/* Copyright 2021 The LightSeq Team Copyright Microsoft DeepSpeed This file is adapted from Microsoft DeepSpeed Licensed under the MIT License. */ #include "cublas_wrappers.h" int cublas_gemm_ex(cublasHandle_t handle, cublasOperation_t transa, cublasOperation_t transb, int m, int n, int k, const float *alpha, const float *beta, const float *A, const float *B, float *C, cublasGemmAlgo_t algo) { cublasStatus_t status = cublasGemmEx(handle, transa, transb, m, n, k, (const void *)alpha, (const void *)A, CUDA_R_32F, (transa == CUBLAS_OP_N) ? m : k, (const void *)B, CUDA_R_32F, (transb == CUBLAS_OP_N) ? k : n, (const void *)beta, C, CUDA_R_32F, m, CUDA_R_32F, algo); if (status != CUBLAS_STATUS_SUCCESS) { fprintf(stderr, "!!!! kernel execution error. (m: %d, n: %d, k: %d, error: %d) \n", m, n, k, (int)status); return EXIT_FAILURE; } return 0; } int cublas_gemm_ex(cublasHandle_t handle, cublasOperation_t transa, cublasOperation_t transb, int m, int n, int k, const float *alpha, const float *beta, const __half *A, const __half *B, __half *C, cublasGemmAlgo_t algo) { cublasStatus_t status = cublasGemmEx( handle, transa, transb, m, n, k, (const void *)alpha, (const void *)A, CUDA_R_16F, (transa == CUBLAS_OP_N) ? m : k, (const void *)B, CUDA_R_16F, (transb == CUBLAS_OP_N) ? k : n, (const void *)beta, (void *)C, CUDA_R_16F, m, CUDA_R_32F, algo); if (status != CUBLAS_STATUS_SUCCESS) { fprintf(stderr, "!!!! kernel execution error. (m: %d, n: %d, k: %d, error: %d) \n", m, n, k, (int)status); return EXIT_FAILURE; } return 0; } int cublas_strided_batched_gemm(cublasHandle_t handle, int m, int n, int k, const float *alpha, const float *beta, const float *A, const float *B, float *C, cublasOperation_t op_A, cublasOperation_t op_B, int stride_A, int stride_B, int stride_C, int batch, cublasGemmAlgo_t algo) { cublasStatus_t status = cublasGemmStridedBatchedEx( handle, op_A, op_B, m, n, k, alpha, A, CUDA_R_32F, (op_A == CUBLAS_OP_N) ? m : k, stride_A, B, CUDA_R_32F, (op_B == CUBLAS_OP_N) ? k : n, stride_B, beta, C, CUDA_R_32F, m, stride_C, batch, CUDA_R_32F, algo); if (status != CUBLAS_STATUS_SUCCESS) { fprintf(stderr, "!!!! kernel execution error. (batch: %d, m: %d, n: %d, k: %d, " "error: %d) \n", batch, m, n, k, (int)status); return EXIT_FAILURE; } return 0; } int cublas_strided_batched_gemm(cublasHandle_t handle, int m, int n, int k, const float *alpha, const float *beta, const __half *A, const __half *B, __half *C, cublasOperation_t op_A, cublasOperation_t op_B, int stride_A, int stride_B, int stride_C, int batch, cublasGemmAlgo_t algo) { cublasStatus_t status = cublasGemmStridedBatchedEx( handle, op_A, op_B, m, n, k, alpha, A, CUDA_R_16F, (op_A == CUBLAS_OP_N) ? m : k, stride_A, B, CUDA_R_16F, (op_B == CUBLAS_OP_N) ? k : n, stride_B, beta, C, CUDA_R_16F, m, stride_C, batch, CUDA_R_32F, algo); if (status != CUBLAS_STATUS_SUCCESS) { fprintf(stderr, "!!!! kernel execution error. (m: %d, n: %d, k: %d, error: %d) \n", m, n, k, (int)status); return EXIT_FAILURE; } return 0; }