+++ /dev/null
-//**************************************************************************
-// Multi-threaded Matrix Multiply benchmark
-//--------------------------------------------------------------------------
-// TA : Christopher Celio
-// Student:
-//
-//
-// This benchmark multiplies two 2-D arrays together and writes the results to
-// a third vector. The input data (and reference data) should be generated
-// using the matmul_gendata.pl perl script and dumped to a file named
-// dataset.h.
-
-
-// print out arrays, etc.
-//#define DEBUG
-
-//--------------------------------------------------------------------------
-// Includes
-
-#include <string.h>
-#include <stdlib.h>
-#include <stdio.h>
-
-
-//--------------------------------------------------------------------------
-// Input/Reference Data
-
-typedef float data_t;
-#include "dataset.h"
-
-
-//--------------------------------------------------------------------------
-// Basic Utilities and Multi-thread Support
-
-__thread unsigned long coreid;
-unsigned long ncores;
-
-#include "util.h"
-
-#define stringify_1(s) #s
-#define stringify(s) stringify_1(s)
-#define stats(code) do { \
-unsigned long _c = -rdcycle(), _i = -rdinstret(); \
-code; \
-_c += rdcycle(), _i += rdinstret(); \
-if (coreid == 0) \
-printf("%s: %ld cycles, %ld.%ld cycles/iter, %ld.%ld CPI\n", \
-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); \
-} while(0)
-
-
-//--------------------------------------------------------------------------
-// Helper functions
-
-void printArrayMT( char name[], int n, data_t arr[] )
-{
- int i;
- if (coreid != 0)
- return;
-
- printf( " %10s :", name );
- for ( i = 0; i < n; i++ )
- printf( " %3ld ", (long) arr[i] );
- printf( "\n" );
-}
-
-void __attribute__((noinline)) verifyMT(size_t n, const data_t* test, const data_t* correct)
-{
- if (coreid != 0)
- return;
-
- size_t i;
- for (i = 0; i < n; i++)
- {
- if (test[i] != correct[i])
- {
- printf("FAILED test[%d]= %3ld, correct[%d]= %3ld\n",
- i, (long)test[i], i, (long)correct[i]);
- exit(-1);
- }
- }
-
- return;
-}
-
-//--------------------------------------------------------------------------
-// matmul function
-
-// single-thread, naive version
-void __attribute__((noinline)) matmul_naive(const int lda, const data_t A[], const data_t B[], data_t C[] )
-{
- int i, j, k;
-
- if (coreid > 0)
- return;
-
- for ( i = 0; i < lda; i++ )
- {
- for ( j = 0; j < lda; j++ )
- {
- for ( k = 0; k < lda; k++ )
- {
- C[i + j*lda] += A[j*lda + k] * B[k*lda + i];
- }
- }
- }
-}
-
-
-
-void __attribute__((noinline)) matmul(const int lda, const data_t A[], const data_t B[], data_t C[] )
-{
-
- // ***************************** //
- // **** ADD YOUR CODE HERE ***** //
- // ***************************** //
- //
- // feel free to make a separate function for MI and MSI versions.
-
- int i, j, k;
-
- /*547287
- for ( i = coreid*lda/ncores; i < (coreid+1)*lda/ncores; i++ )
- {
- for ( j = 0; j < lda; j++ )
- {
- int aIndex = j*lda;
- int cIndex = i + aIndex;
- C[cIndex] += A[aIndex] * B[i];
- C[cIndex] += A[aIndex + 1] * B[1*lda + i];
- C[cIndex] += A[aIndex + 2] * B[2*lda + i];
- C[cIndex] += A[aIndex + 3] * B[3*lda + i];
- C[cIndex] += A[aIndex + 4] * B[4*lda + i];
- C[cIndex] += A[aIndex + 5] * B[5*lda + i];
- C[cIndex] += A[aIndex + 6] * B[6*lda + i];
- C[cIndex] += A[aIndex + 7] * B[7*lda + i];
- C[cIndex] += A[aIndex + 8] * B[8*lda + i];
- C[cIndex] += A[aIndex + 9] * B[9*lda + i];
- C[cIndex] += A[aIndex + 10] * B[10*lda + i];
- C[cIndex] += A[aIndex + 11] * B[11*lda + i];
- C[cIndex] += A[aIndex + 12] * B[12*lda + i];
- C[cIndex] += A[aIndex + 13] * B[13*lda + i];
- C[cIndex] += A[aIndex + 14] * B[14*lda + i];
- C[cIndex] += A[aIndex + 15] * B[15*lda + i];
- C[cIndex] += A[aIndex + 16] * B[16*lda + i];
- C[cIndex] += A[aIndex + 17] * B[17*lda + i];
- C[cIndex] += A[aIndex + 18] * B[18*lda + i];
- C[cIndex] += A[aIndex + 19] * B[19*lda + i];
- C[cIndex] += A[aIndex + 20] * B[20*lda + i];
- C[cIndex] += A[aIndex + 21] * B[21*lda + i];
- C[cIndex] += A[aIndex + 22] * B[22*lda + i];
- C[cIndex] += A[aIndex + 23] * B[23*lda + i];
- C[cIndex] += A[aIndex + 24] * B[24*lda + i];
- C[cIndex] += A[aIndex + 25] * B[25*lda + i];
- C[cIndex] += A[aIndex + 26] * B[26*lda + i];
- C[cIndex] += A[aIndex + 27] * B[27*lda + i];
- C[cIndex] += A[aIndex + 28] * B[28*lda + i];
- C[cIndex] += A[aIndex + 29] * B[29*lda + i];
- C[cIndex] += A[aIndex + 30] * B[30*lda + i];
- C[cIndex] += A[aIndex + 31] * B[31*lda + i];
- }
- }
- */
-
- //492827
- /* for ( i = coreid*lda/ncores; i < (coreid+1)*lda/ncores; i++ )
- {
- for ( j = 0; j < lda; j++ )
- {
-
- int aIndex = j*lda;
- int cIndex = i + aIndex;
- for ( k = 0; k < lda; k++)
- {
- C[cIndex] += A[aIndex + k] * B[k*lda + i];
- /* C[cIndex] += A[aIndex + k+1] * B[(k+1)*lda + i];
- C[cIndex] += A[aIndex + k+2] * B[(k+2)*lda + i];
- C[cIndex] += A[aIndex + k+3] * B[(k+3)*lda + i];
- C[cIndex] += A[aIndex + k+4] * B[(k+4)*lda + i];
- C[cIndex] += A[aIndex + k+5] * B[(k+5)*lda + i];
- C[cIndex] += A[aIndex + k+6] * B[(k+6)*lda + i];
- C[cIndex] += A[aIndex + k+7] * B[(k+7)*lda + i];
- C[cIndex] += A[aIndex + k+8] * B[(k+8)*lda + i];
- C[cIndex] += A[aIndex + k+9] * B[(k+9)*lda + i];
- C[cIndex] += A[aIndex + k+10] * B[(k+10)*lda + i];
- C[cIndex] += A[aIndex + k+11] * B[(k+11)*lda + i];
- C[cIndex] += A[aIndex + k+12] * B[(k+12)*lda + i];
- C[cIndex] += A[aIndex + k+13] * B[(k+13)*lda + i];
- C[cIndex] += A[aIndex + k+14] * B[(k+14)*lda + i];
- C[cIndex] += A[aIndex + k+15] * B[(k+15)*lda + i];*/
- /* }
- }
- }*/
- /*
- //326378
- data_t bTrans[1024];
-
- for (int counti = 0; counti < 32; counti++) {
- for (int countj = 0; countj < 32; countj++) {
- *(bTrans + counti + countj*lda) = *(B + countj + counti*lda);
- }
- }
-
-
- int BLOCKSIZE = 8;
- for ( i = 0; i < lda; i+=BLOCKSIZE )
- {
- for ( int iTemp = i; iTemp < i + BLOCKSIZE; iTemp++ ) {
- int iFlag = iTemp*lda;
- for ( j = coreid*lda/ncores; j < (coreid+1)*lda/ncores; j++ ) {
- int jFlag = j*lda;
- int cLoc = jFlag+iTemp;
- for ( k = 0; k < lda; k+=8) {
- *(C+cLoc) += *(A+jFlag+k) * *(bTrans+iFlag+k);
- *(C+cLoc) += *(A+jFlag+k+1) * *(bTrans+iFlag+k+1);
- *(C+cLoc) += *(A+jFlag+k+2) * *(bTrans+iFlag+k+2);
- *(C+cLoc) += *(A+jFlag+k+3) * *(bTrans+iFlag+k+3);
- *(C+cLoc) += *(A+jFlag+k+4) * *(bTrans+iFlag+k+4);
- *(C+cLoc) += *(A+jFlag+k+5) * *(bTrans+iFlag+k+5);
- *(C+cLoc) += *(A+jFlag+k+6) * *(bTrans+iFlag+k+6);
- *(C+cLoc) += *(A+jFlag+k+7) * *(bTrans+iFlag+k+7);
- }
- }
- }
- }*/
- data_t bTrans[1024];
-
- for (int counti = 0; counti < 32; counti++) {
- for (int countj = 0; countj < 32; countj++) {
- *(bTrans + counti + countj*lda) = *(B + countj + counti*lda);
- }
- }
-
-
- int BLOCKSIZE = 8;
- for ( j = 0; j < lda; j++ )
- {
- //for ( int jTemp = j; jTemp < j + BLOCKSIZE; jTemp++ ) {
- int jFlag = j*lda;
- for ( i = coreid*lda/ncores; i < (coreid+1)*lda/ncores; i+=BLOCKSIZE ) {
- for ( int iTemp = i; iTemp < i + BLOCKSIZE; iTemp++ ) {
-
- int iFlag = iTemp*lda;
- int cLoc = jFlag+iTemp;
- for ( k = 0; k < lda; k+=16) {
- *(C+cLoc) += *(A+jFlag+k) * *(bTrans+iFlag+k);
- *(C+cLoc) += *(A+jFlag+k+1) * *(bTrans+iFlag+k+1);
- *(C+cLoc) += *(A+jFlag+k+2) * *(bTrans+iFlag+k+2);
- *(C+cLoc) += *(A+jFlag+k+3) * *(bTrans+iFlag+k+3);
- *(C+cLoc) += *(A+jFlag+k+4) * *(bTrans+iFlag+k+4);
- *(C+cLoc) += *(A+jFlag+k+5) * *(bTrans+iFlag+k+5);
- *(C+cLoc) += *(A+jFlag+k+6) * *(bTrans+iFlag+k+6);
- *(C+cLoc) += *(A+jFlag+k+7) * *(bTrans+iFlag+k+7);
- *(C+cLoc) += *(A+jFlag+k+8) * *(bTrans+iFlag+k+8);
- *(C+cLoc) += *(A+jFlag+k+9) * *(bTrans+iFlag+k+9);
- *(C+cLoc) += *(A+jFlag+k+10) * *(bTrans+iFlag+k+10);
- *(C+cLoc) += *(A+jFlag+k+11) * *(bTrans+iFlag+k+11);
- *(C+cLoc) += *(A+jFlag+k+12) * *(bTrans+iFlag+k+12);
- *(C+cLoc) += *(A+jFlag+k+13) * *(bTrans+iFlag+k+13);
- *(C+cLoc) += *(A+jFlag+k+14) * *(bTrans+iFlag+k+14);
- *(C+cLoc) += *(A+jFlag+k+15) * *(bTrans+iFlag+k+15);
- }
- }
- }
- //}
- }
-
-
-}
-
-//--------------------------------------------------------------------------
-// Main
-//
-// all threads start executing thread_entry(). Use their "coreid" to
-// differentiate between threads (each thread is running on a separate core).
-
-void thread_entry(int cid, int nc)
-{
- coreid = cid;
- ncores = nc;
-
- // static allocates data in the binary, which is visible to both threads
- static data_t results_data[ARRAY_SIZE];
-
-
-// // Execute the provided, naive matmul
-// barrier(nc);
-// stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));
-//
-//
-// // verify
-// verifyMT(ARRAY_SIZE, results_data, verify_data);
-//
-// // clear results from the first trial
-// size_t i;
-// if (coreid == 0)
-// for (i=0; i < ARRAY_SIZE; i++)
-// results_data[i] = 0;
-// barrier(nc);
-
-
- // Execute your faster matmul
- barrier(nc);
- stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));
-
-#ifdef DEBUG
- printArrayMT("results:", ARRAY_SIZE, results_data);
- printArrayMT("verify :", ARRAY_SIZE, verify_data);
-#endif
-
- // verify
- verifyMT(ARRAY_SIZE, results_data, verify_data);
- barrier(nc);
-
- exit(0);
-}
-
projects / riscv-tests.git / blobdiff