hw1: ex2 optimization
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3 changed files with 14 additions and 1978710 deletions
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@ -17,17 +17,17 @@ LDLIBS = -lrt -Wl,--start-group $(MKLROOT)/lib/intel64/libmkl_intel_lp64.a $(MKL
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const char* dgemm_desc = "Block-based dgemm.";
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const int block_size = 18;
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const int block_size = 27;
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inline int min(int a, int b) {
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return a < b ? a : b;
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}
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inline void naivemm(int r_min, int r_max, int k_min, int k_max, int c_min, int c_max, int n, double* A, double* B, double* C_temp) {
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inline void naivemm(int r_min, int r_max, int k_min, int k_max, int c_min, int c_max, int n, double* A_row, double* B, double* C_temp) {
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for (int i = r_min, ii = 0; i < r_max; ++i, ++ii) {
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for (int j = c_min, jj = 0; j < c_max; ++j, ++jj) {
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for (int k = k_min; k < k_max; k++) {
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C_temp[ii + jj * block_size] += A[i + k * n] * B[k + j * n];
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C_temp[ii + jj * block_size] += A_row[i * n + k] * B[k + j * n];
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}
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}
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}
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@ -44,8 +44,18 @@ inline void store_c(double* C, double* C_temp, int r_min, int r_max, int c_min,
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* where A, B, and C are lda-by-lda matrices stored in column-major format.
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* On exit, A and B maintain their input values. */
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void square_dgemm(int n, double* A, double* B, double* C) {
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double A_row[n * n];
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double C_temp[block_size * block_size];
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for (int m = 0; m < n; ++m) {
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double row_tmp[n];
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memcpy(row_tmp, A + m * n, n * sizeof(double));
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for (int l = 0; l < n; ++l) {
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A_row[l * n + m] = row_tmp[l];
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}
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}
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for (int i = 0; i < n; i += block_size) {
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int i_next = min(i + block_size, n);
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@ -56,7 +66,7 @@ void square_dgemm(int n, double* A, double* B, double* C) {
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for (int k = 0; k < n; k += block_size) {
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int k_next = min(k + block_size, n);
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naivemm(i, i_next, k, k_next, j, j_next, n, A, B, C_temp);
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naivemm(i, i_next, k, k_next, j, j_next, n, A_row, B, C_temp);
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}
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store_c(C, C_temp, i, i_next, j, j_next, n);
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@ -1,4 +0,0 @@
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#Description: Naive, three-loop dgemm.
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Size: 31 Mflop/s: 2431.2 Percentage: 6.61
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#Average percentage of Peak = 6.60652
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