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# mpirun -np 2 python p2p-nonblocking.py | |
import cupy as cp | |
import cupy.cuda.nccl as nccl | |
from mpi4py import MPI | |
import time | |
import os | |
nbytes = 1024*1024*32 | |
data_type = cp.float32 | |
buffsize = nbytes | |
os.environ["NCCL_BUFFSIZE"] = str(buffsize) | |
os.environ["NCCL_P2P_NVL_CHUNKSIZE"] = str(buffsize) | |
os.environ["NCCL_P2P_NET_CHUNKSIZE"] = str(buffsize) | |
os.environ["NCCL_MAX_NCHANNELS"] = "1" | |
os.environ["NCCL_DEBUG"] = "INFO" | |
def run_benchmark(mpi_comm, nccl_comm): | |
if data_type == cp.float32: | |
nccl_dtype = nccl.NCCL_FLOAT32 | |
nbytes_per_elem = 4 | |
nelem = nbytes // nbytes_per_elem | |
memory = cp.zeros(nelem, dtype=data_type) | |
stream = cp.cuda.Stream(non_blocking=True) | |
# warmup to just make the connections | |
nccl.groupStart() | |
if mpi_comm.rank == 0: | |
nccl_comm.send( | |
memory.data.ptr, nelem, nccl_dtype, 1, stream.ptr | |
) | |
elif mpi_comm.rank == 1: | |
nccl_comm.recv( | |
memory.data.ptr, nelem, nccl_dtype, 0, stream.ptr | |
) | |
nccl.groupEnd() | |
a = cp.ones((128,)) | |
b = cp.ones((128,)) | |
cp.cuda.runtime.deviceSynchronize() | |
mpi_comm.barrier() | |
st = time.time() | |
if mpi_comm.rank == 0: | |
pass | |
#nccl_comm.send( | |
# memory.data.ptr, nelem, nccl_dtype, 1, stream.ptr | |
#) | |
elif mpi_comm.rank == 1: | |
print("recv begin") | |
nccl_comm.recv( | |
memory.data.ptr, nelem, nccl_dtype, 0, stream.ptr | |
) | |
print("recv end") | |
print("compute begin") | |
with cp.cuda.Stream(): | |
c = a + b | |
print("compute end") | |
cp.cuda.runtime.deviceSynchronize() | |
en = time.time() | |
print(f"{mpi_comm.rank} took {en-st} seconds") | |
def create_nccl_comm(mpi_comm): | |
root = 0 | |
if mpi_comm.rank == root: | |
uid = nccl.get_unique_id() | |
else: | |
uid = None | |
uid = mpi_comm.bcast(uid, root=root) | |
cp.cuda.runtime.deviceSynchronize() | |
tic = time.time() | |
comm = nccl.NcclCommunicator(mpi_comm.size, uid, mpi_comm.rank) | |
cp.cuda.runtime.deviceSynchronize() | |
print(f"communicator cost: {time.time() - tic:.2f}s") | |
return comm | |
if __name__ == "__main__": | |
world_comm = MPI.COMM_WORLD | |
world_rank = world_comm.rank | |
world_size = world_comm.size | |
nccl_comm = None | |
assert world_size == 2 | |
try: | |
cp.cuda.Device(world_rank).use() | |
nccl_comm = create_nccl_comm(world_comm) | |
run_benchmark(world_comm, nccl_comm) | |
nccl_comm = None | |
MPI.Finalize() | |
world_comm = None | |
except Exception as e: | |
print(f"An error occurred: {e}") | |
if nccl_comm: | |
nccl_comm.abort() | |
world_comm.Abort() |
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