56f02d3bd801bfa8061df124bd2dd592e769b85a
[riscv-tests.git] / mt / az_matmul / az_matmul.c
1 //**************************************************************************
2 // Multi-threaded Matrix Multiply benchmark
3 //--------------------------------------------------------------------------
4 // TA : Christopher Celio
5 // Student:
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 data_t ffmul(data_t a, data_t b) {
110 data_t result = 0;
111
112 for (int i=0; i < b; i++) {
113 result += a;
114 }
115
116 return result;
117 }
118
119
120 //void __attribute__((noinline)) matmul(const int lda, const data_t A[], const data_t B[], data_t C[] )
121 //{
122 //
123 // // ***************************** //
124 // // **** ADD YOUR CODE HERE ***** //
125 // // ***************************** //
126 // //
127 // // feel free to make a separate function for MI and MSI versions.
128 //
129 // static __thread int i, j, k;
130 // static __thread int jlda, ilda;
131 // static __thread data_t tempA1, tempA2, tempA3, tempA4, tempA5, tempA6, tempA7, tempA8;
132 // static __thread int start, end;
133 //
134 // start = coreid*(lda>>1);
135 // end = (coreid+1)*(lda>>1);
136 //
137 // for (j=start; j < end; j+=1) {
138 // jlda = j * lda;
139 // for ( i=0; i < lda; i+=1 ) {
140 // ilda = i*lda;
141 // tempA1 = A[i + jlda];
142 // //tempA2 = A[i+1 + jlda];
143 // //tempA3 = A[i+2 + jlda];
144 // //tempA4 = A[i+3 + jlda];
145 // //tempA5 = A[i+4 + jlda];
146 // //tempA6 = A[i+5 + jlda];
147 // //tempA7 = A[i+6 + jlda];
148 // //tempA8 = A[i+7 + jlda];
149 // //tempC1 = C[i + j*lda];
150 // //tempC2 = C[i+1 + j*lda];
151 // for(k=0; k < lda; k+=1) {
152 // //C[k + jlda] += tempA1 * B[k + i*lda] + tempA2 * B[k + (i+1)*lda] + tempA3 * B[k + (i+2)*lda] + tempA4 * B[k + (i+3)*lda] +
153 // // tempA5 * B[k + (i+4)*lda] + tempA6 * B[k + (i+5)*lda] + tempA7 * B[k + (i+6)*lda] + tempA8 * B[k + (i+7)*lda];
154 //
155 // C[k + jlda] += tempA1* B[k + i*lda];// + ffmul(tempA2,B[k + (i+1)*lda]) + tempA3 * B[k + (i+2)*lda] + tempA4 * B[k + (i+3)*lda] +
156 // // tempA5 * B[k + (i+4)*lda] + tempA6 * B[k + (i+5)*lda] + tempA7 * B[k + (i+6)*lda] + tempA8 * B[k + (i+7)*lda];
157 // //
158 // //C[k+1 + jlda] += tempA1 * B[k+1 + i*lda] + tempA2 * B[k+1 + (i+1)*lda] + tempA3 * B[k+1 + (i+2)*lda] + tempA4 * B[k+1 + (i+3)*lda] +
159 // // tempA5 * B[k+1 + (i+4)*lda] + tempA6 * B[k+1 + (i+5)*lda] + tempA7 * B[k+1 + (i+6)*lda] + tempA8 * B[k+1 + (i+7)*lda];
160 // //
161 // //C[k+2 + jlda] += tempA1 * B[k+2 + i*lda] + tempA2 * B[k+2 + (i+1)*lda] + tempA3 * B[k+2 + (i+2)*lda] + tempA4 * B[k+2 + (i+3)*lda] +
162 // // tempA5 * B[k+2 + (i+4)*lda] + tempA6 * B[k+2 + (i+5)*lda] + tempA7 * B[k+2 + (i+6)*lda] + tempA8 * B[k+2 + (i+7)*lda];
163 // //
164 // //C[k+3 + jlda] += tempA1 * B[k+3 + i*lda] + tempA2 * B[k+3 + (i+1)*lda] + tempA3 * B[k+3 + (i+2)*lda] + tempA4 * B[k+3 + (i+3)*lda] +
165 // // tempA5 * B[k+3 + (i+4)*lda] + tempA6 * B[k+3 + (i+5)*lda] + tempA7 * B[k+3 + (i+6)*lda] + tempA8 * B[k+3 + (i+7)*lda];
166 // //
167 // //C[k+4 + jlda] += tempA1 * B[k+4 + i*lda] + tempA2 * B[k+4 + (i+1)*lda] + tempA3 * B[k+4 + (i+2)*lda] + tempA4 * B[k+4 + (i+3)*lda] +
168 // // tempA5 * B[k+4 + (i+4)*lda] + tempA6 * B[k+4 + (i+5)*lda] + tempA7 * B[k+4 + (i+6)*lda] + tempA8 * B[k+4 + (i+7)*lda];
169 // //
170 // //C[k+5 + jlda] += tempA1 * B[k+5 + i*lda] + tempA2 * B[k+5 + (i+1)*lda] + tempA3 * B[k+5 + (i+2)*lda] + tempA4 * B[k+5 + (i+3)*lda] +
171 // // tempA5 * B[k+5 + (i+4)*lda] + tempA6 * B[k+5 + (i+5)*lda] + tempA7 * B[k+5 + (i+6)*lda] + tempA8 * B[k+5 + (i+7)*lda];
172 // //
173 // //C[k+6 + jlda] += tempA1 * B[k+6 + i*lda] + tempA2 * B[k+6 + (i+1)*lda] + tempA3 * B[k+6 + (i+2)*lda] + tempA4 * B[k+6 + (i+3)*lda] +
174 // // tempA5 * B[k+6 + (i+4)*lda] + tempA6 * B[k+6 + (i+5)*lda] + tempA7 * B[k+6 + (i+6)*lda] + tempA8 * B[k+6 + (i+7)*lda];
175 // //
176 // //C[k+7 + jlda] += tempA1 * B[k+7 + i*lda] + tempA2 * B[k+7 + (i+1)*lda] + tempA3 * B[k+7 + (i+2)*lda] + tempA4 * B[k+7 + (i+3)*lda] +
177 // // tempA5 * B[k+7 + (i+4)*lda] + tempA6 * B[k+7 + (i+5)*lda] + tempA7 * B[k+7 + (i+6)*lda] + tempA8 * B[k+7 + (i+7)*lda];
178 //
179 //
180 // }
181 // }
182 // }
183 //}
184
185
186 void __attribute__((noinline)) matmul(const int lda, const data_t A[], const data_t B[], data_t C[] )
187 {
188
189 // ***************************** //
190 // **** ADD YOUR CODE HERE ***** //
191 // ***************************** //
192 //
193 // feel free to make a separate function for MI and MSI versions.
194
195 static __thread int i, j, k;
196 static __thread data_t tempA0, tempA1, tempA2, tempA3, tempA4, tempA5, tempA6, tempA7;
197 static __thread data_t tempC0, tempC1, tempC2, tempC3, tempC4, tempC5, tempC6, tempC7; //tempC8, tempC9, tempC10, tempC11, tempC12, tempC13, tempC14, tempC15;
198
199 static __thread int start, end, jStride, jToRow, jToCol, iToRow;
200
201 start = coreid << 9;
202 end = (coreid+1) << 9;
203 jStride = 8;
204
205 for (j=start; j < end; j+=jStride) {
206 jToRow = (j>>5)<<5;
207 jToCol = j%32;
208 tempC0 = 0;
209 tempC1 = 0;
210 tempC2 = 0;
211 tempC3 = 0;
212 tempC4 = 0;
213 tempC5 = 0;
214 tempC6 = 0;
215 tempC7 = 0;
216 //tempC8 = 0;
217 //tempC9 = 0;
218 //tempC10 = 0;
219 //tempC11 = 0;
220 //tempC12 = 0;
221 //tempC13 = 0;
222 //tempC14 = 0;
223 //tempC15 = 0;
224
225 for ( i=0; i < lda; i+=2 ) {
226 iToRow = i << 5;
227
228 tempA0 = A[i + jToRow];
229 tempA1 = A[i+1 + jToRow];
230 //tempA2 = A[i+2 + jToRow];
231 //tempA3 = A[i+3 + jToRow];
232 //tempA4 = A[i+4 + jToRow];
233 //tempA5 = A[i+5 + jToRow];
234 //tempA6 = A[i+6 + jToRow];
235 //tempA7 = A[i+7 + jToRow];
236
237 tempC0 += tempA0 * B[(jToCol ) + (iToRow)];
238 tempC1 += tempA0 * B[(jToCol+1 ) + (iToRow)];
239 tempC2 += tempA0 * B[(jToCol+2 ) + (iToRow)];
240 tempC3 += tempA0 * B[(jToCol+3 ) + (iToRow)];
241 tempC4 += tempA0 * B[(jToCol+4 ) + (iToRow)];
242 tempC5 += tempA0 * B[(jToCol+5 ) + (iToRow)];
243 tempC6 += tempA0 * B[(jToCol+6 ) + (iToRow)];
244 tempC7 += tempA0 * B[(jToCol+7 ) + (iToRow)];
245 //tempC8 += tempA0 * B[(jToCol+8 ) + (iToRow)];
246 //tempC9 += tempA0 * B[(jToCol+9 ) + (iToRow)];
247 //tempC10 += tempA0 * B[(jToCol+10) + (iToRow)];
248 //tempC11 += tempA0 * B[(jToCol+11) + (iToRow)];
249 //tempC12 += tempA0 * B[(jToCol+12) + (iToRow)];
250 //tempC13 += tempA0 * B[(jToCol+13) + (iToRow)];
251 //tempC14 += tempA0 * B[(jToCol+14) + (iToRow)];
252 //tempC15 += tempA0 * B[(jToCol+15) + (iToRow)];
253
254 iToRow += 32;
255 tempC0 += tempA1 * B[(jToCol ) + (iToRow)];
256 tempC1 += tempA1 * B[(jToCol+1 ) + (iToRow)];
257 tempC2 += tempA1 * B[(jToCol+2 ) + (iToRow)];
258 tempC3 += tempA1 * B[(jToCol+3 ) + (iToRow)];
259 tempC4 += tempA1 * B[(jToCol+4 ) + (iToRow)];
260 tempC5 += tempA1 * B[(jToCol+5 ) + (iToRow)];
261 tempC6 += tempA1 * B[(jToCol+6 ) + (iToRow)];
262 tempC7 += tempA1 * B[(jToCol+7 ) + (iToRow)];
263 //tempC8 += tempA1 * B[(jToCol+8 ) + (iToRow+32)];
264 //tempC9 += tempA1 * B[(jToCol+9 ) + (iToRow+32)];
265 //tempC10 += tempA1 * B[(jToCol+10) + (iToRow+32)];
266 //tempC11 += tempA1 * B[(jToCol+11) + (iToRow+32)];
267 //tempC12 += tempA1 * B[(jToCol+12) + (iToRow+32)];
268 //tempC13 += tempA1 * B[(jToCol+13) + (iToRow+32)];
269 //tempC14 += tempA1 * B[(jToCol+14) + (iToRow+32)];
270 //tempC15 += tempA1 * B[(jToCol+15) + (iToRow+32)];
271
272 //iToRow += 32;
273 //tempC0 += tempA2 * B[(jToCol ) + (iToRow)];
274 //tempC1 += tempA2 * B[(jToCol+1 ) + (iToRow)];
275 //tempC2 += tempA2 * B[(jToCol+2 ) + (iToRow)];
276 //tempC3 += tempA2 * B[(jToCol+3 ) + (iToRow)];
277 //tempC4 += tempA2 * B[(jToCol+4 ) + (iToRow)];
278 //tempC5 += tempA2 * B[(jToCol+5 ) + (iToRow)];
279 //tempC6 += tempA2 * B[(jToCol+6 ) + (iToRow)];
280 //tempC7 += tempA2 * B[(jToCol+7 ) + (iToRow)];
281 //tempC8 += tempA2 * B[(jToCol+8 ) + (iToRow)];
282 //tempC9 += tempA2 * B[(jToCol+9 ) + (iToRow)];
283 //tempC10 += tempA2 * B[(jToCol+10) + (iToRow)];
284 //tempC11 += tempA2 * B[(jToCol+11) + (iToRow)];
285 //tempC12 += tempA2 * B[(jToCol+12) + (iToRow)];
286 //tempC13 += tempA2 * B[(jToCol+13) + (iToRow)];
287 //tempC14 += tempA2 * B[(jToCol+14) + (iToRow)];
288 //tempC15 += tempA2 * B[(jToCol+15) + (iToRow)];
289
290 //iToRow += 32;
291 //tempC0 += tempA3 * B[(jToCol ) + (iToRow)];
292 //tempC1 += tempA3 * B[(jToCol+1 ) + (iToRow)];
293 //tempC2 += tempA3 * B[(jToCol+2 ) + (iToRow)];
294 //tempC3 += tempA3 * B[(jToCol+3 ) + (iToRow)];
295 //tempC4 += tempA3 * B[(jToCol+4 ) + (iToRow)];
296 //tempC5 += tempA3 * B[(jToCol+5 ) + (iToRow)];
297 //tempC6 += tempA3 * B[(jToCol+6 ) + (iToRow)];
298 //tempC7 += tempA3 * B[(jToCol+7 ) + (iToRow)];
299 //tempC8 += tempA3 * B[(jToCol+8 ) + (iToRow)];
300 //tempC9 += tempA3 * B[(jToCol+9 ) + (iToRow)];
301 //tempC10 += tempA3 * B[(jToCol+10) + (iToRow)];
302 //tempC11 += tempA3 * B[(jToCol+11) + (iToRow)];
303 //tempC12 += tempA3 * B[(jToCol+12) + (iToRow)];
304 //tempC13 += tempA3 * B[(jToCol+13) + (iToRow)];
305 //tempC14 += tempA3 * B[(jToCol+14) + (iToRow)];
306 //tempC15 += tempA3 * B[(jToCol+15) + (iToRow)];
307
308 //iToRow += 32;
309 //tempC0 += tempA4 * B[(jToCol ) + (iToRow)];
310 //tempC1 += tempA4 * B[(jToCol+1 ) + (iToRow)];
311 //tempC2 += tempA4 * B[(jToCol+2 ) + (iToRow)];
312 //tempC3 += tempA4 * B[(jToCol+3 ) + (iToRow)];
313 //tempC4 += tempA4 * B[(jToCol+4 ) + (iToRow)];
314 //tempC5 += tempA4 * B[(jToCol+5 ) + (iToRow)];
315 //tempC6 += tempA4 * B[(jToCol+6 ) + (iToRow)];
316 //tempC7 += tempA4 * B[(jToCol+7 ) + (iToRow)];
317 //
318 //iToRow += 32;
319 //tempC0 += tempA5 * B[(jToCol ) + (iToRow)];
320 //tempC1 += tempA5 * B[(jToCol+1 ) + (iToRow)];
321 //tempC2 += tempA5 * B[(jToCol+2 ) + (iToRow)];
322 //tempC3 += tempA5 * B[(jToCol+3 ) + (iToRow)];
323 //tempC4 += tempA5 * B[(jToCol+4 ) + (iToRow)];
324 //tempC5 += tempA5 * B[(jToCol+5 ) + (iToRow)];
325 //tempC6 += tempA5 * B[(jToCol+6 ) + (iToRow)];
326 //tempC7 += tempA5 * B[(jToCol+7 ) + (iToRow)];
327 //
328 //iToRow += 32;
329 //tempC0 += tempA6 * B[(jToCol ) + (iToRow)];
330 //tempC1 += tempA6 * B[(jToCol+1 ) + (iToRow)];
331 //tempC2 += tempA6 * B[(jToCol+2 ) + (iToRow)];
332 //tempC3 += tempA6 * B[(jToCol+3 ) + (iToRow)];
333 //tempC4 += tempA6 * B[(jToCol+4 ) + (iToRow)];
334 //tempC5 += tempA6 * B[(jToCol+5 ) + (iToRow)];
335 //tempC6 += tempA6 * B[(jToCol+6 ) + (iToRow)];
336 //tempC7 += tempA6 * B[(jToCol+7 ) + (iToRow)];
337 //
338 //iToRow += 32;
339 //tempC0 += tempA7 * B[(jToCol ) + (iToRow)];
340 //tempC1 += tempA7 * B[(jToCol+1 ) + (iToRow)];
341 //tempC2 += tempA7 * B[(jToCol+2 ) + (iToRow)];
342 //tempC3 += tempA7 * B[(jToCol+3 ) + (iToRow)];
343 //tempC4 += tempA7 * B[(jToCol+4 ) + (iToRow)];
344 //tempC5 += tempA7 * B[(jToCol+5 ) + (iToRow)];
345 //tempC6 += tempA7 * B[(jToCol+6 ) + (iToRow)];
346 //tempC7 += tempA7 * B[(jToCol+7 ) + (iToRow)];
347
348 }
349 C[j ] = tempC0;
350 C[j + 1 ] = tempC1;
351 C[j + 2 ] = tempC2;
352 C[j + 3 ] = tempC3;
353 C[j + 4 ] = tempC4;
354 C[j + 5 ] = tempC5;
355 C[j + 6 ] = tempC6;
356 C[j + 7 ] = tempC7;
357 //C[j + 8 ] = tempC8 ;
358 //C[j + 9 ] = tempC9 ;
359 //C[j + 10] = tempC10;
360 //C[j + 11] = tempC11;
361 //C[j + 12] = tempC12;
362 //C[j + 13] = tempC13;
363 //C[j + 14] = tempC14;
364 //C[j + 15] = tempC15;
365 }
366 }
367
368
369
370 //--------------------------------------------------------------------------
371 // Main
372 //
373 // all threads start executing thread_entry(). Use their "coreid" to
374 // differentiate between threads (each thread is running on a separate core).
375
376 void thread_entry(int cid, int nc)
377 {
378 coreid = cid;
379 ncores = nc;
380
381 // static allocates data in the binary, which is visible to both threads
382 static data_t results_data[ARRAY_SIZE];
383
384
385 //// Execute the provided, naive matmul
386 //barrier();
387 //stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier());
388
389 //
390 //// verify
391 //verify(ARRAY_SIZE, results_data, verify_data);
392 //
393 //// clear results from the first trial
394 //size_t i;
395 //if (coreid == 0)
396 // for (i=0; i < ARRAY_SIZE; i++)
397 // results_data[i] = 0;
398 //barrier();
399
400
401 // Execute your faster matmul
402 barrier();
403 stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier());
404
405 #ifdef DEBUG
406 printArray("results:", ARRAY_SIZE, results_data);
407 printArray("verify :", ARRAY_SIZE, verify_data);
408 #endif
409
410 // verify
411 verify(ARRAY_SIZE, results_data, verify_data);
412 barrier();
413
414 exit(0);
415 }
416