From dc0a4b4bcad481de8cc815a08efc66612a7ab43f Mon Sep 17 00:00:00 2001
From: Jean-Baptiste Keck <Jean-Baptiste.Keck@imag.fr>
Date: Thu, 15 Mar 2018 14:03:31 +0100
Subject: [PATCH] cleaned all examples
---
examples/analytic/analytic.py | 35 +++++++++-------
examples/scalar_advection/scalar_advection.py | 6 ++-
examples/scalar_diffusion/scalar_diffusion.py | 41 +++++++++++--------
examples/taylor_green/taylor_green.py | 2 +-
hysop/simulation.py | 2 +-
5 files changed, 53 insertions(+), 33 deletions(-)
diff --git a/examples/analytic/analytic.py b/examples/analytic/analytic.py
index 920ae3d12..f5fc31428 100755
--- a/examples/analytic/analytic.py
+++ b/examples/analytic/analytic.py
@@ -6,9 +6,9 @@ def compute(args):
'''
HySoP Analytic Example: Initialize a field with a space and time dependent analytic formula.
'''
- from hysop import IO, Field, Box, MPIParams, \
+ from hysop import Field, Box, MPIParams, \
Simulation, Problem, ScalarParameter
- from hysop.constants import Implementation, AutotunerFlags
+ from hysop.constants import Implementation
from hysop.operators import AnalyticField
# Define domain
@@ -18,10 +18,15 @@ def compute(args):
# Define parameters and field (time and analytic field)
t = ScalarParameter('t', dtype=args.dtype)
scalar = Field(domain=box, name='S0', nb_components=1, dtype=args.dtype)
+
+ # We need to first get default MPI parameters (even for non MPI jobs)
+ # so we use default domain communicator and task.
+ mpi_params = MPIParams(comm=box.task_comm,
+ task_id=box.current_task())
# Setup implementation specific variables
impl = args.impl
- op_kwds = {}
+ op_kwds = {'mpi_params': mpi_params}
if (impl is Implementation.PYTHON):
# Setup python specific extra operator keyword arguments
# (mapping: variable name => variable value)
@@ -29,11 +34,6 @@ def compute(args):
elif (impl is Implementation.OPENCL_CODEGEN):
# For the OpenCL implementation we need to setup the compute device
# and configure how the code is generated and compiled at runtime.
-
- # We need to first create MPI parameters to initialize an OpenCL environment
- # (even for non MPI jobs) so we use default domain communicator and task.
- mpi_params = MPIParams(comm=box.task_comm,
- task_id=box.current_task())
# Create an explicit OpenCL context from user parameters
from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
@@ -44,7 +44,6 @@ def compute(args):
method = {OpenClKernelConfig: args.opencl_kernel_config}
# Setup opencl specific extra operator keyword arguments
- op_kwds['mpi_params'] = mpi_params
op_kwds['cl_env'] = cl_env
op_kwds['method'] = method
else:
@@ -64,8 +63,10 @@ def compute(args):
data[0][...] *= np.cos(x-t())
elif (impl is Implementation.OPENCL_CODEGEN):
# With the opencl codegen implementation we use a symbolic expression
- # generated using sympy. OpenCL code will be automatically generated.
- # For a vector field, multiple expressions should be given as a tuple.
+ # generated using sympy. OpenCL code will be automatically generated,
+ # compiled and passed trough a runtime parameter autotuner to achieve
+ # maximal performances on a variety of different devices.
+ # For a vector field, multiple symbolic expressions should be given as a tuple.
# Here xs and ts are the symbolic variables representing coordinates and time.
xs = box.frame.coords
ts = t.s
@@ -89,15 +90,21 @@ def compute(args):
problem.insert(analytic)
problem.build()
- # If a visu_rank was provided, display the graph on the given process rank.
- problem.display(args.visu_rank)
+ # If a visu_rank was provided, and show_graph was set,
+ # display the graph on the given process rank.
+ if args.display_graph:
+ problem.display(args.visu_rank)
# Create a simulation and solve the problem
# (do not forget to specify the time parameter here)
simu = Simulation(start=args.tstart, end=args.tend,
nb_iter=args.nb_iter, dt0=args.dt,
t=t)
- problem.solve(simu)
+
+ # Finally solve the problem
+ problem.solve(simu, dry_run=args.dry_run)
+
+ # Finalize
problem.finalize()
diff --git a/examples/scalar_advection/scalar_advection.py b/examples/scalar_advection/scalar_advection.py
index ac15b61a4..333d3e1ff 100644
--- a/examples/scalar_advection/scalar_advection.py
+++ b/examples/scalar_advection/scalar_advection.py
@@ -111,11 +111,15 @@ def compute(args):
dt0 = (args.cfl*dx)/Vinf
if (args.dt is not None):
dt0 = min(args.dt, dt0)
+ dt0 = 0.99*dt0
# Create a simulation and solve the problem
# (do not forget to specify the dt parameter here)
simu = Simulation(start=args.tstart, end=args.tend,
- dt0=dt0, dt=dt)
+ nb_iter=args.nb_iter,
+ max_iter=args.max_iter,
+ times_of_interest=args.dump_times,
+ dt=dt, dt0=dt0)
# Finally solve the problem
problem.solve(simu, dry_run=args.dry_run)
diff --git a/examples/scalar_diffusion/scalar_diffusion.py b/examples/scalar_diffusion/scalar_diffusion.py
index 1ed136bda..497224c44 100644
--- a/examples/scalar_diffusion/scalar_diffusion.py
+++ b/examples/scalar_diffusion/scalar_diffusion.py
@@ -12,16 +12,16 @@ def compute(args):
Simulation, Problem, ScalarParameter, \
MPIParams
- from hysop.constants import Implementation
+ from hysop.constants import Implementation, ComputeGranularity
from hysop.operator.directional.diffusion_dir import DirectionalDiffusion
from hysop.methods import StrangOrder, TimeIntegrator, SpaceDiscretization
from hysop.numerics.splitting.strang import StrangSplitting
- from hysop.numerics.odesolvers.runge_kutta import Euler, RK2, RK3, RK4
# Define domain
+ dim = args.ndim
npts = args.npts
- box = Box(origin=args.box_origin, length=args.box_length, dim=args.ndim)
+ box = Box(origin=args.box_origin, length=args.box_length, dim=dim)
# Get default MPI Parameters from domain (even for serial jobs)
mpi_params = MPIParams(comm=box.task_comm,
@@ -33,11 +33,15 @@ def compute(args):
scalar = Field(domain=box, name='S0', nb_components=1, dtype=args.dtype)
# Diffusion operator discretization parameters
- method = {TimeIntegrator: Euler, SpaceDiscretization: 2}
+ method = {
+ ComputeGranularity: args.compute_granularity,
+ SpaceDiscretization: args.fd_order,
+ TimeIntegrator: args.time_integrator,
+ }
# Setup implementation specific variables
impl = args.impl
- extra_op_kwds = {}
+ extra_op_kwds = { 'mpi_params': mpi_params }
if (impl is Implementation.PYTHON):
pass
elif (impl is Implementation.OPENCL_CODEGEN):
@@ -51,10 +55,10 @@ def compute(args):
# Configure OpenCL kernel generation and tuning (already done by HysopArgParser)
from hysop.methods import OpenClKernelConfig
- method = {OpenClKernelConfig: args.opencl_kernel_config}
+ method[OpenClKernelConfig] = args.opencl_kernel_config
# Setup opencl specific extra operator keyword arguments
- extra_op_kwds['cl_env'] = cl_env
+ extra_op_kwds['cl_env'] = cl_env
else:
msg='Unknown implementation \'{}\'.'.format(impl)
raise ValueError(msg)
@@ -64,12 +68,10 @@ def compute(args):
name='diffusion', dt=dt,
fields=scalar, coeffs=nu,
variables = {scalar: npts},
- method=method, mpi_params=mpi_params,
**extra_op_kwds)
# Build the directional splitting operator graph
- splitting = StrangSplitting(splitting_dim=box.dim,
- order=StrangOrder.STRANG_SECOND_ORDER)
+ splitting = StrangSplitting(splitting_dim=dim, order=args.strang_order)
splitting.push_operators(diffusion)
# Create the problem we want to solve and insert our
@@ -80,8 +82,10 @@ def compute(args):
problem.dump_inputs(fields=scalar, filename='S0', frequency=args.dump_freq)
problem.build()
- # If a visu_rank was provided, display the graph on the given process rank.
- problem.display(args.visu_rank)
+ # If a visu_rank was provided, and show_graph was set,
+ # display the graph on the given process rank.
+ if args.display_graph:
+ problem.display(args.visu_rank)
# Initialize discrete scalar field
dfields = problem.input_discrete_fields
@@ -90,9 +94,14 @@ def compute(args):
# Create a simulation and solve the problem
# (do not forget to specify the dt parameter here)
simu = Simulation(start=args.tstart, end=args.tend,
- dt0=args.dt, nb_iter=args.nb_iter,
- dt=dt)
- problem.solve(simu)
+ nb_iter=args.nb_iter, max_iter=args.max_iter,
+ times_of_interest=args.dump_times,
+ dt=dt, dt0=args.dt)
+
+ # Finally solve the problem
+ problem.solve(simu, dry_run=args.dry_run)
+
+ # Finalize
problem.finalize()
@@ -128,7 +137,7 @@ if __name__=='__main__':
parser = ScalarDiffusionArgParser()
parser.set_defaults(box_origin=(0.0,), box_length=(1.0,),
- tstart=0.0, tend=1.0, nb_iter=500,
+ tstart=0.0, tend=1.0, nb_iter=500,
dump_freq=5, nu=0.01, impl='cl')
parser.run(compute)
diff --git a/examples/taylor_green/taylor_green.py b/examples/taylor_green/taylor_green.py
index 2e273335d..84c4b7fd4 100644
--- a/examples/taylor_green/taylor_green.py
+++ b/examples/taylor_green/taylor_green.py
@@ -158,7 +158,7 @@ def compute(args):
max_iter=args.max_iter,
dt0=args.dt, times_of_interest=args.dump_times,
t=t, dt=dt)
- simu.write_parameters(t, dt_cfl, dt_advec, dt, enstrophy, #TODO dt_stretch
+ simu.write_parameters(t, dt_cfl, dt_advec, dt, enstrophy,
filename='parameters.txt', precision=6)
# Initialize only the vorticity
diff --git a/hysop/simulation.py b/hysop/simulation.py
index 28ce87f9f..74fc8b7da 100644
--- a/hysop/simulation.py
+++ b/hysop/simulation.py
@@ -146,7 +146,7 @@ class Simulation(object):
# backup initial time step, required to reset simulation.
self.max_iter = first_not_None(max_iter, 1e9)
- assert max_iter >= nb_iter
+ assert self.max_iter >= nb_iter
# Starting time for the current iteration
if (t is None):
self.t = ScalarParameter(name='t', dtype=HYSOP_REAL,
--
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