multithreading tests from 152 lab 5

1 files changed, 380 insertions, 0 deletions

diff --git a/mt/aj_matmul/matmul_mi.c b/mt/aj_matmul/matmul_mi.c
new file mode 100644
index 0000000..2280771
--- /dev/null
+++ b/mt/aj_matmul/matmul_mi.c
@@ -0,0 +1,380 @@
+//**************************************************************************
+// 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;
+}
+
+void matrix_sub(int size, data_t A[], data_t B[], data_t C[]) {
+	if (coreid != 0)
+		return;
+
+	for(int i = 0; i < size; i++){
+		C[i] = A[i] + B[i];
+	}
+}
+
+void matrix_add(int size, data_t A[], data_t B[], data_t C[]) {
+	if (coreid != 0)
+		return;
+
+	for(int i = 0; i < size; i++){
+		C[i] = A[i] - B[i];
+	}
+}
+
+void strassen_mult(int dime, const data_t sA[],  const data_t sB[], data_t sC[]) {
+
+	if (coreid != 0)
+		return;
+
+	int height, width;
+	int sub_size = dime*dime/4;
+
+//	data_t 	A_11[sub_size], B_11[sub_size], C_11[sub_size],
+//			A_12[sub_size], B_12[sub_size], C_12[sub_size],
+//			A_21[sub_size], B_21[sub_size], C_21[sub_size],
+//			A_22[sub_size], B_22[sub_size], C_22[sub_size];
+
+	data_t *A_11 = malloc(sub_size*sizeof(data_t));
+	data_t *A_12 = malloc(sub_size*sizeof(data_t));
+	data_t *A_21 = malloc(sub_size*sizeof(data_t));
+	data_t *A_22 = malloc(sub_size*sizeof(data_t));
+	data_t *B_11 = malloc(sub_size*sizeof(data_t));
+	data_t *B_12 = malloc(sub_size*sizeof(data_t));
+	data_t *B_21 = malloc(sub_size*sizeof(data_t));
+	data_t *B_22 = malloc(sub_size*sizeof(data_t));
+	
+	for(height=0; height < dime/2; height++) {
+		for(width= 0; width < dime/2; width++) {
+			A_11[width+(height*dime/2)] = sA[width + height*dime];
+			B_11[width+(height*dime/2)] = sB[width + height*dime];
+			
+			A_12[width+(height*dime/2)] = sA[dime/2 + width + height*dime];
+			B_12[width+(height*dime/2)] = sB[dime/2 + width + height*dime];
+			
+			A_21[width+(height*dime/2)] = sA[(dime*dime)/2 + width + height*dime];
+			B_21[width+(height*dime/2)] = sB[(dime*dime)/2 + width + height*dime];
+			
+			A_22[width+(height*dime/2)] = sA[(dime*dime)/2 + dime/2 + width + height*dime];
+			B_22[width+(height*dime/2)] = sB[(dime*dime)/2 + dime/2 + width + height*dime];
+		}
+	}
+	
+//	data_t		H_1[sub_size], H_2[sub_size], H_3[sub_size], H_4[sub_size], H_5[sub_size], 
+//			H_6[sub_size], H_7[sub_size], H_8[sub_size], H_9[sub_size], H_10[sub_size], 
+//			H_11[sub_size], H_12[sub_size], H_13[sub_size], H_14[sub_size], 
+//			H_15[sub_size], H_16[sub_size], H_17[sub_size], H_18[sub_size];
+
+	data_t *H_1 = malloc(sub_size*sizeof(data_t));
+	data_t *H_2 = malloc(sub_size*sizeof(data_t));
+	data_t *H_3 = malloc(sub_size*sizeof(data_t));
+	data_t *H_4 = malloc(sub_size*sizeof(data_t));
+	data_t *H_5 = malloc(sub_size*sizeof(data_t));
+	data_t *H_6 = malloc(sub_size*sizeof(data_t));
+	data_t *H_7 = malloc(sub_size*sizeof(data_t));
+	data_t *H_8 = malloc(sub_size*sizeof(data_t));
+	data_t *H_9 = malloc(sub_size*sizeof(data_t));
+	data_t *H_10 = malloc(sub_size*sizeof(data_t));
+
+	matrix_add(sub_size, A_11, A_22, H_1); //Helper1
+	matrix_add(sub_size, B_11, B_22, H_2); //Helper2
+	matrix_add(sub_size, A_21, A_22, H_3); //Helper3
+	matrix_sub(sub_size, B_12, B_22, H_4); //Helper4
+	matrix_sub(sub_size, B_21, B_11, H_5); //Helper5
+	matrix_add(sub_size, A_11, A_12, H_6); //Helper6
+	matrix_sub(sub_size, A_21, A_11, H_7); //Helper7
+	matrix_add(sub_size, B_11, B_12, H_8); //Helper8
+	matrix_sub(sub_size, A_12, A_22, H_9); //Helper9
+	matrix_add(sub_size, B_21, B_22, H_10); //Helper10
+
+	free(A_12);
+	free(A_21);
+	free(B_12);
+	free(B_21);
+
+	A_12 = NULL;
+	A_21 = NULL;
+	B_12 = NULL;
+	B_21 = NULL;
+
+//	data_t		M_1[sub_size], M_2[sub_size], M_3[sub_size], M_4[sub_size],
+//			M_5[sub_size], M_6[sub_size], M_7[sub_size];
+
+	data_t *M_1 = malloc(sub_size*sizeof(data_t));
+	data_t *M_2 = malloc(sub_size*sizeof(data_t));
+	data_t *M_3 = malloc(sub_size*sizeof(data_t));
+	data_t *M_4 = malloc(sub_size*sizeof(data_t));
+	data_t *M_5 = malloc(sub_size*sizeof(data_t));
+	data_t *M_6 = malloc(sub_size*sizeof(data_t));
+	data_t *M_7 = malloc(sub_size*sizeof(data_t));
+
+	if (sub_size == 1) {
+		M_1[0] = H_1[0]*H_2[0];
+		M_2[0] = H_3[0]*B_11[0];
+		M_3[0] = A_11[0]*H_4[0];
+		M_4[0] = A_22[0]*H_5[0];
+		M_5[0] = H_6[0]*B_22[0];
+		M_6[0] = H_7[0]*H_8[0];
+		M_7[0] = H_9[0]*H_10[0];
+	} else {
+		strassen_mult(dime/2, H_1, H_2, M_1);
+		strassen_mult(dime/2, H_3, B_11, M_2);
+		strassen_mult(dime/2, A_11, H_4, M_3);
+		strassen_mult(dime/2, A_22, H_5, M_4);
+		strassen_mult(dime/2, H_6, B_22, M_5);
+		strassen_mult(dime/2, H_7, H_8, M_6);
+		strassen_mult(dime/2, H_9, H_10, M_7);
+	}
+
+	free(A_11);
+	free(A_22);
+	free(B_11);
+	free(B_22);
+
+	A_11 = NULL;
+	A_22 = NULL;
+	B_11 = NULL;
+	B_22 = NULL;
+
+	free(H_1);
+	free(H_2);
+	free(H_3);
+	free(H_4);
+	free(H_5);
+	free(H_6);
+	free(H_7);
+	free(H_8);
+	free(H_9);
+	free(H_10);
+
+	H_1 = NULL;
+	H_2 = NULL;
+	H_3 = NULL;
+	H_4 = NULL;
+	H_5 = NULL;
+	H_6 = NULL;
+	H_7 = NULL;
+	H_8 = NULL;
+	H_9 = NULL;
+	H_10 = NULL;
+
+	data_t *H_11 = malloc(sub_size*sizeof(data_t));
+	data_t *H_12 = malloc(sub_size*sizeof(data_t));
+	data_t *H_13 = malloc(sub_size*sizeof(data_t));
+	data_t *H_14 = malloc(sub_size*sizeof(data_t));
+
+	data_t *C_11 = malloc(sub_size*sizeof(data_t));
+	data_t *C_12 = malloc(sub_size*sizeof(data_t));
+	data_t *C_21 = malloc(sub_size*sizeof(data_t));
+	data_t *C_22 = malloc(sub_size*sizeof(data_t));
+
+	matrix_add(sub_size, M_1, M_4, H_11);
+	matrix_add(sub_size, M_5, M_7, H_12);
+	matrix_sub(sub_size, H_11, H_12, C_11);
+
+	matrix_add(sub_size, M_3, M_5, C_12);
+
+	matrix_add(sub_size, M_2, M_4, C_21);
+
+	matrix_sub(sub_size, M_1, M_2, H_13);
+	matrix_add(sub_size, M_3, M_6, H_14);
+	matrix_add(sub_size, H_13, H_14, C_22);
+
+	free(H_11);
+	free(H_12);
+	free(H_13);
+	free(H_14);
+
+	H_11 = NULL;
+	H_12 = NULL;
+	H_13 = NULL;
+	H_14 = NULL;
+
+
+	for(height=0; height < dime/2; height++) {
+		for(width= 0; width < dime/2; width++) {
+			sC[width + height*dime] 				= C_11[width+(height*dime/2)];
+			sC[dime/2 + width + height*dime] 			= C_12[width+(height*dime/2)];
+			sC[(dime*dime)/2 + width + height*dime] 		= C_21[width+(height*dime/2)];
+			sC[(dime*dime)/2 + dime/2 + width + height*dime] = C_22[width+(height*dime/2)];
+		}
+	}
+
+	free(C_11);
+	free(C_12);
+	free(C_21);
+	free(C_22);
+
+	C_11 = NULL;
+	C_12 = NULL;
+	C_21 = NULL;
+	C_22 = NULL;
+
+}
+ 
+//--------------------------------------------------------------------------
+// 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.
+
+	if (coreid > 0)
+	return; 
+
+	strassen_mult(lda, A, B, C);
+
+}
+
+//--------------------------------------------------------------------------
+// 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);
+}
+