diff --git a/examples/fixed_point/heat_equation.py b/examples/fixed_point/heat_equation.py
index 531b0000e1f9066cc0352530c609e0a31add6142..b11af4ab32a0c4f787a3366e532f4ef832a233a6 100644
--- a/examples/fixed_point/heat_equation.py
+++ b/examples/fixed_point/heat_equation.py
@@ -16,6 +16,9 @@ def CS( data, coords, t, component):
chi = lambda x,y,z: np.sqrt((x-pos[0])*(x-pos[0])+(y-pos[1])*(y-pos[1])+0.*z)<=RADIUS
data[...] = 0.
data[chi(x,y,z)] = np.cos(t())
+def init_u(data, coords, component):
+ (x,y,z) = coords
+ data[...] = 0.
def compute(args):
from hysop import Box, Simulation, Problem, Field, MPIParams, IO, IOParams, main_rank
@@ -52,10 +55,10 @@ def compute(args):
# and configure how the code is generated and compiled at runtime.
# Create an explicit OpenCL context from user parameters
- from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
+ from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env, get_device_number
cl_env = get_or_create_opencl_env(mpi_params=mpi_params,
platform_id=args.cl_platform_id,
- device_id=args.cl_device_id)
+ device_id=box.machine_rank%get_device_number() if args.cl_device_id is None else None)
# Configure OpenCL kernel generation and tuning (already done by HysopArgParser)
from hysop.methods import OpenClKernelConfig
@@ -170,6 +173,7 @@ def compute(args):
t=t, dt=dt)
simu.write_parameters(t, fixedPoint.it_num,
filename='parameters.txt', precision=8)
+ problem.initialize_field(u, formula=init_u)
problem.solve(simu, dry_run=args.dry_run)
problem.finalize()
diff --git a/hysop/backend/device/opencl/opencl_tools.py b/hysop/backend/device/opencl/opencl_tools.py
index cc4b66f6d9d69a798fef41653167d8d5722b1c54..2be6854855f6c8be265a429d21eaf5ef8b380552 100644
--- a/hysop/backend/device/opencl/opencl_tools.py
+++ b/hysop/backend/device/opencl/opencl_tools.py
@@ -89,7 +89,7 @@ def convert_device_type(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,
@@ -112,14 +112,14 @@ def convert_precision(precision):
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 = {
@@ -136,6 +136,11 @@ def convert_precision(precision):
return conversion[precision]
+@static_vars(opencl_environments=dict())
+def get_device_number(platform_id = None):
+ platform_id = first_not_None(platform_id, __DEFAULT_PLATFORM_ID__)
+ platform = get_platform(platform_id, strict=True)
+ return len(platform.get_devices())
@static_vars(opencl_environments=dict())
def get_or_create_opencl_env(mpi_params,
@@ -146,35 +151,35 @@ def get_or_create_opencl_env(mpi_params,
**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
+ All environements are kept alive (cached) in a dictionary local to this
function (ie. all opencl operators can share the same OpenClEnvironment).
"""
-
+
platform_id = first_not_None(platform_id, __DEFAULT_PLATFORM_ID__)
device_id = first_not_None(device_id, __DEFAULT_DEVICE_ID__)
device_type = first_not_None(device_type, DeviceType.ALL)
-
+
check_instance(mpi_params, MPIParams)
check_instance(platform_id, int)
check_instance(device_id, int)
check_instance(device_type, DeviceType, allow_none=True)
check_instance(gl_sharing, bool)
-
+
key = (mpi_params, platform_id, device_id, device_type, gl_sharing,)
-
+
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, mpi_params=mpi_params,
+ env = OpenClEnvironment(platform_id=platform_id, device_id=device_id,
+ device_type=device_type, gl_sharing=gl_sharing, mpi_params=mpi_params,
**kargs)
opencl_envs[key] = env
return env
-
+
def create_queue(ctx, props=None):
"""
diff --git a/hysop/domain/domain.py b/hysop/domain/domain.py
index 1f0d43f01528a22d31b1846ac7a23639a90d72a7..5daa7ec03588215046fafdc2ba0eb60383de6799 100644
--- a/hysop/domain/domain.py
+++ b/hysop/domain/domain.py
@@ -12,13 +12,14 @@ from hysop.tools.handle import RegisteredObject, TaggedObjectView
from hysop.tools.types import check_instance
from hysop.tools.numpywrappers import npw
from hysop.symbolic.frame import SymbolicFrame
+from hysop.deps import hashlib, np
class DomainView(TaggedObjectView):
"""Abstract base class for views on domains. """
__metaclass__ = ABCMeta
__slots__ = ('_domain', '_topology_state')
-
+
@debug
def __new__(cls, topology_state, domain=None, **kwds):
"""Create and initialize a DomainView."""
@@ -41,7 +42,7 @@ class DomainView(TaggedObjectView):
def _get_topology_state(self):
"""Return the topology state altering this domain view."""
return self._topology_state
-
+
def _get_dim(self):
"""Return the dimension of the domain."""
return self._domain._dim
@@ -61,6 +62,16 @@ class DomainView(TaggedObjectView):
def _get_task_rank(self):
"""Return the rank of the process in the task communicator."""
return self._domain._task_rank
+ def _get_machine_comm(self):
+ """
+ Return the communicator that owns the current process.
+ This is the sub-communicator which has been obtained by splitting.
+ the parent communicator by machine name.
+ """
+ return self._domain._machine_comm
+ def _get_machine_rank(self):
+ """Return the rank of the process in the machine communicator."""
+ return self._domain._machine_rank
def _get_proc_tasks(self):
"""Return mapping between mpi process rank and task identifier."""
return self._domain._proc_tasks
@@ -73,7 +84,7 @@ class DomainView(TaggedObjectView):
def _get_frame(self):
"""Get symbolic frame associated to this domain."""
return self._domain._frame
-
+
def task_on_proc(self, parent_rank):
"""Get task identifier for a given mpi process (parent communicator rank)."""
if parent_rank >= len(self._domain._proc_tasks):
@@ -84,7 +95,7 @@ class DomainView(TaggedObjectView):
def current_task(self):
"""Get task number of the current mpi process."""
return self.task_on_proc(self._domain._parent_rank)
-
+
def is_on_task(self, params):
"""Test if the current process corresponds to param task."""
if isinstance(params, MPIParams):
@@ -96,7 +107,7 @@ class DomainView(TaggedObjectView):
msg=msg.format(type(params))
raise TypeError(msg)
return (self.current_task() == task_id)
-
+
def print_topologies(self):
"""Print all topologies registered on the domain."""
print self.short_description() + ' defined the following topologies:'
@@ -129,11 +140,11 @@ class DomainView(TaggedObjectView):
def __hash__(self):
return id(self._domain) ^ hash(self._topology_state)
-
+
def __str__(self):
"""Equivalent to self.long_description()"""
return self.long_description()
-
+
domain = property(_get_domain)
dim = property(_get_dim)
proc_tasks = property(_get_proc_tasks)
@@ -141,18 +152,20 @@ class DomainView(TaggedObjectView):
parent_rank = property(_get_parent_rank)
task_comm = property(_get_task_comm)
task_rank = property(_get_task_rank)
+ machine_comm = property(_get_machine_comm)
+ machine_rank = property(_get_machine_rank)
registered_topologies = property(_get_registered_topologies)
frame = property(_get_frame)
-
+
class Domain(RegisteredObject):
"""Abstract base class for the description of physical domains. """
__metaclass__ = ABCMeta
-
+
@debug
def __new__(cls, dim, parent_comm=None, proc_tasks=None, **kwds):
"""
- Create or get an existing physical domain of given dim on a specified MPI
+ Create or get an existing physical domain of given dim on a specified MPI
communicator and specific tasks.
Parameters
@@ -190,33 +203,33 @@ class Domain(RegisteredObject):
-----
*Parent communicator is split according to proc_tasks.
*About MPI Tasks
- proc_tasks[n] = 12 means that task 12 owns proc n
+ proc_tasks[n] = 12 means that task 12 owns proc n
or equivalently that proc n is dedicated to task 12.
- *A dupped parent_comm will return another idenpendent domain instance,
- because MPI communicators are hashed trough their python object id.
+ *A dupped parent_comm will return another idenpendent domain instance,
+ because MPI communicators are hashed trough their python object id.
"""
-
+
dim = int(dim)
parent_comm = parent_comm or main_comm
proc_tasks = proc_tasks or [HYSOP_DEFAULT_TASK_ID,] * parent_comm.Get_size()
proc_tasks = npw.asdimarray(proc_tasks)
assert proc_tasks.size == parent_comm.Get_size()
-
+
npw.set_readonly(proc_tasks)
-
+
# double check types, to be sure RegisteredObject will work as expected
check_instance(dim, int)
check_instance(parent_comm, MPI.Intracomm)
check_instance(proc_tasks, npw.ndarray, dtype=HYSOP_DIM)
- obj = super(Domain,cls).__new__(cls, dim=dim, parent_comm=parent_comm,
+ obj = super(Domain,cls).__new__(cls, dim=dim, parent_comm=parent_comm,
proc_tasks=proc_tasks, tag_prefix='d', **kwds)
if not obj.obj_initialized:
obj.__initialize(dim, parent_comm, proc_tasks)
return obj
-
+
@debug
def __initialize(self, dim, parent_comm, proc_tasks):
parent_rank = parent_comm.Get_rank()
@@ -227,15 +240,24 @@ class Domain(RegisteredObject):
else:
assert len(proc_tasks) == parent_size
task_comm = parent_comm.Split(color=proc_tasks[parent_rank],
- key=parent_rank)
+ key=parent_rank)
task_rank = task_comm.Get_rank()
-
+
+ # Build a per-machine communicator in order to get a rank on local machines
+ # Split accoring to machine name hashed and converted to integer (strings generally differs only from a single character)
+ machine_comm = parent_comm.Split(
+ color=np.int32(int(hashlib.md5(MPI.Get_processor_name()).hexdigest(),16)%np.iinfo(np.int32).max),
+ key=parent_rank)
+ machine_rank = machine_comm.Get_rank()
+
self._dim = dim
self._parent_comm = parent_comm
self._parent_rank = parent_rank
self._task_comm = task_comm
self._task_rank = task_rank
+ self._machine_comm = machine_comm
+ self._machine_rank = machine_rank
self._proc_tasks = proc_tasks
self._registered_topologies = {}
self._frame = SymbolicFrame(dim=dim)
@@ -271,5 +293,3 @@ class Domain(RegisteredObject):
def view(self, topology_state):
"""Return a view of this domain altered by some topology_state."""
pass
-
-
diff --git a/hysop/operator/parameter_plotter.py b/hysop/operator/parameter_plotter.py
index e45dfe07295fc5f0da2d1276d91576d947071cae..231a2e0daf83d0b1e07585fd9f1c59cfb9bcff19 100644
--- a/hysop/operator/parameter_plotter.py
+++ b/hysop/operator/parameter_plotter.py
@@ -17,18 +17,18 @@ class PlottingOperator(ComputationalGraphOperator):
def __init__(self, name=None,
dump_dir=None,
- update_frequency=1,
- save_frequency=100,
- axes_shape=(1,),
+ update_frequency=1,
+ save_frequency=100,
+ axes_shape=(1,),
figsize=(30,18),
visu_rank=0,
- fig=None,
+ fig=None,
axes=None,
**kwds):
-
+
import matplotlib
import matplotlib.pyplot as plt
-
+
check_instance(name, str)
check_instance(update_frequency, int, minval=0)
check_instance(save_frequency, int, minval=0)
@@ -39,15 +39,15 @@ class PlottingOperator(ComputationalGraphOperator):
if (fig is None) ^ (axes is None):
msg='figure and axes should be specified at the same time.'
raise RuntimeError(msg)
-
+
dump_dir = first_not_None(dump_dir, IO.default_path())
imgpath = '{}/{}.png'.format(dump_dir, name)
-
+
if (fig is None):
fig, axes = plt.subplots(*axes_shape, figsize=figsize)
fig.canvas.mpl_connect('key_press_event', self.on_key_press)
fig.canvas.mpl_connect('close_event', self.on_close)
-
+
axes = npw.asarray(axes).reshape(axes_shape)
self.fig = fig
@@ -79,7 +79,7 @@ class PlottingOperator(ComputationalGraphOperator):
def _save(self, simulation, **kwds):
if simulation.should_dump(frequency=self.save_frequency, with_last=True):
self.save(simulation=simulation, **kwds)
-
+
@abstractmethod
def update(self, **kwds):
pass
@@ -87,7 +87,7 @@ class PlottingOperator(ComputationalGraphOperator):
def save(self, **kwds):
self.fig.savefig(self.imgpath, dpi=self.fig.dpi,
bbox_inches='tight')
-
+
def on_close(self, event):
self.running = False
@@ -100,14 +100,15 @@ class PlottingOperator(ComputationalGraphOperator):
class ParameterPlotter(PlottingOperator):
"""
- Base operator to plot parameters during runtime.
+ Base operator to plot parameters during runtime.
"""
-
- def __init__(self, name, parameters, alloc_size=128,
+
+ def __init__(self, name, parameters, alloc_size=128,
fig=None, axes=None, shape=None, **kwds):
-
+
input_params = {}
if (fig is not None) and (axes is not None):
+ import matplotlib
custom_axes = True
axes_shape=None
check_instance(parameters, dict, keys=matplotlib.axes.Axes, values=dict)
@@ -127,7 +128,7 @@ class ParameterPlotter(PlottingOperator):
else:
raise TypeError(type(parameters))
check_instance(_parameters, dict, keys=(int,tuple,list), values=(TensorParameter,list,tuple,dict))
-
+
parameters = {}
axes_shape = (1,)*2
for (pos,params) in _parameters.iteritems():
@@ -158,7 +159,7 @@ class ParameterPlotter(PlottingOperator):
_params[_pname] = _p
parameters[pos] = _params
- super(ParameterPlotter, self).__init__(name=name, input_params=input_params,
+ super(ParameterPlotter, self).__init__(name=name, input_params=input_params,
axes_shape=axes_shape, axes=axes, fig=fig, **kwds)
self.custom_axes = custom_axes
@@ -198,7 +199,7 @@ class ParameterPlotter(PlottingOperator):
return self.axes[i]
else:
return self.axes.flatten()[i]
-
+
def update(self, simulation, **kwds):
# expand memory if required
if (self.counter+1>self.times.size):
@@ -219,4 +220,3 @@ class ParameterPlotter(PlottingOperator):
lines[pos][p].set_xdata(times[:self.counter])
lines[pos][p].set_ydata(data[pos][p][:self.counter])
self.counter += 1
-