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Make NCCL collectives work on communicators with only one rank

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This commit is contained in:
Sylvain Jeaugey 2016-06-06 14:35:00 -07:00
parent bd3cf73e6e
commit 7edfc57228
5 changed files with 61 additions and 39 deletions
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5
src/all_gather.cu
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@ -442,6 +442,10 @@ ncclResult_t ncclAllGatherWithType(const void* sendbuff, void* recvbuff,
args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1; args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1;
args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1; args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1;
if (comm->nDev == 1) {
if (sendbuff != recvbuff)
CUDACHECK(cudaMemcpyAsync(recvbuff, sendbuff, count*sizeof(T), cudaMemcpyDeviceToDevice, stream));
} else {
if( comm->useRemoteRecv ) { if( comm->useRemoteRecv ) {
AllGatherKernel<NUM_THREADS, UNROLL_COUNT, true, T> AllGatherKernel<NUM_THREADS, UNROLL_COUNT, true, T>
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
@ -449,6 +453,7 @@ ncclResult_t ncclAllGatherWithType(const void* sendbuff, void* recvbuff,
AllGatherKernel<NUM_THREADS, UNROLL_COUNT, false, T> AllGatherKernel<NUM_THREADS, UNROLL_COUNT, false, T>
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
} }
}
return ncclSuccess; return ncclSuccess;
} }

5
src/all_reduce.cu
View File

@ -432,6 +432,10 @@ ncclResult_t ncclAllReduceWithTypeAndFunc(const void* sendbuff, void* recvbuff,
args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1; args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1;
args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1; args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1;
if (comm->nDev == 1) {
if (sendbuff != recvbuff)
CUDACHECK(cudaMemcpyAsync(recvbuff, sendbuff, count*sizeof(T), cudaMemcpyDeviceToDevice, stream));
} else {
if( comm->useRemoteRecv ) { if( comm->useRemoteRecv ) {
AllReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, true, T> AllReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, true, T>
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
@ -439,6 +443,7 @@ ncclResult_t ncclAllReduceWithTypeAndFunc(const void* sendbuff, void* recvbuff,
AllReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, false, T> AllReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, false, T>
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
} }
}
return ncclSuccess; return ncclSuccess;
} }

2
src/broadcast.cu
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@ -348,6 +348,7 @@ ncclResult_t ncclBcastWithType(void* buff, const int count, const int root,
args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1; args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1;
args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1; args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1;
if (comm->nDev != 1) {
if (comm->useRemoteRecv) { if (comm->useRemoteRecv) {
if (index == (rootId + comm->nDev - 1) % comm->nDev) { if (index == (rootId + comm->nDev - 1) % comm->nDev) {
BroadcastKernel<NUM_THREADS, UNROLL_COUNT, true, END, T> BroadcastKernel<NUM_THREADS, UNROLL_COUNT, true, END, T>
@ -371,6 +372,7 @@ ncclResult_t ncclBcastWithType(void* buff, const int count, const int root,
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
} }
} }
}
return ncclSuccess; return ncclSuccess;
} }

5
src/reduce.cu
View File

@ -336,6 +336,10 @@ ncclResult_t ncclReduceWithTypeAndFunc(const void* sendbuff, void* recvbuff,
args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1; args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1;
args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1; args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1;
if (comm->nDev == 1) {
if (sendbuff != recvbuff)
CUDACHECK(cudaMemcpyAsync(recvbuff, sendbuff, count*sizeof(T), cudaMemcpyDeviceToDevice, stream));
} else {
if (index == (rootId + 1) % comm->nDev) { if (index == (rootId + 1) % comm->nDev) {
ReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, BEGIN, T> ReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, BEGIN, T>
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
@ -346,6 +350,7 @@ ncclResult_t ncclReduceWithTypeAndFunc(const void* sendbuff, void* recvbuff,
ReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, MIDDLE, T> ReduceKernel<NUM_THREADS, UNROLL_COUNT, FUNC, MIDDLE, T>
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
} }
}
return ncclSuccess; return ncclSuccess;
} }

5
src/reduce_scatter.cu
View File

@ -444,8 +444,13 @@ ncclResult_t ncclReduceScatterWithTypeAndFunc(const void* sendbuff,
args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1; args.ThisChunkDoneFlag = comm->ptrs[nextId].local->flags + 1;
args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1; args.PrevChunkDoneFlag = comm->ptrs[prevId].remote->flags + 1;
if (comm->nDev == 1) {
if (sendbuff != recvbuff)
CUDACHECK(cudaMemcpyAsync(recvbuff, sendbuff, recvcount*sizeof(T), cudaMemcpyDeviceToDevice, stream));
} else {
ReduceScatterKernel<NUM_THREADS, UNROLL_COUNT, FUNC, T> ReduceScatterKernel<NUM_THREADS, UNROLL_COUNT, FUNC, T>
<<<1, NUM_THREADS + 1, 0, stream>>>(args); <<<1, NUM_THREADS + 1, 0, stream>>>(args);
}
return ncclSuccess; return ncclSuccess;
} }