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/*************************************************************************
* Copyright (c) 2015-2020, NVIDIA CORPORATION. All rights reserved.
*
* See LICENSE.txt for license information
************************************************************************/
#include "devcomm.h"
#include "primitives.h"
#include "collectives.h"
template<class FUNC, typename T, int UNROLL>
class ncclFunction<ncclFuncReduce, NCCL_ALGO_RING, NCCL_PROTO_SIMPLE, FUNC, T, UNROLL> {
public:
__device__ void run(struct ncclWorkElem* args) {
const int tid = threadIdx.x;
const int nthreads = args->nThreads-WARP_SIZE;
const int bid = args->coll.bid;
const int nChannels = args->coll.nChannels;
struct ncclDevComm* comm = args->comm;
struct ncclChannel* channel = comm->channels+blockIdx.x;
struct ncclRing* ring = &channel->ring;
const int stepSize = comm->buffSizes[NCCL_PROTO_SIMPLE] / (sizeof(T)*NCCL_STEPS);
const int chunkSize = stepSize * REDUCE_CHUNKSTEPS;
const int nranks = comm->nRanks;
const ssize_t loopSize = nChannels*(ssize_t)chunkSize;
const ssize_t size = args->coll.count;
const int rank = ring->devUserRanks[0];
const int prevRank = ring->devUserRanks[nranks-1];
const int root = args->coll.root;
// Compute pointers
const T * __restrict__ thisInput = (const T*)args->sendbuff;
T * __restrict__ thisOutput = (T*)args->recvbuff;
ncclPrimitives<UNROLL, REDUCE_CHUNKSTEPS/REDUCE_SLICESTEPS, REDUCE_SLICESTEPS, T, 1, 1, 0, FUNC>
prims(tid, nthreads, &ring->prev, &ring->next, NULL, stepSize, channel, comm, ncclShmem->ptrs, 0);
for (ssize_t gridOffset = 0; gridOffset < size; gridOffset += loopSize) {
int realChunkSize = min(chunkSize, DIVUP(size-gridOffset,nChannels));
ALIGN_SIZE(realChunkSize, nthreads*sizeof(uint64_t)/sizeof(T));
ssize_t offset = gridOffset + bid*realChunkSize;
int nelem = min(realChunkSize, size-offset);
if (prevRank == root) {
prims.send(thisInput+offset, nelem);
} else if (rank == root) {
prims.recvReduceCopy(thisInput+offset, thisOutput+offset, nelem);
} else {
prims.recvReduceSend(thisInput+offset, nelem);
}
}
}
};
template<class FUNC, typename T, int UNROLL>
class ncclFunction<ncclFuncReduce, NCCL_ALGO_RING, NCCL_PROTO_LL, FUNC, T, UNROLL> {
public:
__device__ void run(struct ncclWorkElem* args) {
const int tid = threadIdx.x;
const int nthreads = args->nThreads;
const int bid = args->coll.bid;
const int nChannels = args->coll.nChannels;
struct ncclDevComm* comm = args->comm;
struct ncclChannel* channel = comm->channels+blockIdx.x;
struct ncclRing* ring = &channel->ring;
const int stepLines = comm->buffSizes[NCCL_PROTO_LL] / (sizeof(union ncclLLFifoLine)*NCCL_STEPS);
ssize_t chunkSize = stepLines * sizeof(uint64_t) / sizeof(T);
const int nranks = comm->nRanks;
const ssize_t loopSize = nChannels*chunkSize;
const ssize_t size = args->coll.count;
const int rank = comm->rank;
const int prevRank = ring->devUserRanks[nranks-1];
const int root = args->coll.root;
ncclLLPrimitives<T, FUNC, 1, 1> LLprims(tid, nthreads, &ring->prev, &ring->next, stepLines, channel, comm);
// Compute pointers
const T * __restrict__ thisInput = (const T*)args->sendbuff;
T * __restrict__ thisOutput = (T*)args->recvbuff;
for (ssize_t gridOffset = 0; gridOffset < size; gridOffset += loopSize) {
if (size-gridOffset < loopSize) {
chunkSize = args->coll.lastChunkSize;
}
ssize_t offset = gridOffset + bid*chunkSize;
int nelem = min(chunkSize, size-offset);
if (prevRank == root) {
LLprims.send(thisInput+offset, nelem);
} else if (rank == root) {
LLprims.recvReduceCopy(thisInput+offset, thisOutput+offset, nelem);
} else {
LLprims.recvReduceSend(thisInput+offset, nelem);
}
}
}
};
#include "prims_ll128.h"
template<class FUNC, typename T, int UNROLL>
class ncclFunction<ncclFuncReduce, NCCL_ALGO_RING, NCCL_PROTO_LL128, FUNC, T, UNROLL> {
public:
__device__ void run(struct ncclWorkElem* args) {
const int tid = threadIdx.x;
const int nthreads = args->nThreads;
const int bid = args->coll.bid;
const int nChannels = args->coll.nChannels;
struct ncclDevComm* comm = args->comm;
struct ncclChannel* channel = comm->channels+blockIdx.x;
struct ncclRing* ring = &channel->ring;
const int stepSize = comm->buffSizes[NCCL_PROTO_LL128] / (sizeof(uint64_t)*NCCL_STEPS);
ssize_t chunkSize = stepSize*NCCL_LL128_DATAELEMS*sizeof(uint64_t) / (NCCL_LL128_LINEELEMS*sizeof(T));
const ssize_t minChunkSize = (NCCL_LL128_SHMEM_ELEMS_PER_THREAD*nthreads*NCCL_LL128_DATAELEMS*sizeof(uint64_t))/(NCCL_LL128_LINEELEMS*sizeof(T));
const int nranks = comm->nRanks;
const ssize_t loopSize = nChannels*chunkSize;
const ssize_t size = args->coll.count;
const int rank = comm->rank;
const int prevRank = ring->devUserRanks[nranks-1];
const int root = args->coll.root;
ncclLL128Primitives<T, FUNC, 1, 1> LLprims(tid, nthreads, &ring->prev, &ring->next, stepSize, channel, comm);
// Compute pointers
const T * __restrict__ thisInput = (const T*)args->sendbuff;
T * __restrict__ thisOutput = (T*)args->recvbuff;
for (ssize_t gridOffset = 0; gridOffset < size; gridOffset += loopSize) {
chunkSize = min(DIVUP(size-gridOffset, nChannels*minChunkSize)*minChunkSize, chunkSize);
ssize_t offset = gridOffset + bid*chunkSize;
int nelem = min(chunkSize, size-offset);
if (prevRank == root) {
LLprims.send(thisInput+offset, nelem);
} else if (rank == root) {
LLprims.recvReduceCopy(thisInput+offset, thisOutput+offset, nelem);
} else {
LLprims.recvReduceSend(thisInput+offset, nelem);
}
}
}
};
template<int PROTO, class REDOP, typename T, int UNROLL>
class ncclFunction<ncclFuncReduce, NCCL_ALGO_TREE, PROTO, REDOP, T, UNROLL> {
public:
__device__ void run(struct ncclWorkElem* args) {}
};
template<int PROTO, class REDOP, typename T, int UNROLL>
class ncclFunction<ncclFuncReduce, NCCL_ALGO_COLLNET, PROTO, REDOP, T, UNROLL> {
public:
__device__ void run(struct ncclWorkElem* args) {}
};
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