The Torch-UCC plugin is a research prototype that enables collective communication over UCC for distributed PyTorch applications that load the plugin at application runtime.
The torch-ucc plugin is licensed as:
In order to contribute to torch-ucc, please sign up with an appropriate Contributor Agreement. Follow these instructions when submitting contributions and changes.
Required packages:
# Build
UCX_HOME=<PATH_TO_UCX> UCC_HOME=<PATH_TO_UCC> WITH_CUDA=<PATH_TO_CUDA> python setup.py install
UCX_HOME required, specifies path to UCX installation directory
UCC_HOME required, specifies path to UCC installation directory
WITH_CUDA optional, if WITH_CUDA=no is set then only CPU tensors are supported
Configuration variables
Name | Values | Description |
---|---|---|
TORCH_UCC_ALLGATHER_BLOCKING_WAIT | 0 or 1 | Sets behavior of wait function for CUDA Allgather. Async collective in PyTorch |
TORCH_UCC_ALLREDUCE_BLOCKING_WAIT | 0 or 1 | Sets behavior of wait function for CUDA Allreduce. |
TORCH_UCC_ALLTOALL_BLOCKING_WAIT | 0 or 1 | Sets behavior of wait function for CUDA Alltoall. |
TORCH_UCC_BCAST_BLOCKING_WAIT | 0 or 1 | Sets behavior of wait function for CUDA Bcast. |
export LD_LIBRARY_PATH=<PATH_TO_UCX>/lib:<PATH_TO_UCC>/lib:$LD_LIBRARY_PATH
python example.py
import torch
import torch.distributed as dist
import torch_ucc
....
dist.init_process_group('ucc', rank=comm_rank, world_size=comm_size)
....
dist.all_to_all_single(recv_tensor, send_tensor)