| import argparse |
| import logging |
| import os |
| |
| import torch |
| import torch.distributed as c10d |
| |
| |
| logging.basicConfig( |
| format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO |
| ) |
| |
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser( |
| description="Simple script to simulate NCCL errors. The script is " |
| "supposed to be run on multiple different nodes simultaneously with " |
| "appropriate rank and world_size. The script run an allreduce() on " |
| "the rank 0 node and aborts all the other nodes to simulate an error " |
| "in NCCL" |
| ) |
| parser.add_argument("addr", help="address of the master node to connect to.") |
| parser.add_argument("port", help="port of the master node to connect to.") |
| parser.add_argument("rank", help="rank of this node") |
| parser.add_argument("world_size", help="number of nodes in process group") |
| args = parser.parse_args() |
| rank = int(args.rank) |
| world_size = int(args.world_size) |
| port = int(args.port) |
| |
| store = c10d.TCPStore(args.addr, port, world_size, rank == 0) |
| process_group = c10d.ProcessGroupNCCL(store, rank, world_size) |
| logging.info("Running first allreduce") |
| process_group.allreduce(torch.rand(10).cuda(rank)).wait() |
| if rank == 0: |
| logging.info("Running second allreduce only on rank 0") |
| work = process_group.allreduce(torch.rand(10).cuda(rank)) |
| logging.info("Waiting for allreduce to complete...") |
| work.wait() |
| logging.info("Second allreduce successful: %s", work.is_success()) |
| else: |
| logging.info("Aborting all other ranks.") |
| os.abort() |