--- /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[] )
+{
+
+ // ***************************** //
+ // **** ADD YOUR CODE HERE ***** //
+ // ***************************** //
+ //
+ // feel free to make a separate function for MI and MSI versions.
+
+
+
+ data_t *b1;
+ data_t *b2;
+ data_t *b3;
+ data_t *b4;
+ data_t c1;
+ data_t c2;
+ data_t c3;
+ data_t c4;
+ data_t a1;
+ data_t a2;
+ data_t a3;
+ data_t a4;
+ data_t a5;
+ data_t a6;
+ data_t a7;
+ data_t a8;
+ int i, j, k;
+ static data_t BB[1024];
+
+
+
+ //transpose B
+ if (coreid == 0 | coreid == 1) {
+ for ( k = 0; k < lda; k++) {
+ for ( i = coreid*(lda/2); i < (coreid+1)*(lda/2); i++ ) {
+ BB[i*lda + k] = B[k*lda + i];
+ }
+ }
+ }
+ barrier();
+
+ for ( i = 0; i < lda; i+=4 ) {
+ for ( j = coreid*(lda/ncores); j < (coreid+1)*(lda/ncores); j++ ) {
+ c1 = 0; c2 = 0; c3 = 0; c4 = 0;
+ b1 = &BB[(i+0)*lda];
+ b2 = &BB[(i+1)*lda];
+ b3 = &BB[(i+2)*lda];
+ b4 = &BB[(i+3)*lda];
+ for ( k = 0; k < lda; k+=8 ) {
+
+ a1 = A[j*lda + k+0];
+ a2 = A[j*lda + k+1];
+ a3 = A[j*lda + k+2];
+ a4 = A[j*lda + k+3];
+ a5 = A[j*lda + k+4];
+ a6 = A[j*lda + k+5];
+ a7 = A[j*lda + k+6];
+ a8 = A[j*lda + k+7];
+
+ c1 += a1 * b1[k+0];
+ c1 += a2 * b1[k+1];
+ c1 += a3 * b1[k+2];
+ c1 += a4 * b1[k+3];
+ c1 += a5 * b1[k+4];
+ c1 += a6 * b1[k+5];
+ c1 += a7 * b1[k+6];
+ c1 += a8 * b1[k+7];
+
+ c2 += a1 * b2[k+0];
+ c2 += a2 * b2[k+1];
+ c2 += a3 * b2[k+2];
+ c2 += a4 * b2[k+3];
+ c2 += a5 * b2[k+4];
+ c2 += a6 * b2[k+5];
+ c2 += a7 * b2[k+6];
+ c2 += a8 * b2[k+7];
+
+ c3 += a1 * b3[k+0];
+ c3 += a2 * b3[k+1];
+ c3 += a3 * b3[k+2];
+ c3 += a4 * b3[k+3];
+ c3 += a5 * b3[k+4];
+ c3 += a6 * b3[k+5];
+ c3 += a7 * b3[k+6];
+ c3 += a8 * b3[k+7];
+
+ c4 += a1 * b4[k+0];
+ c4 += a2 * b4[k+1];
+ c4 += a3 * b4[k+2];
+ c4 += a4 * b4[k+3];
+ c4 += a5 * b4[k+4];
+ c4 += a6 * b4[k+5];
+ c4 += a7 * b4[k+6];
+ c4 += a8 * b4[k+7];
+
+
+ }
+ C[i+0 + j*lda] = c1;
+ C[i+1 + j*lda] = c2;
+ C[i+2 + j*lda] = c3;
+ C[i+3 + j*lda] = c4;
+ }
+ }
+
+}
+
+//--------------------------------------------------------------------------
+// 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);
+}
+
projects / riscv-tests.git / blobdiff