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Diffstat (limited to 'mt/af_matmul/keeptrying3.c')
-rw-r--r-- | mt/af_matmul/keeptrying3.c | 253 |
1 files changed, 253 insertions, 0 deletions
diff --git a/mt/af_matmul/keeptrying3.c b/mt/af_matmul/keeptrying3.c new file mode 100644 index 0000000..9c28faa --- /dev/null +++ b/mt/af_matmul/keeptrying3.c @@ -0,0 +1,253 @@ +//************************************************************************** +// 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; +} + +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(); + 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); +} |