def __init__(self, mpi_comm,
batched_copy=False):
super(NonCudaAwareCommunicator, self).__init__(mpi_comm)
if not nccl._available:
raise RuntimeError(
'NCCL is not available. '
'Please confirm that NCCL is enabled in CuPy.'
)
if nccl.get_version() < 2302:
warnings.warn('NCCL 2.2 and older versions are deprecated.',
DeprecationWarning)
# We have to delay the initialization of communicators. This is because
# NCCL's communicators use the current CUDA devices at the time of
# initialization. Therefore, we have to initialize NCCL communicators
# after users set the devices to use.
self.inter_mpi_comm = None
self.intra_nccl_comm = None
self.gpu_buffer_a = _memory_utility.DeviceMemory()
self.gpu_buffer_b = _memory_utility.DeviceMemory()
self.cpu_buffer_a = _memory_utility.HostPinnedMemory()
self.cpu_buffer_b = _memory_utility.HostPinnedMemory()
self.batched_copy = batched_copy
def __init__(self, mpi_comm):
super(NonCudaAwareCommunicator, self).__init__(mpi_comm)
if not nccl._available:
raise RuntimeError('NCCL is not available. '
'Please confirm that NCCL is enabled in CuPy.')
# We have to delay the initialization of communicators. This is because
# NCCL's communicators use the current CUDA devices at the time of
# initialization. Therefore, we have to initialize NCCL communicators
# after users set the devices to use.
self.inter_mpi_comm = None
self.intra_nccl_comm = None
self.gpu_buffer_a = _memory_utility.DeviceMemory()
self.gpu_buffer_b = _memory_utility.DeviceMemory()
self.cpu_buffer_a = _memory_utility.HostPinnedMemory()
self.cpu_buffer_b = _memory_utility.HostPinnedMemory()
def __init__(self, mpi_comm):
super(NonCudaAwareCommunicator, self).__init__(mpi_comm, use_nccl=True)
self.gpu_buffer_a = _memory_utility.DeviceMemory()
self.gpu_buffer_b = _memory_utility.DeviceMemory()
self.cpu_buffer_a = _memory_utility.HostPinnedMemory()
self.cpu_buffer_b = _memory_utility.HostPinnedMemory()
