本文将介绍一种使用C语言实现矩阵乘法的高效方法,即分块算法。分块算法的基本思想是将两个大矩阵分成若干个小矩阵,然后对每对小矩阵进行乘法运算,最后将结果合并成一个大矩阵。这样可以减少缓存失效的次数,提高运算速度。下面给出具体的代码实现。
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#define N 1000 // 矩阵的大小
#define B 100 // 分块的大小
// 生成一个随机矩阵
void generate_matrix(double *A) {
srand(time(NULL));
for (int i = 0; i < N * N; i++) {
A[i] = rand() % 10;
}
}
// 打印一个矩阵
void print_matrix(double *A) {
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
printf("%.2f ", A[i * N + j]);
}
printf("\n");
}
}
// 普通的矩阵乘法
void normal_multiply(double *A, double *B, double *C) {
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
double sum = 0;
for (int k = 0; k < N; k++) {
sum += A[i * N + k] * B[k * N + j];
}
C[i * N + j] = sum;
}
}
}
// 分块的矩阵乘法
void block_multiply(double *A, double *B, double *C) {
for (int i = 0; i < N; i += B) {
for (int j = 0; j < N; j += B) {
for (int k = 0; k < N; k += B) {
// 对每个小矩阵进行乘法运算
for (int ii = i; ii < i + B && ii < N; ii++) {
for (int jj = j; jj < j + B && jj < N; jj++) {
double sum = 0;
for (int kk = k; kk < k + B && kk < N; kk++) {
sum += A[ii * N + kk] * B[kk * N + jj];
}
C[ii * N + jj] += sum;
}
}
}
}
}
}
// 测试两种方法的运行时间
void test_time() {
double *A = malloc(sizeof(double) * N * N);
double *B = malloc(sizeof(double) * N * N);
double *C1 = malloc(sizeof(double) * N * N);
double *C2 = malloc(sizeof(double) * N * N);
generate_matrix(A);
generate_matrix(B);
clock_t start, end;
start = clock();
normal_multiply(A, B, C1);
end = clock();
printf("Normal multiply time: %.3f s\n", (double)(end - start) / CLOCKS_PER_SEC);
start = clock();
block_multiply(A, B, C2);
end = clock();
printf("Block multiply time: %.3f s\n", (double)(end - start) / CLOCKS_PER_SEC);
free(A);
free(B);
free(C1);
free(C2);
}
// 主函数
int main() {
test_time();
return 0;
}
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