b6475625fb
Add support for alternating rings, allow for cross-nic rings without cross-rail communication. Add support for user buffer registration for network send/recv. Optimize aggregated operations to better utilize all channels. Add flattening for BCM PCI gen5 switches. Add support for inter-node NVLink communication Add support for port fusion in NET/IB. Add support for ReduceScatter and AllGather using Collnet. Update net API to v8. Fix hang during A2A connection.
486 wiersze
15 KiB
C++
486 wiersze
15 KiB
C++
/*************************************************************************
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* Copyright (c) 2015-2022, NVIDIA CORPORATION. All rights reserved.
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*
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* See LICENSE.txt for license information
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************************************************************************/
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#ifndef NCCL_DEVICE_H_
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#define NCCL_DEVICE_H_
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#include "nccl.h"
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#include "nccl_common.h"
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#include "align.h"
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#include <stdint.h>
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extern const char* ncclFuncStr[NCCL_NUM_FUNCTIONS];
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extern const char* ncclAlgoStr[NCCL_NUM_ALGORITHMS];
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extern const char* ncclProtoStr[NCCL_NUM_PROTOCOLS];
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#define NCCL_MAX_OPS 2048
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#define NCCL_STEPS 8
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#include "net_device.h"
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enum ncclDevRedOp_t {
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ncclDevSum, ncclDevProd, ncclDevMinMax,
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ncclDevPreMulSum, ncclDevSumPostDiv,
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ncclNumDevRedOps
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};
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struct ncclDevRedOpFull {
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ncclDevRedOp_t op;
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ncclRedOp_t proxyOp;
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bool scalarArgIsPtr;
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uint64_t scalarArg;
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};
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union ncclLLFifoLine {
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/* Flags have to be *after* data, because otherwise, an incomplete receive
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from the network may receive the flag but not the data.
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Note this is assuming that either we receive contiguous chunks of data
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(sockets) or data is written with an atomicity of 8 bytes (IB/RDMA). */
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struct {
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uint32_t data1;
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uint32_t flag1;
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uint32_t data2;
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uint32_t flag2;
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};
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uint64_t v[2];
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int4 i4;
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};
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#define WARP_SIZE 32
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#define MAXCHANNELS 32
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#define NCCL_MAX_NTHREADS 640
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#define NCCL_SIMPLE_MAX_NTHREADS 512
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#define NCCL_LL_MAX_NTHREADS 512
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#define NCCL_LL_LINES_PER_THREAD 8
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#ifdef TEST_LL_CLEANUP
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#define NCCL_LL_CLEAN_MASK 0x078 // Set to 0x100 to disable cleanup
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#define NCCL_LL_FLAG_MAX 0x100
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#define NCCL_LL_FLAG(a) ((uint32_t)((a) % NCCL_LL_FLAG_MAX))
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#else
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#define NCCL_LL_CLEAN_MASK 0x7ffffff8
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#define NCCL_LL_FLAG(a) ((uint32_t)(a))
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#endif
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// Make sure the clean mask will last for at least NCCL_NSTEPS
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static_assert(NCCL_LL_CLEAN_MASK % NCCL_STEPS == 0, "Invalid NCCL_LL_CLEAN_MASK value");
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#define NCCL_LL128_LINESIZE 128
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#define NCCL_LL128_LINEELEMS (NCCL_LL128_LINESIZE/sizeof(uint64_t))
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#define NCCL_LL128_DATAELEMS (NCCL_LL128_LINEELEMS-1)
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#define NCCL_LL128_MAX_NTHREADS 640
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#define NCCL_LL128_ELEMS_PER_THREAD 120
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#define NCCL_LL128_SHMEM_ELEMS_PER_THREAD 8
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#define NCCL_LL128_SHMEM_SIZE (NCCL_LL128_SHMEM_ELEMS_PER_THREAD*NCCL_LL128_MAX_NTHREADS)
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#define NCCL_DIRECT_WRITE 0x01
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#define NCCL_DIRECT_READ 0x02
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#define NCCL_DIRECT_NIC 0x04
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#define NCCL_IPC_WRITE 0x08
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#define NCCL_IPC_READ 0x10
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#define NCCL_NVLS_MIN_POLL 0x20
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struct ncclConnInfo {
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// Regular comm mechanism
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char *buffs[NCCL_NUM_PROTOCOLS]; // Local for recv, remote for send
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void* mhandles[NCCL_NUM_PROTOCOLS];
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uint64_t *tail; // Local for recv, remote for send
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uint64_t *head; // Local for send, remote for recv
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int flags; // Direct communication / other flags
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int shared; // Buffers are shared
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void **ptrExchange; // Pointer exchange for direct communication
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uint64_t* redOpArgExchange; // PreOp scaler exchange for direct pull case
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struct ncclConnFifo* connFifo; // Used for GPU - Proxy communication
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uint64_t step; // Keep where we are
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uint64_t llLastCleaning;
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ncclNetDeviceHandle_t netDeviceHandle;
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};
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struct ncclProxyConnector {
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int tpRank;
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int tpLocalRank;
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int sameProcess;
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struct ncclProxyConnection* connection;
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ncclResult_t (*proxyProgress)(struct ncclProxyState* proxyState, struct ncclProxyArgs*); // Copied from transport if necessary
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};
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struct ncclConnector {
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int connected;
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struct ncclProxyConnector proxyConn;
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struct ncclTransportComm* transportComm;
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void* transportResources;
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struct ncclConnInfo conn;
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};
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struct ncclRing {
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// Shortcuts for userRanks[1] and userRanks[n-1]
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int prev;
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int next;
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// Maps an internal nccl index to user-specified rank order. This is necessary
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// since we need to know how the user expects data to be ordered across
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// devices. Ordered from current device.
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int* userRanks;
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int index; // This rank's index in the ring
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};
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// The root of each tree only has one node down (+1 intra-node).
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#define NCCL_MAX_TREE_ARITY_TOP 2
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// Nodes inside the binary tree can have to two nodes down (+1 intra-node).
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#define NCCL_MAX_TREE_ARITY 3
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struct ncclTree {
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int depth;
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int up;
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int down[NCCL_MAX_TREE_ARITY];
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};
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#define NCCL_MAX_DIRECT_ARITY 7
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struct ncclDirect {
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int depth;
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int out;
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int nHeads; // Number of parallel N<->1<->net operations we'll do in parallel; size of up/down
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int headRank; // Index in 0..nHeads-1 I am the head rank of. -1 if I'm not a head rank (no local NIC)
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int shift; // Shuffling of send/recv for scatter/gather operations, basically localRank%nHeads
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// The heads[...] are guaranteed to be in rotated order start with self:
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// headRank, (headRank+1)%nHeads, (headRank+2)%nHeads, ...
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int heads[NCCL_MAX_DIRECT_ARITY+1];
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int up[NCCL_MAX_DIRECT_ARITY];
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int down[NCCL_MAX_DIRECT_ARITY];
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};
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#define NCCL_MAX_NVLS_ARITY 8
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#define NCCL_MAX_NVLS_TREE_ARITY 3
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struct ncclNvls {
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int out;
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int nHeads; // Number of parallel N<->1<->net operations we'll do in parallel; size of up/down
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int headRank; // Index in 0..nHeads-1 I am the head rank of. -1 if I'm not a head rank (no local NIC)
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int up[NCCL_MAX_NVLS_ARITY];
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int down;
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int treeUp;
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int treeDown[NCCL_MAX_NVLS_TREE_ARITY];
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int node;
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int nNodes;
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};
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#define NCCL_MAX_CONNS 2
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struct ncclChannelPeer {
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struct ncclConnector send[NCCL_MAX_CONNS];
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struct ncclConnector recv[NCCL_MAX_CONNS];
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int refCount;
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};
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struct ncclDevComm;
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/* ncclWork is to be a power of two, currently 8x64 bytes, */
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/* to make sure reads to host from the CUDA kernel are aligned. */
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/* Make sure to adjust padding at the end of ncclWorkElem. */
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#define NCCL_WORK_SIZE 512
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enum ncclWorkType : uint8_t {
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ncclWorkTypeUnused=0,
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ncclWorkTypeColl=1,
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ncclWorkTypeP2p=2,
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ncclWorkTypeRegColl=3
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};
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enum ncclWorkP2PType : uint8_t {
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ncclWorkP2pTypeUnused=0,
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ncclWorkP2pTypeSend,
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ncclWorkP2pTypeRecv
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};
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struct ncclWorkHeader {
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union {
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int32_t workNext; // when isLast=0: Offset from kernel argument workHead
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uint32_t doneAcks; // when isLast=1: Monotonic (mod 1<<32) ack value to send back.
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};
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uint16_t funcIndex;
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uint8_t isLast:1; // last work for this kernel
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uint8_t inFifo:1; // is this work in the fifo
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enum ncclWorkType type;
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};
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struct ncclWorkElem {
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union {
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uint8_t flagBits;
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struct {
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uint8_t isUsed:1, redOpArgIsPtr:1, regUsed:1, oneNode:1;
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};
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};
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uint8_t nWarps;
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uint8_t direct;
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uint32_t root;
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const void *sendbuff;
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void *recvbuff;
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size_t count;
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uint64_t redOpArg;
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uint64_t chunkCount:25, workCount:39;
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union {
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struct {
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uint64_t lastChunkCount:25;
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uint64_t workOffset:39;
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};
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struct {
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uint64_t bid:32;
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uint64_t nChannels:32;
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};
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};
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};
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#define NCCL_MAX_WORK_ELEMENTS ((NCCL_WORK_SIZE - alignUp(sizeof(ncclWorkHeader), alignof(ncclWorkElem)))/sizeof(ncclWorkElem))
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static_assert(NCCL_MAX_WORK_ELEMENTS == 9, "Sanity check: NCCL_MAX_WORK_ELEMENTS == 9");
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struct ncclWorkElemP2p {
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int peer : 30;
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int proto : 2;
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enum ncclWorkP2PType p2pType;
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uint8_t reg:1;
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uint8_t nWarps:5;
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uint8_t warpStart;
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uint8_t ngroups;
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// Important not to use any fields with greater than 4-byte alignment since
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// we need sizeof(ncclWorkElemP2p)==28, but that would be padded up to 32 if
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// there were 8-byte fields.
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//void* buff;
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uint32_t buffHi32, buffLo32; // buff = buffHi32<<32 | buffLo32;
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//size_t count;
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uint32_t countHi32, countLo32; // count = countHi32<<32 | countLo32;
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int chunkSize;
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};
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static_assert(((NCCL_WORK_SIZE - alignUp(sizeof(ncclWorkHeader), alignof(ncclWorkElemP2p)))/sizeof(ncclWorkElemP2p)) >= 16, "Sanity check: NCCL_MAX_WORK_ELEMENTS_P2P == 16");
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#define NCCL_MAX_WORK_ELEMENTS_P2P 16
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struct ncclWorkElemReg {
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struct ncclWorkElem elem;
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void* dnInputs[NCCL_MAX_DIRECT_ARITY+1];
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void* dnOutputs[NCCL_MAX_DIRECT_ARITY+1];
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void* upOutputs[NCCL_MAX_DIRECT_ARITY+1];
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};
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#define NCCL_MAX_WORK_ELEMENTS_REG ((NCCL_WORK_SIZE - alignUp(sizeof(ncclWorkHeader), alignof(ncclWorkElemReg)))/sizeof(ncclWorkElemReg))
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static_assert(NCCL_MAX_WORK_ELEMENTS_REG == 2, "Sanity check: NCCL_MAX_WORK_ELEMENTS_REG == 2");
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// Number of named barriers supported by CUDA
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#define NCCL_MAX_GROUPS 16
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struct ncclWork {
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struct ncclWorkHeader header;
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union {
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char pad[NCCL_WORK_SIZE - sizeof(struct ncclWorkHeader)];
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struct ncclWorkElem elems[NCCL_MAX_WORK_ELEMENTS];
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struct ncclWorkElemP2p p2pElems[NCCL_MAX_WORK_ELEMENTS_P2P];
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struct ncclWorkElemReg regElems[NCCL_MAX_WORK_ELEMENTS_REG];
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};
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};
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static_assert(sizeof(struct ncclWork) == NCCL_WORK_SIZE, "Sanity check: sizeof(struct ncclWork) == NCCL_WORK_SIZE");
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static_assert(sizeof(struct ncclWork)%16 == 0, "Sanity check: sizeof(struct ncclWork)%16 == 0");
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struct ncclDevChannelPeer {
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// Stripped version of ncclChannelPeer where we only keep the ncclConnInfo
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// instead of the full ncclConnector.
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struct ncclConnInfo send[NCCL_MAX_CONNS];
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struct ncclConnInfo recv[NCCL_MAX_CONNS];
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};
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struct alignas(16) ncclDevChannel {
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struct ncclDevChannelPeer** peers;
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struct ncclRing ring;
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struct ncclTree tree;
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struct ncclTree collnetChain;
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struct ncclDirect collnetDirect;
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struct ncclNvls nvls;
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uint32_t* workFifoDone; // Location of done counter, device writes index+1 of last work processed
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};
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struct ncclDevComm {
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int rank;
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int nRanks;
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int node;
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int nNodes;
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int buffSizes[NCCL_NUM_PROTOCOLS];
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int p2pChunkSize;
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// Operation list for aggregation
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int workFifoDepth;
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struct ncclWork* workFifoHeap; // may be cudaHost or GDR memory
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int* collNetDenseToUserRank;
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// Flag to ask NCCL kernels to abort
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volatile uint32_t* abortFlag;
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// Channels, device side
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struct ncclDevChannel* channels/*[MAXCHANNELS]*/;
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};
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struct alignas(16) ncclDevCommAndChannels {
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struct ncclDevComm comm;
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struct ncclDevChannel channels[MAXCHANNELS];
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};
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#ifdef __CUDA_ARCH__
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#define NCCL_CUDA_ARCH __CUDA_ARCH__
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#else
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#define NCCL_CUDA_ARCH 0
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#endif
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template<typename T>
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__host__ __device__ constexpr T min_constexpr(T a) { return a; }
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template<typename T, typename ...Ts>
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__host__ __device__ constexpr T min_constexpr(T a, T b, Ts ...c) {
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return min_constexpr<T>((a < b ? a : b), c...);
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}
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template<typename T>
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__host__ __device__ constexpr T max_constexpr(T a) { return a; }
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template<typename T, typename ...Ts>
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__host__ __device__ constexpr T max_constexpr(T a, T b, Ts ...c) {
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return max_constexpr<T>((a > b ? a : b), c...);
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}
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// Calculate the unroll factor given:
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// * bytePerPack: number of bytes accessed per instruction
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// * insns: max permissible unroll value
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// * bytes: desired number of in-flight bytes per iteration ( = unroll*bytePerPack)
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__host__ __device__ constexpr int ncclCalcUnroll(int bytePerPack, int insns, int bytes) {
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return min_constexpr(insns, (bytes + bytePerPack-1)/bytePerPack);
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}
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// Note that all unroll value logic should depend on a given cudaArch argument
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// and not __CUDA_ARCH__ since these need to be host-side executable where the
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// arch value is strictly runtime only. By defaulting to NCCL_CUDA_ARCH, device
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// side code can elide passing the arch for brevity.
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__host__ __device__ constexpr int ncclCollUnroll(int cudaArch = NCCL_CUDA_ARCH) {
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// Our collective unroll should move to the same bytes&insns model as NVLS.
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return cudaArch >= 800 ? 8 : 4;
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}
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__host__ __device__ constexpr int ncclNvlsUnrollBytes(int cudaArch = NCCL_CUDA_ARCH) { return 4*16; }
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__host__ __device__ constexpr int ncclNvlsUnrollInsns(int cudaArch = NCCL_CUDA_ARCH) { return 16; }
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__host__ __device__ constexpr int ncclNvlsUnroll(int bytePerPack, int cudaArch = NCCL_CUDA_ARCH) {
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return ncclCalcUnroll(bytePerPack, ncclNvlsUnrollInsns(cudaArch), ncclNvlsUnrollBytes(cudaArch));
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}
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// The amount of dynamic shmem per warp
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__host__ __device__ constexpr int ncclShmemScratchWarpSize(int cudaArch = NCCL_CUDA_ARCH) {
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return (max_constexpr<int>(
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/*LL */0,
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/*LL128 */(NCCL_LL128_SHMEM_ELEMS_PER_THREAD*WARP_SIZE)*sizeof(uint64_t),
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/*SIMPLE*/(ncclCollUnroll(cudaArch)*WARP_SIZE + 1)*16,
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// NVLS needs an extra 16B to read unaligned data.
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/*NVLS */WARP_SIZE*(cudaArch >= 900 ? ncclNvlsUnrollBytes(cudaArch) : 0) + 16
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) + 15) & -16; // pad to 16 bytes
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}
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// The amount of dynamic shmem per block
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__host__ __device__ constexpr int ncclShmemDynamicSize(int cudaArch = NCCL_CUDA_ARCH) {
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return cudaArch < 700 ? 0 : ncclShmemScratchWarpSize(cudaArch)*(NCCL_MAX_NTHREADS/WARP_SIZE);
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}
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// Host-side table of kernel function pointers.
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extern int const ncclDevKernelCount;
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extern void* const ncclDevKernelList[/*ncclDevKernelCount*/];
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// Table of most specialized kernel function to run given func index.
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extern int const ncclDevFuncRowToId[];
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extern void* const ncclDevKernelForFunc[/*funcIndex*/];
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extern bool const ncclDevKernelForFuncIsSpecialized[/*funcIndex*/];
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// Launch a one-rank reduction on stream.
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ncclResult_t ncclLaunchOneRank(void* dst, void const* src, size_t nElts, struct ncclDevRedOpFull redOp, ncclDataType_t type, cudaStream_t stream);
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// `ncclNvlsSupported()` needs to be in sync with "func_valid" in "src/device/generate.py"
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inline bool ncclNvlsSupported(int devRedOp, int type) {
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switch (type) {
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case ncclInt32:
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case ncclUint32:
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case ncclInt64:
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case ncclUint64:
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case ncclFloat16:
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#if defined(__CUDA_BF16_TYPES_EXIST__)
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case ncclBfloat16:
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#endif
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return devRedOp == ncclDevSum || devRedOp == ncclDevMinMax;
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case ncclFloat:
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case ncclDouble:
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return devRedOp == ncclDevSum;
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default:
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return false;
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}
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}
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// `ncclDevFuncIndex()` needs to be in sync with "all_functions()" in "src/device/generate.py"
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inline int ncclDevFuncId(int coll, int devRedOp, int type, int algo, int proto) {
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#if defined(__CUDA_BF16_TYPES_EXIST__)
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constexpr int NumTypes = ncclNumTypes;
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#else
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constexpr int NumTypes = ncclNumTypes + 1;
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#endif
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int row;
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do {
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row = 0; // ncclDevFuncIndex_P2p
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if (coll == ncclFuncSendRecv) break;
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row += 1;
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int nAlgos = 3;
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if (coll == ncclFuncAllGather) {
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int algo1 = algo == NCCL_ALGO_RING ? 0 :
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algo == NCCL_ALGO_COLLNET_DIRECT ? 1 :
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/*algo == NCCL_ALGO_NVLS*/ 2;
|
|
row += algo1*NCCL_NUM_PROTOCOLS + proto;
|
|
break;
|
|
}
|
|
row += nAlgos*NCCL_NUM_PROTOCOLS;
|
|
|
|
nAlgos = 1;
|
|
if (coll == ncclFuncBroadcast) {
|
|
row += proto;
|
|
break;
|
|
}
|
|
row += nAlgos*NCCL_NUM_PROTOCOLS;
|
|
|
|
nAlgos = NCCL_NUM_ALGORITHMS;
|
|
if (coll == ncclFuncAllReduce) {
|
|
row += ((devRedOp*NumTypes + type)*nAlgos + algo)*NCCL_NUM_PROTOCOLS + proto;
|
|
break;
|
|
}
|
|
row += ncclNumDevRedOps*NumTypes*nAlgos*NCCL_NUM_PROTOCOLS;
|
|
|
|
nAlgos = 1;
|
|
if (coll == ncclFuncReduce) {
|
|
row += (devRedOp*NumTypes + type)*NCCL_NUM_PROTOCOLS + proto;
|
|
break;
|
|
}
|
|
row += ncclNumDevRedOps*NumTypes*nAlgos*NCCL_NUM_PROTOCOLS;
|
|
|
|
nAlgos = 3;
|
|
if (coll == ncclFuncReduceScatter) {
|
|
int algo1 = algo == NCCL_ALGO_RING ? 0 :
|
|
algo == NCCL_ALGO_COLLNET_DIRECT ? 1 :
|
|
/*algo == NCCL_ALGO_NVLS*/ 2;
|
|
row += ((devRedOp*NumTypes + type)*nAlgos + algo1)*NCCL_NUM_PROTOCOLS + proto;
|
|
break;
|
|
}
|
|
row += ncclNumDevRedOps*NumTypes*nAlgos*NCCL_NUM_PROTOCOLS;
|
|
} while (false);
|
|
|
|
return ncclDevFuncRowToId[row];
|
|
}
|
|
|
|
inline int ncclDevFuncId_P2p() { return ncclDevFuncRowToId[0]; }
|
|
|
|
#endif
|