diff --git a/t6.cpp b/t6.cpp
new file mode 100644
index 0000000..0ca1044
--- /dev/null
+++ b/t6.cpp
@@ -0,0 +1,77 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+
+typedef struct {
+    float* values;
+    int* rowIndex;
+    int* colIndex;
+    int nonZeroCount;
+} SparseMatrix;
+
+void sparseToDense(SparseMatrix* A, float** denseA, int rows, int cols) {
+    for (int i = 0; i < rows; i++) {
+        for (int j = 0; j < cols; j++) {
+            denseA[i][j] = 0.0;
+        }
+    }
+
+    for (int k = 0; k < A->nonZeroCount; k++) {
+        int row = A->rowIndex[k];
+        int col = A->colIndex[k];
+        float val = A->values[k];
+        denseA[row][col] = val;
+    }
+}
+
+void matmul(float** A, float** B, float** C, int n) {
+    for (int i = 0; i < n; i++) {
+        for (int j = 0; j < n; j++) {
+            float sum = 0.0;
+            for (int k = 0; k < n; k++) {
+                sum += A[i][k] * B[k][j];
+            }
+            C[i][j] = sum;
+        }
+    }
+}
+
+int main() {
+    // 假设已经有了两个稀疏矩阵A和B
+    SparseMatrix A, B;
+    // 初始化A和B...
+
+    int rowsA = A.rowIndex[A.nonZeroCount];
+    int colsA = A.colIndex[A.nonZeroCount];
+    int rowsB = B.rowIndex[B.nonZeroCount];
+    int colsB = B.colIndex[B.nonZeroCount];
+
+    float** denseA = (float**)malloc(rowsA * sizeof(float*));
+    float** denseB = (float**)malloc(rowsB * sizeof(float*));
+    float** denseC = (float**)malloc(rowsA * sizeof(float*));
+
+    for (int i = 0; i < rowsA; i++) {
+        denseA[i] = (float*)malloc(colsA * sizeof(float));
+        memset(denseA[i], 0, colsA * sizeof(float));
+    }
+    for (int i = 0; i < rowsB; i++) {
+        denseB[i] = (float*)malloc(colsB * sizeof(float));
+        memset(denseB[i], 0, colsB * sizeof(float));
+    }
+    for (int i = 0; i < rowsA; i++) {
+        denseC[i] = (float*)malloc(colsB * sizeof(float));
+        memset(denseC[i], 0, colsB * sizeof(float));
+    }
+
+    sparseToDense(&A, denseA, rowsA, colsA);
+    sparseToDense(&B, denseB, rowsB, colsB);
+
+    clock_t start = clock();
+    matmul(denseA, denseB, denseC, rowsA);
+    clock_t end = clock();
+
+    printf("优化的稀疏矩阵乘法耗时: %lf 毫秒\n", 1000.0 * (end - start) / CLOCKS_PER_SEC);
+
+    return 0;
+}
+