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步骤六.cpp

@@ -0,0 +1,75 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include <time.h>
+
+#define SIZE 100
+#define MAX_NONZEROS 1000
+
+typedef struct {
+    float values[MAX_NONZEROS];
+    int rowIndex[MAX_NONZEROS];
+    int colIndex[MAX_NONZEROS];
+    int nonZeroCount;
+} SparseMatrix;
+
+void initSparseMatrix(SparseMatrix *matrix, int nonZeroCount) {
+    matrix->nonZeroCount = nonZeroCount;
+    for (int i = 0; i < nonZeroCount; i++) {
+        matrix->values[i] = (float)(rand() % 100) / 10.0f;
+        matrix->rowIndex[i] = rand() % SIZE;
+        matrix->colIndex[i] = rand() % SIZE;
+    }
+}
+
+void sparseToDense(const SparseMatrix *sparse, float dense[SIZE][SIZE]) {
+    for (int i = 0; i < SIZE; i++) {
+        for (int j = 0; j < SIZE; j++) {
+            dense[i][j] = 0.0f;
+        }
+    }
+    for (int i = 0; i < sparse->nonZeroCount; i++) {
+        dense[sparse->rowIndex[i]][sparse->colIndex[i]] = sparse->values[i];
+    }
+}
+
+void matmul(float A[SIZE][SIZE], float B[SIZE][SIZE], float C[SIZE][SIZE]) {
+    for (int i = 0; i < SIZE; i++) {
+        for (int j = 0; j < SIZE; j++) {
+            for (int k = 0; k < SIZE; k++) {
+                C[i][j] += A[i][k] * B[k][j];
+            }
+        }
+    }
+}
+
+int main() {
+    SparseMatrix A, B;
+    clock_t start, end;
+    float denseA[SIZE][SIZE], denseB[SIZE][SIZE], denseC[SIZE][SIZE];
+
+    initSparseMatrix(&A, 500); 
+    initSparseMatrix(&B, 300); 
+    
+    start = clock();
+
+    sparseToDense(&A, denseA);
+    sparseToDense(&B, denseB);
+
+    matmul(denseA, denseB, denseC);
+
+    end = clock();
+
+    double timeSpent = double(end - start) / CLOCKS_PER_SEC;
+
+    printf("优化后的稀疏矩阵乘法用时: %e", timeSpent);
+
+    printf("Result matrix C (partial):\n");
+    for (int i = 0; i < 10; i++) {
+        for (int j = 0; j < 10; j++) {
+            printf("%.2f ", denseC[i][j]);
+        }
+        printf("\n");
+    }
+
+    return 0;
+}