/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ /*! * Copyright (c) 2018 by Contributors * \file Use external cblas library call. */ #include <tvm/runtime/registry.h> #include <tvm/runtime/util.h> #include <dmlc/logging.h> #include "../cblas/gemm_common.h" #include "cublas_utils.h" namespace tvm { namespace contrib { using namespace runtime; inline cublasOperation_t BooleanToTranspose(bool item) { return item ? CUBLAS_OP_T : CUBLAS_OP_N; } struct CublasSgemmOp { typedef float TDatatype; cublasHandle_t handle; explicit CublasSgemmOp(cublasHandle_t hdl) : handle(hdl) {} void operator()(bool ta, bool tb, int M, int N, int K, float alpha, float* A, int lda, float* B, int ldb, float beta, float* C, int ldc) { CHECK_CUBLAS_ERROR(cublasSgemm(handle, BooleanToTranspose(ta), BooleanToTranspose(tb), M, N, K, &alpha, A, lda, B, ldb, &beta, C, ldc)); } }; struct CublasDgemmOp { typedef double TDatatype; cublasHandle_t handle; explicit CublasDgemmOp(cublasHandle_t hdl) : handle(hdl) {} void operator()(bool ta, bool tb, int M, int N, int K, double alpha, double* A, int lda, double* B, int ldb, double beta, double* C, int ldc) { CHECK_CUBLAS_ERROR(cublasDgemm(handle, BooleanToTranspose(ta), BooleanToTranspose(tb), M, N, K, &alpha, A, lda, B, ldb, &beta, C, ldc)); } }; struct CublasSgemmBatchOp { typedef float TDatatype; cublasHandle_t handle; explicit CublasSgemmBatchOp(cublasHandle_t hdl) : handle(hdl) {} void operator()(int batch_size, bool ta, bool tb, int M, int N, int K, float alpha, float* A, int a_stride, int lda, float* B, int b_stride, int ldb, float beta, float* C, int c_stride, int ldc) { CHECK_CUBLAS_ERROR(cublasSgemmStridedBatched(handle, BooleanToTranspose(ta), BooleanToTranspose(tb), M, N, K, &alpha, A, lda, a_stride, B, ldb, b_stride, &beta, C, ldc, c_stride, batch_size)); } }; struct CublasDgemmBatchOp { typedef double TDatatype; cublasHandle_t handle; explicit CublasDgemmBatchOp(cublasHandle_t hdl) : handle(hdl) {} void operator()(int batch_size, bool ta, bool tb, int M, int N, int K, double alpha, double* A, int a_stride, int lda, double* B, int b_stride, int ldb, double beta, double* C, int c_stride, int ldc) { CHECK_CUBLAS_ERROR(cublasDgemmStridedBatched(handle, BooleanToTranspose(ta), BooleanToTranspose(tb), M, N, K, &alpha, A, lda, a_stride, B, ldb, b_stride, &beta, C, ldc, c_stride, batch_size)); } }; // matrix multiplication for row major TVM_REGISTER_GLOBAL("tvm.contrib.cublas.matmul") .set_body([](TVMArgs args, TVMRetValue *ret) { DLTensor* A = args[0]; CHECK(TypeMatch(A->dtype, kDLFloat, 32) || TypeMatch(A->dtype, kDLFloat, 64)); CuBlasThreadEntry* entry_ptr = CuBlasThreadEntry::ThreadLocal(); if (TypeMatch(A->dtype, kDLFloat, 32)) CallGemm(args, ret, CublasSgemmOp(entry_ptr->handle)); else CallGemm(args, ret, CublasDgemmOp(entry_ptr->handle)); }); TVM_REGISTER_GLOBAL("tvm.contrib.cublas.batch_matmul") .set_body([](TVMArgs args, TVMRetValue* ret) { DLTensor* A = args[0]; CHECK(TypeMatch(A->dtype, kDLFloat, 32) || TypeMatch(A->dtype, kDLFloat, 64)); CuBlasThreadEntry* entry_ptr = CuBlasThreadEntry::ThreadLocal(); if (TypeMatch(A->dtype, kDLFloat, 32)) CallBatchGemm(args, ret, CublasSgemmBatchOp(entry_ptr->handle)); else CallBatchGemm(args, ret, CublasDgemmBatchOp(entry_ptr->handle)); }); } // namespace contrib } // namespace tvm