--- /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.
+ int i, j, k;
+ int temp0, temp1,temp2,temp3,temp4,temp5,temp6,temp7;
+ int start = coreid*lda/2;
+ int end = start + lda/2;
+ int j_lda;
+ int temp_i;
+ int temp_A0, temp_A1, temp_A2, temp_A3 ;
+
+ for ( i = start; i < end; i+=8){
+ for ( j = 0; j < lda; j++)
+ {
+ j_lda = j*lda;
+ temp0 = C[(i+0) + j_lda];
+ temp1 = C[(i+1) + j_lda];
+ temp2 = C[(i+2) + j_lda];
+ temp3 = C[(i+3) + j_lda];
+ temp4 = C[(i+4) + j_lda];
+ temp5 = C[(i+5) + j_lda];
+ temp6 = C[(i+6) + j_lda];
+ temp7 = C[(i+7) + j_lda];
+
+
+
+ for ( k = 0; k < lda; k+=4)
+ {
+ temp_i = i;
+ temp_A0 = A[j_lda + (k+0)] ;
+ temp_A1 = A[j_lda + (k+1)] ;
+ temp_A2 = A[j_lda + (k+2)] ;
+ temp_A3 = A[j_lda + (k+3)] ;
+
+
+ temp0 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp0 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp0 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp0 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+ temp1 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp1 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp1 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp1 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+ temp2 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp2 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp2 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp2 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+
+ temp3 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp3 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp3 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp3 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+ temp4 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp4 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp4 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp4 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+ temp5 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp5 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp5 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp5 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+ temp6 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp6 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp6 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp6 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+
+ temp7 += temp_A0 * B[(k+0)*lda + temp_i];
+ temp7 += temp_A1 * B[(k+1)*lda + temp_i];
+ temp7 += temp_A2 * B[(k+2)*lda + temp_i];
+ temp7 += temp_A3 * B[(k+3)*lda + temp_i];
+ temp_i++;
+
+ }
+
+ C[i + j*lda] = temp0;
+ C[(i+1) + j*lda] = temp1;
+ C[(i+2) + j*lda] = temp2;
+ C[(i+3) + j*lda] = temp3;
+ C[(i+4) + j*lda] = temp4;
+ C[(i+5) + j*lda] = temp5;
+ C[(i+6) + j*lda] = temp6;
+ C[(i+7) + j*lda] = temp7;
+
+ }
+ }
+}
+
+//--------------------------------------------------------------------------
+// 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