def __init__(self, cfg):
super(OpenMPBackend, self).__init__(cfg)
# Take the alignment requirement to be 32-bytes
self.alignb = 32
from pyfr.backends.openmp import (blasext, cblas, packing, provider,
types)
# Register our data types
self.const_matrix_cls = types.OpenMPConstMatrix
self.matrix_cls = types.OpenMPMatrix
self.matrix_bank_cls = types.OpenMPMatrixBank
self.matrix_rslice_cls = types.OpenMPMatrixRSlice
self.mpi_matrix_cls = types.OpenMPMPIMatrix
self.mpi_view_cls = types.OpenMPMPIView
self.queue_cls = types.OpenMPQueue
self.view_cls = types.OpenMPView
# Template lookup
self.lookup = DottedTemplateLookup('pyfr.backends.openmp.kernels')
# Kernel provider classes
kprovcls = [
provider.OpenMPPointwiseKernelProvider,
blasext.OpenMPBlasExtKernels, packing.OpenMPPackingKernels,
cblas.OpenMPCBLASKernels
]
self._providers = [k(self) for k in kprovcls]
# Pointwise kernels
self.pointwise = self._providers[0]
def __init__(self, cfg):
super(CUDABackend, self).__init__(cfg)
# Get the desired CUDA device
devid = cfg.get('backend-cuda', 'device-id', 'round-robin')
if not re.match(r'(round-robin|local-rank|\d+)$', devid):
raise ValueError('Invalid device-id')
# Handle the local-rank case
if devid == 'local-rank':
devid = str(get_local_rank())
# In the non round-robin case set CUDA_DEVICE to be the desired
# CUDA device number (used by pycuda.autoinit)
os.environ.pop('CUDA_DEVICE', None)
if devid != 'round-robin':
os.environ['CUDA_DEVICE'] = devid
# Create a CUDA context
from pycuda.autoinit import context
import pycuda.driver as cuda
# Take the required alignment to be 128 bytes
self.alignb = 128
# Some CUDA devices share L1 cache and shared memory; on these
# devices CUDA allows us to specify a preference between L1
# cache and shared memory. For the sake of CUBLAS (which
# benefits greatly from more shared memory but fails to
# declare its preference) we set the global default to
# PREFER_SHARED.
context.set_cache_config(cuda.func_cache.PREFER_SHARED)
from pyfr.backends.cuda import (blasext, cublas, packing, provider,
types)
# Register our data types
self.base_matrix_cls = types.CUDAMatrixBase
self.const_matrix_cls = types.CUDAConstMatrix
self.matrix_cls = types.CUDAMatrix
self.matrix_bank_cls = types.CUDAMatrixBank
self.matrix_rslice_cls = types.CUDAMatrixRSlice
self.mpi_matrix_cls = types.CUDAMPIMatrix
self.mpi_view_cls = types.CUDAMPIView
self.queue_cls = types.CUDAQueue
self.view_cls = types.CUDAView
# Template lookup
self.lookup = DottedTemplateLookup('pyfr.backends.cuda.kernels')
# Instantiate the base kernel providers
kprovs = [
provider.CUDAPointwiseKernelProvider, blasext.CUDABlasExtKernels,
packing.CUDAPackingKernels, cublas.CUDACUBLASKernels
]
self._providers = [k(self) for k in kprovs]
# Pointwise kernels
self.pointwise = self._providers[0]
def lookup(self):
pkg = f'pyfr.backends.{self.name}.kernels'
dfltargs = dict(fpdtype=self.fpdtype,
soasz=self.soasz,
csubsz=self.csubsz,
math=math)
return DottedTemplateLookup(pkg, dfltargs)
def lookup(self):
pkg = 'pyfr.backends.{0}.kernels'.format(self.name)
dfltargs = dict(alignb=self.alignb,
fpdtype=self.fpdtype,
soasz=self.soasz,
math=math)
return DottedTemplateLookup(pkg, dfltargs)
def __init__(self, cfg):
super().__init__(cfg)
import pymic as mic
# Get the device ID to use
devid = cfg.get('backend-mic', 'device-id', 'local-rank')
# Handle the local-rank case
if devid == 'local-rank':
devid = str(get_local_rank())
# Get a handle to the desired device
self.dev = mic.devices[int(devid)]
# Default stream
self.sdflt = self.dev.get_default_stream()
# Take the alignment requirement to be 64-bytes
self.alignb = 64
from pyfr.backends.mic import (blasext, cblas, packing, provider,
types)
# Register our data types
self.base_matrix_cls = types.MICMatrixBase
self.const_matrix_cls = types.MICConstMatrix
self.matrix_cls = types.MICMatrix
self.matrix_bank_cls = types.MICMatrixBank
self.matrix_rslice_cls = types.MICMatrixRSlice
self.queue_cls = types.MICQueue
self.view_cls = types.MICView
self.xchg_matrix_cls = types.MICXchgMatrix
self.xchg_view_cls = types.MICXchgView
# Template lookup
self.lookup = DottedTemplateLookup('pyfr.backends.mic.kernels',
fpdtype=self.fpdtype,
alignb=self.alignb)
# Kernel provider classes
kprovcls = [
provider.MICPointwiseKernelProvider, blasext.MICBlasExtKernels,
packing.MICPackingKernels, cblas.MICCBLASKernels
]
self._providers = [k(self) for k in kprovcls]
# Pointwise kernels
self.pointwise = self._providers[0]
def __init__(self, cfg):
super(OpenCLBackend, self).__init__(cfg)
import pyopencl as cl
# Get the platform/device info from the config file
platid = cfg.get('backend-opencl', 'platform-id', '0').lower()
devid = cfg.get('backend-opencl', 'device-id', 'local-rank').lower()
devtype = cfg.get('backend-opencl', 'device-type', 'all').upper()
# Handle the local-rank case
if devid == 'local-rank':
devid = str(get_local_rank())
# Map the device type to the corresponding PyOpenCL constant
devtype = getattr(cl.device_type, devtype)
# Determine the OpenCL platform to use
for i, platform in enumerate(cl.get_platforms()):
if platid == str(i) or platid == platform.name.lower():
break
else:
raise ValueError('No suitable OpenCL platform found')
# Determine the OpenCL device to use
for i, device in enumerate(platform.get_devices(devtype)):
if devid == str(i) or devid == device.name.lower():
break
else:
raise ValueError('No suitable OpenCL device found')
# Create a OpenCL context on this device
self.ctx = cl.Context([device])
# Create a queue for initialisation-type operations
self.qdflt = cl.CommandQueue(self.ctx)
# Compute the alignment requirement for the context
self.alignb = device.mem_base_addr_align // 8
from pyfr.backends.opencl import (blasext, clblas, packing, provider,
types)
# Register our data types
self.base_matrix_cls = types.OpenCLMatrixBase
self.const_matrix_cls = types.OpenCLConstMatrix
self.matrix_cls = types.OpenCLMatrix
self.matrix_bank_cls = types.OpenCLMatrixBank
self.matrix_rslice_cls = types.OpenCLMatrixRSlice
self.mpi_matrix_cls = types.OpenCLMPIMatrix
self.mpi_view_cls = types.OpenCLMPIView
self.queue_cls = types.OpenCLQueue
self.view_cls = types.OpenCLView
# Template lookup
self.lookup = DottedTemplateLookup('pyfr.backends.opencl.kernels')
# Instantiate the base kernel providers
kprovs = [
provider.OpenCLPointwiseKernelProvider,
blasext.OpenCLBlasExtKernels, packing.OpenCLPackingKernels,
clblas.OpenCLClBLASKernels
]
self._providers = [k(self) for k in kprovs]
# Pointwise kernels
self.pointwise = self._providers[0]
