--- /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 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 i2;
+ size_t j;
+ size_t j2;
+ size_t k;
+ size_t k2;
+ size_t max_dim = lda*lda;
+ size_t block_size = lda/2;
+ data_t temp_mat[16] = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
+ if (coreid == 0) {
+ //making a 16x16 block
+ //First block: Top 16x16 block left of A and top left of B = top left of C
+ //Second block: top right 16x16 right block of A and top right of B = top right of C
+ for (j2= 0; j2 < 2; j2++) {
+ for (i2 = 0; i2 < 2; i2++) {
+ //for (j2= 0; j2 < 2; j2++) {
+ //K represents which row of A and C
+ for (k = 0; k < block_size; k++) {
+ int rowIndex = k*32;
+ for (i = i2*block_size; i < i2*block_size+block_size; i++) {
+ int elementA = A[rowIndex+i];
+ int columnIndex = i%32*32;
+ for (j = 0; j < block_size; j++) {
+ temp_mat[j] += elementA*B[columnIndex+j+j2*block_size];
+ }
+ }
+ //Put temp_mat into actual result Matrix
+ for (k2 = 0; k2 < block_size; k2++) {
+ C[rowIndex+k2+j2*block_size] += temp_mat[k2];
+ temp_mat[k2] = 0;
+ }
+ }
+ }
+ }
+ } else {
+ for (j2= 0; j2 < 2; j2++) {
+ for (i2 = 0; i2 < 2; i2++) {
+ //for (j2= 0; j2 < 2; j2++) {
+ //K represents which row of A and C
+ for (k = block_size; k < lda; k++) {
+ int rowIndex = k*32;
+ for (i = i2*block_size; i < i2*block_size+block_size; i++) {
+ int elementA = A[rowIndex+i];
+ int columnIndex = i%32*32;
+ for (j = 0; j < block_size; j++) {
+ temp_mat[j] += elementA*B[columnIndex+j+j2*block_size];
+ }
+ }
+ //Put temp_mat into actual result Matrix
+ for (k2 = 0; k2 < block_size; k2++) {
+ C[rowIndex+k2+j2*block_size] += temp_mat[k2];
+ temp_mat[k2] = 0;
+ }
+ }
+ }
+ }
+ }
+
+
+ //size_t half_lda = lda/2;
+ // k = which pair of row we're on
+
+
+
+
+
+
+/*
+ for (k = coreid*lda/ncores; k < (lda/ncores + coreid*lda/ncores); k += 2) {
+ //printf("%d", k);
+ for (i = 0; i < lda ; i++) {
+ int elementA = A[32*k+i];
+ int elementA2 = A[i + 32*(k+1)];
+ int column = i%32*32;
+ for (j = 0; j < lda; j++) {
+ C[32*k + j] += elementA*B[column+j];
+ C[32*(k+1) + j] += elementA2*B[column+j];
+ }
+ }
+
+ }
+*/
+
+/*
+ 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];
+ int row= (int)(i/32)*32;
+ int row2 = (i+1)/32*32;
+ int row3 = (i+2)/32*32;
+ int row4 = (i+3)/32*32;
+ int row5 = (i+4)/32*32;
+ int row6 = (i+5)/32*32;
+ int row7 = (i+6)/32*32;
+ int row8 = (i+7)/32*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 < lda; j++) {
+ sum = B[
+ C[row+j]+=element*B[column+j];
+ C[row2+j]+=element2*B[column2+j];
+ C[row3+j]+=element3*B[column3+j];
+ C[row4+j]+=element4*B[column4+j];
+ C[row5+j]+=element5*B[column5+j];
+ C[row6+j]+=element6*B[column6+j];
+ C[row7+j]+=element7*B[column7+j];
+ C[row8+j]+=element8*B[column8+j];
+ C[row+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];
+ }
+ }
+ */
+
+
+
+
+
+
+ // ***************************** //
+ // **** 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);
+}