multithreading tests from 152 lab 5
[riscv-tests.git] / mt / af_matmul / matmul_mi.c~
1 //**************************************************************************
2 // Multi-threaded Matrix Multiply benchmark
3 //--------------------------------------------------------------------------
4 // TA : Christopher Celio
5 // Student: Felix Li $ Ronald Lee
6 //
7 //
8 // This benchmark multiplies two 2-D arrays together and writes the results to
9 // a third vector. The input data (and reference data) should be generated
10 // using the matmul_gendata.pl perl script and dumped to a file named
11 // dataset.h.
12
13
14 // print out arrays, etc.
15 //#define DEBUG
16
17 //--------------------------------------------------------------------------
18 // Includes
19
20 #include <string.h>
21 #include <stdlib.h>
22 #include <stdio.h>
23
24
25 //--------------------------------------------------------------------------
26 // Input/Reference Data
27
28 typedef float data_t;
29 #include "dataset.h"
30
31
32 //--------------------------------------------------------------------------
33 // Basic Utilities and Multi-thread Support
34
35 __thread unsigned long coreid;
36 unsigned long ncores;
37
38 #include "util.h"
39
40 #define stringify_1(s) #s
41 #define stringify(s) stringify_1(s)
42 #define stats(code) do { \
43 unsigned long _c = -rdcycle(), _i = -rdinstret(); \
44 code; \
45 _c += rdcycle(), _i += rdinstret(); \
46 if (coreid == 0) \
47 printf("%s: %ld cycles, %ld.%ld cycles/iter, %ld.%ld CPI\n", \
48 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); \
49 } while(0)
50
51
52 //--------------------------------------------------------------------------
53 // Helper functions
54
55 void printArray( char name[], int n, data_t arr[] )
56 {
57 int i;
58 if (coreid != 0)
59 return;
60
61 printf( " %10s :", name );
62 for ( i = 0; i < n; i++ )
63 printf( " %3ld ", (long) arr[i] );
64 printf( "\n" );
65 }
66
67 void __attribute__((noinline)) verify(size_t n, const data_t* test, const data_t* correct)
68 {
69 if (coreid != 0)
70 return;
71
72 size_t i;
73 for (i = 0; i < n; i++)
74 {
75 if (test[i] != correct[i])
76 {
77 printf("FAILED test[%d]= %3ld, correct[%d]= %3ld\n",
78 i, (long)test[i], i, (long)correct[i]);
79 exit(-1);
80 }
81 }
82
83 return;
84 }
85
86 //--------------------------------------------------------------------------
87 // matmul function
88
89 // single-thread, naive version
90 void __attribute__((noinline)) matmul_naive(const int lda, const data_t A[], const data_t B[], data_t C[] )
91 {
92 int i, j, k;
93
94 if (coreid > 0)
95 return;
96
97 for ( i = 0; i < lda; i++ )
98 for ( j = 0; j < lda; j++ )
99 {
100 for ( k = 0; k < lda; k++ )
101 {
102 C[i + j*lda] += A[j*lda + k] * B[k*lda + i];
103 }
104 }
105
106 }
107
108
109
110 void __attribute__((noinline)) matmul(const int lda, const data_t A[], const data_t B[], data_t C[] )
111 {
112 int i,j,k,l;
113 data_t element1, element2, element3, element4, element5, element6, element7, element8;
114 int row, row2;
115 int column1, column2, column3, column4, column5, column6, column7, column8;
116 data_t temp[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
117 data_t temp2[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
118 if (coreid == 0){
119 for (i=0; i<32; i+=2){
120 row = i*32;
121 row2 = (i+1)*32;
122 for (j=0; j<16; j+=4){
123 element1 = A[row+j];
124 element2 = A[row+j+1];
125 element3 = A[row+j+2];
126 element4 = A[row+j+3];
127 column1 = j*32;
128 column2 = (j+1)*32;
129 column3 = (j+2)*32;
130 column4 = (j+3)*32;
131 element5 = A[row2+j];
132 element6 = A[row2+j+1];
133 element7 = A[row2+j+2];
134 element8 = A[row2+j+3];
135
136 for (k=0; k<32; k+=4){
137 temp[k]+=element1*B[column1+k]+element2*B[column2+k]+element3*B[column3+k]+element4*B[column4+k];
138 temp[k+1]+=element1*B[column1+k+1]+element2*B[column2+k+1]+element3*B[column3+k+1]+element4*B[column4+k+1];
139 temp[k+2]+=element1*B[column1+k+2]+element2*B[column2+k+2]+element3*B[column3+k+2]+element4*B[column4+k+2];
140 temp[k+3]+=element1*B[column1+k+3]+element2*B[column2+k+3]+element3*B[column3+k+3]+element4*B[column4+k+3];
141 temp2[k]+=element5*B[column1+k]+element6*B[column2+k]+element7*B[column3+k]+element8*B[column4+k];
142 temp2[k+1]+=element5*B[column1+k+1]+element6*B[column2+k+1]+element7*B[column3+k+1]+element8*B[column4+k+1];
143 temp2[k+2]+=element5*B[column1+k+2]+element6*B[column2+k+2]+element7*B[column3+k+2]+element8*B[column4+k+2];
144 temp2[k+3]+=element5*B[column1+k+3]+element6*B[column2+k+3]+element7*B[column3+k+3]+element8*B[column4+k+3];
145 }
146 if (j==12){
147 for (l=0; l<32; l++){
148 C[row+l]+=temp[l];
149 C[row2+l]+=temp2[l];
150 temp[l]=0;
151 temp2[l]=0;
152 }
153 }
154 }
155 }
156 }
157 else if (coreid==1){
158 for (i=0; i<32; i+=2){
159 row = (31-i)*32;
160 row2 = (31-i-1)*32;
161 for (j=16; j<32; j+=4){
162 element1 = A[row+j];
163 element2 = A[row+j+1];
164 element3 = A[row+j+2];
165 element4 = A[row+j+3];
166 element5 = A[row2+j];
167 element6 = A[row2+j+1];
168 element7 = A[row2+j+2];
169 element8 = A[row2+j+3];
170 column1 = j*32;
171 column2 = (j+1)*32;
172 column3 = (j+2)*32;
173 column4 = (j+3)*32;
174 for (k=0; k<32; k+=4){
175 temp[k]+=element1*B[column1+k]+element2*B[column2+k]+element3*B[column3+k]+element4*B[column4+k];
176 temp[k+1]+=element1*B[column1+k+1]+element2*B[column2+k+1]+element3*B[column3+k+1]+element4*B[column4+k+1];
177 temp[k+2]+=element1*B[column1+k+2]+element2*B[column2+k+2]+element3*B[column3+k+2]+element4*B[column4+k+2];
178 temp[k+3]+=element1*B[column1+k+3]+element2*B[column2+k+3]+element3*B[column3+k+3]+element4*B[column4+k+3];
179 temp2[k]+=element5*B[column1+k]+element6*B[column2+k]+element7*B[column3+k]+element8*B[column4+k];
180 temp2[k+1]+=element5*B[column1+k+1]+element6*B[column2+k+1]+element7*B[column3+k+1]+element8*B[column4+k+1];
181 temp2[k+2]+=element5*B[column1+k+2]+element6*B[column2+k+2]+element7*B[column3+k+2]+element8*B[column4+k+2];
182 temp2[k+3]+=element5*B[column1+k+3]+element6*B[column2+k+3]+element7*B[column3+k+3]+element8*B[column4+k+3];
183 }
184 if (j==28){
185 for (l=0; l<32; l++){
186 C[row+l]+=temp[l];
187 C[row2+l]+=temp2[l];
188 temp[l]=0;
189 temp2[l]=0;
190 }
191 }
192 }
193 }
194 }
195 // ***************************** //
196 // **** ADD YOUR CODE HERE ***** //
197 // ***************************** //
198 //
199 // feel free to make a separate function for MI and MSI versions.
200
201 }
202
203 //--------------------------------------------------------------------------
204 // Main
205 //
206 // all threads start executing thread_entry(). Use their "coreid" to
207 // differentiate between threads (each thread is running on a separate core).
208
209 void thread_entry(int cid, int nc)
210 {
211 coreid = cid;
212 ncores = nc;
213
214 // static allocates data in the binary, which is visible to both threads
215 static data_t results_data[ARRAY_SIZE];
216
217
218 // Execute the provided, naive matmul
219 barrier();
220 stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier());
221
222
223 // verify
224 verify(ARRAY_SIZE, results_data, verify_data);
225
226 // clear results from the first trial
227 size_t i;
228 if (coreid == 0)
229 for (i=0; i < ARRAY_SIZE; i++)
230 results_data[i] = 0;
231 barrier();
232
233
234 // Execute your faster matmul
235 barrier();
236 stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier());
237
238 #ifdef DEBUG
239 printArray("results:", ARRAY_SIZE, results_data);
240 printArray("verify :", ARRAY_SIZE, verify_data);
241 #endif
242
243 // verify
244 verify(ARRAY_SIZE, results_data, verify_data);
245 barrier();
246
247 exit(0);
248 }