X-Git-Url: https://git.libre-soc.org/?a=blobdiff_plain;ds=sidebyside;f=mt%2Fag_matmul%2Fmatmul_mi.c;fp=mt%2Fag_matmul%2Fmatmul_mi.c;h=9782d781e2ce859f4ce97527a7b64a1be21c37dd;hb=60f056880ec6929c5f23af4d66aea0f0cb7b0245;hp=0000000000000000000000000000000000000000;hpb=4412b96c81ca09dcce6305579dd86d4bf3b808da;p=riscv-tests.git diff --git a/mt/ag_matmul/matmul_mi.c b/mt/ag_matmul/matmul_mi.c new file mode 100755 index 0000000..9782d78 --- /dev/null +++ b/mt/ag_matmul/matmul_mi.c @@ -0,0 +1,230 @@ +//************************************************************************** +// 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[] ) +{ + int i, j, k; + + for ( i = 0; i < lda; i+=2 ) + { + for (k = 0; k < lda; k+=4) + { + int d0 = B[k*lda + i]; + int c0 = B[k*lda + i + 1]; + int d1 = B[(k+1)*lda + i]; + int c1 = B[(k+1)*lda + i + 1]; + int d2 = B[(k+2)*lda + i]; + int c2 = B[(k+2)*lda + i + 1]; + int d3 = B[(k+3)*lda + i]; + int c3 = B[(k+3)*lda + i + 1]; + + for ( j = coreid*(lda/ncores); j < (coreid+1)*(lda/ncores); j+=4) + { + + int sum = A[j*lda + k] * d0; + sum += A[j*lda + k + 1] * d1; + sum += A[j*lda + k + 2] * d2; + sum += A[j*lda + k + 3] * d3; + C[j*lda +i] += sum; + + sum = A[j*lda + k] * c0; + sum += A[j*lda + k + 1] * c1; + sum += A[j*lda + k + 2] * c2; + sum += A[j*lda + k + 3] * c3; + C[j*lda + i + 1] += sum; + + sum = A[(j+1)*lda + k] * d0; + sum += A[(j+1)*lda + k + 1] * d1; + sum += A[(j+1)*lda + k + 2] * d2; + sum += A[(j+1)*lda + k + 3] * d3; + C[(j+1)*lda +i] += sum; + + sum = A[(j+1)*lda + k] * c0; + sum += A[(j+1)*lda + k + 1] * c1; + sum += A[(j+1)*lda + k + 2] * c2; + sum += A[(j+1)*lda + k + 3] * c3; + C[(j+1)*lda + i + 1] += sum; + + sum = A[(j+2)*lda + k] * d0; + sum += A[(j+2)*lda + k + 1] * d1; + sum += A[(j+2)*lda + k + 2] * d2; + sum += A[(j+2)*lda + k + 3] * d3; + C[(j+2)*lda +i] += sum; + + sum = A[(j+2)*lda + k] * c0; + sum += A[(j+2)*lda + k + 1] * c1; + sum += A[(j+2)*lda + k + 2] * c2; + sum += A[(j+2)*lda + k + 3] * c3; + C[(j+2)*lda + i + 1] += sum; + + sum = A[(j+3)*lda + k] * d0; + sum += A[(j+3)*lda + k + 1] * d1; + sum += A[(j+3)*lda + k + 2] * d2; + sum += A[(j+3)*lda + k + 3] * d3; + C[(j+3)*lda +i] += sum; + + sum = A[(j+3)*lda + k] * c0; + sum += A[(j+3)*lda + k + 1] * c1; + sum += A[(j+3)*lda + k + 2] * c2; + sum += A[(j+3)*lda + k + 3] * c3; + C[(j+3)*lda + i + 1] += sum; + + } + barrier(); + } + } +} + +//-------------------------------------------------------------------------- +// 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); +} +