dw_cholesky_grain.c 8.9 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384
  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2009, 2010 Université de Bordeaux 1
  4. * Copyright (C) 2010 Mehdi Juhoor <mjuhoor@gmail.com>
  5. * Copyright (C) 2010 Centre National de la Recherche Scientifique
  6. *
  7. * StarPU is free software; you can redistribute it and/or modify
  8. * it under the terms of the GNU Lesser General Public License as published by
  9. * the Free Software Foundation; either version 2.1 of the License, or (at
  10. * your option) any later version.
  11. *
  12. * StarPU is distributed in the hope that it will be useful, but
  13. * WITHOUT ANY WARRANTY; without even the implied warranty of
  14. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
  15. *
  16. * See the GNU Lesser General Public License in COPYING.LGPL for more details.
  17. */
  18. #include "dw_cholesky.h"
  19. #include "dw_cholesky_models.h"
  20. /*
  21. * Some useful functions
  22. */
  23. static struct starpu_task *create_task(starpu_tag_t id)
  24. {
  25. struct starpu_task *task = starpu_task_create();
  26. task->cl_arg = NULL;
  27. task->use_tag = 1;
  28. task->tag_id = id;
  29. return task;
  30. }
  31. /*
  32. * Create the codelets
  33. */
  34. static starpu_codelet cl11 =
  35. {
  36. .where = STARPU_CPU|STARPU_CUDA,
  37. .cpu_func = chol_cpu_codelet_update_u11,
  38. #ifdef STARPU_USE_CUDA
  39. .cuda_func = chol_cublas_codelet_update_u11,
  40. #endif
  41. .nbuffers = 1,
  42. .model = &chol_model_11
  43. };
  44. static struct starpu_task * create_task_11(starpu_data_handle dataA, unsigned k, unsigned reclevel)
  45. {
  46. // printf("task 11 k = %d TAG = %llx\n", k, (TAG11(k)));
  47. struct starpu_task *task = create_task(TAG11_AUX(k, reclevel));
  48. task->cl = &cl11;
  49. /* which sub-data is manipulated ? */
  50. task->buffers[0].handle = starpu_data_get_sub_data(dataA, 2, k, k);
  51. task->buffers[0].mode = STARPU_RW;
  52. /* this is an important task */
  53. task->priority = STARPU_MAX_PRIO;
  54. /* enforce dependencies ... */
  55. if (k > 0) {
  56. starpu_tag_declare_deps(TAG11_AUX(k, reclevel), 1, TAG22_AUX(k-1, k, k, reclevel));
  57. }
  58. return task;
  59. }
  60. static starpu_codelet cl21 =
  61. {
  62. .where = STARPU_CPU|STARPU_CUDA,
  63. .cpu_func = chol_cpu_codelet_update_u21,
  64. #ifdef STARPU_USE_CUDA
  65. .cuda_func = chol_cublas_codelet_update_u21,
  66. #endif
  67. .nbuffers = 2,
  68. .model = &chol_model_21
  69. };
  70. static void create_task_21(starpu_data_handle dataA, unsigned k, unsigned j, unsigned reclevel)
  71. {
  72. struct starpu_task *task = create_task(TAG21_AUX(k, j, reclevel));
  73. task->cl = &cl21;
  74. /* which sub-data is manipulated ? */
  75. task->buffers[0].handle = starpu_data_get_sub_data(dataA, 2, k, k);
  76. task->buffers[0].mode = STARPU_R;
  77. task->buffers[1].handle = starpu_data_get_sub_data(dataA, 2, k, j);
  78. task->buffers[1].mode = STARPU_RW;
  79. if (j == k+1) {
  80. task->priority = STARPU_MAX_PRIO;
  81. }
  82. /* enforce dependencies ... */
  83. if (k > 0) {
  84. starpu_tag_declare_deps(TAG21_AUX(k, j, reclevel), 2, TAG11_AUX(k, reclevel), TAG22_AUX(k-1, k, j, reclevel));
  85. }
  86. else {
  87. starpu_tag_declare_deps(TAG21_AUX(k, j, reclevel), 1, TAG11_AUX(k, reclevel));
  88. }
  89. starpu_task_submit(task);
  90. }
  91. static starpu_codelet cl22 =
  92. {
  93. .where = STARPU_CPU|STARPU_CUDA,
  94. .cpu_func = chol_cpu_codelet_update_u22,
  95. #ifdef STARPU_USE_CUDA
  96. .cuda_func = chol_cublas_codelet_update_u22,
  97. #endif
  98. .nbuffers = 3,
  99. .model = &chol_model_22
  100. };
  101. static void create_task_22(starpu_data_handle dataA, unsigned k, unsigned i, unsigned j, unsigned reclevel)
  102. {
  103. // printf("task 22 k,i,j = %d,%d,%d TAG = %llx\n", k,i,j, TAG22_AUX(k,i,j));
  104. struct starpu_task *task = create_task(TAG22_AUX(k, i, j, reclevel));
  105. task->cl = &cl22;
  106. /* which sub-data is manipulated ? */
  107. task->buffers[0].handle = starpu_data_get_sub_data(dataA, 2, k, i);
  108. task->buffers[0].mode = STARPU_R;
  109. task->buffers[1].handle = starpu_data_get_sub_data(dataA, 2, k, j);
  110. task->buffers[1].mode = STARPU_R;
  111. task->buffers[2].handle = starpu_data_get_sub_data(dataA, 2, i, j);
  112. task->buffers[2].mode = STARPU_RW;
  113. if ( (i == k + 1) && (j == k +1) ) {
  114. task->priority = STARPU_MAX_PRIO;
  115. }
  116. /* enforce dependencies ... */
  117. if (k > 0) {
  118. starpu_tag_declare_deps(TAG22_AUX(k, i, j, reclevel), 3, TAG22_AUX(k-1, i, j, reclevel), TAG21_AUX(k, i, reclevel), TAG21_AUX(k, j, reclevel));
  119. }
  120. else {
  121. starpu_tag_declare_deps(TAG22_AUX(k, i, j, reclevel), 2, TAG21_AUX(k, i, reclevel), TAG21_AUX(k, j, reclevel));
  122. }
  123. starpu_task_submit(task);
  124. }
  125. /*
  126. * code to bootstrap the factorization
  127. * and construct the DAG
  128. */
  129. static void _dw_cholesky_grain(float *matA, unsigned size, unsigned ld, unsigned nblocks, unsigned nbigblocks, unsigned reclevel)
  130. {
  131. /* create a new codelet */
  132. struct starpu_task *entry_task = NULL;
  133. /* create all the DAG nodes */
  134. unsigned i,j,k;
  135. starpu_data_handle dataA;
  136. /* monitor and partition the A matrix into blocks :
  137. * one block is now determined by 2 unsigned (i,j) */
  138. starpu_matrix_data_register(&dataA, 0, (uintptr_t)matA, ld, size, size, sizeof(float));
  139. starpu_data_set_sequential_consistency_flag(dataA, 0);
  140. struct starpu_data_filter f;
  141. f.filter_func = starpu_vertical_block_filter_func;
  142. f.nchildren = nblocks;
  143. f.get_nchildren = NULL;
  144. f.get_child_ops = NULL;
  145. struct starpu_data_filter f2;
  146. f2.filter_func = starpu_block_filter_func;
  147. f2.nchildren = nblocks;
  148. f2.get_nchildren = NULL;
  149. f2.get_child_ops = NULL;
  150. starpu_data_map_filters(dataA, 2, &f, &f2);
  151. for (k = 0; k < nbigblocks; k++)
  152. {
  153. struct starpu_task *task = create_task_11(dataA, k, reclevel);
  154. /* we defer the launch of the first task */
  155. if (k == 0) {
  156. entry_task = task;
  157. }
  158. else {
  159. starpu_task_submit(task);
  160. }
  161. for (j = k+1; j<nblocks; j++)
  162. {
  163. create_task_21(dataA, k, j, reclevel);
  164. for (i = k+1; i<nblocks; i++)
  165. {
  166. if (i <= j)
  167. create_task_22(dataA, k, i, j, reclevel);
  168. }
  169. }
  170. }
  171. /* schedule the codelet */
  172. int ret = starpu_task_submit(entry_task);
  173. if (STARPU_UNLIKELY(ret == -ENODEV))
  174. {
  175. fprintf(stderr, "No worker may execute this task\n");
  176. exit(-1);
  177. }
  178. if (nblocks == nbigblocks)
  179. {
  180. /* stall the application until the end of computations */
  181. starpu_tag_wait(TAG11_AUX(nblocks-1, reclevel));
  182. starpu_data_unpartition(dataA, 0);
  183. return;
  184. }
  185. else {
  186. STARPU_ASSERT(reclevel == 0);
  187. unsigned ndeps_tags = (nblocks - nbigblocks)*(nblocks - nbigblocks);
  188. starpu_tag_t *tag_array = malloc(ndeps_tags*sizeof(starpu_tag_t));
  189. STARPU_ASSERT(tag_array);
  190. unsigned ind = 0;
  191. for (i = nbigblocks; i < nblocks; i++)
  192. for (j = nbigblocks; j < nblocks; j++)
  193. {
  194. if (i <= j)
  195. tag_array[ind++] = TAG22_AUX(nbigblocks - 1, i, j, reclevel);
  196. }
  197. starpu_tag_wait_array(ind, tag_array);
  198. free(tag_array);
  199. starpu_data_unpartition(dataA, 0);
  200. starpu_data_unregister(dataA);
  201. float *newmatA = &matA[nbigblocks*(size/nblocks)*(ld+1)];
  202. _dw_cholesky_grain(newmatA, size/nblocks*(nblocks - nbigblocks), ld, (nblocks - nbigblocks)*2, (nblocks - nbigblocks)*2, reclevel+1);
  203. }
  204. }
  205. void initialize_system(float **A, unsigned dim, unsigned pinned)
  206. {
  207. starpu_init(NULL);
  208. starpu_helper_cublas_init();
  209. if (pinned)
  210. {
  211. starpu_data_malloc_pinned_if_possible((void **)A, dim*dim*sizeof(float));
  212. }
  213. else {
  214. *A = malloc(dim*dim*sizeof(float));
  215. }
  216. }
  217. void dw_cholesky_grain(float *matA, unsigned size, unsigned ld, unsigned nblocks, unsigned nbigblocks)
  218. {
  219. struct timeval start;
  220. struct timeval end;
  221. gettimeofday(&start, NULL);
  222. _dw_cholesky_grain(matA, size, ld, nblocks, nbigblocks, 0);
  223. gettimeofday(&end, NULL);
  224. double timing = (double)((end.tv_sec - start.tv_sec)*1000000 + (end.tv_usec - start.tv_usec));
  225. fprintf(stderr, "Computation took (in ms)\n");
  226. printf("%2.2f\n", timing/1000);
  227. double flop = (1.0f*size*size*size)/3.0f;
  228. fprintf(stderr, "Synthetic GFlops : %2.2f\n", (flop/timing/1000.0f));
  229. starpu_helper_cublas_shutdown();
  230. starpu_shutdown();
  231. }
  232. int main(int argc, char **argv)
  233. {
  234. /* create a simple definite positive symetric matrix example
  235. *
  236. * Hilbert matrix : h(i,j) = 1/(i+j+1)
  237. * */
  238. parse_args(argc, argv);
  239. float *mat;
  240. mat = malloc(size*size*sizeof(float));
  241. initialize_system(&mat, size, pinned);
  242. unsigned i,j;
  243. for (i = 0; i < size; i++)
  244. {
  245. for (j = 0; j < size; j++)
  246. {
  247. mat[j +i*size] = (1.0f/(1.0f+i+j)) + ((i == j)?1.0f*size:0.0f);
  248. //mat[j +i*size] = ((i == j)?1.0f*size:0.0f);
  249. }
  250. }
  251. #ifdef CHECK_OUTPUT
  252. printf("Input :\n");
  253. for (j = 0; j < size; j++)
  254. {
  255. for (i = 0; i < size; i++)
  256. {
  257. if (i <= j) {
  258. printf("%2.2f\t", mat[j +i*size]);
  259. }
  260. else {
  261. printf(".\t");
  262. }
  263. }
  264. printf("\n");
  265. }
  266. #endif
  267. dw_cholesky_grain(mat, size, size, nblocks, nbigblocks);
  268. #ifdef CHECK_OUTPUT
  269. printf("Results :\n");
  270. for (j = 0; j < size; j++)
  271. {
  272. for (i = 0; i < size; i++)
  273. {
  274. if (i <= j) {
  275. printf("%2.2f\t", mat[j +i*size]);
  276. }
  277. else {
  278. printf(".\t");
  279. mat[j+i*size] = 0.0f; // debug
  280. }
  281. }
  282. printf("\n");
  283. }
  284. fprintf(stderr, "compute explicit LLt ...\n");
  285. float *test_mat = malloc(size*size*sizeof(float));
  286. STARPU_ASSERT(test_mat);
  287. SSYRK("L", "N", size, size, 1.0f,
  288. mat, size, 0.0f, test_mat, size);
  289. fprintf(stderr, "comparing results ...\n");
  290. for (j = 0; j < size; j++)
  291. {
  292. for (i = 0; i < size; i++)
  293. {
  294. if (i <= j) {
  295. printf("%2.2f\t", test_mat[j +i*size]);
  296. }
  297. else {
  298. printf(".\t");
  299. }
  300. }
  301. printf("\n");
  302. }
  303. #endif
  304. return 0;
  305. }