg):
+ if isinstance(arg, set):
+ return arg
+ elif isinstance(arg, tuple) or isinstance(arg,list):
+ return set(arg)
+ elif isinstance(arg, np.ndarray):
+ return set([x for x in arg])
+ else:
+ return set([arg])
+
+def extend_array(value, dim, dtype=None, fillval=None):
+ """
+ Extend value to have specified dimension.
+ If fillval is None, the last value is used to complete the array.
+ Returns a np.ndarray of specified dtype and size dim.
+ """
+ value = to_list(value)
+ assert len(value)<=dim
+ if fillval==None:
+ fillval = value[-1]
+ value = np.asarray( value + [fillval]*(dim-len(value)), dtype=dtype)
+ return value
+
+def first_not_None(a0,*args):
+ if len(args)==0:
+ return next((a for a in a0 if a is not None), None)
+ else:
+ return next((a for a in (a0,)+args if a is not None), None)
+
+
diff --git a/hysop/tools/units.py b/hysop/tools/units.py
new file mode 100644
index 0000000000000000000000000000000000000000..190c5e307fc98db658fd448b714997232ed95f2e
--- /dev/null
+++ b/hysop/tools/units.py
@@ -0,0 +1,54 @@
+from hysop.deps import np
+
+def binary_unit2str(b,unit,rounded):
+ bb=int(b)
+ prefix=['','ki','Mi','Gi','Ti','Pi','Ei','Zi','Yi']
+ i=0
+ while bb>=1024:
+ bb>>=10
+ i+=1
+ return '{}{}{}'.format(round(b/2.0**(10*i),rounded),prefix[i],unit)
+
+def decimal_unit2str(b,unit,rounded):
+ bb=int(b)
+ prefix=['','k','M','G','T','P','E','Z','Y']
+ i=0
+ while bb>=1000:
+ bb/=1000
+ i+=1
+ return '{}{}{}'.format(round(b/10.0**(3*i),rounded),prefix[i],unit)
+
+def unit2str(b,unit,decimal,rounded=2):
+ if not isinstance(b, (int,long,float,np.integer,np.floating)):
+ return b
+
+ if decimal:
+ return decimal_unit2str(b,unit,rounded)
+ else:
+ return binary_unit2str(b,unit,rounded)
+
+def bytes2str(b,decimal=True,rounded=2):
+ return unit2str(b,'B',decimal)
+
+def bdw2str(bdw,decimal=True,rounded=2):
+ return unit2str(bdw,'B/s',decimal,rounded)
+
+def freq2str(freq,decimal=True,rounded=2):
+ return unit2str(freq,'Hz',decimal,rounded)
+
+
+def time2str(t, on_zero=None, on_none=None):
+ if not isinstance(t, (float,int,long,np.dtype)):
+ return t
+ if t is None:
+ return (on_none or '{:8d}'.format(-1))
+ elif t<1e-9:
+ return (on_zero or '{:8d}'.format(0))
+ elif t<1e-6:
+ return '{:>6.1f}ns'.format(t*1e9)
+ elif t<1e-3:
+ return '{:>6.1f}us'.format(t*1e6)
+ elif t<1e+1:
+ return '{:>6.1f}ms'.format(t*1e3)
+ else:
+ return '{:>6.2f}s'.format(t)
diff --git a/precision.conf.in b/precision.conf.in
new file mode 100644
index 0000000000000000000000000000000000000000..684320ca931385dc5c178002b9ba45e74bf33e5f
--- /dev/null
+++ b/precision.conf.in
@@ -0,0 +1,23 @@
+!> Select float precision for the whole code.
+!! This is a generated file, do not edit.
+!! Usage :
+!! cmake -DDOUBLEPREC=ON ...
+!! with value = simple or value = double
+module precision
+
+ use mpi, only: MPI_DOUBLE_PRECISION, MPI_FLOAT
+ use, intrinsic :: iso_c_binding
+ use, intrinsic :: iso_fortran_env
+
+ implicit none
+ !> Floats precision
+ integer, parameter :: sp = REAL32
+ integer, parameter :: dp = 8!REAL64
+ !> Chosen precision (set during config. using -DDOUBLEPREC=... with cmake)
+ integer, parameter :: wp = @WORKING_PRECISION@
+ !> integer precision
+ integer, parameter :: ip = 8!int64
+ !> MPI type for float
+ integer, parameter :: MPI_REAL_WP = @MPI_PRECISION@
+
+end module precision
diff --git a/setup.py.in b/setup.py.in
index fc07171d8e85d9ceec8f272f9b36bd5c306ea6a3..8aeb7c90af78cda61ed8c9da32599d1d41c7caa0 100644
--- a/setup.py.in
+++ b/setup.py.in
@@ -1,7 +1,6 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
-"""
-setup.py file for @PYPACKAGE_NAME@
+"""setup.py file for @PYPACKAGE_NAME@
"""
from setuptools import find_packages
@@ -16,26 +15,51 @@ import fnmatch
# tools to deal with fortran dependencies.
import sys
-sys.path.append('@CMAKE_SOURCE_DIR@/')
+sys.path.append('@CMAKE_BINARY_DIR@/')
import sort_f90
-enable_cpp = "@WITH_LIB_CXX@"
+# --- Check if c++ interface is enabled ---
+enable_cpp = "@USE_CXX@"
if enable_cpp:
swig_executable = find_executable("@SWIG_EXECUTABLE@")
def parseCMakeVar(var):
+ """
+ Post-process cmake list-like variables.
+
+ Example::
+
+ a = parseCMakeVar("var1;var2;var3;")
+ # --> a = ['var', 'var2', 'var3']
+ """
if var != "":
- return var.split(';')
+ res = list(set(var.split(';')))
+ # list/set stuff to avoid duplicates
+ # remove empty strings to avoid '-I -I' things leading to bugs
+ if res.count(''):
+ res.remove('')
+ return res
else:
- return None
+ return []
+
def parseCMakeDefines(var):
+ """
+ Post-process cmake variables, corresponding
+ to pre-processor definitions.
+
+ Example::
+
+ res = parseCMakeDefines("-DVAR=VAL1:-DVAR2=VAL2:-DVAR3=VAL3")
+ # --> res = [('VAR', 'VAL1'), ('VAR2', 'VAL2'), ('VAR3', 'VAL3')]
+ """
defines = parseCMakeVar(var)
- if defines == None:
+ if len(defines)==0:
return None
-
- # regex to match compiler defines like -DMACRO_NAME or -DMACRO_NAME = MACRO_VALUE
+
+ # regex to match compiler defines like -DMACRO_NAME or
+ # -DMACRO_NAME = MACRO_VALUE
p = re.compile('\s*(?:-D)?\s*(\w+)(?:\s*=\s*(\w+))?\s*')
res = list()
@@ -44,26 +68,57 @@ def parseCMakeDefines(var):
if m:
res.append(m.group(1,2))
else:
- print "\tWarning: Could extract cmake define from '",d,"'."
+ print "\tWarning: Could not extract cmake define from '", d, "'."
return res
-
+# --- external libraries to be linked with ---
hysop_link_libraries = parseCMakeVar("@HYSOP_LINK_LIBRARIES@")
-hysop_link_libraries_names = set([])
-hysop_link_libraries_dirs = set([])
-# use set to avoid dupl.
-link_list = ""
+
+# deal with macosx framework ...
+extra_flags = []
for lib in hysop_link_libraries:
- hysop_link_libraries_names.add(os.path.basename(lib))
- hysop_link_libraries_dirs.add(os.path.dirname(lib))
- link_list += lib + " "
-hysop_link_libraries_names = list(hysop_link_libraries_names)
-hysop_link_libraries_dirs = list(hysop_link_libraries_dirs)
+ res = lib.find('framework')
+ if res >= 0:
+ index = hysop_link_libraries.index(lib)
+ filename = os.path.basename(lib)
+ hysop_link_libraries.pop(index)
+ filename = filename.split('.')[0]
+ extra_flags.append('-framework ' + filename)
+hysop_link_libraries += extra_flags
def create_fortran_extension(name, pyf_file=None, src_dirs=None, sources=None,
libdir=None, libs=None, debug_mode=0):
"""Create a new f2py module from fortran files
+
+ Parameters
+ ----------
+ name: string
+ python module name
+ pyf_file: string, optional
+ f2py interface file (absolute path)
+ src_dirs: list, optional
+ all directories containing fortran sources (absolute path)
+ that must be taken into account. Warning: dir. scan is not
+ recursive.
+ sources: list, optional
+ all fortran files that must be taken into account
+ libs: list of strings, optional
+ names of all libraries to be linked with to build f2py module
+ --> for -l option
+ libdir: list of strings, optional
+ list of directories, absolute path to libraries listed in libs
+ --> for -L... option
+ debug_mode: boolean, optional
+ if true enable f2py debug mode, default=False
+
+ Notes
+ -----
+ * either sources or src_dirs is required but both
+ can be used simultaneously.
+ * only .f90 and .f95 files are taken into account.
"""
+
+ # --- Collect list of fortran files ---
if sources is None:
sources = []
assert src_dirs is not None
@@ -71,34 +126,33 @@ def create_fortran_extension(name, pyf_file=None, src_dirs=None, sources=None,
for sdir in src_dirs:
sources += glob.glob(os.path.join(sdir, '*.f95'))
sources += glob.glob(os.path.join(sdir, '*.f90'))
- f2py_options = ['--no-lower', '--no-wrap-functions']
- options = []
+
# Reorder source list with fortran modules
# dependencies. It seems that this is not taken into
# account in f2py or distutils.
if pyf_file is not None:
sources.append(pyf_file)
sources = sort_f90.sort(sources)
- if debug_mode > 0:
+ # --- set f2py options ---
+ f2py_options = ['--no-lower', '--no-wrap-functions']
+ options = []
+ if debug_mode == 1:
options.append(('F2PY_REPORT_ON_ARRAY_COPY', '1'))
if os.uname()[0] == 'Linux':
options.append(('F2PY_REPORT_ATEXIT', '1'))
- inc_dir = '@MPI_Fortran_INCLUDE_PATH@'.split(';')
- # To avoid -I -I in compiler call, which results in a bug:
- while inc_dir.count('') > 0:
- inc_dir.remove('')
- inc_dir.append('@CMAKE_BINARY_DIR@/Modules')
+
+ # --- set include dir ---
+ inc_dir = parseCMakeVar("@FORTRAN_INCLUDE_DIRS@")
+ inc_dir += parseCMakeVar("@MPI_Fortran_INCLUDE_PATH@")
+ inc_dir += parseCMakeVar('@CMAKE_Fortran_MODULE_DIRECTORY@')
+
+ # --- set compilation flags ---
fortran_flags = ['@Fortran_FLAGS@']
-
- #includes = parseCMakeVar("@FORTRAN_INCLUDE_DIRS@")
- #if(includes != None):
- #for exti in includes:
- #inc_dir.append(exti)
- #libs += hysop_link_libraries_names
- #libdir += hysop_link_libraries_dirs
+
# we trust cmake for external libraries and
# add them to linker, without using libraries option
extra_link_args = hysop_link_libraries
+
ext_fort = Extension(name=name,
sources=sources,
f2py_options=f2py_options,
@@ -114,39 +168,58 @@ def create_fortran_extension(name, pyf_file=None, src_dirs=None, sources=None,
def create_swig_extension(name, inc_dirs, src_dirs=None, sources=None):
"""Create a python module from C++ files, using swig
+
+ Parameters
+ ----------
+ name: string
+ module name
+ inc_dirs: list
+ list of directories for includes (-I ...), absolute path
+ containing headers (.hpp) and swig files (.i)
+ sources: list, optional
+ all c++ files that must be taken into account
+ src_dirs: list, optional
+ all directories containing fortran sources (absolute path)
+ that must be taken into account. Warning: no recursive scan
+ in src_dirs.
+
+ Notes
+ -----
+ * either sources, src_dirs or inc_dirs is required but all
+ can be used simultaneously.
+ * only .cpp files are taken into account.
+ * main config file for swig is assumed to be
+ name.i in CMAKE_SOURCE_DIR/swig/
+
"""
- swig_dir = os.path.join('@CMAKE_SOURCE_DIR@', 'swig')
- swig_config_file = os.path.join(swig_dir, name+'.i')
+ swig_dir = os.path.join('@CMAKE_SOURCE_DIR@', 'swig')
+ swig_config_file = os.path.join(swig_dir, name + '.i')
include_dirs = set(inc_dirs)
if sources is None:
sources = []
- if(src_dirs == None):
- assert(inc_dirs != None)
- for idir in inc_dirs:
- #sources += glob.glob(os.path.join(idir, '**/*.cpp'), recursive=True)
- for root, dirnames, filenames in os.walk(idir):
- for filename in fnmatch.filter(filenames, '*.cpp'):
- sources.append(os.path.join(root, filename))
- else:
- for sdir in src_dirs:
- sources += glob.glob(os.path.join(sdir, '*.cpp'))
- #else:
- #for f in sources:
- #include_dirs.add(os.path.dirname(f))
+ assert (src_dirs is not None) or (inc_dirs is not None)
+ if(src_dirs is None):
+ assert(inc_dirs is not None)
+ for idir in inc_dirs:
+ for root, dirnames, filenames in os.walk(idir):
+ for filename in fnmatch.filter(filenames, '*.cpp'):
+ sources.append(os.path.join(root, filename))
+ else:
+ for sdir in src_dirs:
+ sources += glob.glob(os.path.join(sdir, '*.cpp'))
- sources.insert(0,swig_config_file)
+ sources.insert(0, swig_config_file)
include_dirs = list(include_dirs)
name = 'hysop._' + name
swig_opts = ['-I' + swig_dir,
'-O', '-Wextra', '-Werror',
'-c++', '-extranative', '-safecstrings']
-
+
extern_includes = parseCMakeVar("@CXX_EXT_INCLUDES@")
- if(extern_includes != None):
- for exti in extern_includes:
- include_dirs.append(exti)
+ for exti in extern_includes:
+ include_dirs.append(exti)
libraries = parseCMakeVar("@CXX_EXT_LIBS@")
library_dirs = parseCMakeVar("@CXX_EXT_LIB_DIRS@")
@@ -170,38 +243,15 @@ def create_swig_extension(name, inc_dirs, src_dirs=None, sources=None):
# List of modules (directories) to be included
with_test = "@WITH_TESTS@" is "ON"
if with_test:
- packages = find_packages(exclude=["*fakef2py*", "*gpu*"],where="@CMAKE_SOURCE_DIR@")
+ packages = find_packages(exclude=["*opencl*"], where="@CMAKE_SOURCE_DIR@")
else:
- packages = find_packages(exclude=["*tests*","*fakef2py*", "*gpu*"],where="@CMAKE_SOURCE_DIR@")
-
-# packages = ['hysop',
-# 'hysop.domain',
-# 'hysop.fields',
-# 'hysop.operator',
-# 'hysop.operator.discrete',
-# 'hysop.problem',
-# 'hysop.tools',
-# 'hysop.numerics',
-# 'hysop.numerics.integrators',
-# ]
-
-# packages_for_tests = ['hysop.domain.tests',
-# 'hysop.fields.tests',
-# 'hysop.operator.tests',
-# 'hysop.numerics.tests',
-# 'hysop.tools.tests',
-# 'hysop.problem.tests',
-# 'hysop.numerics.tests',
-# ]
-
-# if "@USE_MPI@" is "ON":
-# packages.append('hysop.mpi')
-# packages_for_tests.append('hysop.mpi.tests')
+ packages = find_packages(exclude=["*tests*", "*opencl*"],
+ where="@CMAKE_SOURCE_DIR@")
if "@WITH_GPU@" is "ON":
- packages.append('hysop.gpu')
+ packages.append('hysop.backend.device.opencl')
if with_test:
- packages.append('hysop.gpu.tests')
+ packages.append('hysop.backend.device.opencl.tests')
# Enable this to get debug info
DISTUTILS_DEBUG = 1
@@ -221,44 +271,57 @@ if enable_fortran is "ON":
hysoplib = ['@HYSOP_LIBRARY_NAME@']
f2py_options = ['--no-lower']
fortran_src = set([])
- fortran_src.add('f2py/parameters.f90')
+ # -- list of directories which contains fortran sources --
+ # path must be relative to hysop package directory
+ subdirs = ['common_f', ]
+
+ ####fortran_src.add('f2py/parameters.f90')
# -- fftw fortran sources --
withfftw = "@WITH_FFTW@"
if withfftw is "ON":
- fortran_src.add('f2py/fftw2py.f90')
+ subdirs.append(os.path.join('numerics', 'fftw_f'))
fftwdirs = parseCMakeVar('@FFTWLIB@')
hysop_libdir.extend(fftwdirs)
- else:
- packages.append('hysop.fakef2py')
- packages.append('hysop.fakef2py.fftw2py')
+
# -- scales sources --
withscales = '@WITH_SCALES@'
if withscales is "ON":
- fortran_src.add('f2py/scales2py.f90')
- else:
- packages.append('hysop.fakef2py')
- packages.append('hysop.fakef2py.scales2py')
+ subdirs.append('scales_f')
+ #fortran_src.add('f2py/scales2py.f90')
+
+
+ # -- other fortran sources --
+ withextras = '@WITH_EXTRAS@'
+ if withextras is "ON":
+ subdirs.append(os.path.join('numerics', 'extras_f'))
+
# -- set full path to fortran sources --
fortran_src = list(fortran_src)
for i in xrange(len(fortran_src)):
fortran_src[i] = os.path.join(fortran_root, fortran_src[i])
+ precision_file = os.path.join('@GENERATED_FORTRAN_FILES_DIR@',
+ 'precision.f95')
+ fortran_src.insert(0, precision_file)
+
# === Draft for future implementation of fortran interface ===
# -- f2py signature file --
- pyf_file = os.path.join(fortran_root, 'f2hysop.pyf')
- # -- list of directories which contains fortran sources --
- # those dirs must be in hysop package directory
- subdirs = ['fortran',]
+ f2hysop = "@F_2_HYSOP@"
+ pyf_file = os.path.join('@GENERATED_FORTRAN_FILES_DIR@', f2hysop+'.pyf')
+ # change from relative path in subdirs to absolute path in num_dirs
num_dirs = []
for sd in subdirs:
num_dirs.append(os.path.join(fortran_root, sd))
-
+
+ hysop_libdir = [ld.strip() for ld in hysop_libdir]
+ # hysop_libdir = ' '.join([ '-L{}'.format(ld) if ld[1]!='L' else hysop_libdir])
+ num_dirs.append('@GENERATED_FORTRAN_FILES_DIR@')
# create python interface to fortran sources
# For the moment, it includes the 'old' interface
# to scales and fftw (in sources) and the new
# interface, in src_dirs
- ext['f2hysop'] = create_fortran_extension(
- name='hysop.f2hysop',
+ ext[f2hysop] = create_fortran_extension(
+ name='hysop.'+f2hysop,
sources=fortran_src,
libdir=hysop_libdir,
libs=hysoplib,
@@ -268,12 +331,6 @@ if enable_fortran is "ON":
for ex in ext:
ext_modules.append(ext[ex])
-else:
- packages.append('hysop.fakef2py')
- packages.append('hysop.fakef2py.scales2py')
- packages.append('hysop.fakef2py.fftw2py')
-
-
# --- C++ files and swig interface --
if enable_cpp is "ON":
@@ -281,27 +338,28 @@ if enable_cpp is "ON":
swig_include_dirs = [os.path.join('@CMAKE_SOURCE_DIR@','swig')]
cpp_include_dirs = ['src/fftw','src/hysop++/src']
- for id in cpp_include_dirs:
- swig_include_dirs.append(os.path.join('@CMAKE_SOURCE_DIR@', id))
+ for d in cpp_include_dirs:
+ swig_include_dirs.append(os.path.join('@CMAKE_SOURCE_DIR@', d))
ext = {}
cpp2hysop = "@CPP_2_HYSOP@"
- ext[cpp2hysop] = create_swig_extension(name=cpp2hysop, inc_dirs=swig_include_dirs)
+ ext[cpp2hysop] = create_swig_extension(name=cpp2hysop,
+ inc_dirs=swig_include_dirs)
for ex in ext:
ext_modules.append(ext[ex])
data_files = []
-if "@WITH_GPU@" is "ON":
- cl_src_dirs = ["cl_src", "cl_src/kernels",
- "cl_src/advection", "cl_src/remeshing"]
- for cl_dir in cl_src_dirs:
- data_files.append(
- ('./hysop/gpu/' + cl_dir,
- ['@CMAKE_SOURCE_DIR@/hysop/gpu/' + cl_dir + '/'
- + cl_file
- for cl_file in os.listdir(
- '@CMAKE_SOURCE_DIR@/hysop/gpu/' + cl_dir + '/')
- if cl_file[0] != '.' and cl_file[0] != '#' and cl_file[-3:] == '.cl']))
+# if "@WITH_GPU@" is "ON":
+ # cl_src_dirs = ["cl_src", "cl_src/kernels",
+ # "cl_src/advection", "cl_src/remeshing"]
+ # for cl_dir in cl_src_dirs:
+ # data_files.append(
+ # ('./hysop/gpu/' + cl_dir,
+ # ['@CMAKE_SOURCE_DIR@/hysop/gpu/' + cl_dir + '/'
+ # + cl_file
+ # for cl_file in os.listdir(
+ # '@CMAKE_SOURCE_DIR@/hysop/gpu/' + cl_dir + '/')
+ # if cl_file[0] != '.' and cl_file[0] != '#' and cl_file[-3:] == '.cl']))
descr = 'Hybrid Computation with Particles.'
authors = 'G.H Cottet, J.M Etancelin, J.B Keck, C.Mimeau, F.Pérignon, C. Picard'
diff --git a/sort_f90.py b/sort_f90.py
index fb1f6a93cdb947c1fc9361561c05f842ab9bcc21..86257d4cfdbc396d6cc93c1fe1b6aefcfc9fad7a 100644
--- a/sort_f90.py
+++ b/sort_f90.py
@@ -1,61 +1,58 @@
"""
-Dependency scanner for F90/95 modules.
+Dependency scanner for F90/95 modules.
-The sort function provided below sorts fortran source files in order of
-increasing dependency. That is, the sorting order makes sure that modules are
-compiled before they are USE'd.
+The sort function provided below sorts fortran source files in order of
+increasing dependency. That is, the sorting order makes sure that modules are
+compiled before they are USE'd.
See:
http://scipy.org/scipy/numpy/ticket/752
-The regular expressions are modified versions from the SCons.Scanner.Fortran
+The regular expressions are modified versions from the SCons.Scanner.Fortran
module. The copyright notice for Scons is included below.
:Author: David Huard, Pearu Peterson
:Date: May, 2008
-"""
-"""
-Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008 The SCons Foundation
-
-Permission is hereby granted, free of charge, to any person obtaining
-a copy of this software and associated documentation files (the
-"Software"), to deal in the Software without restriction, including
-without limitation the rights to use, copy, modify, merge, publish,
-distribute, sublicense, and/or sell copies of the Software, and to
-permit persons to whom the Software is furnished to do so, subject to
-the following conditions:
-
-The above copyright notice and this permission notice shall be included
-in all copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY
-KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
-WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
-NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
-LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
-WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+Copyright (c) 2001, 2002, 2003, 2004, 2005,
+ 2006, 2007, 2008 The SCons Foundation
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be included
+in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY
+KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
+WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
+LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
-import re, copy, os
-import warnings
+import re
-__all__ = ['FortranFileSorter', 'sort']
+__all__ = ['FortranFileSorter', 'sort']
"""
Regular expression for a module name
------------------------------------
An alphanumeric word not beginning with a numeric character.
-
+
[a-z_] : a letter or an underscore
\w* : any number of alphanumeric characters
"""
modulename = """[a-z_]\w*"""
-
"""
Regular expression for a USE statement
--------------------------------------
@@ -95,8 +92,8 @@ Here is a breakdown of the regex:
(modulename_regex) : match the module name that is being USE'd, see above.
"""
use_regex = \
-"(?i)(?:^|;)\s*USE(?:\s+|(?:(?:\s*,\s*(?:NON_)?INTRINSIC)?\s*::))\s*(%s)"%\
-modulename
+ "(?i)(?:^|;)\s*USE(?:\s+|(?:(?:\s*,\s*(?:NON_)?INTRINSIC)?\s*::))\s*(%s)" %\
+ modulename
"""
@@ -123,7 +120,7 @@ Here is a breakdown of the regex:
that make up the defined module name and
save it in a group
"""
-def_regex = """(?i)^\s*MODULE\s+(?!PROCEDURE)(%s)"""%modulename
+def_regex = """(?i)^\s*MODULE\s+(?!PROCEDURE)(%s)""" % modulename
"""
@@ -203,18 +200,20 @@ remove all the comments.
.*$ : ignore the rest of the line
"""
comment_regex = r'(^.*)!?.*$'
-
+
+
class FortranFileSorter:
"""Given a list of fortran 90/95 files, return a file list sorted by module
dependency. If a file depends on a parent through a USE MODULE statement,
this parent file will occur earlier in the list.
-
+
Parameters
----------
files : sequence
The sequence of file names to be sorted.
-
+
"""
+
def __init__(self, files):
self.files = files
self.use_regex = re.compile(use_regex, re.MULTILINE)
@@ -239,11 +238,11 @@ class FortranFileSorter:
def match_defined(self, code):
"""Return the set of defined module in a code string."""
return set(map(str.lower, self.def_regex.findall(code)))
-
+
def match_included(self, code):
"""Return the set of included files in a code string."""
return set(self.include_regex.findall(code))
-
+
def externals(self):
"""Return the modules that are used but not defined in the list of
files."""
@@ -252,7 +251,7 @@ class FortranFileSorter:
all_used = reduce(set.union, self.mod_used.values())
all_defined = reduce(set.union, self.mod_defined.values())
return all_used.difference(all_defined)
-
+
def scan(self):
"""For each file, identify the set of modules that are
defined, used but not defined in the same file, and the set of
@@ -263,28 +262,28 @@ class FortranFileSorter:
self.included = {}
for f in self.files:
code = self.read_code(f)
- code = self.uncomment(code)
+ code = self.uncomment(code)
self.mod_defined[f] = self.match_defined(code)
self.mod_used[f] = self.match_used(code)
self.included[f] = self.match_included(code)
-
- # Remove from used the modules defined internally.
- # That is, keep elements in used but not in defined.
- self.mod_used[f].difference_update(self.mod_defined[f])
-
- # TODO : Deal with include (do we have too?)
+
+ # Remove from used the modules defined internally.
+ # That is, keep elements in used but not in defined.
+ self.mod_used[f].difference_update(self.mod_defined[f])
+
+ # TODO : Deal with include (do we have too?)
def sort(self):
"""Sort the files in order of dependency.
- """
+ """
ordered_list = []
-
+
# Take care of modules not defined anywhere in the files. eg.
- # an intrinsic module by assuming them known from the
+ # an intrinsic module by assuming them known from the
# start.
defined = self.externals()
-
- # This cycles through the files, and appends those whose dependencies
- # are already satisfied by the files in the ordered list.
+
+ # This cycles through the files, and appends those whose dependencies
+ # are already satisfied by the files in the ordered list.
remaining = set(self.files)
goon = True
while goon:
@@ -292,21 +291,20 @@ class FortranFileSorter:
for f in remaining:
dependencies_satisfied = self.mod_used[f].issubset(defined)
if dependencies_satisfied:
- ordered_list.append(f)
+ ordered_list.append(f)
defined.update(self.mod_defined[f])
goon = True
remaining.difference_update(set(ordered_list))
ordered_list.extend(list(remaining))
return ordered_list
-
-
-
+
+
def sort(files):
"""Given a list of fortran 90/95 files, return a file list sorted by module
dependency. If a file depends on a parent through a USE MODULE statement,
this parent file will occur earlier in the list.
-
+
Parameters
----------
files : sequence
@@ -314,13 +312,10 @@ def sort(files):
"""
FS = FortranFileSorter(files)
FS.scan()
- return FS.sort()
+ return FS.sort()
import sys
if __name__ == "__main__":
print sys.argv[1:]
sort(sys.argv[1:])
-
-
-
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index 5eea76945fb822e3da511063aaf27f35d84576f3..a3d17a69c40c655407f1087e02f7df41d14dd11a 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -10,12 +10,7 @@
set(${HYSOP_LIBRARY_NAME}_SRCDIRS
.)
-# --- fftw interface ---
-if(WITH_FFTW)
- list(APPEND ${HYSOP_LIBRARY_NAME}_SRCDIRS fftw)
-endif()
-
-if(WITH_LIB_CXX)
+if(USE_CXX)
list(APPEND ${HYSOP_LIBRARY_NAME}_SRCDIRS hysop++/src)
endif()
@@ -81,25 +76,25 @@ target_link_libraries(${HYSOP_LIBRARY_NAME} PRIVATE ${HYSOP_LINK_LIBRARIES})
# way that does not depends on python.
# At the time it only includes fftw tests.
if(WITH_FORTRAN_TESTS)
- if(WITH_FFTW)
- # Set the name of a executable file that will be linked with libHYSOP_LIBRARY_NAME.
- # Useful to test libhysop in a way that does not depend on python.
- set(EXE_NAME ${HYSOP_LIBRARY_NAME}Run)
- # A main file to create an executable (test purpose)
- # Any files in these dirs will be used to create HySoP exec (linked with libhysop)
- set(${EXE_NAME}_SRCDIRS main)
- # Source and header files list, to generate a working executable based on libhysop.
- get_sources("${${EXE_NAME}_SRCDIRS}")
- get_headers("${${EXE_NAME}_SRCDIRS}")
- set(${EXE_NAME}_SRCS ${SOURCES_FILES})
- set(${EXE_NAME}_HDRS ${HDRS_FILES})
- list(APPEND ${EXE_NAME}_SRC ${${EXE_NAME}_HDRS})
- include_directories(${${EXE_NAME}_HDRS})
- add_executable(${EXE_NAME} ${${EXE_NAME}_SRCS})
- add_dependencies(${EXE_NAME} ${HYSOP_LIBRARY_NAME})
+ # if(WITH_FFTW)
+ # # Set the name of a executable file that will be linked with libHYSOP_LIBRARY_NAME.
+ # # Useful to test libhysop in a way that does not depend on python.
+ # set(EXE_NAME ${HYSOP_LIBRARY_NAME}Run)
+ # # A main file to create an executable (test purpose)
+ # # Any files in these dirs will be used to create HySoP exec (linked with libhysop)
+ # set(${EXE_NAME}_SRCDIRS main)
+ # # Source and header files list, to generate a working executable based on libhysop.
+ # get_sources("${${EXE_NAME}_SRCDIRS}")
+ # get_headers("${${EXE_NAME}_SRCDIRS}")
+ # set(${EXE_NAME}_SRCS ${SOURCES_FILES})
+ # set(${EXE_NAME}_HDRS ${HDRS_FILES})
+ # list(APPEND ${EXE_NAME}_SRC ${${EXE_NAME}_HDRS})
+ # include_directories(${${EXE_NAME}_HDRS})
+ # add_executable(${EXE_NAME} ${${EXE_NAME}_SRCS})
+ # add_dependencies(${EXE_NAME} ${HYSOP_LIBRARY_NAME})
- # libs to link with EXE_NAME
- target_link_libraries(${EXE_NAME} ${HYSOP_LIBRARY_NAME})
- target_link_libraries(${EXE_NAME} ${HYSOP_LINK_LIBRARIES})
- endif()
-endif()
\ No newline at end of file
+ # # libs to link with EXE_NAME
+ # target_link_libraries(${EXE_NAME} ${HYSOP_LIBRARY_NAME})
+ # target_link_libraries(${EXE_NAME} ${HYSOP_LINK_LIBRARIES})
+ # endif()
+endif()
diff --git a/src/extras/arnoldi.f90 b/src/extras/arnoldi.f90
deleted file mode 100644
index 386498094fa218387456692073ffcafff4cf3ef2..0000000000000000000000000000000000000000
--- a/src/extras/arnoldi.f90
+++ /dev/null
@@ -1,219 +0,0 @@
-!=========================================================================
-!Computation of global modes using a time stepping (snapshots) technique
-!=========================================================================
-!=========================================================================
-!Reads snapshots, constructs the Hessenberg matrix
-!and computes the eigen-values/eigen-functions
-!=========================================================================
-module arnoldi
-
- use client_data
-
- implicit none
-
-contains
-
-!======================
-subroutine arnoldi3d(Mu,ncli,nt,nfp,nmodes,Tps)
- implicit none
- integer, intent(in) :: ncli ! number of snapshot
- integer, intent(in) :: nt ! total number of points per snapshot
- integer, intent(in) :: nmodes ! number of desired modes
- integer, intent(in) :: nfp ! number of desired eigen functions
- real(mk), intent(in) :: Tps ! sampling time step
- real(mk), dimension(:,:), intent(inout) :: Mu ! snapshots
-
- real(mk), dimension(:,:), allocatable :: un ! orthonomalized Krylov basis
- real(mk), dimension(:,:), allocatable :: Hessenberg ! Hessenberg matrix
- complex(mk), dimension(:), allocatable :: VP ! eigenvalues
- complex(mk), dimension(:,:), allocatable :: FP, FP_J ! eigen functions
- real(mk), dimension(:), allocatable :: reslog, res ! residuals
- integer, dimension(:), allocatable :: t ! sorting array
- real(mk), dimension(:), allocatable :: tab !
- real(mk) :: norm, prod, error !
-
- integer :: i,j,k,nmax
-
- allocate(un(nt,ncli),Hessenberg(ncli,ncli-1),VP(ncli-1),FP(ncli-1,ncli-1),FP_J(nt,ncli))
-
- nmax=0
- VP=(0.,0.); FP=(0.,0.); FP_J=(0.,0.)
- Hessenberg=0.
-
- !==================================
- ! Arnoldi method
- !==================================
-
- norm = dot_product(Mu(:,1),Mu(:,1))
- norm = sqrt(norm)
- un(:,1) = Mu(:,1)/norm ! first normalized vector u1
-
- do j=2,ncli ! construct a normalized base u2... un
- un(:,j)=Mu(:,j) ! w=Mu_j (We have Mu_j=U(:,j+1))
- do i=1,j-1
- Hessenberg(i,j-1)=dot_product(un(:,i),un(:,j))
- un(:,j)=un(:,j)-un(:,i)*Hessenberg(i,j-1)
- enddo
-
- norm = dot_product(un(:,j),un(:,j))
- Hessenberg(j,j-1) = sqrt(norm)
-
- un(:,j) = un(:,j)/Hessenberg(j,j-1)! normalization
-
- enddo
-
-! do i=1,nt
-! print *, 'Krylov basis:', un(i,:)
-! enddo
-
- do i=1,ncli-1
- print *, 'Hessenberg matrix:', Hessenberg(i,:)
- enddo
-
-
-!Check orthonormalization
-!==================================
-
- print *,'check ortho'
-
- prod=0.
- do i=1,ncli
- do j=1,ncli
- prod=dot_product(un(:,j),un(:,i))
- if (abs(prod).gt.1e-14) then
- print *,i,j,abs(prod)
- endif
- enddo
- enddo
-
-
-!Eigen-values and Eigen-functions related to Hessenberg matrix
-! +
-!Eigen-values related to Jacobian matrix ==> spectra
-!==============================================================
-
- open(unit=10, file='spectrum.dat')
- open(unit=11, file='spectrum_log.dat')
-
-call spectrum(Hessenberg(1:ncli-1,:),ncli-1,VP,FP)
-
- do i=1,ncli-1
- write(10,*) dble(VP(i)), aimag(VP(i))
- write(11,*) dble(log(VP(i)))/Tps, ATAN(aimag(VP(i)/DBLE(VP(i))))/Tps
- enddo
- close(10)
- close(11)
-
-!Eigen-functions related to Jacobian matrix
-!==========================================
- FP_J(1:nt,1:ncli-1)=matmul(un(1:nt,1:ncli-1),FP(1:ncli-1,1:ncli-1))
-! do i=1,nt
-! print *, 'FP_J', (FP_J(i,j),j=1,ncli-1)
-! enddo
-
-!Residual calculation with respect to each mode
-!==============================================
-
- allocate(res(ncli-1),reslog(ncli-1))
- error = Hessenberg(ncli,ncli-1)
- print *,'last Hess',Hessenberg(ncli,ncli-1)
-
- do i=1,ncli-1
- res(i) = abs(FP(ncli-1,i))*error
- reslog(i)=-log10(res(i))
- print *,'residual',reslog(i),res(i)
- enddo
-
-
-!Modes are sorted with respect to residual
-!==========================================
- allocate(t(ncli-1))
-
- do i=1,ncli-1
- t(i)=i
- enddo
-
- call sort(reslog,ncli-1,t)
-
- open(unit=201,file='spectrum_res.dat')
- write(201,*)'VARIABLES ="WR","WI","RES"'
-
- do i=1,nmodes
- write(201,100) dble(log(VP(t(i))))/Tps,&
- ATAN(aimag(VP(t(i))/DBLE(VP(t(i)))))/Tps,&
- res(t(i))
- enddo
- close(201)
-!
-!Write the associated eigen functions
-!====================================
-! allocate(tab(nfp))
-!
-! open(unit=107, file='table.dat')
-! open(unit=108, file='spectrum_sorted.dat')
-!
-! do i=1,nfp
-!! call ecriture(FP_J(:,t(h)))
-! write(108,*) ATAN(aimag(VP(t(i))/DBLE(VP(t(i)))))/Tps,&
-! dble(log(VP(t(i))))/Tps
-! enddo
-! close(108)
-!
-100 format (5(2x,e19.13))
-
-end subroutine arnoldi3d
-
-!===================
-!Spectrum subroutine
-!===================
-subroutine spectrum(A,n,VP,VR)
- implicit none
- integer :: INFO
- integer :: n,LWORK
- real(mk), dimension(n,n) :: A
- real(mk), dimension(:), allocatable :: RWORK
- complex(mk), dimension(1,n) :: VL
- complex(mk), dimension(n,n) :: VR
- complex(mk), dimension(:), allocatable :: WORK
- complex(mk), dimension(n):: VP
-
- LWORK=4*n
- allocate(WORK(LWORK),RWORK(2*n))
- call ZGEEV('N','V', n, A*(1.,0.), n, VP, VL, 1, VR, n,&
- WORK, LWORK, RWORK, INFO )
- print *, 'VP', VP
-
-end subroutine spectrum
-
-!==================
-!Sorting subroutine
-!==================
-subroutine sort(t,n,ind)
- implicit none
- integer :: i, j, n, tp1
- real(mk), dimension(1:n) :: t
- real(mk) :: temp
- integer, dimension(1:n) :: ind
-
- do i=1,n
- do j=i+1,n
- if ((t(i))<(t(j))) then
-
- temp=t(i)
- tp1=ind(i)
-
- t(i)=t(j)
- ind(i)=ind(j)
-
- t(j)=temp
- ind(j)=tp1
-
- endif
- enddo
- enddo
-
- return
-
-end subroutine sort
-
-end module arnoldi
diff --git a/src/hysop++/src/data/index.h b/src/hysop++/src/data/index.h
index 3166beb24b6648d32a9675345f754f44ce2457c5..c0dcb6993b9d28022ef20c481c6c398aa0c61da2 100644
--- a/src/hysop++/src/data/index.h
+++ b/src/hysop++/src/data/index.h
@@ -58,7 +58,7 @@ namespace hysop {
virtual void onIndexOverflow(std::size_t pos) {};
virtual void onIndexUndeflow(std::size_t pos) {};
-__attribute__((optimize("unroll-loops")))
+//__attribute__((optimize("unroll-loops")))
Index& operator++() { //prefix
for (int d = Dim-1; d >=0; d--) {
m_ids[d]++;
@@ -74,7 +74,7 @@ __attribute__((optimize("unroll-loops")))
m_id++;
return *this;
};
-__attribute__((optimize("unroll-loops")))
+//__attribute__((optimize("unroll-loops")))
Index& operator--() { //prefix
for (int d = 0; d < Dim; d++) {
if(m_ids[d]!=0) {
diff --git a/src/hysop++/src/data/multi_array/multi_array_view.h b/src/hysop++/src/data/multi_array/multi_array_view.h
index c23d35371edd959aac8728283a3010efe253eb29..d2931c9b0d95af8ad7208e1e3f6801efdb42d532 100644
--- a/src/hysop++/src/data/multi_array/multi_array_view.h
+++ b/src/hysop++/src/data/multi_array/multi_array_view.h
@@ -37,14 +37,18 @@ namespace hysop {
/* Implementation */
-// remove boost warning
+// remove anoying boost warning
+#if defined(__GNUG__) and !defined(__clang__)
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
+#endif
template <typename T, std::size_t Dim>
multi_array_view<T,Dim>::multi_array_view(const boost_multi_array_view<T,Dim>& view) :
super(view) {
}
+#if defined(__GNUG__) and !defined(__clang__)
#pragma GCC diagnostic pop
+#endif
template <typename T, std::size_t Dim>
multi_array_view<T,Dim>& multi_array_view<T,Dim>::operator=(const boost_multi_array_view<T,Dim>& other) {
diff --git a/src/hysop++/src/utils/constants.h b/src/hysop++/src/utils/constants.h
index 07ef13458cd91f6df1e9b7ef42f2b9ba2bf44a46..585ed629e11ec6c9ef537f4f92dc35926cd208cd 100644
--- a/src/hysop++/src/utils/constants.h
+++ b/src/hysop++/src/utils/constants.h
@@ -14,7 +14,7 @@ namespace hysop {
#ifdef HAS_QUADMATHS
static const __float128 pi = acosq(-1.0Q);
#else
- static constexpr long double pi = acosl(-1.0L);
+ static const long double pi = acosl(-1.0L);
#endif
}
}
diff --git a/swig/hysop++/fft.i b/swig/hysop++/fft.i
index db23284037b7c4a8d636891d75dbaf95c7295b2a..dd62b768631dd89b95e11a8fff4d76102ae13351 100644
--- a/swig/hysop++/fft.i
+++ b/swig/hysop++/fft.i
@@ -48,7 +48,9 @@
%template(Fftw3f) hysop::fft::Fftw3<float>;
%template(Fftw3d) hysop::fft::Fftw3<double>;
%template(Fftw3l) hysop::fft::Fftw3<long double>;
-%template(Fftw3q) hysop::fft::Fftw3<__float128>;
+#ifdef HAS_QUADMATHS
+ %template(Fftw3q) hysop::fft::Fftw3<__float128>;
+#endif
/* fft transforms */
%ignore hysop::fft::operator<<;
diff --git a/trashed_examples/LevelSet3D/levelSet3D.py b/trashed_examples/LevelSet3D/levelSet3D.py
index 2ee37c14589160681b89cace46f1a8f2b7c050b7..ef4b982ed43346ca34f9816921c242ebeb1750cb 100644
--- a/trashed_examples/LevelSet3D/levelSet3D.py
+++ b/trashed_examples/LevelSet3D/levelSet3D.py
@@ -12,7 +12,7 @@ from hysop.numerics.remeshing import L6_4 as remesh_formula
from hysop.numerics.remeshing import Linear
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.gpu.gpu_transfer import DataTransfer
from hysop.problem.problem import Problem
@@ -34,7 +34,7 @@ def vitesse(res, x, y, z, t=0.):
return res
-def volume(_simu, var):
+def volume(_simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -96,9 +96,9 @@ topo_s = advec.advec_dir[0].discreteFields[scal].topology
velocity = Analytic(variables={velo: topo_v},
method={Support: 'gpu'})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, diagnostics_shape=(1, 2),
+ in_fields=[scal], variables={scal: topo_s},
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/LevelSet3D/levelSet3D_Scales.py b/trashed_examples/LevelSet3D/levelSet3D_Scales.py
index 251b45a43f73837ee812b1ddaaffdb9b5e5f4ff1..4572efca65c05ea6a821d5ec7c7fc02ed89eef70 100644
--- a/trashed_examples/LevelSet3D/levelSet3D_Scales.py
+++ b/trashed_examples/LevelSet3D/levelSet3D_Scales.py
@@ -6,7 +6,7 @@ from hysop.tools.parameters import Discretization, IOParams
from hysop.methods_keys import Scales, MultiScale
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.problem.problem import Problem
from hysop.problem.simulation import Simulation
@@ -27,7 +27,7 @@ def vitesse(res, x, y, z, t=0.):
return res
-def volume(_simu, var):
+def volume(_simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -68,9 +68,9 @@ topo_s = advec.discreteFields[scal].topology
velocity = Analytic(variables={velo: topo_v})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, res_shape=1,
+ in_fields=[scal], discretization=topo_s,
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/LevelSet3D/levelSet3D_Scales_MultiScale.py b/trashed_examples/LevelSet3D/levelSet3D_Scales_MultiScale.py
index b50c7baed82c2fc85b038266d226360af67f4ae3..8b970f960006b1dade145fbb5d8d4bb85a06f456 100644
--- a/trashed_examples/LevelSet3D/levelSet3D_Scales_MultiScale.py
+++ b/trashed_examples/LevelSet3D/levelSet3D_Scales_MultiScale.py
@@ -6,7 +6,7 @@ from hysop.tools.parameters import Discretization, IOParams
from hysop.methods_keys import Scales, MultiScale
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.problem.problem import Problem
from hysop.problem.simulation import Simulation
@@ -27,7 +27,7 @@ def vitesse(res, x, y, z, t=0.):
return res
-def volume(_simu, var):
+def volume(_simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -69,9 +69,9 @@ advec.discretize()
velocity = Analytic(variables={velo: topo_v})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, diagnostics_shape=(1, 2),
+ in_fields=[scal], variables={scal: topo_s},
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/LevelSet3D/levelSet3D_gpu.py b/trashed_examples/LevelSet3D/levelSet3D_gpu.py
index b12d157daac86fcc9af693a5d49003d7552b6fb3..e51895da6366910a6085b1fd090d6a696582473c 100755
--- a/trashed_examples/LevelSet3D/levelSet3D_gpu.py
+++ b/trashed_examples/LevelSet3D/levelSet3D_gpu.py
@@ -12,7 +12,7 @@ from hysop.numerics.remeshing import L6_4 as remesh_formula
from hysop.numerics.remeshing import Linear
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.gpu.gpu_transfer import DataTransfer
from hysop.problem.problem import Problem
@@ -34,7 +34,7 @@ def vitesse(res, x, y, z, t=0.):
return res
-def volume(_simu, var):
+def volume(_simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -88,9 +88,9 @@ topo_s = advec.advec_dir[0].discreteFields[scal].topology
velocity = Analytic(variables={velo: topo_v})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, diagnostics_shape=1,
+ in_fields=[scal], variables={scal: topo_s},
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/LevelSet3D/levelSet3D_gpu_MultiScale.py b/trashed_examples/LevelSet3D/levelSet3D_gpu_MultiScale.py
index 2bfef8a41982257b679f9180b8b25a79b9b833bb..3d05e5019213b42d16b5135878ac931f47d1840d 100644
--- a/trashed_examples/LevelSet3D/levelSet3D_gpu_MultiScale.py
+++ b/trashed_examples/LevelSet3D/levelSet3D_gpu_MultiScale.py
@@ -12,7 +12,7 @@ from hysop.numerics.remeshing import L6_4 as remesh_formula
from hysop.numerics.remeshing import Linear
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.gpu.gpu_transfer import DataTransfer
from hysop.problem.problem import Problem
@@ -34,7 +34,7 @@ def vitesse(res, x, y, z, t=0.):
return res
-def volume(_simu, var):
+def volume(_simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -89,9 +89,9 @@ topo_s = advec.advec_dir[0].discreteFields[scal].topology
velocity = Analytic(variables={velo: topo_v})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, diagnostics_shape=(1, 2),
+ in_fields=[scal], variables={scal: topo_s},
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/LevelSet3D/levelSet3D_only_gpu.py b/trashed_examples/LevelSet3D/levelSet3D_only_gpu.py
index 5a87c8e07f120f1c90c351b78b58cc290b46d794..a163a5fd25e6216c551015af7378c953c4672cce 100644
--- a/trashed_examples/LevelSet3D/levelSet3D_only_gpu.py
+++ b/trashed_examples/LevelSet3D/levelSet3D_only_gpu.py
@@ -12,7 +12,7 @@ from hysop.numerics.remeshing import L6_4 as remesh_formula
from hysop.numerics.remeshing import Linear
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.gpu.gpu_transfer import DataTransfer
from hysop.problem.problem import Problem
@@ -20,7 +20,7 @@ from hysop.problem.simulation import Simulation
sin, cos, pi, sqrt = np.sin, np.cos, np.pi, np.sqrt
-def volume(_simu, var):
+def volume(_simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -78,9 +78,9 @@ topo_s = advec.advec_dir[0].discreteFields[scal].topology
velocity = Analytic(variables={velo: topo_v},
method={Support: 'gpu'})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, diagnostics_shape=(1, 2),
+ in_fields=[scal], variables={scal: topo_s},
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/LevelSet3D/levelSet3D_only_gpu_MultiScale.py b/trashed_examples/LevelSet3D/levelSet3D_only_gpu_MultiScale.py
index 5a689da0c2cf7752957fa921bd2ddb76b9a5fc2a..0726d2328d3ba3fdbb281acce52108d4e5c5b79d 100644
--- a/trashed_examples/LevelSet3D/levelSet3D_only_gpu_MultiScale.py
+++ b/trashed_examples/LevelSet3D/levelSet3D_only_gpu_MultiScale.py
@@ -12,7 +12,7 @@ from hysop.numerics.remeshing import L6_4 as remesh_formula
from hysop.numerics.remeshing import Linear
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.gpu.gpu_transfer import DataTransfer
from hysop.problem.problem import Problem
@@ -20,7 +20,7 @@ from hysop.problem.simulation import Simulation
sin, cos, pi, sqrt = np.sin, np.cos, np.pi, np.sqrt
-def volume(_simu, var):
+def volume(simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -80,9 +80,9 @@ topo_s = advec.advec_dir[0].discreteFields[scal].topology
velocity = Analytic(variables={velo: topo_v},
method={Support: 'gpu'})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, diagnostics_shape=(1, 2),
+ in_fields=[scal], variables={scal: topo_s},
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/LevelSet3D/levelSet3D_python.py b/trashed_examples/LevelSet3D/levelSet3D_python.py
index fc845ee45bc9242367b87fec1b67ce2a2322a848..3a3d071d9243ca0eb4ce620e73978329100a8b63 100644
--- a/trashed_examples/LevelSet3D/levelSet3D_python.py
+++ b/trashed_examples/LevelSet3D/levelSet3D_python.py
@@ -12,7 +12,7 @@ from hysop.numerics.remeshing import L2_1 as remesh_formula
from hysop.numerics.interpolation import Linear
from hysop.operator.advection import Advection
from hysop.operator.analytic import Analytic
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.hdf_io import HDF_Writer
from hysop.gpu.gpu_transfer import DataTransfer
from hysop.problem.problem import Problem
@@ -34,7 +34,7 @@ def vitesse(res, x, y, z, t=0.):
return res
-def volume(_simu, var):
+def volume(_simu, var, **kwds):
v_loc = np.sum(var[0].data[0] > 0.5) * np.prod(
var[0].topology.mesh.space_step)
return main_comm.allreduce(sendobj=v_loc, op=MPI.SUM)
@@ -100,9 +100,9 @@ topo_s = advec.advec_dir[0].discreteFields[scal].topology
velocity = Analytic(variables={velo: topo_v})
#method={Support: 'gpu'})
-volume_m = CustomMonitor(function=volume, res_shape=1,
- variables={scal: topo_s},
- io_params=IOParams(filename="volume.dat"))
+volume_m = Custom(function=volume, diagnostics_shape=(1, 2),
+ in_fields=[scal], variables={scal: topo_s},
+ io_params=IOParams(filename="volume.dat"))
p = HDF_Writer(variables={scal: topo_s},
io_params=IOParams(frequency=outputModulo,
filename="levelset",
diff --git a/trashed_examples/Multiphase/NS_planeJet_hybrid_MS_MP.py b/trashed_examples/Multiphase/NS_planeJet_hybrid_MS_MP.py
index 0529eebf6eb0a9f50727fd60fe460482381f0a36..bcf74505fc3fb023a20fe7a8f10f2a043b913dad 100644
--- a/trashed_examples/Multiphase/NS_planeJet_hybrid_MS_MP.py
+++ b/trashed_examples/Multiphase/NS_planeJet_hybrid_MS_MP.py
@@ -39,7 +39,7 @@ from hysop.operator.stretching import Stretching
from hysop.operator.poisson import Poisson
from hysop.operator.differential import Curl
from hysop.operator.adapt_timestep import AdaptTimeStep
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.redistribute_inter import RedistributeInter
from hysop.operator.redistribute_intra import RedistributeIntra
from hysop.gpu.gpu_transfer import DataTransfer
@@ -372,13 +372,14 @@ if IS_OUTPUT:
io_params=IOParams(frequency=1,
filename='energy.dat',
fileformat=ASCII))
- maxvelo = CustomMonitor(variables={velo: topo_F_0g_1d},
- function=calc_maxvelo,
- res_shape=3,
- mpi_params=mpi_params_UW,
- io_params=IOParams(frequency=1,
- filename='maxvelo.dat',
- fileformat=ASCII))
+ maxvelo = Custom(in_fields=[velo],
+ variables={velo: topo_F_0g_1d},
+ function=calc_maxvelo,
+ diagnostics_shape=(1, 4),
+ mpi_params=mpi_params_UW,
+ io_params=IOParams(frequency=1,
+ filename='maxvelo.dat',
+ fileformat=ASCII))
if box.is_on_task(TASK_UW):
for op in (p_velo, p_velo_xy, p_velo_xz, energy, maxvelo):
op.discretize()
diff --git a/trashed_examples/Multiphase/RTI.py b/trashed_examples/Multiphase/RTI.py
index 4534e86e61e2c3e6a5e131084012d1e86a212df0..2e23829a6b00e086a4fbe07a68629b54074ce483 100644
--- a/trashed_examples/Multiphase/RTI.py
+++ b/trashed_examples/Multiphase/RTI.py
@@ -42,7 +42,7 @@ from hysop.operator.multiresolution_filter import MultiresolutionFilter
from hysop.operator.multiphase_gradp import MultiphaseGradP
from hysop.operator.multiphase_baroclinic_rhs import MultiphaseBaroclinicRHS
from hysop.operator.adapt_timestep import AdaptTimeStep
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.redistribute_inter import RedistributeInter
from hysop.operator.redistribute_intra import RedistributeIntra
from hysop.gpu.gpu_transfer import DataTransfer
@@ -338,13 +338,14 @@ if IS_OUTPUT:
io_params=IOParams(frequency=1,
filename='energy.dat',
fileformat=ASCII))
- maxvelo = CustomMonitor(variables={velo: topo_C_1d},
- function=calc_maxvelo,
- res_shape=3,
- mpi_params=mpi_params_UW,
- io_params=IOParams(frequency=1,
- filename='maxvelo.dat',
- fileformat=ASCII))
+ maxvelo = Custom(in_fields=[velo],
+ variables={velo: topo_C_1d},
+ function=calc_maxvelo,
+ diagnostics_shape=(1, 4),
+ mpi_params=mpi_params_UW,
+ io_params=IOParams(frequency=1,
+ filename='maxvelo.dat',
+ fileformat=ASCII))
if box.is_on_task(TASK_UW):
for op in (p_velo, energy, maxvelo):
op.discretize()
diff --git a/trashed_examples/Plane_jet/NS_planeJet_hybrid_MS.py b/trashed_examples/Plane_jet/NS_planeJet_hybrid_MS.py
index bee1729fe1b86ccafb94b021338fe88ea2b9c978..6f65a4f347897448a95269ecbcb04f6a8ae99cc9 100644
--- a/trashed_examples/Plane_jet/NS_planeJet_hybrid_MS.py
+++ b/trashed_examples/Plane_jet/NS_planeJet_hybrid_MS.py
@@ -33,7 +33,7 @@ from hysop.operator.stretching import Stretching
from hysop.operator.poisson import Poisson
from hysop.operator.differential import Curl
from hysop.operator.adapt_timestep import AdaptTimeStep
-from hysop.operator.custom import CustomMonitor
+from hysop.operators import Custom
from hysop.operator.redistribute_inter import RedistributeInter
from hysop.operator.redistribute_intra import RedistributeIntra
from hysop.gpu.gpu_transfer import DataTransfer
@@ -299,13 +299,14 @@ if IS_OUTPUT:
io_params=IOParams(frequency=1,
filename='energy.dat',
fileformat=ASCII))
- maxvelo = CustomMonitor(variables={velo: topo_CPU_velo_scales},
- function=calc_maxvelo,
- res_shape=3,
- mpi_params=mpi_params_UW,
- io_params=IOParams(frequency=1,
- filename='maxvelo.dat',
- fileformat=ASCII))
+ maxvelo = Custom(in_fields=[velo],
+ variables={velo: topo_CPU_velo_scales},
+ function=calc_maxvelo,
+ diagnostics_shape=(1, 4),
+ mpi_params=mpi_params_UW,
+ io_params=IOParams(frequency=1,
+ filename='maxvelo.dat',
+ fileformat=ASCII))
if box.isOnTask(TASK_UW):
for op in (p_velo, p_velo_xy, p_velo_xz, energy, maxvelo):
op.discretize()
diff --git a/trashed_examples/RMI/RMI_hybrid.py b/trashed_examples/RMI/RMI_hybrid.py
index 9760b46d08b0f58284a586c4d8c30ea1e047d21e..b62eeab10eea67bd5a25fe0fa242940a9fb1bb3c 100644
--- a/trashed_examples/RMI/RMI_hybrid.py
+++ b/trashed_examples/RMI/RMI_hybrid.py
@@ -40,7 +40,7 @@ from hysop.operator.baroclinic import Baroclinic
from hysop.operator.penalization import PenalizeVorticity
from hysop.operator.poisson import Poisson
from hysop.operator.adapt_timestep import AdaptTimeStep
-from hysop.operator.custom import CustomMonitor, CustomOp
+from hysop.operators import Custom
from hysop.operator.redistribute_inter import RedistributeInter
from hysop.operator.redistribute_intra import RedistributeIntra
from hysop.gpu.gpu_transfer import DataTransfer
@@ -129,17 +129,15 @@ def func_scal_to_rho(simu, f_in, f_out):
temp_maxvelo = npw.zeros((3, ))
-maxvelo_values = npw.zeros((3, ))
-def calc_maxvelo(simu, v):
+def calc_maxvelo(simu, v, w=None, maxvelo_values):
temp_maxvelo[0] = np.max(np.abs(v[0].data[0]))
temp_maxvelo[1] = np.max(np.abs(v[0].data[1]))
temp_maxvelo[2] = np.max(np.abs(v[0].data[2]))
v[0].topology.comm.Allreduce(sendbuf=[temp_maxvelo, 3, HYSOP_MPI_REAL],
recvbuf=[maxvelo_values, 3, HYSOP_MPI_REAL],
op=MPI.MAX)
- return maxvelo_values
ctime = MPI.Wtime()
# Domain
@@ -222,10 +220,11 @@ advec = Advection(velo,
method={Scales: 'p_64', MultiScale: 'L4_4'})
stretch = Stretching(velo, vorti, discretization=d_uw_ghosts,
mpi_params=mpi_params_UW)
-scal_to_rho = CustomOp([scal, ], [rho, ], func_scal_to_rho,
- variables={scal: d_uw_ghosts,
- rho: d_uw_ghosts},
- mpi_params=mpi_params_UW)
+scal_to_rho = Custom(in_fields=[scal, ], out_fields=[rho, ],
+ function=func_scal_to_rho,
+ variables={scal: d_uw_ghosts,
+ rho: d_uw_ghosts},
+ mpi_params=mpi_params_UW)
penal = PenalizeVorticity(velocity=velo, vorticity=vorti,
discretization=d_uw_ghosts,
obstacles=[bc_t, bc_b], coeff=1e8,
@@ -291,13 +290,14 @@ if IS_OUTPUT:
io_params=IOParams(frequency=1,
filename='energy.dat',
fileformat=ASCII))
- maxvelo = CustomMonitor(variables={velo: topo_CPU_velo_scales},
- function=calc_maxvelo,
- res_shape=3,
- mpi_params=mpi_params_UW,
- io_params=IOParams(frequency=1,
- filename='maxvelo.dat',
- fileformat=ASCII))
+ maxvelo = Custom(in_fields=[velo],
+ variables={velo: topo_CPU_velo_scales},
+ function=calc_maxvelo,
+ diagnostics_shape=(1, 4),
+ mpi_params=mpi_params_UW,
+ io_params=IOParams(frequency=1,
+ filename='maxvelo.dat',
+ fileformat=ASCII))
if box.is_on_task(TASK_UW):
for op in (p_velo, p_rho, energy, maxvelo):
op.discretize()