Add task4_pro.cpp

task4_pro.cpp

@@ -0,0 +1,104 @@
+#include <stdio.h>
+#include <ctime>
+#include <arm_neon.h> //启用 NEON 指令
+#include <stdlib.h>
+
+#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);
+
+}