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//**************************************************************************
// 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 printArray( 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)) verify(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();
stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier());
// verify
verify(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();
// Execute your faster matmul
barrier();
stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier());
#ifdef DEBUG
printArray("results:", ARRAY_SIZE, results_data);
printArray("verify :", ARRAY_SIZE, verify_data);
#endif
// verify
verify(ARRAY_SIZE, results_data, verify_data);
barrier();
exit(0);
}
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