--- /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 printArray( 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)) verify(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
+ 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
+void __attribute__((noinline)) matmul(const int lda, const data_t A[], const data_t B[], data_t C[] )\r
+{\r
+ static __thread int i, j, k;\r
+ static __thread data_t tempA0, tempA1, tempA2, tempA3, tempA4, tempA5, tempA6, tempA7;\r
+ static __thread data_t tempC0, tempC1, tempC2, tempC3, tempC4, tempC5, tempC6, tempC7, tempC8, tempC9, tempC10, tempC11, tempC12, tempC13, tempC14, tempC15;\r
+\r
+ static __thread int start, end, jStride, jToRow, jToCol;\r
+ static data_t A1[1024], B1[1024];;\r
+ \r
+ start = coreid << 9;\r
+ end = (coreid+1) << 9;\r
+ jStride = 8;\r
+\r
+ if (coreid == 0) { \r
+ for (j=start; j < end; j+=jStride) {\r
+ jToRow = (j>>5)<<5;\r
+ jToCol = j%32;\r
+ tempC0 = 0;\r
+ tempC1 = 0;\r
+ tempC2 = 0;\r
+ tempC3 = 0;\r
+ tempC4 = 0;\r
+ tempC5 = 0;\r
+ tempC6 = 0;\r
+ tempC7 = 0;\r
+ for ( i=0; i < lda; i+=2 ) {\r
+ tempA0 = A[i + jToRow];\r
+ tempA1 = A[i+1 + jToRow];\r
+ tempC0 += tempA0 * B[(jToCol ) + (i<<5)];\r
+ tempC1 += tempA0 * B[(jToCol+1 ) + (i<<5)];\r
+ tempC2 += tempA0 * B[(jToCol+2 ) + (i<<5)];\r
+ tempC3 += tempA0 * B[(jToCol+3 ) + (i<<5)];\r
+ tempC4 += tempA0 * B[(jToCol+4 ) + (i<<5)];\r
+ tempC5 += tempA0 * B[(jToCol+5 ) + (i<<5)];\r
+ tempC6 += tempA0 * B[(jToCol+6 ) + (i<<5)];\r
+ tempC7 += tempA0 * B[(jToCol+7 ) + (i<<5)];\r
+ tempC0 += tempA1 * B[(jToCol ) + ((i+1)<<5)];\r
+ tempC1 += tempA1 * B[(jToCol+1 ) + ((i+1)<<5)];\r
+ tempC2 += tempA1 * B[(jToCol+2 ) + ((i+1)<<5)];\r
+ tempC3 += tempA1 * B[(jToCol+3 ) + ((i+1)<<5)];\r
+ tempC4 += tempA1 * B[(jToCol+4 ) + ((i+1)<<5)];\r
+ tempC5 += tempA1 * B[(jToCol+5 ) + ((i+1)<<5)];\r
+ tempC6 += tempA1 * B[(jToCol+6 ) + ((i+1)<<5)];\r
+ tempC7 += tempA1 * B[(jToCol+7 ) + ((i+1)<<5)];\r
+ }\r
+ C[j] =tempC0;\r
+ C[j + 1 ]=tempC1;\r
+ C[j + 2 ]=tempC2;\r
+ C[j + 3 ]=tempC3;\r
+ C[j + 4 ]=tempC4;\r
+ C[j + 5 ]=tempC5;\r
+ C[j + 6 ]=tempC6;\r
+ C[j + 7 ]=tempC7;\r
+ }\r
+ }\r
+ else { \r
+ for (i = 0; i < 1024; i++) {\r
+ A1[i] = A[i];\r
+ B1[i] = B[i];\r
+ }\r
+ for (j=start; j < end; j+=jStride) {\r
+ jToRow = (j>>5)<<5;\r
+ jToCol = j%32;\r
+ tempC0 = 0;\r
+ tempC1 = 0;\r
+ tempC2 = 0;\r
+ tempC3 = 0;\r
+ tempC4 = 0;\r
+ tempC5 = 0;\r
+ tempC6 = 0;\r
+ tempC7 = 0;\r
+ for ( i=0; i < lda; i+=2 ) {\r
+ tempA0 = A1[i + jToRow];\r
+ tempA1 = A1[i+1 + jToRow];\r
+ tempC0 += tempA0 * B1[(jToCol ) + (i<<5)];\r
+ tempC1 += tempA0 * B1[(jToCol+1 ) + (i<<5)];\r
+ tempC2 += tempA0 * B1[(jToCol+2 ) + (i<<5)];\r
+ tempC3 += tempA0 * B1[(jToCol+3 ) + (i<<5)];\r
+ tempC4 += tempA0 * B1[(jToCol+4 ) + (i<<5)];\r
+ tempC5 += tempA0 * B1[(jToCol+5 ) + (i<<5)];\r
+ tempC6 += tempA0 * B1[(jToCol+6 ) + (i<<5)];\r
+ tempC7 += tempA0 * B1[(jToCol+7 ) + (i<<5)];\r
+ tempC0 += tempA1 * B1[(jToCol ) + ((i+1)<<5)];\r
+ tempC1 += tempA1 * B1[(jToCol+1 ) + ((i+1)<<5)];\r
+ tempC2 += tempA1 * B1[(jToCol+2 ) + ((i+1)<<5)];\r
+ tempC3 += tempA1 * B1[(jToCol+3 ) + ((i+1)<<5)];\r
+ tempC4 += tempA1 * B1[(jToCol+4 ) + ((i+1)<<5)];\r
+ tempC5 += tempA1 * B1[(jToCol+5 ) + ((i+1)<<5)];\r
+ tempC6 += tempA1 * B1[(jToCol+6 ) + ((i+1)<<5)];\r
+ tempC7 += tempA1 * B1[(jToCol+7 ) + ((i+1)<<5)];\r
+ }\r
+ C[j] =tempC0;\r
+ C[j + 1 ]=tempC1;\r
+ C[j + 2 ]=tempC2;\r
+ C[j + 3 ]=tempC3;\r
+ C[j + 4 ]=tempC4;\r
+ C[j + 5 ]=tempC5;\r
+ C[j + 6 ]=tempC6;\r
+ C[j + 7 ]=tempC7;\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();\r
+ //stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier());\r
+ \r
+ //\r
+ //// verify\r
+ //verify(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();\r
+\r
+ \r
+ // Execute your faster matmul\r
+ barrier();\r
+ stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier());\r
+ \r
+#ifdef DEBUG\r
+ printArray("results:", ARRAY_SIZE, results_data);\r
+ printArray("verify :", ARRAY_SIZE, verify_data);\r
+#endif\r
+ \r
+ // verify\r
+ verify(ARRAY_SIZE, results_data, verify_data);\r
+ barrier();\r
+\r
+ exit(0);\r
+}\r
+\r
+\r
projects / riscv-tests.git / blobdiff