--- /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 , jj , kk;
+ int start_i = coreid*lda/2;
+ int end_i = start_i + lda/2;
+ int step_j, step_k;
+ int start_k, end_k, start_j, end_j;
+ int j_lda;
+ int pos_A , pos_B, pos_C;
+ data_t temp00, temp01,temp02,temp03,temp04,temp05,temp06,temp07;
+ data_t temp10, temp11,temp12,temp13,temp14,temp15,temp16,temp17;
+ data_t temp_A0, temp_A1, temp_A2, temp_A3, temp_A4, temp_A5, temp_A6, temp_A7;
+
+ temp00 = 0;
+ temp01 = 0;
+ temp02 = 0;
+ temp03 = 0;
+ temp04 = 0;
+ temp05 = 0;
+ temp06 = 0;
+ temp07 = 0;
+
+ temp10 = 0;
+ temp11 = 0;
+ temp12 = 0;
+ temp13 = 0;
+ temp14 = 0;
+ temp15 = 0;
+ temp16 = 0;
+ temp17 = 0;
+
+ if (coreid == 0)
+ {
+ step_k = 1;
+ start_k= 0;
+ end_k = lda;
+
+ step_j = 2;
+ start_j= 0;
+ end_j = lda;
+
+ }else
+ {
+
+ step_k = -1;
+ start_k = lda-1;
+ end_k = -1;
+
+ step_j = -2;
+ start_j= lda-2;
+ end_j = -2;
+ }
+
+ for( kk = start_k ; kk!= end_k ; kk+=(step_k*16) )
+ {
+ for( jj = start_j ; jj!= end_j ; jj+=(step_j*8) )
+ {
+ for ( i = start_i; i < end_i; i+=8 )
+ {
+ //pos_C = i + jj*lda;
+ for ( j = jj; j != (jj+(step_j*8)) ; j+=step_j )
+ {
+
+ pos_C = i + j*lda;
+ temp00 = C[(pos_C + 0)];
+ temp01 = C[(pos_C + 1)];
+ temp02 = C[(pos_C + 2)];
+ temp03 = C[(pos_C + 3)];
+ temp04 = C[(pos_C + 4)];
+ temp05 = C[(pos_C + 5)];
+ temp06 = C[(pos_C + 6)];
+ temp07 = C[(pos_C + 7)];
+
+ //pos_C += lda;
+ pos_C = i + (j+1)*lda;
+
+ temp10 = C[(pos_C + 0)];
+ temp11 = C[(pos_C + 1)];
+ temp12 = C[(pos_C + 2)];
+ temp13 = C[(pos_C + 3)];
+ temp14 = C[(pos_C + 4)];
+ temp15 = C[(pos_C + 5)];
+ temp16 = C[(pos_C + 6)];
+ temp17 = C[(pos_C + 7)];
+
+ pos_B = kk*lda + i;
+ pos_A = j*lda + kk;
+ for ( k = kk; k != (kk+(step_k*16)) ; k+=step_k )
+ {
+ temp_A0 = A[ pos_A ] ;
+ temp_A1 = A[pos_A +lda];
+
+ temp00 += temp_A0 * B[(pos_B + 0)];
+ temp01 += temp_A0 * B[(pos_B + 1)];
+ temp02 += temp_A0 * B[(pos_B + 2)];
+ temp03 += temp_A0 * B[(pos_B + 3)];
+ temp04 += temp_A0 * B[(pos_B + 4)];
+ temp05 += temp_A0 * B[(pos_B + 5)];
+ temp06 += temp_A0 * B[(pos_B + 6)];
+ temp07 += temp_A0 * B[(pos_B + 7)];
+
+ temp10 += temp_A1 * B[(pos_B + 0)];
+ temp11 += temp_A1 * B[(pos_B + 1)];
+ temp12 += temp_A1 * B[(pos_B + 2)];
+ temp13 += temp_A1 * B[(pos_B + 3)];
+ temp14 += temp_A1 * B[(pos_B + 4)];
+ temp15 += temp_A1 * B[(pos_B + 5)];
+ temp16 += temp_A1 * B[(pos_B + 6)];
+ temp17 += temp_A1 * B[(pos_B + 7)];
+
+ pos_B += (lda*step_k) ;
+ pos_A += step_k;
+ }
+ //barrier();
+
+ C[(pos_C + 0)] = temp10;
+ C[(pos_C + 1)] = temp11;
+ C[(pos_C + 2)] = temp12;
+ C[(pos_C + 3)] = temp13;
+ C[(pos_C + 4)] = temp14;
+ C[(pos_C + 5)] = temp15;
+ C[(pos_C + 6)] = temp16;
+ C[(pos_C + 7)] = temp17;
+ //barrier();
+
+ pos_C = i + j*lda;
+ //pos_C -= lda;
+ C[(pos_C + 0)] = temp00;
+ C[(pos_C + 1)] = temp01;
+ C[(pos_C + 2)] = temp02;
+ C[(pos_C + 3)] = temp03;
+ C[(pos_C + 4)] = temp04;
+ C[(pos_C + 5)] = temp05;
+ C[(pos_C + 6)] = temp06;
+ C[(pos_C + 7)] = temp07;
+ //barrier();
+ //pos_C += step_j * lda;
+ }
+ //barrier();
+ }
+ //barrier();
+
+ }
+ //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();
+
+
+ //printf("input1_data");
+exit(0);
+
+}
projects / riscv-tests.git / blobdiff