Add task6.cpp

main
pv3e4i5aj 22 hours ago
parent 1ee718b12a
commit 387e354d5b

@ -0,0 +1,153 @@
#include <stdio.h>
#include <arm_neon.h>
#include <ctime>
#include <stdlib.h>
#define M 27
#define N 25
#define Q 12
//A(M*N),B(N*Q),C(M*Q),transposed(Q*N)对于矩阵维度的说明
void transposeMatrix(float** matrix, float** transposed) {
for (int i = 0; i < N; i++) {
for (int j = 0; j < Q; j++) {
transposed[j][i] = matrix[i][j];
}
}
}
void matmul_optimized(float** A, float** B, float** C) {
for (int i = 0; i < M; i++) {
for (int j = 0; j < Q; j++) {
float sum = 0.0f;
for (int k = 0; k < N; k += 4)
{
float32x4_t vecA, vecB, vecC;
if (k + 4 <= N)
{
// 加载A和B的4个元素进行向量化计算
vecA = vld1q_f32(&A[i][k]);
vecB = vld1q_f32(&B[j][k]);
// 向量化乘法并累加结果
vecC = vmulq_f32(vecA, vecB);
sum += vgetq_lane_f32(vecC, 0) + vgetq_lane_f32(vecC, 1) +
vgetq_lane_f32(vecC, 2) + vgetq_lane_f32(vecC, 3);
}
else
{
// 处理剩余的元素
for (int m = k; m < N; m++)
{
sum += A[i][m] * B[j][m];
}
}
}
C[i][j] = sum;
}
}
}
int main()
{
//矩阵 A 的 COO 格式
float A_values[] = {1, 2, 3,4,5};
int A_rowIndex[] = {0, 0, 1, 2, 2};
int A_colIndex[] = {0, 2, 1,0, 2};
int A_nonZeroCount = 5;
// 矩阵 B 的 COO 格式
float B_values[] = {6,8,7,9};
int B_rowIndex[] = {0,2, 1, 2};
int B_colIndex[] ={0,0,1, 2};
int B_nonZeroCount=4;
//动态分配内存
float** denseMatrixA = (float**)malloc(M * sizeof(float*));
float** denseMatrixB = (float**)malloc(N * sizeof(float*));
float** C = (float**)malloc(M * sizeof(float*));
float** transposed = (float**)malloc(Q * sizeof(float*));
for (int i = 0; i < M; i++) {
denseMatrixA[i] = (float*)malloc(N * sizeof(float));
C[i] = (float*)malloc(Q * sizeof(float));
}
for (int i = 0; i < N; ++i)
{
denseMatrixB[i] = (float*)malloc(Q * sizeof(float));
}
for (int i = 0; i < Q; ++i)
{
transposed[i] = (float*)malloc(N * sizeof(float));
}
// 实现稀疏矩阵转换为普通矩阵
for(int i=0;i<M;i++)
{
for(int j=0;j<N;j++)
{
denseMatrixA[i][j]=0;
}
}
for(int i=0;i<N;i++)
{
for(int j=0;j<Q;j++)
{
denseMatrixB[i][j]=0;
}
}
for(int i = 0; i < A_nonZeroCount; i++)
{
int row = A_rowIndex[i];
int col = A_colIndex[i];
denseMatrixA[row][col] = A_values[i];
}
for(int i = 0; i < B_nonZeroCount; i++)
{
int row = B_rowIndex[i];
int col = B_colIndex[i];
denseMatrixB[row][col] = B_values[i];
}
//打印常规矩阵
printf("A的常规矩阵为\n");
for(int i=0;i<M;i++)
{
for(int j=0;j<N;j++)
{
printf("%.1f ",denseMatrixA[i][j]);
}
printf("\n");
}
printf("B的常规矩阵为\n");
for(int i=0;i<N;i++)
{
for(int j=0;j<Q;j++)
{
printf("%.1f ",denseMatrixB[i][j]);
}
printf("\n");
}
//为了之后的运用NEON来相乘需要对B进行转置
transposeMatrix(denseMatrixB,transposed) ;
clock_t start = clock();
matmul_optimized(denseMatrixA,transposed,C);
clock_t end = clock();
// 计算并输出优化的稀疏矩阵乘法的时间
double time_spent = double(end - start) / CLOCKS_PER_SEC;
printf("当矩阵A的维度为%d*%d,矩阵B的维度为%d*%d时优化的稀疏矩阵乘法的用时%lf秒\n", M,N,N,Q,time_spent);
// 释放动态分配的内存
for (int i = 0; i < M; ++i) {
free(denseMatrixA[i]);free(C[i]);
}
for (int i = 0; i < N ;++i) {
free(denseMatrixB[i]);
}
for (int i = 0; i < Q ;++i) {
free(transposed[i]);
}
free(denseMatrixA); free(denseMatrixB); free(C);free(transposed);
}
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