+++ /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;
-}
-
-data_t mult(data_t x, data_t y)
-{ data_t result = 0;
- size_t i;
- for (i=0; i < x; i++) {
- result += y;
- }
- return result;
-}
-//--------------------------------------------------------------------------
-// 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, j, k, l;
- int row,row2, row3, row4, column, column2, column3, column4, column5, column6, column7, column8;
- data_t element, element2, element3, element4, element5, element6, element7, element8;
- data_t element9, element10, element11, element12, element13, element14, element15, element16;
- data_t elementB1,elementB2,elementB3,elementB4;
- data_t temp_mat[128]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
- //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 (l=coreid*32/ncores; l<32*(1+coreid)/ncores; l+=4){
- row=l*lda;
- row2=(l+1)*lda;
- row3=(l+2)*lda;
- row4=(l+3)*lda;
- for (i=0; i<lda; i+=4){
- element = A[row+i];
- element2 = A[row+i+1];
- element3 = A[row+i+2];
- element4 = A[row+i+3];
-
- element5 = A[row2+i];
- element6 = A[row2+i+1];
- element7 = A[row2+i+2];
- element8 = A[row2+i+3];
-
- element9 = A[row3+i];
- element10 = A[row3+i+1];
- element11 = A[row3+i+2];
- element12 = A[row3+i+3];
-
- element13 = A[row4+i];
- element14 = A[row4+i+1];
- element15 = A[row4+i+2];
- element16 = A[row4+i+3];
-
- column=i*lda;
- column2=(i+1)*lda;
- column3=(i+2)*lda;
- column4=(i+3)*lda;
-
-
- for (j=0; j<lda; j+=4){
-
- temp_mat[j]+=element*B[column+j]+element2*B[column2+j]+element3*B[column3+j]+element4*B[column4+j];
- temp_mat[j+1]+=element*B[column+j+1]+element2*B[column2+j+1]+element3*B[column3+j+1]+element4*B[column4+j+1];
- temp_mat[j+2]+=element*B[column+j+2]+element2*B[column2+j+2]+element3*B[column3+j+2]+element4*B[column4+j+2];
- temp_mat[j+3]+=element*B[column+j+3]+element2*B[column2+j+3]+element3*B[column3+j+3]+element4*B[column4+j+3];
-
- temp_mat[j+lda]+=element5*B[column+j]+element6*B[column2+j]+element7*B[column3+j]+element8*B[column4+j];
- temp_mat[j+1+lda]+=element5*B[column+j+1]+element6*B[column2+j+1]+element7*B[column3+j+1]+element8*B[column4+j+1];
- temp_mat[j+2+lda]+=element5*B[column+j+2]+element6*B[column2+j+2]+element7*B[column3+j+2]+element8*B[column4+j+2];
- temp_mat[j+3+lda]+=element5*B[column+j+3]+element6*B[column2+j+3]+element7*B[column3+j+3]+element8*B[column4+j+3];
-
- temp_mat[j+2*lda]+=element9*B[column+j]+element10*B[column2+j]+element11*B[column3+j]+element12*B[column4+j];
- temp_mat[j+1+2*lda]+=element9*B[column+j+1]+element10*B[column2+j+1]+element11*B[column3+j+1]+element12*B[column4+j+1];
- temp_mat[j+2+2*lda]+=element9*B[column+j+2]+element10*B[column2+j+2]+element11*B[column3+j+2]+element12*B[column4+j+2];
- temp_mat[j+3+2*lda]+=element9*B[column+j+3]+element10*B[column2+j+3]+element11*B[column3+j+3]+element12*B[column4+j+3];
-
- temp_mat[j+3*lda]+=element13*B[column+j]+element14*B[column2+j]+element15*B[column3+j]+element16*B[column4+j];
- temp_mat[j+1+3*lda]+=element13*B[column+j+1]+element14*B[column2+j+1]+element15*B[column3+j+1]+element16*B[column4+j+1];
- temp_mat[j+2+3*lda]+=element13*B[column+j+2]+element14*B[column2+j+2]+element15*B[column3+j+2]+element16*B[column4+j+2];
- temp_mat[j+3+3*lda]+=element13*B[column+j+3]+element14*B[column2+j+3]+element15*B[column3+j+3]+element16*B[column4+j+3];
-
-
- }
-
- }
-
- for(k=0; k<32; k++){
- C[row+k]=temp_mat[k];
- temp_mat[k]=0;
- C[row2+k]=temp_mat[k+lda];
- temp_mat[k+lda]=0;
- C[row3+k]=temp_mat[k+2*lda];
- temp_mat[k+2*lda]=0;
- C[row4+k]=temp_mat[k+3*lda];
- temp_mat[k+3*lda]=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