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//**************************************************************************
// Multi-threaded Matrix Multiply benchmark
//--------------------------------------------------------------------------
// TA : Christopher Celio
// Student: Ryan Ricks
//
//
// 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[] )
{
int i,j,k,a,b,a1,a2,a3,c;
for (j=coreid; j<lda; j+=8){
a=j*lda;
a1=(j+2)*lda;
a2=(j+4)*lda;
a3=(j+6)*lda;
for (k=0;k<lda; k++)
{
b = k*lda;
for (i=0;i<lda;i++){
c = B[b+i];
C[i+a]+=A[a+k]*c;
C[i+a1]+=A[a1+k]*c;
C[i+a2]+=A[a2+k]*c;
C[i+a3]+=A[a3+k]*c;
}
}
}
// ***************************** //
// **** 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);
}
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