forked from pi7mcrg2k/operator_optimization
Merge pull request 'Problem 1-6' (#1) from p8sljnpht/operator_optimization:main into main
commit
6c1d167b8b
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#include <stdio.h>
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#include <time.h>
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#include <stdlib.h>
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#define SIZE 1024
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void vector_add_optimized(float* A, float* B, float* C, int size);
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int main() {
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float A[SIZE], B[SIZE], C[SIZE];
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int i;
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srand(time(0));
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for(i=0; i<SIZE; i++) {
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A[i] = rand() % 100;
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B[i] = rand() % 100;
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}
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clock_t start = clock();
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vector_add_optimized(A, B, C, SIZE);
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clock_t end = clock();
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printf("初始向量加法时间：%lf\n", (double)(end-start) / CLOCKS_PER_SEC);
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}
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void vector_add_optimized(float* A, float* B, float* C, int size) {
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int i;
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for(i=0; i<size; i++) {
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C[i] = A[i] + B[i];
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}
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}
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#include <arm_neon.h>
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#include <stdio.h>
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#include <time.h>
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#include <stdlib.h>
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#define SIZE 1024
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void vector_add_optimized(float* A, float* B, float* C, int size);
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int main() {
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float A[SIZE], B[SIZE], C[SIZE];
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int i;
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srand(time(0));
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for(i=0; i<SIZE; i++) {
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A[i] = rand() % 100;
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B[i] = rand() % 100;
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}
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clock_t start = clock();
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vector_add_optimized(A, B, C, SIZE);
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clock_t end = clock();
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printf("使用NEON 优化向量加法时间：%lf\n", (double)(end-start) / CLOCKS_PER_SEC);
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}
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void vector_add_optimized(float* A, float* B, float* C, int size) {
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int i;
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for(i=0; i<size; i+=4) {
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float32x4_t vecA = vld1q_f32(&A[i]);
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float32x4_t vecB = vld1q_f32(&B[i]);
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float32x4_t vecC = vaddq_f32(vecA, vecB);
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vst1q_f32(&C[i], vecC);
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}
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}
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#include <stdio.h>
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#include <time.h>
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#include <stdlib.h>
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#define SIZE 1024
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void matmul_optimized(float** A, float** B, float** C, int n);
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int main() {
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int n = SIZE;
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// 分配内存空间
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float** A = (float**)malloc(sizeof(float*) * n);
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float** B = (float**)malloc(sizeof(float*) * n);
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float** C = (float**)malloc(sizeof(float*) * n);
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int i, j;
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for(i=0; i<n; i++) {
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A[i] = (float*)malloc(sizeof(float) * n);
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B[i] = (float*)malloc(sizeof(float) * n);
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C[i] = (float*)malloc(sizeof(float) * n);
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}
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// 随机化
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srand(time(0));
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for(i=0; i<n; i++)
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for(j=0; j<n; j++) {
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A[i][j] = rand() % 100;
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B[i][j] = rand() % 100;
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}
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// 计算并计时
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clock_t start = clock();
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matmul_optimized(A, B, C, SIZE);
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clock_t end = clock();
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printf("初始向量乘法时间：%lf\n", (double)(end-start) / CLOCKS_PER_SEC);
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// 释放内存空间
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for(i=0; i<n; 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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}
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free(A); free(B); free(C);
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}
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void matmul_optimized(float** A, float** B, float** C, int n) {
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int i, j, k;
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for(i=0; i<n; i++)
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for(j=0; j<n; j++) {
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C[i][j] = 0;
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for(k=0; k<n; k++) {
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C[i][j] = A[i][k] * B[k][j];
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}
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}
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}
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#include <arm_neon.h>
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#include <stdio.h>
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#include <time.h>
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#include <stdlib.h>
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#define SIZE 1024
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void matmul_optimized(float** A, float** B, float** C, int n);
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int main() {
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int n = SIZE;
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// 分配内存空间
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float** A = (float**)malloc(sizeof(float*) * n);
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float** B = (float**)malloc(sizeof(float*) * n);
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float** C = (float**)malloc(sizeof(float*) * n);
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int i, j;
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for(i=0; i<n; i++) {
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A[i] = (float*)malloc(sizeof(float) * n);
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B[i] = (float*)malloc(sizeof(float) * n);
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C[i] = (float*)malloc(sizeof(float) * n);
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}
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// 随机化
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srand(time(0));
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for(i=0; i<n; i++)
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for(j=0; j<n; j++) {
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A[i][j] = rand() % 100;
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B[i][j] = rand() % 100;
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}
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// 计算并计时
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clock_t start = clock();
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matmul_optimized(A, B, C, SIZE);
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clock_t end = clock();
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printf("使用 NEON 优化稠密矩阵乘法时间：%lf\n", (double)(end-start) / CLOCKS_PER_SEC);
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// 释放内存空间
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for(i=0; i<n; 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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}
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free(A); free(B); free(C);
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}
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void matmul_optimized(float** A, float** B, float** C, int n) {
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int i, j, k;
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float32x4_t vecA, vecB, vecC;
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for(i=0; i<n; i++)
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for(j=0; j<n; j++) {
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vecC = vdupq_n_f32(0.0);
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for(k=0; k<n; k+=4) {
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vecA = vld1q_f32(&A[i][k]);
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vecB = vld1q_f32(&A[k][j]);
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vecC = vmlaq_f32(vecC, vecA, vecB);
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}
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C[i][j] = 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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}
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#include <stdio.h>
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#include <time.h>
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#include <stdlib.h>
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#define SIZE 1024
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void sparce_matmul_coo(float*, int*, int*, int,
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float*, int*, int*, int, float*, int*, int*, int*);
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int main() {
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// 矩阵 A 的 COO 格式
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float A_values[] = {1, 2, 3, 4, 5};
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int A_rowIndex[] = {0, 0, 1, 2, 2};
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int A_colIndex[] = {0, 2, 1, 0, 2};
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int A_nonZeroCount = 5;
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// 矩阵 B 的 Coo 格式
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float B_values[] = {6, 8, 7, 9};
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int B_rowIndex[] = {0, 2, 1, 2};
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int B_colIndex[] = {0, 0, 1, 2};
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int B_nonZeroCount = 4;// 结果矩阵 C 的 Coo 格式
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float C_values[SIZE];
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int C_rowIndex[SIZE];
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int C_colIndex[SIZE];
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int C_nonZeroCount = 0;
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clock_t start = clock();
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sparce_matmul_coo(A_values, A_rowIndex, A_colIndex, A_nonZeroCount,
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B_values, B_rowIndex, B_colIndex, B_nonZeroCount,
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C_values, C_rowIndex, C_colIndex, &C_nonZeroCount);
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clock_t end = clock();
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printf("基础的稀疏矩阵乘法时间：%lf\n", (double)(end-start) / CLOCKS_PER_SEC);
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}
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void sparce_matmul_coo(float* A_values, int* A_rowIndex, int* A_colIndex, int A_nonZeroCount,
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float* B_values, int* B_rowIndex, int* B_colIndex, int B_nonZeroCount,
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float* C_values, int* C_rowIndex, int* C_colIndex, int* C_nonZeroCount) {
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int currentIndex = 0;
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int i, j, k;
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int rowA, colA, rowB, colB;
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float valueA, valueB, product;
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// 遍历 A 的非零元素
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for(i=0; i<A_nonZeroCount; i++) {
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rowA = A_rowIndex[i];
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colA = A_colIndex[i];
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valueA = A_values[i];
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// 遍历 B 的非零元素
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for(j=0; j<B_nonZeroCount; j++) {
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rowB = B_rowIndex[j];
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colB = B_colIndex[j];
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valueB = B_values[j];
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// 如果 A 的列和 B 的行匹配，则计算乘积并存储结果
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if (colA == rowB) {
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product = valueA * valueB;
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// 检查是否已有此(rowA, colB) 项
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int found = 0;
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for(k=0; k<currentIndex; k++) {
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if(C_rowIndex[k] == rowA && C_colIndex[k] == colB) {
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C_values[k] += product;
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break;
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}
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}
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if (!found) {
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C_values[currentIndex] = product;
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C_rowIndex[currentIndex] = rowA;
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C_colIndex[currentIndex] = colB;
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currentIndex++;
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}
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}
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}
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}
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*C_nonZeroCount = currentIndex;
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}
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@ -0,0 +1,88 @@
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#include <arm_neon.h>
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#include <stdio.h>
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#include <time.h>
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#include <stdlib.h>
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#include <string.h>
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#define SIZE 1024
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#define DENSE_MATRIX_SIZE 5
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float** sparce_matmul_coo(float* A_values, int* A_rowIndex, int* A_colIndex, int A_nonZeroCount,
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float* B_values, int* B_rowIndex, int* B_colIndex, int B_nonZeroCount);
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void matmul_optimized(float** A, float** B, float** C, int n);
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void print_matrix(float** m, int rows, int cols);
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int main() {
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// 矩阵 A 的 COO 格式
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float A_values[] = {1, 2, 3, 4, 5};
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int A_rowIndex[] = {0, 0, 1, 2, 2};
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int A_colIndex[] = {0, 2, 1, 0, 2};
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int A_nonZeroCount = 5;
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// 矩阵 B 的 Coo 格式
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float B_values[] = {6, 8, 7, 9};
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int B_rowIndex[] = {0, 2, 1, 2};
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int B_colIndex[] = {0, 0, 1, 2};
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int B_nonZeroCount = 4;// 结果矩阵 C 的 Coo 格式
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float C_values[SIZE];
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int C_rowIndex[SIZE];
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int C_colIndex[SIZE];
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int C_nonZeroCount = 0;
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clock_t start = clock();
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float** ans = sparce_matmul_coo(A_values, A_rowIndex, A_colIndex, A_nonZeroCount,
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B_values, B_rowIndex, B_colIndex, B_nonZeroCount);
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clock_t end = clock();
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printf("优化的稀疏矩阵乘法时间：%lf\n", (double)(end-start) / CLOCKS_PER_SEC);
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print_matrix(ans, DENSE_MATRIX_SIZE, DENSE_MATRIX_SIZE);
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}
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float** sparce_matmul_coo(float* A_values, int* A_rowIndex, int* A_colIndex, int A_nonZeroCount,
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float* B_values, int* B_rowIndex, int* B_colIndex, int B_nonZeroCount) {
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// 分配内存空间
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float** A = (float**)malloc(sizeof(float*) * DENSE_MATRIX_SIZE);
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float** B = (float**)malloc(sizeof(float*) * DENSE_MATRIX_SIZE);
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float** C = (float**)malloc(sizeof(float*) * DENSE_MATRIX_SIZE);
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int i;
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for(i=0; i<DENSE_MATRIX_SIZE; i++) {
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A[i] = (float*)malloc(sizeof(float) * DENSE_MATRIX_SIZE);
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B[i] = (float*)malloc(sizeof(float) * DENSE_MATRIX_SIZE);
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C[i] = (float*)malloc(sizeof(float) * DENSE_MATRIX_SIZE);
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memset(A[i], 0, sizeof(float) * DENSE_MATRIX_SIZE);
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memset(B[i], 0, sizeof(float) * DENSE_MATRIX_SIZE);
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memset(C[i], 0, sizeof(float) * DENSE_MATRIX_SIZE);
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}
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for (i=0; i<A_nonZeroCount; i++) A[A_rowIndex[i]][A_colIndex[i]] = A_values[i];
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for (i=0; i<B_nonZeroCount; i++) B[B_rowIndex[i]][B_colIndex[i]] = B_values[i];
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matmul_optimized(A, B, C, DENSE_MATRIX_SIZE);
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// 释放内存空间
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for(i=0; i<DENSE_MATRIX_SIZE; i++) {
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free(A[i]);
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free(B[i]);
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}
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free(A); free(B);
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return C;
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}
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void matmul_optimized(float** A, float** B, float** C, int n) {
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int i, j, k;
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float32x4_t vecA, vecB, vecC;
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for(i=0; i<n; i++)
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for(j=0; j<n; j++) {
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vecC = vdupq_n_f32(0.0);
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for(k=0; k<n; k+=4) {
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vecA = vld1q_f32(&A[i][k]);
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vecB = vld1q_f32(&A[k][j]);
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vecC = vmlaq_f32(vecC, vecA, vecB);
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}
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C[i][j] = 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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}
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void print_matrix(float** m, int rows, int cols) {
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int i, j;
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for(i=0; i<rows; i++) {
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for(j=0; j<cols; j++) {
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printf("%5.0f ", m[i][j]);
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}
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printf("\n");
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}
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}
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Reference in new issue