+++ /dev/null
-//**************************************************************************\r
-// Multi-threaded Matrix Multiply benchmark\r
-//--------------------------------------------------------------------------\r
-// TA : Christopher Celio\r
-// Student:\r
-//\r
-//\r
-// This benchmark multiplies two 2-D arrays together and writes the results to\r
-// a third vector. The input data (and reference data) should be generated\r
-// using the matmul_gendata.pl perl script and dumped to a file named\r
-// dataset.h.\r
-\r
-\r
-// print out arrays, etc.\r
-//#define DEBUG\r
-\r
-//--------------------------------------------------------------------------\r
-// Includes\r
-\r
-#include <string.h>\r
-#include <stdlib.h>\r
-#include <stdio.h>\r
-\r
-\r
-//--------------------------------------------------------------------------\r
-// Input/Reference Data\r
-\r
-typedef float data_t;\r
-#include "dataset.h"\r
-\r
-\r
-//--------------------------------------------------------------------------\r
-// Basic Utilities and Multi-thread Support\r
-\r
-__thread unsigned long coreid;\r
-unsigned long ncores;\r
-\r
-#include "util.h"\r
-\r
-#define stringify_1(s) #s\r
-#define stringify(s) stringify_1(s)\r
-#define stats(code) do { \\r
-unsigned long _c = -rdcycle(), _i = -rdinstret(); \\r
-code; \\r
-_c += rdcycle(), _i += rdinstret(); \\r
-if (coreid == 0) \\r
-printf("%s: %ld cycles, %ld.%ld cycles/iter, %ld.%ld CPI\n", \\r
-stringify(code), _c, _c/DIM_SIZE/DIM_SIZE/DIM_SIZE, 10*_c/DIM_SIZE/DIM_SIZE/DIM_SIZE%10, _c/_i, 10*_c/_i%10); \\r
-} while(0)\r
-\r
-\r
-//--------------------------------------------------------------------------\r
-// Helper functions\r
-\r
-void printArrayMT( char name[], int n, data_t arr[] )\r
-{\r
- int i;\r
- if (coreid != 0)\r
- return;\r
- \r
- printf( " %10s :", name );\r
- for ( i = 0; i < n; i++ )\r
- printf( " %3ld ", (long) arr[i] );\r
- printf( "\n" );\r
-}\r
-\r
-void __attribute__((noinline)) verifyMT(size_t n, const data_t* test, const data_t* correct)\r
-{\r
- if (coreid != 0)\r
- return;\r
- \r
- size_t i;\r
- for (i = 0; i < n; i++)\r
- {\r
- if (test[i] != correct[i])\r
- {\r
- printf("FAILED test[%d]= %3ld, correct[%d]= %3ld\n",\r
- i, (long)test[i], i, (long)correct[i]);\r
- exit(-1);\r
- }\r
- }\r
- \r
- return;\r
-}\r
-\r
-//--------------------------------------------------------------------------\r
-// matmul function\r
-\r
-// single-thread, naive version\r
-void __attribute__((noinline)) matmul_naive(const int lda, const data_t A[], const data_t B[], data_t C[] )\r
-{\r
- \r
- int i, j, k;\r
- \r
- if (coreid > 0)\r
- return;\r
- \r
- for ( i = 0; i < lda; i++ )\r
- for ( j = 0; j < lda; j++ )\r
- {\r
- for ( k = 0; k < lda; k++ )\r
- {\r
- C[i + j*lda] += A[j*lda + k] * B[k*lda + i];\r
- }\r
- }\r
- \r
-}\r
-\r
-\r
-\r
-void __attribute__((noinline)) matmul(const int lda, const data_t A[], const data_t B[], data_t C[] )\r
-{\r
- \r
- // ***************************** //\r
- // **** ADD YOUR CODE HERE ***** //\r
- // ***************************** //\r
- //\r
- // feel free to make a separate function for MI and MSI versions.\r
- \r
- int m, i, j, k, iB0, iB1;\r
- data_t tempC0, tempC1, tempC2, tempC3, tempC4, tempC5, tempC6, tempC7;\r
- data_t tempA0, tempA1;\r
- \r
- if (coreid == 0){\r
- for (m = 0; m < 2; m++){\r
- for (j = 0; j < lda/2; j++){\r
- for (i = 0; i < lda; i+=8){\r
- tempC0 = C[i + j*lda];\r
- tempC1 = C[i + j*lda+1];\r
- tempC2 = C[i + j*lda+2];\r
- tempC3 = C[i + j*lda+3];\r
- tempC4 = C[i + j*lda+4];\r
- tempC5 = C[i + j*lda+5];\r
- tempC6 = C[i + j*lda+6];\r
- tempC7 = C[i + j*lda+7];\r
- iB0 = m*lda*lda/2+i;\r
- iB1 = iB0+lda;\r
- for (k = m*lda/2; k < (m+1)*lda/2; k+=2){\r
- tempA0 = A[j*lda+k];\r
- tempA1 = A[j*lda+k+1];\r
- tempC0 += tempA0*B[iB0]+tempA1*B[iB1];\r
- tempC1 += tempA0*B[iB0+1]+tempA1*B[iB1+1];\r
- tempC2 += tempA0*B[iB0+2]+tempA1*B[iB1+2];\r
- tempC3 += tempA0*B[iB0+3]+tempA1*B[iB1+3];\r
- tempC4 += tempA0*B[iB0+4]+tempA1*B[iB1+4];\r
- tempC5 += tempA0*B[iB0+5]+tempA1*B[iB1+5];\r
- tempC6 += tempA0*B[iB0+6]+tempA1*B[iB1+6];\r
- tempC7 += tempA0*B[iB0+7]+tempA1*B[iB1+7];\r
- iB0 += 2*lda;\r
- iB1 += 2*lda;\r
- \r
- }\r
- C[i + j*lda] = tempC0;\r
- C[i + j*lda + 1] = tempC1;\r
- C[i + j*lda + 2] = tempC2;\r
- C[i + j*lda + 3] = tempC3;\r
- C[i + j*lda + 4] = tempC4;\r
- C[i + j*lda + 5] = tempC5;\r
- C[i + j*lda + 6] = tempC6;\r
- C[i + j*lda + 7] = tempC7;\r
- }\r
- }\r
- }\r
- } else {\r
- for (m = 2; m > 0; m--){\r
- for (j = lda-1; j >= lda/2; j--){\r
- for (i = lda-1; i >= 0; i-=8){\r
- tempC0 = C[i + j*lda];\r
- tempC1 = C[i + j*lda - 1];\r
- tempC2 = C[i + j*lda - 2];\r
- tempC3 = C[i + j*lda - 3];\r
- tempC4 = C[i + j*lda - 4];\r
- tempC5 = C[i + j*lda - 5];\r
- tempC6 = C[i + j*lda - 6];\r
- tempC7 = C[i + j*lda - 7];\r
- for (k = m*lda/2-1; k >= (m-1)*lda/2; k-=2){\r
- tempA0 = A[j*lda+k];\r
- tempA1 = A[j*lda+k-1];\r
- tempC0 += tempA0*B[k*lda+i]+tempA1*B[(k-1)*lda+i];\r
- tempC1 += tempA0*B[k*lda+i-1]+tempA1*B[(k-1)*lda+i-1];\r
- tempC2 += tempA0*B[k*lda+i-2]+tempA1*B[(k-1)*lda+i-2];\r
- tempC3 += tempA0*B[k*lda+i-3]+tempA1*B[(k-1)*lda+i-3];\r
- tempC4 += tempA0*B[k*lda+i-4]+tempA1*B[(k-1)*lda+i-4];\r
- tempC5 += tempA0*B[k*lda+i-5]+tempA1*B[(k-1)*lda+i-5];\r
- tempC6 += tempA0*B[k*lda+i-6]+tempA1*B[(k-1)*lda+i-6];\r
- tempC7 += tempA0*B[k*lda+i-7]+tempA1*B[(k-1)*lda+i-7];\r
- }\r
- C[i + j*lda] = tempC0;\r
- C[i + j*lda - 1] = tempC1;\r
- C[i + j*lda - 2] = tempC2;\r
- C[i + j*lda - 3] = tempC3;\r
- C[i + j*lda - 4] = tempC4;\r
- C[i + j*lda - 5] = tempC5;\r
- C[i + j*lda - 6] = tempC6;\r
- C[i + j*lda - 7] = tempC7;\r
- }\r
- }\r
- }\r
- }\r
-}\r
-\r
-//--------------------------------------------------------------------------\r
-// Main\r
-//\r
-// all threads start executing thread_entry(). Use their "coreid" to\r
-// differentiate between threads (each thread is running on a separate core).\r
-\r
-void thread_entry(int cid, int nc)\r
-{\r
- coreid = cid;\r
- ncores = nc;\r
- \r
- // static allocates data in the binary, which is visible to both threads\r
- static data_t results_data[ARRAY_SIZE];\r
- \r
- \r
-// // Execute the provided, naive matmul\r
-// barrier(nc);\r
-// stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));\r
-// \r
-// \r
-// // verify\r
-// verifyMT(ARRAY_SIZE, results_data, verify_data);\r
-// \r
-// // clear results from the first trial\r
-// size_t i;\r
-// if (coreid == 0)\r
-// for (i=0; i < ARRAY_SIZE; i++)\r
-// results_data[i] = 0;\r
-// barrier(nc);\r
- \r
- \r
- // Execute your faster matmul\r
- barrier(nc);\r
- stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));\r
- \r
-#ifdef DEBUG\r
- printArrayMT("results:", ARRAY_SIZE, results_data);\r
- printArrayMT("verify :", ARRAY_SIZE, verify_data);\r
-#endif\r
- \r
- // verify\r
- verifyMT(ARRAY_SIZE, results_data, verify_data);\r
- barrier(nc);\r
- \r
- exit(0);\r
-}\r
-\r
projects / riscv-tests.git / blobdiff