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#include <stdio.h>
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#include <ctime>
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#include <arm_neon.h> //启用 NEON 指令
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#include <stdlib.h>
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#define SIZE 1024
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void transposeMatrix(float** matrix, float** transposed, int size) {
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for (int i = 0; i < size; i++) {
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for (int j = 0; j < size; j++) {
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transposed[j][i] = matrix[i][j];
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}
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}
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}
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void matmul(float** A, float** B, float** C, int n) {
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for (int i = 0; i < n; i++) {
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for (int j = 0; j < n; j++) {
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float sum = 0.0f;
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for (int k = 0; k < n; k += 4)
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{
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float32x4_t vecA, vecB, vecC;
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if (k + 4 <= n)
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{
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// 加载A和B的4个元素，进行向量化计算
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vecA = vld1q_f32(&A[i][k]);
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vecB = vld1q_f32(&B[j][k]);
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// 向量化乘法并累加结果
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vecC = vmulq_f32(vecA, vecB);
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sum += vgetq_lane_f32(vecC, 0) + vgetq_lane_f32(vecC, 1) +
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vgetq_lane_f32(vecC, 2) + vgetq_lane_f32(vecC, 3);
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}
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else
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{
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// 处理剩余的元素
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for (int m = k; m < n; m++)
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{
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sum += A[i][m] * B[j][m];
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}
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}
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}
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C[i][j] = sum;
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}
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}
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}
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int main() {
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srand(time(NULL));
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float** A = (float**)malloc(SIZE * sizeof(float*));
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float** B = (float**)malloc(SIZE * sizeof(float*));
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float** C = (float**)malloc(SIZE * sizeof(float*));
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float** transposed = (float**)malloc(SIZE * sizeof(float*));
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for (int i = 0; i < SIZE; i++) {
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A[i] = (float*)malloc(SIZE * sizeof(float));
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B[i] = (float*)malloc(SIZE * sizeof(float));
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C[i] = (float*)malloc(SIZE * sizeof(float));
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transposed[i] = (float*)malloc(SIZE * sizeof(float));
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}
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for (int i = 0; i < SIZE; i++) {
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for (int j = 0; j < SIZE; j++) {
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A[i][j] = (float)(rand() % 100) / 100.0f;
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B[i][j] = (float)(rand() % 100) / 100.0f;
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}
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}
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transposeMatrix(B, transposed, SIZE);
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clock_t start = clock();
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matmul(A, transposed, C, SIZE);
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clock_t end = clock();
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// 计算并输出矩阵乘法的时间
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double multiply_time_spent = double(end - start) / CLOCKS_PER_SEC;
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printf("使用优化的向量乘法：\n当SIZE取%d时，优化的向量乘法时间：%lf秒\n", SIZE, multiply_time_spent);
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for (int i = 0; i < SIZE; i++) {
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free(A[i]);
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free(B[i]);
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free(C[i]);
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free(transposed[i]);
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}
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free(A);
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free(B);
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free(C);
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free(transposed);
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return 0;
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} |
