def _specialize_iet(cls, graph, **kwargs):
options = kwargs['options']
platform = kwargs['platform']
# Flush denormal numbers
avoid_denormals(graph)
# Distributed-memory parallelism
optimize_halospots(graph)
if options['mpi']:
mpiize(graph, mode=options['mpi'])
# Lower IncrDimensions so that blocks of arbitrary shape may be used
relax_incr_dimensions(graph, counter=generator())
# SIMD-level parallelism
ompizer = Ompizer()
ompizer.make_simd(graph, simd_reg_size=platform.simd_reg_size)
# Misc optimizations
hoist_prodders(graph)
# Symbol definitions
data_manager = DataManager()
data_manager.place_definitions(graph)
data_manager.place_casts(graph)
return graph
def _make_passes_mapper(cls, **kwargs):
options = kwargs['options']
platform = kwargs['platform']
blocker = Blocker(options['blockinner'], options['blocklevels']
or cls.BLOCK_LEVELS)
ompizer = Ompizer()
return {
'denormals':
partial(avoid_denormals),
'optcomms':
partial(optimize_halospots),
'wrapping':
partial(loop_wrapping),
'blocking':
partial(blocker.make_blocking),
'openmp':
partial(ompizer.make_parallel),
'mpi':
partial(mpiize, mode=options['mpi']),
'simd':
partial(ompizer.make_simd, simd_reg_size=platform.simd_reg_size),
'prodders':
partial(hoist_prodders)
}
def _specialize_iet(cls, graph, **kwargs):
options = kwargs['options']
sregistry = kwargs['sregistry']
# Distributed-memory parallelism
if options['mpi']:
mpiize(graph, mode=options['mpi'])
# Shared-memory parallelism
if options['openmp']:
ompizer = Ompizer(sregistry, options)
ompizer.make_parallel(graph)
# Symbol definitions
DataManager(sregistry).process(graph)
return graph
def _specialize_iet(cls, graph, **kwargs):
options = kwargs['options']
# Distributed-memory parallelism
if options['mpi']:
mpiize(graph, mode=options['mpi'])
# Shared-memory parallelism
if options['openmp']:
ompizer = Ompizer()
ompizer.make_parallel(graph)
# Symbol definitions
data_manager = DataManager()
data_manager.place_definitions(graph)
data_manager.place_casts(graph)
return graph
def _specialize_iet(cls, graph, **kwargs):
options = kwargs['options']
platform = kwargs['platform']
sregistry = kwargs['sregistry']
# Distributed-memory parallelism
optimize_halospots(graph)
if options['mpi']:
mpiize(graph, mode=options['mpi'])
# Lower IncrDimensions so that blocks of arbitrary shape may be used
relax_incr_dimensions(graph, sregistry=sregistry)
# SIMD-level parallelism
ompizer = Ompizer(sregistry, options)
ompizer.make_simd(graph, simd_reg_size=platform.simd_reg_size)
# Shared-memory parallelism
ompizer.make_parallel(graph)
# Misc optimizations
hoist_prodders(graph)
# Symbol definitions
DataManager(sregistry).process(graph)
return graph
def _specialize_iet(cls, graph, **kwargs):
options = kwargs['options']
platform = kwargs['platform']
# Flush denormal numbers
avoid_denormals(graph)
# Distributed-memory parallelism
optimize_halospots(graph)
if options['mpi']:
mpiize(graph, mode=options['mpi'])
# Tiling
blocker = Blocker(options['blockinner'], options['blocklevels']
or cls.BLOCK_LEVELS)
blocker.make_blocking(graph)
# Shared-memory and SIMD-level parallelism
ompizer = Ompizer()
ompizer.make_simd(graph, simd_reg_size=platform.simd_reg_size)
if options['openmp']:
ompizer.make_parallel(graph)
# Misc optimizations
hoist_prodders(graph)
# Symbol definitions
data_manager = DataManager()
data_manager.place_definitions(graph)
data_manager.place_casts(graph)
return graph
def _make_iet_passes_mapper(cls, **kwargs):
options = kwargs['options']
platform = kwargs['platform']
ompizer = Ompizer()
return {
'denormals': avoid_denormals,
'optcomms': optimize_halospots,
'wrapping': loop_wrapping,
'blocking': partial(relax_incr_dimensions, counter=generator()),
'openmp': ompizer.make_parallel,
'mpi': partial(mpiize, mode=options['mpi']),
'simd': partial(ompizer.make_simd, simd_reg_size=platform.simd_reg_size),
'prodders': hoist_prodders
}