+++ /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[] )
-{
- size_t i;
- size_t j;
- size_t k;
- size_t max_dim = 32*32;
- data_t temp_mat[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
- data_t temp_mat2[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
- //for (i=coreid*max_dim/ncores; i<(max_dim/ncores+coreid*max_dim/ncores); i+=8){
- for (i=coreid*max_dim/ncores; i<(max_dim/ncores+coreid*max_dim/ncores)/2; i+=8){
- data_t element=A[i];
- data_t element2 = A[i+1];
- data_t element3 = A[i+2];
- data_t element4 = A[i+3];
- data_t element5 = A[i+4];
- data_t element6 = A[i+5];
- data_t element7 = A[i+6];
- data_t element8 = A[i+7];
- data_t elementA2 = A[i+32*8];
- data_t elementA21 = A[i+32*8+1];
- data_t elementA22 = A[i+32*8+2];
- data_t elementA23 = A[i+32*8+3];
- data_t elementA24 = A[i+32*8+4];
- data_t elementA25 = A[i+32*8+5];
- data_t elementA26 = A[i+32*8+6];
- data_t elementA27 = A[i+32*8+7];
- int row= (int)(i/32)*32;
- int row2 = row+8*32;
- int column = i%32*32;
- int column2 = (i+1)%32*32;
- int column3 = (i+2)%32*32;
- int column4 = (i+3)%32*32;
- int column5 = (i+4)%32*32;
- int column6 = (i+5)%32*32;
- int column7 = (i+6)%32*32;
- int column8 = (i+7)%32*32;
-
- for (j=0; j<32; j++){
- temp_mat[j]+=element*B[column+j]+element2*B[column2+j]+element3*B[column3+j]+element4*B[column4+j]+element5*B[column5+j]+element6*B[column6+j]+element7*B[column7+j]+element8*B[column8+j];
-
- temp_mat2[j]+=elementA2*B[column+j]+elementA21*B[column2+j]+elementA22*B[column3+j]+elementA23*B[column4+j]+elementA24*B[column5+j]+elementA25*B[column6+j]+elementA26*B[column7+j]+elementA27*B[column8+j];
- }
- if (i%32==24){
- for(k=0; k<32; k++){
- C[row+k]=temp_mat[k];
- C[row2+k]=temp_mat2[k];
- temp_mat[k]=0;
- temp_mat2[k]=0;
-
- }
- }
- }
-
-
-
-
-
- // ***************************** //
- // **** ADD YOUR CODE HERE ***** //
- // ***************************** //
- //
- // feel free to make a separate function for MI and MSI versions.
-
-}
-
-//--------------------------------------------------------------------------
-// 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