399 lines
16 KiB
C
399 lines
16 KiB
C
/*************************************************************************
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* Copyright (c) 2015-2021, 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_H_
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#define NCCL_H_
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#include <cuda_runtime.h>
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#include <cuda_fp16.h>
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#if CUDART_VERSION >= 11000
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#include <cuda_bf16.h>
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#endif
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#define NCCL_MAJOR 2
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#define NCCL_MINOR 14
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#define NCCL_PATCH 3
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#define NCCL_SUFFIX ""
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#define NCCL_VERSION_CODE 21403
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#define NCCL_VERSION(X,Y,Z) (((X) <= 2 && (Y) <= 8) ? (X) * 1000 + (Y) * 100 + (Z) : (X) * 10000 + (Y) * 100 + (Z))
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#ifdef __cplusplus
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extern "C" {
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#endif
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/* Opaque handle to communicator */
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typedef struct ncclComm* ncclComm_t;
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#define NCCL_UNIQUE_ID_BYTES 128
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typedef struct { char internal[NCCL_UNIQUE_ID_BYTES]; } ncclUniqueId;
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/* Error type */
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typedef enum { ncclSuccess = 0,
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ncclUnhandledCudaError = 1,
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ncclSystemError = 2,
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ncclInternalError = 3,
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ncclInvalidArgument = 4,
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ncclInvalidUsage = 5,
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ncclRemoteError = 6,
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ncclInProgress = 7,
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ncclNumResults = 8 } ncclResult_t;
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/* Communicator configuration. Users can assign value to attributes to specify the
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* behavior of a communicator. */
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typedef struct ncclConfig_v21400 {
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/* attributes that users should never touch. */
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size_t size;
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unsigned int magic;
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unsigned int version;
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/* attributes that users are able to customize. */
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int blocking;
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} ncclConfig_t;
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/* Config initializer must be assigned to initialize config structure when it is created.
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* Not initialized config will result in NCCL error. */
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#define NCCL_CONFIG_INITIALIZER { \
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sizeof(ncclConfig_t), /* size */ \
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0xcafebeef, /* magic */ \
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NCCL_VERSION(NCCL_MAJOR, NCCL_MINOR, NCCL_PATCH), /* version */ \
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1 /* blocking */ \
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}
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/* Return the NCCL_VERSION_CODE of the NCCL library in the supplied integer.
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* This integer is coded with the MAJOR, MINOR and PATCH level of the
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* NCCL library
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*/
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ncclResult_t ncclGetVersion(int *version);
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ncclResult_t pncclGetVersion(int *version);
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/* Generates an Id to be used in ncclCommInitRank. ncclGetUniqueId should be
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* called once and the Id should be distributed to all ranks in the
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* communicator before calling ncclCommInitRank. */
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ncclResult_t ncclGetUniqueId(ncclUniqueId* uniqueId);
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ncclResult_t pncclGetUniqueId(ncclUniqueId* uniqueId);
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/* Create a new communicator (multi thread/process version) with a configuration
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* set by users. */
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ncclResult_t ncclCommInitRankConfig(ncclComm_t* comm, int nranks, ncclUniqueId commId, int rank, ncclConfig_t* config);
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ncclResult_t pncclCommInitRankConfig(ncclComm_t* comm, int nranks, ncclUniqueId commId, int rank, ncclConfig_t* config);
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/* Creates a new communicator (multi thread/process version).
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* rank must be between 0 and nranks-1 and unique within a communicator clique.
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* Each rank is associated to a CUDA device, which has to be set before calling
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* ncclCommInitRank.
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* ncclCommInitRank implicitly syncronizes with other ranks, so it must be
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* called by different threads/processes or use ncclGroupStart/ncclGroupEnd. */
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ncclResult_t ncclCommInitRank(ncclComm_t* comm, int nranks, ncclUniqueId commId, int rank);
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ncclResult_t pncclCommInitRank(ncclComm_t* comm, int nranks, ncclUniqueId commId, int rank);
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/* Creates a clique of communicators (single process version).
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* This is a convenience function to create a single-process communicator clique.
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* Returns an array of ndev newly initialized communicators in comm.
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* comm should be pre-allocated with size at least ndev*sizeof(ncclComm_t).
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* If devlist is NULL, the first ndev CUDA devices are used.
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* Order of devlist defines user-order of processors within the communicator. */
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ncclResult_t ncclCommInitAll(ncclComm_t* comm, int ndev, const int* devlist);
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ncclResult_t pncclCommInitAll(ncclComm_t* comm, int ndev, const int* devlist);
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/* Finalize a communicator. ncclCommFinalize flushes all issued communications,
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* and marks communicator state as ncclInProgress. The state will change to ncclSuccess
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* when the communicator is globally quiescent and related resources are freed; then,
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* calling ncclCommDestroy can locally free the rest of the resources (e.g. communicator
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* itself) without blocking. */
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ncclResult_t ncclCommFinalize(ncclComm_t comm);
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ncclResult_t pncclCommFinalize(ncclComm_t comm);
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/* Frees local resources associated with communicator object. */
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ncclResult_t ncclCommDestroy(ncclComm_t comm);
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ncclResult_t pncclCommDestroy(ncclComm_t comm);
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/* Frees resources associated with communicator object and aborts any operations
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* that might still be running on the device. */
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ncclResult_t ncclCommAbort(ncclComm_t comm);
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ncclResult_t pncclCommAbort(ncclComm_t comm);
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/* Returns a string for each error code. */
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const char* ncclGetErrorString(ncclResult_t result);
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const char* pncclGetErrorString(ncclResult_t result);
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/* Returns a human-readable message of the last error that occurred.
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* comm is currently unused and can be set to NULL
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*/
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const char* ncclGetLastError(ncclComm_t comm);
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const char* pncclGetError(ncclComm_t comm);
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/* Checks whether the comm has encountered any asynchronous errors */
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ncclResult_t ncclCommGetAsyncError(ncclComm_t comm, ncclResult_t *asyncError);
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ncclResult_t pncclCommGetAsyncError(ncclComm_t comm, ncclResult_t *asyncError);
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/* Gets the number of ranks in the communicator clique. */
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ncclResult_t ncclCommCount(const ncclComm_t comm, int* count);
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ncclResult_t pncclCommCount(const ncclComm_t comm, int* count);
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/* Returns the cuda device number associated with the communicator. */
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ncclResult_t ncclCommCuDevice(const ncclComm_t comm, int* device);
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ncclResult_t pncclCommCuDevice(const ncclComm_t comm, int* device);
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/* Returns the user-ordered "rank" associated with the communicator. */
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ncclResult_t ncclCommUserRank(const ncclComm_t comm, int* rank);
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ncclResult_t pncclCommUserRank(const ncclComm_t comm, int* rank);
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/* Reduction operation selector */
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typedef enum { ncclNumOps_dummy = 5 } ncclRedOp_dummy_t;
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typedef enum { ncclSum = 0,
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ncclProd = 1,
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ncclMax = 2,
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ncclMin = 3,
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ncclAvg = 4,
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/* ncclNumOps: The number of built-in ncclRedOp_t values. Also
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* serves as the least possible value for dynamic ncclRedOp_t's
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* as constructed by ncclRedOpCreate*** functions. */
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ncclNumOps = 5,
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/* ncclMaxRedOp: The largest valid value for ncclRedOp_t.
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* It is defined to be the largest signed value (since compilers
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* are permitted to use signed enums) that won't grow
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* sizeof(ncclRedOp_t) when compared to previous NCCL versions to
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* maintain ABI compatibility. */
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ncclMaxRedOp = 0x7fffffff>>(32-8*sizeof(ncclRedOp_dummy_t))
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} ncclRedOp_t;
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/* Data types */
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typedef enum { ncclInt8 = 0, ncclChar = 0,
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ncclUint8 = 1,
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ncclInt32 = 2, ncclInt = 2,
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ncclUint32 = 3,
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ncclInt64 = 4,
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ncclUint64 = 5,
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ncclFloat16 = 6, ncclHalf = 6,
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ncclFloat32 = 7, ncclFloat = 7,
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ncclFloat64 = 8, ncclDouble = 8,
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#if defined(__CUDA_BF16_TYPES_EXIST__)
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ncclBfloat16 = 9,
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ncclNumTypes = 10
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#else
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ncclNumTypes = 9
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#endif
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} ncclDataType_t;
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/* ncclScalarResidence_t: Location and dereferencing logic for scalar arguments. */
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typedef enum {
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/* ncclScalarDevice: The scalar is in device-visible memory and will be
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* dereferenced while the collective is running. */
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ncclScalarDevice = 0,
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/* ncclScalarHostImmediate: The scalar is in host-visible memory and will be
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* dereferenced before the ncclRedOpCreate***() function returns. */
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ncclScalarHostImmediate = 1
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} ncclScalarResidence_t;
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/*
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* ncclRedOpCreatePreMulSum
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*
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* Creates a new reduction operator which pre-multiplies input values by a given
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* scalar locally before reducing them with peer values via summation. For use
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* only with collectives launched against *comm* and *datatype*. The
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* *residence* argument indicates how/when the memory pointed to by *scalar*
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* will be dereferenced. Upon return, the newly created operator's handle
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* is stored in *op*.
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*/
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ncclResult_t ncclRedOpCreatePreMulSum(ncclRedOp_t *op, void *scalar, ncclDataType_t datatype, ncclScalarResidence_t residence, ncclComm_t comm);
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ncclResult_t pncclRedOpCreatePreMulSum(ncclRedOp_t *op, void *scalar, ncclDataType_t datatype, ncclScalarResidence_t residence, ncclComm_t comm);
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/*
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* ncclRedOpDestroy
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*
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* Destroys the reduction operator *op*. The operator must have been created by
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* ncclRedOpCreatePreMul with the matching communicator *comm*. An operator may be
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* destroyed as soon as the last NCCL function which is given that operator returns.
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*/
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ncclResult_t ncclRedOpDestroy(ncclRedOp_t op, ncclComm_t comm);
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ncclResult_t pncclRedOpDestroy(ncclRedOp_t op, ncclComm_t comm);
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/*
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* Collective communication operations
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*
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* Collective communication operations must be called separately for each
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* communicator in a communicator clique.
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*
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* They return when operations have been enqueued on the CUDA stream.
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*
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* Since they may perform inter-CPU synchronization, each call has to be done
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* from a different thread or process, or need to use Group Semantics (see
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* below).
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*/
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/*
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* Reduce
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*
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* Reduces data arrays of length count in sendbuff into recvbuff using op
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* operation.
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* recvbuff may be NULL on all calls except for root device.
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* root is the rank (not the CUDA device) where data will reside after the
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* operation is complete.
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*
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* In-place operation will happen if sendbuff == recvbuff.
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*/
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ncclResult_t ncclReduce(const void* sendbuff, void* recvbuff, size_t count, ncclDataType_t datatype,
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ncclRedOp_t op, int root, ncclComm_t comm, cudaStream_t stream);
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ncclResult_t pncclReduce(const void* sendbuff, void* recvbuff, size_t count, ncclDataType_t datatype,
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ncclRedOp_t op, int root, ncclComm_t comm, cudaStream_t stream);
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/*
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* (deprecated) Broadcast (in-place)
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*
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* Copies count values from root to all other devices.
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* root is the rank (not the CUDA device) where data resides before the
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* operation is started.
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*
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* This operation is implicitely in place.
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*/
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ncclResult_t ncclBcast(void* buff, size_t count, ncclDataType_t datatype, int root,
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ncclComm_t comm, cudaStream_t stream);
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ncclResult_t pncclBcast(void* buff, size_t count, ncclDataType_t datatype, int root,
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ncclComm_t comm, cudaStream_t stream);
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/*
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* Broadcast
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*
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* Copies count values from root to all other devices.
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* root is the rank (not the CUDA device) where data resides before the
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* operation is started.
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*
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* In-place operation will happen if sendbuff == recvbuff.
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*/
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ncclResult_t ncclBroadcast(const void* sendbuff, void* recvbuff, size_t count, ncclDataType_t datatype, int root,
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ncclComm_t comm, cudaStream_t stream);
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ncclResult_t pncclBroadcast(const void* sendbuff, void* recvbuff, size_t count, ncclDataType_t datatype, int root,
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ncclComm_t comm, cudaStream_t stream);
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/*
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* All-Reduce
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*
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* Reduces data arrays of length count in sendbuff using op operation, and
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* leaves identical copies of result on each recvbuff.
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*
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* In-place operation will happen if sendbuff == recvbuff.
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*/
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ncclResult_t ncclAllReduce(const void* sendbuff, void* recvbuff, size_t count,
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ncclDataType_t datatype, ncclRedOp_t op, ncclComm_t comm, cudaStream_t stream);
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ncclResult_t pncclAllReduce(const void* sendbuff, void* recvbuff, size_t count,
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ncclDataType_t datatype, ncclRedOp_t op, ncclComm_t comm, cudaStream_t stream);
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/*
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* Reduce-Scatter
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*
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* Reduces data in sendbuff using op operation and leaves reduced result
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* scattered over the devices so that recvbuff on rank i will contain the i-th
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* block of the result.
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* Assumes sendcount is equal to nranks*recvcount, which means that sendbuff
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* should have a size of at least nranks*recvcount elements.
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*
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* In-place operations will happen if recvbuff == sendbuff + rank * recvcount.
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*/
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ncclResult_t ncclReduceScatter(const void* sendbuff, void* recvbuff,
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size_t recvcount, ncclDataType_t datatype, ncclRedOp_t op, ncclComm_t comm,
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cudaStream_t stream);
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ncclResult_t pncclReduceScatter(const void* sendbuff, void* recvbuff,
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size_t recvcount, ncclDataType_t datatype, ncclRedOp_t op, ncclComm_t comm,
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cudaStream_t stream);
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/*
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* All-Gather
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*
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* Each device gathers sendcount values from other GPUs into recvbuff,
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* receiving data from rank i at offset i*sendcount.
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* Assumes recvcount is equal to nranks*sendcount, which means that recvbuff
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* should have a size of at least nranks*sendcount elements.
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*
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* In-place operations will happen if sendbuff == recvbuff + rank * sendcount.
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*/
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ncclResult_t ncclAllGather(const void* sendbuff, void* recvbuff, size_t sendcount,
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ncclDataType_t datatype, ncclComm_t comm, cudaStream_t stream);
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ncclResult_t pncclAllGather(const void* sendbuff, void* recvbuff, size_t sendcount,
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ncclDataType_t datatype, ncclComm_t comm, cudaStream_t stream);
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/*
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* Send
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*
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* Send data from sendbuff to rank peer.
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*
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* Rank peer needs to call ncclRecv with the same datatype and the same count from this
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* rank.
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*
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* This operation is blocking for the GPU. If multiple ncclSend and ncclRecv operations
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* need to progress concurrently to complete, they must be fused within a ncclGroupStart/
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* ncclGroupEnd section.
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*/
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ncclResult_t ncclSend(const void* sendbuff, size_t count, ncclDataType_t datatype, int peer,
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ncclComm_t comm, cudaStream_t stream);
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ncclResult_t pncclSend(const void* sendbuff, size_t count, ncclDataType_t datatype, int peer,
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ncclComm_t comm, cudaStream_t stream);
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/*
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* Receive
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*
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* Receive data from rank peer into recvbuff.
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*
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* Rank peer needs to call ncclSend with the same datatype and the same count to this
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* rank.
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*
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* This operation is blocking for the GPU. If multiple ncclSend and ncclRecv operations
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* need to progress concurrently to complete, they must be fused within a ncclGroupStart/
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* ncclGroupEnd section.
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*/
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ncclResult_t pncclRecv(void* recvbuff, size_t count, ncclDataType_t datatype, int peer,
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ncclComm_t comm, cudaStream_t stream);
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ncclResult_t ncclRecv(void* recvbuff, size_t count, ncclDataType_t datatype, int peer,
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ncclComm_t comm, cudaStream_t stream);
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/*
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* Group semantics
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*
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* When managing multiple GPUs from a single thread, and since NCCL collective
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* calls may perform inter-CPU synchronization, we need to "group" calls for
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* different ranks/devices into a single call.
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*
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* Grouping NCCL calls as being part of the same collective operation is done
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* using ncclGroupStart and ncclGroupEnd. ncclGroupStart will enqueue all
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* collective calls until the ncclGroupEnd call, which will wait for all calls
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* to be complete. Note that for collective communication, ncclGroupEnd only
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* guarantees that the operations are enqueued on the streams, not that
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* the operation is effectively done.
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*
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* Both collective communication and ncclCommInitRank can be used in conjunction
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* of ncclGroupStart/ncclGroupEnd, but not together.
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*
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* Group semantics also allow to fuse multiple operations on the same device
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* to improve performance (for aggregated collective calls), or to permit
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* concurrent progress of multiple send/receive operations.
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*/
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/*
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* Group Start
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*
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* Start a group call. All calls to NCCL until ncclGroupEnd will be fused into
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* a single NCCL operation. Nothing will be started on the CUDA stream until
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* ncclGroupEnd.
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*/
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ncclResult_t ncclGroupStart();
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ncclResult_t pncclGroupStart();
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/*
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* Group End
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*
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* End a group call. Start a fused NCCL operation consisting of all calls since
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* ncclGroupStart. Operations on the CUDA stream depending on the NCCL operations
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* need to be called after ncclGroupEnd.
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*/
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ncclResult_t ncclGroupEnd();
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ncclResult_t pncclGroupEnd();
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#ifdef __cplusplus
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} // end extern "C"
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#endif
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#endif // end include guard
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