gemm.h 4.8 KB
Newer Older
W
wangliu 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.

Licensed 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. */
Z
zhaojiaying01 已提交
14 15

#pragma once
W
wangliu 已提交
16
#include <vector>
Z
zhaojiaying01 已提交
17

Z
zhaojiaying01 已提交
18 19 20 21
// 矩阵取值运算宏,假设矩阵按行存储
#define A(i, j) A[(i)*lda + (j)]
#define B(i, j) B[(i)*ldb + (j)]
#define C(i, j) C[(i)*ldc + (j)]
Z
zhaojiaying01 已提交
22 23

#define MR 4
24
#define NR 8
Z
zhaojiaying01 已提交
25

W
wangliu 已提交
26
#define s_min(i, j) ((i) < (j) ? (i) : (j))
Z
zhaojiaying01 已提交
27 28 29 30

namespace paddle_mobile {
namespace operators {
namespace math {
W
wangliu 已提交
31 32 33 34
struct Gemmer {
  int MC = 0;
  int KC = 0;
  int NC = 0;
Z
zhaojiaying01 已提交
35

W
wangliu 已提交
36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135
  float *packedA;
  float *packedB;
  float *packedC;
  float *zero;
  static std::vector<Gemmer *> gemmers;

  // 将 A 矩阵分块复制到连续内存(ColMajor)
  void PackMatrixA(int m, int k, int m_tail, const float *A, int lda,
                   float *buffer);

  // 将 B 矩阵分块复制到连续内存(ColMajor)
  void PackMatrixB(int k, int n, int n_tail, const float *B, int ldb,
                   float *buffer);

  // 将 A 矩阵分块复制到连续内存(RowMajor)
  void PackMatrixA_(int m, int k, int m_tail, const float *A, int lda,
                    float *buffer);

  // 将 B 矩阵分块复制到连续内存(RowMajor)
  void PackMatrixB_(int k, int n, int n_tail, const float *B, int ldb,
                    float *buffer);

  // 分块矩阵乘法
  void InnerKernel(int mc, int nc, float alpha, const float *a, const float *b,
                   float beta, float *c, float *C, int ldc, bool relu);

  void InnerKernelWithBn(int mc, int nc, float alpha, const float *a,
                         const float *b, float beta, float *c, float *C,
                         int ldc, bool relu, float *new_scale, float *new_bias);

  // 向量矩阵乘法 (M = 1)
  void VectorKernel(int m, int n, int k, float alpha, const float *A, int lda,
                    const float *B, int ldb, float beta, float *C, int ldc,
                    bool relu);

  void VectorKernelWithBn(int m, int n, int k, float alpha, const float *A,
                          int lda, const float *B, int ldb, float beta,
                          float *C, int ldc, bool relu, float *new_scale,
                          float *new_bias);

  // 计算一个更小的 C 矩阵分块
  void AddDot4x4(int k, const float *a, const float *b, float *c, int ldc);

  void AddDot4x8(int k, const float *a, const float *b, float *c, int ldc);

  // 分块矩阵乘法结果回写
  // C = A * B
  void WriteBasic(int mc, int nc, float *c, float *C, int ldc);

  // C = alpha * A * B + beta * C
  void WriteWithAlphaBeta(int mc, int nc, float *c, float *C, int ldc);

  // C = A * B + C
  void WriteWithAdd(int mc, int nc, float *c, float *C, int ldc);

  // C = A * B + C, relu(C)
  void WriteWithAddRelu(int mc, int nc, float *c, float *C, int ldc);

  // C = A * B, batchnorm(C)
  void WriteWithBn(int mc, int nc, float *c, float *C, int ldc,
                   float *new_scale, float *new_bias);

  // C = A * B, batchnorm(C), relu(C)
  void WriteWithBnRelu(int mc, int nc, float *c, float *C, int ldc,
                       float *new_scale, float *new_bias);

  // 向量矩阵乘法结果回写
  // C = A * B
  void VecWriteBasic(int n, float *c, float *C, int ldc);

  // C = alpha * A * B + beta * C
  void VecWriteWithAlphaBeta(int n, float *c, float *C, int ldc);

  // C = A * B + C
  void VecWriteWithAdd(int n, float *c, float *C, int ldc);

  // C = A * B + C, relu(C)
  void VecWriteWithAddRelu(int n, float *c, float *C, int ldc);

  // C = A * B, batchnorm(C)
  void VecWriteWithBn(int n, float *c, float *C, int ldc, float *new_scale,
                      float *new_bias);

  // C = A * B, batchnorm(C), relu(C)
  void VecWriteWithBnRelu(int n, float *c, float *C, int ldc, float *new_scale,
                          float *new_bias);

  // 32位 float 矩阵乘法
  void Sgemm(int m, int n, int k, float alpha, const float *A, int lda,
             const float *B, int ldb, float beta, float *C, int ldc, bool relu);

  // 32位 float 矩阵乘法, 并对结果进行 batchnrom
  void SgemmWithBn(int m, int n, int k, float alpha, const float *A, int lda,
                   const float *B, int ldb, float beta, float *C, int ldc,
                   bool relu, float *new_scale, float *new_bias);

  // 64位 double 矩阵乘法
  void dgemm(int m, int n, int k, float alpha, const double *A, int lda,
             const double *B, int ldb, float beta, double *C, int ldc);
};
Z
zhaojiaying01 已提交
136 137 138 139

}  // namespace math
}  // namespace operators
}  // namespace paddle_mobile