cholesky_tag.c 10 KB

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  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2008-2017,2020 Université de Bordeaux
  4. * Copyright (C) 2012,2013 Inria
  5. * Copyright (C) 2010-2013,2015,2017 CNRS
  6. * Copyright (C) 2013 Thibaut Lambert
  7. * Copyright (C) 2010 Mehdi Juhoor
  8. *
  9. * StarPU is free software; you can redistribute it and/or modify
  10. * it under the terms of the GNU Lesser General Public License as published by
  11. * the Free Software Foundation; either version 2.1 of the License, or (at
  12. * your option) any later version.
  13. *
  14. * StarPU is distributed in the hope that it will be useful, but
  15. * WITHOUT ANY WARRANTY; without even the implied warranty of
  16. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
  17. *
  18. * See the GNU Lesser General Public License in COPYING.LGPL for more details.
  19. */
  20. /*
  21. * This version of the Cholesky factorization uses explicit dependency
  22. * declaration through dependency tags.
  23. * It also uses data partitioning to split the matrix into submatrices
  24. */
  25. /* Note: this is using fortran ordering, i.e. column-major ordering, i.e.
  26. * elements with consecutive row number are consecutive in memory */
  27. #include "cholesky.h"
  28. #include <starpu_perfmodel.h>
  29. #if defined(STARPU_USE_CUDA) && defined(STARPU_HAVE_MAGMA)
  30. #include "magma.h"
  31. #endif
  32. /*
  33. * Some useful functions
  34. */
  35. static struct starpu_task *create_task(starpu_tag_t id)
  36. {
  37. struct starpu_task *task = starpu_task_create();
  38. task->cl_arg = NULL;
  39. task->use_tag = 1;
  40. task->tag_id = id;
  41. return task;
  42. }
  43. /*
  44. * Create the codelets
  45. */
  46. static struct starpu_task * create_task_11(starpu_data_handle_t dataA, unsigned k)
  47. {
  48. /* FPRINTF(stdout, "task 11 k = %d TAG = %llx\n", k, (TAG11(k))); */
  49. struct starpu_task *task = create_task(TAG11(k));
  50. task->cl = &cl11;
  51. /* which sub-data is manipulated ? */
  52. task->handles[0] = starpu_data_get_sub_data(dataA, 2, k, k);
  53. /* this is an important task */
  54. if (!noprio_p)
  55. task->priority = STARPU_MAX_PRIO;
  56. /* enforce dependencies ... */
  57. if (k > 0)
  58. {
  59. starpu_tag_declare_deps(TAG11(k), 1, TAG22(k-1, k, k));
  60. }
  61. int n = starpu_matrix_get_nx(task->handles[0]);
  62. task->flops = FLOPS_SPOTRF(n);
  63. return task;
  64. }
  65. static void create_task_21(starpu_data_handle_t dataA, unsigned k, unsigned m)
  66. {
  67. int ret;
  68. struct starpu_task *task = create_task(TAG21(k, m));
  69. task->cl = &cl21;
  70. /* which sub-data is manipulated ? */
  71. task->handles[0] = starpu_data_get_sub_data(dataA, 2, k, k);
  72. task->handles[1] = starpu_data_get_sub_data(dataA, 2, m, k);
  73. if (!noprio_p && (m == k+1))
  74. {
  75. task->priority = STARPU_MAX_PRIO;
  76. }
  77. /* enforce dependencies ... */
  78. if (k > 0)
  79. {
  80. starpu_tag_declare_deps(TAG21(k, m), 2, TAG11(k), TAG22(k-1, m, k));
  81. }
  82. else
  83. {
  84. starpu_tag_declare_deps(TAG21(k, m), 1, TAG11(k));
  85. }
  86. int nx = starpu_matrix_get_nx(task->handles[0]);
  87. task->flops = FLOPS_STRSM(nx, nx);
  88. ret = starpu_task_submit(task);
  89. if (ret != -ENODEV) STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");
  90. return ret;
  91. }
  92. static int create_task_22(starpu_data_handle_t dataA, unsigned k, unsigned m, unsigned n)
  93. {
  94. int ret;
  95. /* FPRINTF(stdout, "task 22 k,n,m = %d,%d,%d TAG = %llx\n", k,m,n, TAG22(k,m,n)); */
  96. struct starpu_task *task = create_task(TAG22(k, m, n));
  97. task->cl = &cl22;
  98. /* which sub-data is manipulated ? */
  99. task->handles[0] = starpu_data_get_sub_data(dataA, 2, n, k);
  100. task->handles[1] = starpu_data_get_sub_data(dataA, 2, m, k);
  101. task->handles[2] = starpu_data_get_sub_data(dataA, 2, m, n);
  102. if (!noprio_p && (n == k + 1) && (m == k +1) )
  103. {
  104. task->priority = STARPU_MAX_PRIO;
  105. }
  106. /* enforce dependencies ... */
  107. if (k > 0)
  108. {
  109. starpu_tag_declare_deps(TAG22(k, m, n), 3, TAG22(k-1, m, n), TAG21(k, n), TAG21(k, m));
  110. }
  111. else
  112. {
  113. starpu_tag_declare_deps(TAG22(k, m, n), 2, TAG21(k, n), TAG21(k, m));
  114. }
  115. int nx = starpu_matrix_get_nx(task->handles[0]);
  116. task->flops = FLOPS_SGEMM(nx, nx, nx);
  117. ret = starpu_task_submit(task);
  118. if (ret != -ENODEV) STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");
  119. return ret;
  120. }
  121. /*
  122. * code to bootstrap the factorization
  123. * and construct the DAG
  124. */
  125. static void _cholesky(starpu_data_handle_t dataA, unsigned nblocks)
  126. {
  127. int ret;
  128. double start;
  129. double end;
  130. struct starpu_task *entry_task = NULL;
  131. /* create all the DAG nodes */
  132. unsigned k, m, n;
  133. start = starpu_timing_now();
  134. for (k = 0; k < nblocks; k++)
  135. {
  136. starpu_iteration_push(k);
  137. struct starpu_task *task = create_task_11(dataA, k);
  138. /* we defer the launch of the first task */
  139. if (k == 0)
  140. {
  141. entry_task = task;
  142. }
  143. else
  144. {
  145. int ret = starpu_task_submit(task);
  146. if (STARPU_UNLIKELY(ret == -ENODEV))
  147. {
  148. FPRINTF(stderr, "No worker may execute this task\n");
  149. exit(0);
  150. }
  151. }
  152. for (m = k+1; m<nblocks; m++)
  153. {
  154. ret = create_task_21(dataA, k, m);
  155. if (ret == -ENODEV) return 77;
  156. for (n = k+1; n<nblocks; n++)
  157. {
  158. if (n <= m)
  159. {
  160. ret = create_task_22(dataA, k, m, n);
  161. if (ret == -ENODEV) return 77;
  162. }
  163. }
  164. }
  165. starpu_iteration_pop();
  166. }
  167. /* schedule the codelet */
  168. ret = starpu_task_submit(entry_task);
  169. if (ret == -ENODEV) return 77;
  170. STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");
  171. /* stall the application until the end of computations */
  172. starpu_tag_wait(TAG11(nblocks-1));
  173. starpu_data_unpartition(dataA, STARPU_MAIN_RAM);
  174. end = starpu_timing_now();
  175. double timing = end - start;
  176. unsigned nx = starpu_matrix_get_nx(dataA);
  177. double flop = (1.0f*nx*nx*nx)/3.0f;
  178. PRINTF("# size\tms\tGFlops\n");
  179. PRINTF("%u\t%.0f\t%.1f\n", nx, timing/1000, (flop/timing/1000.0f));
  180. return 0;
  181. }
  182. static int initialize_system(int argc, char **argv, float **A, unsigned pinned)
  183. {
  184. int ret;
  185. int flags = STARPU_MALLOC_SIMULATION_FOLDED;
  186. #ifdef STARPU_HAVE_MAGMA
  187. magma_init();
  188. #endif
  189. ret = starpu_init(NULL);
  190. if (ret == -ENODEV)
  191. return 77;
  192. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  193. init_sizes();
  194. parse_args(argc, argv);
  195. #ifdef STARPU_USE_CUDA
  196. initialize_chol_model(&chol_model_11,"chol_model_11",cpu_chol_task_11_cost,cuda_chol_task_11_cost);
  197. initialize_chol_model(&chol_model_21,"chol_model_21",cpu_chol_task_21_cost,cuda_chol_task_21_cost);
  198. initialize_chol_model(&chol_model_22,"chol_model_22",cpu_chol_task_22_cost,cuda_chol_task_22_cost);
  199. #else
  200. initialize_chol_model(&chol_model_11,"chol_model_11",cpu_chol_task_11_cost,NULL);
  201. initialize_chol_model(&chol_model_21,"chol_model_21",cpu_chol_task_21_cost,NULL);
  202. initialize_chol_model(&chol_model_22,"chol_model_22",cpu_chol_task_22_cost,NULL);
  203. #endif
  204. starpu_cublas_init();
  205. if (pinned)
  206. flags |= STARPU_MALLOC_PINNED;
  207. starpu_malloc_flags((void **)A, size_p*size_p*sizeof(float), flags);
  208. return 0;
  209. }
  210. static void cholesky(float *matA, unsigned size, unsigned ld, unsigned nblocks)
  211. {
  212. starpu_data_handle_t dataA;
  213. /* monitor and partition the A matrix into blocks :
  214. * one block is now determined by 2 unsigned (m,n) */
  215. starpu_matrix_data_register(&dataA, STARPU_MAIN_RAM, (uintptr_t)matA, ld, size, size, sizeof(float));
  216. starpu_data_set_sequential_consistency_flag(dataA, 0);
  217. /* Split into blocks of complete rows first */
  218. struct starpu_data_filter f =
  219. {
  220. .filter_func = starpu_matrix_filter_block,
  221. .nchildren = nblocks
  222. };
  223. /* Then split rows into tiles */
  224. struct starpu_data_filter f2 =
  225. {
  226. /* Note: here "vertical" is for row-major, we are here using column-major. */
  227. .filter_func = starpu_matrix_filter_vertical_block,
  228. .nchildren = nblocks
  229. };
  230. starpu_data_map_filters(dataA, 2, &f, &f2);
  231. _cholesky(dataA, nblocks);
  232. starpu_data_unregister(dataA);
  233. }
  234. static void shutdown_system(float **matA, unsigned dim, unsigned pinned)
  235. {
  236. int flags = STARPU_MALLOC_SIMULATION_FOLDED;
  237. if (pinned)
  238. flags |= STARPU_MALLOC_PINNED;
  239. starpu_free_flags(*matA, dim*dim*sizeof(float), flags);
  240. starpu_cublas_shutdown();
  241. starpu_shutdown();
  242. }
  243. int main(int argc, char **argv)
  244. {
  245. /* create a simple definite positive symetric matrix example
  246. *
  247. * Hilbert matrix : h(i,j) = 1/(i+j+1)
  248. * */
  249. float *mat = NULL;
  250. int ret = initialize_system(argc, argv, &mat, pinned_p);
  251. if (ret) return ret;
  252. #ifndef STARPU_SIMGRID
  253. unsigned m,n;
  254. for (n = 0; n < size_p; n++)
  255. {
  256. for (m = 0; m < size_p; m++)
  257. {
  258. mat[m +n*size_p] = (1.0f/(1.0f+n+m)) + ((n == m)?1.0f*size_p:0.0f);
  259. /* mat[m +n*size_p] = ((n == m)?1.0f*size_p:0.0f); */
  260. }
  261. }
  262. /* #define PRINT_OUTPUT */
  263. #ifdef PRINT_OUTPUT
  264. FPRINTF(stdout, "Input :\n");
  265. for (m = 0; m < size_p; m++)
  266. {
  267. for (n = 0; n < size_p; n++)
  268. {
  269. if (n <= m)
  270. {
  271. FPRINTF(stdout, "%2.2f\t", mat[m +n*size_p]);
  272. }
  273. else
  274. {
  275. FPRINTF(stdout, ".\t");
  276. }
  277. }
  278. FPRINTF(stdout, "\n");
  279. }
  280. #endif
  281. #endif
  282. cholesky(mat, size_p, size_p, nblocks_p);
  283. #ifndef STARPU_SIMGRID
  284. #ifdef PRINT_OUTPUT
  285. FPRINTF(stdout, "Results :\n");
  286. for (m = 0; m < size_p; m++)
  287. {
  288. for (n = 0; n < size_p; n++)
  289. {
  290. if (n <= m)
  291. {
  292. FPRINTF(stdout, "%2.2f\t", mat[m +n*size_p]);
  293. }
  294. else
  295. {
  296. FPRINTF(stdout, ".\t");
  297. }
  298. }
  299. FPRINTF(stdout, "\n");
  300. }
  301. #endif
  302. if (check_p)
  303. {
  304. FPRINTF(stderr, "compute explicit LLt ...\n");
  305. for (m = 0; m < size_p; m++)
  306. {
  307. for (n = 0; n < size_p; n++)
  308. {
  309. if (n > m)
  310. {
  311. mat[m+n*size_p] = 0.0f; /* debug */
  312. }
  313. }
  314. }
  315. float *test_mat = malloc(size_p*size_p*sizeof(float));
  316. STARPU_ASSERT(test_mat);
  317. STARPU_SSYRK("L", "N", size_p, size_p, 1.0f,
  318. mat, size_p, 0.0f, test_mat, size_p);
  319. FPRINTF(stderr, "comparing results ...\n");
  320. #ifdef PRINT_OUTPUT
  321. for (m = 0; m < size_p; m++)
  322. {
  323. for (n = 0; n < size_p; n++)
  324. {
  325. if (n <= m)
  326. {
  327. FPRINTF(stdout, "%2.2f\t", test_mat[m +n*size_p]);
  328. }
  329. else
  330. {
  331. FPRINTF(stdout, ".\t");
  332. }
  333. }
  334. FPRINTF(stdout, "\n");
  335. }
  336. #endif
  337. for (m = 0; m < size_p; m++)
  338. {
  339. for (n = 0; n < size_p; n++)
  340. {
  341. if (n <= m)
  342. {
  343. float orig = (1.0f/(1.0f+m+n)) + ((m == n)?1.0f*size_p:0.0f);
  344. float err = fabsf(test_mat[m +n*size_p] - orig) / orig;
  345. if (err > 0.0001)
  346. {
  347. FPRINTF(stderr, "Error[%u, %u] --> %2.6f != %2.6f (err %2.6f)\n", m, n, test_mat[m +n*size_p], orig, err);
  348. assert(0);
  349. }
  350. }
  351. }
  352. }
  353. free(test_mat);
  354. }
  355. #endif
  356. shutdown_system(&mat, size_p, pinned_p);
  357. return 0;
  358. }