X-Git-Url: https://git.libre-soc.org/?a=blobdiff_plain;f=mt%2Faf_matmul%2Ffailedattempt.c;fp=mt%2Faf_matmul%2Ffailedattempt.c;h=acd4a12c8eac2de6f9a84486bd8282e5edd30e33;hb=60f056880ec6929c5f23af4d66aea0f0cb7b0245;hp=0000000000000000000000000000000000000000;hpb=4412b96c81ca09dcce6305579dd86d4bf3b808da;p=riscv-tests.git diff --git a/mt/af_matmul/failedattempt.c b/mt/af_matmul/failedattempt.c new file mode 100644 index 0000000..acd4a12 --- /dev/null +++ b/mt/af_matmul/failedattempt.c @@ -0,0 +1,298 @@ +//************************************************************************** +// 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 +#include +#include + + +//-------------------------------------------------------------------------- +// 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); +}