--- /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[] )
+{
+ size_t c_start = lda / ncores * coreid;
+ size_t c_row;
+ size_t c_col;
+ size_t colSplit = 0;
+ size_t i;
+ size_t useSplit = 0;
+ data_t a1;
+ data_t a2;
+ data_t a3;
+ data_t a4;
+ data_t a5;
+ data_t a6;
+ data_t a7;
+ data_t a8;
+ data_t c1;
+ data_t c2;
+ data_t c3;
+ data_t c4;
+ data_t c5;
+ data_t c6;
+ data_t c7;
+ data_t c8;
+ size_t block;
+ for (block = 0; block < 2; block++) {
+ for (colSplit = 0; colSplit < 4; colSplit++) {
+ useSplit = (coreid == 0) ? colSplit : (colSplit + 2 ) % 4;
+ for (c_row = c_start + block * 8; c_row < c_start + block * 8 + 8; c_row += 2) {
+ for (c_col = 0; c_col < lda; c_col+=4) {
+ c1 = C[c_row*lda+c_col];
+ c2 = C[(c_row+1)*lda+c_col];
+ c3 = C[c_row*lda+c_col+1];
+ c4 = C[(c_row+1)*lda+c_col+1];
+ c5 = C[c_row*lda+c_col+2];
+ c6 = C[(c_row+1)*lda+c_col+2];
+ c7 = C[c_row*lda+c_col+3];
+ c8 = C[(c_row+1)*lda+c_col+3];
+ for (i = useSplit * lda / 4; i < (useSplit + 1) * lda / 4; i+=4) {
+ a1 = A[c_row*lda+i];
+ a2 = A[(c_row+1)*lda+i];
+ a3 = A[c_row*lda+i+1];
+ a4 = A[(c_row+1)*lda+i+1];
+ a5 = A[c_row*lda+i+2];
+ a6 = A[(c_row+1)*lda+i+2];
+ a7 = A[c_row*lda+i+3];
+ a8 = A[(c_row+1)*lda+i+3];
+
+ c1 += a1 * B[i*lda+c_col];
+ c2 += a2 * B[i*lda+c_col];
+
+ c1 += a3 * B[(i+1)*lda+c_col];
+ c2 += a4 * B[(i+1)*lda+c_col];
+
+ c1 += a5 * B[(i+2)*lda+c_col];
+ c2 += a6 * B[(i+2)*lda+c_col];
+
+ c1 += a7 * B[(i+3)*lda+c_col];
+ c2 += a8 * B[(i+3)*lda+c_col];
+
+ c3 += a1 * B[i*lda+c_col+1];
+ c4 += a2 * B[i*lda+c_col+1];
+
+ c3 += a3 * B[(i+1)*lda+c_col+1];
+ c4 += a4 * B[(i+1)*lda+c_col+1];
+
+ c3 += a5 * B[(i+2)*lda+c_col+1];
+ c4 += a6 * B[(i+2)*lda+c_col+1];
+
+ c3 += a7 * B[(i+3)*lda+c_col+1];
+ c4 += a8 * B[(i+3)*lda+c_col+1];
+
+ c5 += a1 * B[i*lda+c_col+2];
+ c6 += a2 * B[i*lda+c_col+2];
+
+ c5 += a3 * B[(i+1)*lda+c_col+2];
+ c6 += a4 * B[(i+1)*lda+c_col+2];
+
+ c5 += a5 * B[(i+2)*lda+c_col+2];
+ c6 += a6 * B[(i+2)*lda+c_col+2];
+
+ c5 += a7 * B[(i+3)*lda+c_col+2];
+ c6 += a8 * B[(i+3)*lda+c_col+2];
+
+ c7 += a1 * B[i*lda+c_col+3];
+ c8 += a2 * B[i*lda+c_col+3];
+
+ c7 += a3 * B[(i+1)*lda+c_col+3];
+ c8 += a4 * B[(i+1)*lda+c_col+3];
+
+ c7 += a5 * B[(i+2)*lda+c_col+3];
+ c8 += a6 * B[(i+2)*lda+c_col+3];
+
+ c7 += a7 * B[(i+3)*lda+c_col+3];
+ c8 += a8 * B[(i+3)*lda+c_col+3];
+ }
+
+ C[c_row*lda+c_col] = c1;
+ C[(c_row+1)*lda+c_col] = c2;
+
+ C[c_row*lda+c_col+1] = c3;
+ C[(c_row+1)*lda+c_col+1] = c4;
+
+ C[c_row*lda+c_col+2] = c5;
+ C[(c_row+1)*lda+c_col+2] = c6;
+
+ C[c_row*lda+c_col+3] = c7;
+ C[(c_row+1)*lda+c_col+3] = c8;
+ }
+ }
+ }
+ }
+}
+
+//--------------------------------------------------------------------------
+// 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