Clean up canonical mt benchmarks and reorganize extra versions in /mt. All versions...
[riscv-tests.git] / mt / ba_matmul / matmul_mi.c
diff --git a/mt/ba_matmul/matmul_mi.c b/mt/ba_matmul/matmul_mi.c
deleted file mode 100755 (executable)
index 3f712c1..0000000
+++ /dev/null
@@ -1,271 +0,0 @@
-//**************************************************************************
-// 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 printArrayMT( 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)) verifyMT(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(nc);
-//   stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));
-   
-   // verify
-//   verifyMT(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(nc);
-
-   
-   // Execute your faster matmul
-   barrier(nc);
-   stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));
-#ifdef DEBUG
-   printArrayMT("results:", ARRAY_SIZE, results_data);
-   printArrayMT("verify :", ARRAY_SIZE, verify_data);
-#endif
-   
-   // verify
-   verifyMT(ARRAY_SIZE, results_data, verify_data);
-   barrier(nc);
-
-   exit(0);
-}
-