def _init_visualization_and_io(self, sim):
if self.config.output:
output_cls = io.format_name_to_cls[self.config.output_format]
else:
output_cls = io.LBOutput
if self.config.mode != 'visualization':
return lambda subdomain: output_cls(self.config, subdomain.id)
# basic_fields = sim.fields()
# XXX compute total storage requirements
for subdomain in self.subdomains:
size = reduce(operator.mul, subdomain.size)
vis_lock = mp.Lock()
vis_buffer = Array(ctypes.c_float, size, lock=vis_lock)
vis_geo_buffer = Array(ctypes.c_uint8, size, lock=vis_lock)
subdomain.set_vis_buffers(vis_buffer, vis_geo_buffer)
vis_lock = mp.Lock()
vis_config = Value(io.VisConfig, lock=vis_lock)
vis_config.iteration = -1
vis_config.field_name = ''
vis_config.all_blocks = False
# Start the visualizatione engine.
vis_class = None
for engine in util.get_visualization_engines():
if engine.name == self.config.vis_engine:
vis_class = engine
break
if vis_class is None:
self.config.logger.warning('Requested visualization engine not '
'available.')
try:
vis_class = util.get_visualization_engines().next()
except StopIteration:
self.config.logger.warning(
'No visualization backends available. Falling back to '
'batch mode.')
self.config.mode = 'batch'
return lambda subdomain: output_cls(self.config, subdomain.id)
# Event to signal that the visualization process should be terminated.
self._vis_quit_event = Event()
self._vis_process = Process(
target=lambda: vis_class(
self.config, self.subdomains, self._vis_quit_event,
self._quit_event, vis_config).run(),
name='VisEngine')
self._vis_process.start()
return lambda subdomain: io.VisualizationWrapper(
self.config, subdomain, vis_config, output_cls)
def _init_visualization_and_io(self, sim):
if self.config.output:
output_cls = io.format_name_to_cls[self.config.output_format]
else:
# Dummy output class. Does not actually save data, but does provide
# utility functions common to all output classes.
output_cls = io.LBOutput
if self.config.mode != 'visualization':
return lambda subdomain: output_cls(self.config, subdomain.id)
# XXX compute total storage requirements
self._vis_geo_queues = []
for subdomain in self.subdomain_specs:
self._vis_geo_queues.append(subdomain.init_visualization())
vis_lock = mp.Lock()
vis_config = Value(io.VisConfig, lock=vis_lock)
vis_config.iteration = -1
vis_config.field_name = ''
vis_config.all_subdomains = False
# Start the visualizatione engine.
vis_class = None
for engine in util.get_visualization_engines():
if engine.name == self.config.vis_engine:
vis_class = engine
break
if vis_class is None:
self.config.logger.warning('Requested visualization engine not '
'available.')
try:
vis_class = util.get_visualization_engines().next()
except StopIteration:
self.config.logger.warning(
'No visualization backends available. Falling back to '
'batch mode.')
self.config.mode = 'batch'
return lambda subdomain: output_cls(self.config, subdomain.id)
# Event to signal that the visualization process should be terminated.
self._vis_quit_event = Event()
self._vis_process = Process(
target=lambda: vis_class(
self.config, self.subdomain_specs, self._vis_quit_event,
self._quit_event, vis_config, self._vis_geo_queues).run(),
name='VisEngine')
self._vis_process.start()
return lambda subdomain: io.VisualizationWrapper(
self.config, subdomain, vis_config, output_cls)
def _init_visualization_and_io(self, sim):
if self.config.output:
output_cls = io.format_name_to_cls[self.config.output_format]
else:
# Dummy output class. Does not actually save data, but does provide
# utility functions common to all output classes.
output_cls = io.LBOutput
if self.config.mode != 'visualization':
return lambda subdomain: output_cls(self.config, subdomain.id)
# XXX compute total storage requirements
self._vis_geo_queues = []
for subdomain in self.subdomain_specs:
self._vis_geo_queues.append(subdomain.init_visualization())
vis_lock = mp.Lock()
vis_config = Value(io.VisConfig, lock=vis_lock)
vis_config.iteration = -1
vis_config.field_name = b''
vis_config.all_subdomains = False
# Start the visualizatione engine.
vis_class = None
for engine in util.get_visualization_engines():
if engine.name == self.config.vis_engine:
vis_class = engine
break
if vis_class is None:
self.config.logger.warning('Requested visualization engine not '
'available.')
try:
vis_class = next(util.get_visualization_engines())
except StopIteration:
self.config.logger.warning(
'No visualization backends available. Falling back to '
'batch mode.')
self.config.mode = 'batch'
return lambda subdomain: output_cls(self.config, subdomain.id)
# Event to signal that the visualization process should be terminated.
self._vis_quit_event = Event()
self._vis_process = Process(
target=lambda: vis_class(
self.config, self.subdomain_specs, self._vis_quit_event,
self._quit_event, vis_config, self._vis_geo_queues).run(),
name='VisEngine')
self._vis_process.start()
return lambda subdomain: io.VisualizationWrapper(
self.config, subdomain, vis_config, output_cls)
def _init_visualization_and_io(self, sim):
if self.config.output:
output_cls = io.format_name_to_cls[self.config.output_format]
else:
output_cls = io.LBOutput
if self.config.mode != 'visualization':
return lambda subdomain: output_cls(self.config, subdomain.id)
# basic_fields = sim.fields()
# XXX compute total storage requirements
for subdomain in self.subdomains:
size = reduce(operator.mul, subdomain.size)
vis_lock = mp.Lock()
vis_buffer = Array(ctypes.c_float, size, lock=vis_lock)
vis_geo_buffer = Array(ctypes.c_uint8, size, lock=vis_lock)
subdomain.set_vis_buffers(vis_buffer, vis_geo_buffer)
vis_lock = mp.Lock()
vis_config = Value(io.VisConfig, lock=vis_lock)
vis_config.iteration = -1
vis_config.field_name = ''
vis_config.all_blocks = False
# Start the visualizatione engine.
vis_class = util.get_visualization_engines().next()
# Event to signal that the visualization process should be terminated.
self._vis_quit_event = Event()
self._vis_process = Process(
target=lambda: vis_class(
self.config, self.subdomains, self._vis_quit_event,
self._quit_event, vis_config).run(),
name='VisEngine')
self._vis_process.start()
return lambda subdomain: io.VisualizationWrapper(
self.config, subdomain, vis_config, output_cls)
def __init__(self, lb_class, lb_geo=None, default_config=None):
"""
:param lb_class: class describing the simulation, derived from LBSim
:param lb_geo: class describing the global geometry in terms of
SubdomainSpec, derived from LBGeometry
:param default_config: dictionary mapping command line option names
to their new default values
"""
self._config_parser = config.LBConfigParser()
self._lb_class = lb_class
# Use a default global geometry is one has not been
# specified explicitly.
if lb_geo is None:
if self.dim == 2:
lb_geo = LBGeometry2D
else:
lb_geo = LBGeometry3D
self._lb_geo = lb_geo
self._tmpdir = tempfile.mkdtemp()
group = self._config_parser.add_group('Runtime mode settings')
group.add_argument('--mode', help='runtime mode', type=str,
choices=['batch', 'visualization', 'benchmark'], default='batch'),
group.add_argument('--every',
help='save/visualize simulation results every N iterations ',
metavar='N', type=int, default=100)
group.add_argument('--from', dest='from_',
help='save/visualize simulation results from N iterations ', metavar='N',
type=int, default=0)
group.add_argument('--perf_stats_every',
help='how often to display performance stats',
metavar='N', type=int, default=1000)
group.add_argument('--max_iters',
help='number of iterations to run; use 0 to run indefinitely',
type=int, default=0)
group.add_argument('--init_iters',
help='number of iterations to use for the '
'initialization phase. If <= 0, no initialization '
'phase is run.', type=int, default=0)
group.add_argument('--output',
help='save simulation results to FILE', metavar='FILE',
type=str, default='')
group.add_argument('--output_format',
help='output format', type=str,
choices=list(io.format_name_to_cls.keys()), default='npy')
group.add_argument('--nooutput_compress', dest='output_compress',
action='store_false', default=True,
help='stores the output in compressed files'
'if the selected format supports it')
group.add_argument('--backends',
type=str, default='cuda,opencl',
help='computational backends to use; multiple backends '
'can be separated by a comma')
group.add_argument('--vis_engine',
type=str, default='pygame',
help='visualization engine to use')
group.add_argument('--gpus', nargs='+', default=0, type=int,
help='which GPUs to use')
group.add_argument('--debug_dump_dists', action='store_true',
default=False, help='dump the contents of the distribution '
'arrays to files'),
group.add_argument('--debug_single_process', action='store_true',
default=False,
help='If True, will run the controller, master and subdomain '
'runner in a single process, which can be helpful for '
'debugging.')
group.add_argument('--debug_dump_node_type_map', action='store_true',
default=False, help='Dump the contents of the node type map '
'into a file'),
group.add_argument('--base_name', type=str, default='',
help='Specifies the base file name that will be used for '
'logging, checkpoint and data output. This makes it '
'possible to avoid specifying --log, --output, and '
'--checkpoint_file separately. Whenever some of '
'these options are specified, their value takes '
'precedence over the one automatically generated '
'using --base_name.')
group.add_argument('--log', type=str, default='',
help='name of the file to which data is to be logged')
group.add_argument('--loglevel', type=int, default=logging.INFO,
help='minimum log level for the file logger')
group.add_argument('--nobulk_boundary_split',
dest='bulk_boundary_split', action='store_false',
default=True,
help='Disable separate handling of bulk and '
'boundary nodes (increases parallelism)')
group.add_argument('--cluster_spec', type=str, default='',
help='path of a Python module with the cluster specification')
group.add_argument('--cluster_sync', type=str, default='',
help='local_path:dest_path; if specified, will send the '
'contents of "local_path" to "dest_path" on all cluster '
'machines before starting the simulation.')
group.add_argument('--nocluster_pbs', action='store_false', default=True,
dest='cluster_pbs',
help='If True, standard PBS variables will be used to run '
'the job in a cluster.')
group.add_argument('--cluster_pbs_initscript', type=str,
default='sailfish-init.sh', help='Script to execute on remote '
'nodes in order to set the environment prior to starting '
'a machine master.')
group.add_argument('--cluster_interface', type=str,
dest='cluster_interface',
default='',
help='Network interface to use on PBS/LSF nodes for '
'internode communication.')
group.add_argument('--nocluster_lsf', action='store_false',
default=True, dest='cluster_lsf', help='If True, '
'standard LSF variables will be used to run the job '
'in a cluster.')
group.add_argument('--nofdust', action='store_false',
default=True, dest='fdust', help='If True, will use '
'logical GPUs 0..n via libfairydust (if present).')
group.add_argument('--nocheck_invalid_results_host', action='store_false',
dest='check_invalid_results_host',
default=True, help='If True, will terminate the simulation if '
'the results obtained on the host contain invalid values '
'(inf, nan).')
group.add_argument('--nocheck_invalid_results_gpu',
action='store_false', dest='check_invalid_results_gpu',
default=True, help='If True, will terminate the simulation '
'when invalid values (inf, nan) are detected in the domain '
'during the simulation.')
group.add_argument('--compress_intersubdomain_data',
action='store_true', default=False, help='Uses blosc to '
'compress data exchanged between subdomains. Can improve '
'performance in distributed simulations limited by bandwidth '
'available between computational nodes.')
group.add_argument('--seed', type=int, default=int(time.time()),
help='PRNG seed value')
group = self._config_parser.add_group('Checkpointing')
group.add_argument('--checkpoint_file', type=str, help='Location of '
'the checkpoint file.', metavar='PATH', default='')
group.add_argument('--single_checkpoint', action='store_true',
default=False,
help='If True, only a single checkpoint file will be '
'generated. If multiple checkpoints are requested, only the '
'last one will be retained. This is useful together with '
'--check_invalid_results_gpu')
group.add_argument('--restore_from', type=str, metavar='PATH',
help='Location of a checkpoint file from which to start the '
'simulation.', default='')
group.add_argument('--norestore_time', action='store_false',
dest='restore_time',
default=True, help='If True, and simulation time'
' will be restored when reading a checkpoint.')
group.add_argument('--final_checkpoint', action='store_true',
default=False, help='Generates a checkpoint after the simulation '
'is completed.')
group.add_argument('--checkpoint_every', type=int, default=0,
metavar='N', help='Generates a checkpoint every N steps.')
group.add_argument('--checkpoint_from', type=int, default=0,
metavar='N', help='Starts generating checkpoints after N '
'steps of the simulation have been completed.')
group = self._config_parser.add_group('Benchmarking')
group.add_argument('--benchmark_sample_from', type=int, default=1000,
metavar='N', help='Start sampling performance '
'data at N-th iteration.')
group.add_argument('--benchmark_minibatch', type=int, default=50,
help='Number of simulation steps used for batching '
'for purposes of standard deviation calculation.')
group = self._config_parser.add_group('Simulation-specific settings')
for base in lb_class.mro():
if 'add_options' in base.__dict__:
base.add_options(group, self.dim)
group = self._config_parser.add_group('Geometry settings')
lb_geo.add_options(group)
group = self._config_parser.add_group('Code generator options')
codegen.BlockCodeGenerator.add_options(group)
# Backend options
for backend in util.get_backends():
group = self._config_parser.add_group(
"'{0}' backend options".format(backend.name))
backend.add_options(group)
# Do not try to import visualization engine modules if we already
# know that the simulation will be running in batch mode.
if (default_config is None or 'mode' not in default_config or
default_config['mode'] == 'visualization'):
for engine in util.get_visualization_engines():
group = self._config_parser.add_group(
"'{0}' visualization engine".format(engine.name))
engine.add_options(group)
# Set default values defined by the simulation-specific class.
defaults = {}
lb_class.update_defaults(defaults)
self._config_parser.set_defaults(defaults)
if default_config is not None:
self._config_parser.set_defaults(default_config)
def __init__(self, lb_class, lb_geo=None, default_config=None):
"""
:param lb_class: class describing the simulation, derived from LBSim
:param lb_geo: class describing the global geometry in terms of
SubdomainSpec, derived from LBGeometry
:param default_config: dictionary mapping command line option names
to their new default values
"""
self._config_parser = config.LBConfigParser()
self._lb_class = lb_class
# Use a default global geometry is one has not been
# specified explicitly.
if lb_geo is None:
if self.dim == 2:
lb_geo = LBGeometry2D
else:
lb_geo = LBGeometry3D
self._lb_geo = lb_geo
self._tmpdir = tempfile.mkdtemp()
group = self._config_parser.add_group('Runtime mode settings')
group.add_argument('--mode', help='runtime mode', type=str,
choices=['batch', 'visualization', 'benchmark'], default='batch'),
group.add_argument('--every',
help='save/visualize simulation results every N iterations ',
metavar='N', type=int, default=100)
group.add_argument('--from', dest='from_',
help='save/visualize simulation results from N iterations ', metavar='N',
type=int, default=0)
group.add_argument('--perf_stats_every',
help='how often to display performance stats',
metavar='N', type=int, default=1000)
group.add_argument('--max_iters',
help='number of iterations to run; use 0 to run indefinitely',
type=int, default=0)
group.add_argument('--init_iters',
help='number of iterations to use for the '
'initialization phase. If <= 0, no initialization '
'phase is run.', type=int, default=0)
group.add_argument('--output',
help='save simulation results to FILE', metavar='FILE',
type=str, default='')
group.add_argument('--output_format',
help='output format', type=str,
choices=list(io.format_name_to_cls.keys()), default='npy')
group.add_argument('--nooutput_compress', dest='output_compress',
action='store_false', default=True,
help='stores the output in compressed files'
'if the selected format supports it')
group.add_argument('--backends',
type=str, default='cuda,opencl',
help='computational backends to use; multiple backends '
'can be separated by a comma')
group.add_argument('--vis_engine',
type=str, default='pygame',
help='visualization engine to use')
group.add_argument('--gpus', nargs='+', default=0, type=int,
help='which GPUs to use')
group.add_argument('--debug_dump_dists', action='store_true',
default=False, help='dump the contents of the distribution '
'arrays to files'),
group.add_argument('--debug_single_process', action='store_true',
default=False,
help='If True, will run the controller, master and subdomain '
'runner in a single process, which can be helpful for '
'debugging.')
group.add_argument('--debug_dump_node_type_map', action='store_true',
default=False, help='Dump the contents of the node type map '
'into a file'),
group.add_argument('--base_name', type=str, default='',
help='Specifies the base file name that will be used for '
'logging, checkpoint and data output. This makes it '
'possible to avoid specifying --log, --output, and '
'--checkpoint_file separately. Whenever some of '
'these options are specified, their value takes '
'precedence over the one automatically generated '
'using --base_name.')
group.add_argument('--log', type=str, default='',
help='name of the file to which data is to be logged')
group.add_argument('--loglevel', type=int, default=logging.INFO,
help='minimum log level for the file logger')
group.add_argument('--nobulk_boundary_split',
dest='bulk_boundary_split', action='store_false',
default=True,
help='Disable separate handling of bulk and '
'boundary nodes (increases parallelism)')
group.add_argument('--cluster_spec', type=str, default='',
help='path of a Python module with the cluster specification')
group.add_argument('--cluster_sync', type=str, default='',
help='local_path:dest_path; if specified, will send the '
'contents of "local_path" to "dest_path" on all cluster '
'machines before starting the simulation.')
group.add_argument('--nocluster_pbs', action='store_false', default=True,
dest='cluster_pbs',
help='If True, standard PBS variables will be used to run '
'the job in a cluster.')
group.add_argument('--cluster_pbs_initscript', type=str,
default='sailfish-init.sh', help='Script to execute on remote '
'nodes in order to set the environment prior to starting '
'a machine master.')
group.add_argument('--cluster_interface', type=str,
dest='cluster_interface',
default='',
help='Network interface to use on PBS/LSF nodes for '
'internode communication.')
group.add_argument('--nocluster_lsf', action='store_false',
default=True, dest='cluster_lsf', help='If True, '
'standard LSF variables will be used to run the job '
'in a cluster.')
group.add_argument('--nofdust', action='store_false',
default=True, dest='fdust', help='If True, will use '
'logical GPUs 0..n via libfairydust (if present).')
group.add_argument('--nocheck_invalid_results_host', action='store_false',
dest='check_invalid_results_host',
default=True, help='If True, will terminate the simulation if '
'the results obtained on the host contain invalid values '
'(inf, nan).')
group.add_argument('--nocheck_invalid_results_gpu',
action='store_false', dest='check_invalid_results_gpu',
default=True, help='If True, will terminate the simulation '
'when invalid values (inf, nan) are detected in the domain '
'during the simulation.')
group.add_argument('--compress_intersubdomain_data',
action='store_true', default=False, help='Uses blosc to '
'compress data exchanged between subdomains. Can improve '
'performance in distributed simulations limited by bandwidth '
'available between computational nodes.')
group.add_argument('--seed', type=int, default=int(time.time()),
help='PRNG seed value')
group = self._config_parser.add_group('Checkpointing')
group.add_argument('--checkpoint_file', type=str, help='Location of '
'the checkpoint file.', metavar='PATH', default='')
group.add_argument('--single_checkpoint', action='store_true',
default=False,
help='If True, only a single checkpoint file will be '
'generated. If multiple checkpoints are requested, only the '
'last one will be retained. This is useful together with '
'--check_invalid_results_gpu')
group.add_argument('--restore_from', type=str, metavar='PATH',
help='Location of a checkpoint file from which to start the '
'simulation.', default='')
group.add_argument('--norestore_time', action='store_false',
dest='restore_time',
default=True, help='If True, and simulation time'
' will be restored when reading a checkpoint.')
group.add_argument('--final_checkpoint', action='store_true',
default=False, help='Generates a checkpoint after the simulation '
'is completed.')
group.add_argument('--checkpoint_every', type=int, default=0,
metavar='N', help='Generates a checkpoint every N steps.')
group.add_argument('--checkpoint_from', type=int, default=0,
metavar='N', help='Starts generating checkpoints after N '
'steps of the simulation have been completed.')
group = self._config_parser.add_group('Benchmarking')
group.add_argument('--benchmark_sample_from', type=int, default=1000,
metavar='N', help='Start sampling performance '
'data at N-th iteration.')
group.add_argument('--benchmark_minibatch', type=int, default=50,
help='Number of simulation steps used for batching '
'for purposes of standard deviation calculation.')
group = self._config_parser.add_group('Simulation-specific settings')
for base in lb_class.mro():
if 'add_options' in base.__dict__:
base.add_options(group, self.dim)
group = self._config_parser.add_group('Geometry settings')
lb_geo.add_options(group)
group = self._config_parser.add_group('Code generator options')
codegen.BlockCodeGenerator.add_options(group)
# Backend options
for backend in util.get_backends():
group = self._config_parser.add_group(
"'{0}' backend options".format(backend.name))
backend.add_options(group)
# Do not try to import visualization engine modules if we already
# know that the simulation will be running in batch mode.
if (default_config is None or 'mode' not in default_config or
default_config['mode'] == 'visualization'):
for engine in util.get_visualization_engines():
group = self._config_parser.add_group(
"'{0}' visualization engine".format(engine.name))
engine.add_options(group)
# Set default values defined by the simulation-specific class.
defaults = {}
lb_class.update_defaults(defaults)
self._config_parser.set_defaults(defaults)
if default_config is not None:
self._config_parser.set_defaults(default_config)
