diff --git a/task4_pro.cpp b/task4_pro.cpp new file mode 100644 index 0000000..95dc5de --- /dev/null +++ b/task4_pro.cpp @@ -0,0 +1,104 @@ +#include +#include +#include //启用 NEON 指令 +#include + +#define M 1000 +#define N 1021 +#define Q 1000 +//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(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() { + srand(time(NULL)); + + float** A = (float**)malloc(M * sizeof(float*)); + float** B = (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++) { + A[i] = (float*)malloc(N * sizeof(float)); + C[i] = (float*)malloc(Q * sizeof(float)); + } + for (int i = 0; i < N; ++i) + { + B[i] = (float*)malloc(Q * sizeof(float)); + } + for (int i = 0; i < Q; ++i) + { + transposed[i] = (float*)malloc(N * sizeof(float)); + } + // 初始化矩阵数据 + for (int i = 0; i < M; i++) { + for (int j = 0; j < N; j++) { + A[i][j] = (float)(rand() % 100) / 100.0f; + } + } + for (int i = 0; i < N; i++) { + for (int j = 0; j < Q; j++) { + B[i][j] = (float)(rand() % 100) / 100.0f; + } + } + + transposeMatrix(B, transposed); + + clock_t start = clock(); + matmul(A, transposed, C); + clock_t end = clock(); + + // 计算并输出矩阵乘法的时间 + double multiply_time_spent = double(end - start) / CLOCKS_PER_SEC; + printf("使用优化的向量乘法:\n当矩阵A的维度为%d*%d,矩阵B的维度为%d*%d时,优化的向量乘法时间:%lf秒\n", M,N,N,Q,multiply_time_spent); + + // 释放动态分配的内存 + for (int i = 0; i < M; ++i) { + free(A[i]);free(C[i]); + } + for (int i = 0; i < N ;++i) { + free(B[i]); + } + for (int i = 0; i < Q ;++i) { + free(transposed[i]); + } + free(A); free(B); free(C);free(transposed); + +} \ No newline at end of file