cholesky_implicit.c 9.3 KB

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  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2009-2013 Université de Bordeaux 1
  4. * Copyright (C) 2010 Mehdi Juhoor <mjuhoor@gmail.com>
  5. * Copyright (C) 2010, 2011, 2012 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 "cholesky.h"
  19. #include "../sched_ctx_utils/sched_ctx_utils.h"
  20. /*
  21. * Create the codelets
  22. */
  23. struct starpu_perfmodel chol_model_11;
  24. struct starpu_perfmodel chol_model_21;
  25. struct starpu_perfmodel chol_model_22;
  26. static struct starpu_codelet cl11 =
  27. {
  28. .type = STARPU_SEQ,
  29. .cpu_funcs = {chol_cpu_codelet_update_u11, NULL},
  30. #ifdef STARPU_USE_CUDA
  31. .cuda_funcs = {chol_cublas_codelet_update_u11, NULL},
  32. #elif defined(STARPU_SIMGRID)
  33. .cuda_funcs = {(void*)1, NULL},
  34. #endif
  35. .nbuffers = 1,
  36. .modes = {STARPU_RW},
  37. .model = &chol_model_11
  38. };
  39. static struct starpu_codelet cl21 =
  40. {
  41. .type = STARPU_SEQ,
  42. .cpu_funcs = {chol_cpu_codelet_update_u21, NULL},
  43. #ifdef STARPU_USE_CUDA
  44. .cuda_funcs = {chol_cublas_codelet_update_u21, NULL},
  45. #elif defined(STARPU_SIMGRID)
  46. .cuda_funcs = {(void*)1, NULL},
  47. #endif
  48. .nbuffers = 2,
  49. .modes = {STARPU_R, STARPU_RW},
  50. .model = &chol_model_21
  51. };
  52. static struct starpu_codelet cl22 =
  53. {
  54. .type = STARPU_SEQ,
  55. .max_parallelism = INT_MAX,
  56. .cpu_funcs = {chol_cpu_codelet_update_u22, NULL},
  57. #ifdef STARPU_USE_CUDA
  58. .cuda_funcs = {chol_cublas_codelet_update_u22, NULL},
  59. #elif defined(STARPU_SIMGRID)
  60. .cuda_funcs = {(void*)1, NULL},
  61. #endif
  62. .nbuffers = 3,
  63. .modes = {STARPU_R, STARPU_R, STARPU_RW},
  64. .model = &chol_model_22
  65. };
  66. /*
  67. * code to bootstrap the factorization
  68. * and construct the DAG
  69. */
  70. static void callback_turn_spmd_on(void *arg STARPU_ATTRIBUTE_UNUSED)
  71. {
  72. cl22.type = STARPU_SPMD;
  73. }
  74. static int _cholesky(starpu_data_handle_t dataA, unsigned nblocks)
  75. {
  76. int ret;
  77. double start;
  78. double end;
  79. unsigned i,j,k;
  80. unsigned long n = starpu_matrix_get_nx(dataA);
  81. unsigned long nn = n/nblocks;
  82. int prio_level = noprio?STARPU_DEFAULT_PRIO:STARPU_MAX_PRIO;
  83. start = starpu_timing_now();
  84. if (bound || bound_lp || bound_mps)
  85. starpu_bound_start(bound_deps, 0);
  86. /* create all the DAG nodes */
  87. for (k = 0; k < nblocks; k++)
  88. {
  89. starpu_data_handle_t sdatakk = starpu_data_get_sub_data(dataA, 2, k, k);
  90. ret = starpu_insert_task(&cl11,
  91. STARPU_PRIORITY, prio_level,
  92. STARPU_RW, sdatakk,
  93. STARPU_CALLBACK, (k == 3*nblocks/4)?callback_turn_spmd_on:NULL,
  94. STARPU_FLOPS, (double) FLOPS_SPOTRF(nn),
  95. 0);
  96. if (ret == -ENODEV) return 77;
  97. STARPU_CHECK_RETURN_VALUE(ret, "starpu_insert_task");
  98. for (j = k+1; j<nblocks; j++)
  99. {
  100. starpu_data_handle_t sdatakj = starpu_data_get_sub_data(dataA, 2, k, j);
  101. ret = starpu_insert_task(&cl21,
  102. STARPU_PRIORITY, (j == k+1)?prio_level:STARPU_DEFAULT_PRIO,
  103. STARPU_R, sdatakk,
  104. STARPU_RW, sdatakj,
  105. STARPU_FLOPS, (double) FLOPS_STRSM(nn, nn),
  106. 0);
  107. if (ret == -ENODEV) return 77;
  108. STARPU_CHECK_RETURN_VALUE(ret, "starpu_insert_task");
  109. for (i = k+1; i<nblocks; i++)
  110. {
  111. if (i <= j)
  112. {
  113. starpu_data_handle_t sdataki = starpu_data_get_sub_data(dataA, 2, k, i);
  114. starpu_data_handle_t sdataij = starpu_data_get_sub_data(dataA, 2, i, j);
  115. ret = starpu_insert_task(&cl22,
  116. STARPU_PRIORITY, ((i == k+1) && (j == k+1))?prio_level:STARPU_DEFAULT_PRIO,
  117. STARPU_R, sdataki,
  118. STARPU_R, sdatakj,
  119. STARPU_RW, sdataij,
  120. STARPU_FLOPS, (double) FLOPS_SGEMM(nn, nn, nn),
  121. 0);
  122. if (ret == -ENODEV) return 77;
  123. STARPU_CHECK_RETURN_VALUE(ret, "starpu_insert_task");
  124. }
  125. }
  126. }
  127. }
  128. starpu_task_wait_for_all();
  129. if (bound || bound_lp || bound_mps)
  130. starpu_bound_stop();
  131. end = starpu_timing_now();
  132. double timing = end - start;
  133. double flop = FLOPS_SPOTRF(n);
  134. if(with_ctxs || with_noctxs || chole1 || chole2)
  135. update_sched_ctx_timing_results((flop/timing/1000.0f), (timing/1000000.0f));
  136. else
  137. {
  138. FPRINTF(stderr, "Computation took (in ms)\n");
  139. FPRINTF(stdout, "%2.2f\n", timing/1000);
  140. FPRINTF(stderr, "Synthetic GFlops : %2.2f\n", (flop/timing/1000.0f));
  141. if (bound_lp)
  142. {
  143. FILE *f = fopen("cholesky.lp", "w");
  144. starpu_bound_print_lp(f);
  145. }
  146. if (bound_mps)
  147. {
  148. FILE *f = fopen("cholesky.mps", "w");
  149. starpu_bound_print_mps(f);
  150. }
  151. if (bound)
  152. {
  153. double res;
  154. starpu_bound_compute(&res, NULL, 0);
  155. FPRINTF(stderr, "Theoretical GFlops: %2.2f\n", (flop/res/1000000.0f));
  156. }
  157. }
  158. return 0;
  159. }
  160. static int cholesky(float *matA, unsigned size, unsigned ld, unsigned nblocks)
  161. {
  162. starpu_data_handle_t dataA;
  163. /* monitor and partition the A matrix into blocks :
  164. * one block is now determined by 2 unsigned (i,j) */
  165. starpu_matrix_data_register(&dataA, STARPU_MAIN_RAM, (uintptr_t)matA, ld, size, size, sizeof(float));
  166. struct starpu_data_filter f =
  167. {
  168. .filter_func = starpu_matrix_filter_vertical_block,
  169. .nchildren = nblocks
  170. };
  171. struct starpu_data_filter f2 =
  172. {
  173. .filter_func = starpu_matrix_filter_block,
  174. .nchildren = nblocks
  175. };
  176. starpu_data_map_filters(dataA, 2, &f, &f2);
  177. int ret = _cholesky(dataA, nblocks);
  178. starpu_data_unpartition(dataA, STARPU_MAIN_RAM);
  179. starpu_data_unregister(dataA);
  180. return ret;
  181. }
  182. static void execute_cholesky(unsigned size, unsigned nblocks)
  183. {
  184. int ret;
  185. float *mat = NULL;
  186. unsigned i,j;
  187. #ifndef STARPU_SIMGRID
  188. starpu_malloc((void **)&mat, (size_t)size*size*sizeof(float));
  189. for (i = 0; i < size; i++)
  190. {
  191. for (j = 0; j < size; j++)
  192. {
  193. mat[j +i*size] = (1.0f/(1.0f+i+j)) + ((i == j)?1.0f*size:0.0f);
  194. /* mat[j +i*size] = ((i == j)?1.0f*size:0.0f); */
  195. }
  196. }
  197. #endif
  198. /* #define PRINT_OUTPUT */
  199. #ifdef PRINT_OUTPUT
  200. FPRINTF(stdout, "Input :\n");
  201. for (j = 0; j < size; j++)
  202. {
  203. for (i = 0; i < size; i++)
  204. {
  205. if (i <= j)
  206. {
  207. FPRINTF(stdout, "%2.2f\t", mat[j +i*size]);
  208. }
  209. else
  210. {
  211. FPRINTF(stdout, ".\t");
  212. }
  213. }
  214. FPRINTF(stdout, "\n");
  215. }
  216. #endif
  217. ret = cholesky(mat, size, size, nblocks);
  218. #ifdef PRINT_OUTPUT
  219. FPRINTF(stdout, "Results :\n");
  220. for (j = 0; j < size; j++)
  221. {
  222. for (i = 0; i < size; i++)
  223. {
  224. if (i <= j)
  225. {
  226. FPRINTF(stdout, "%2.2f\t", mat[j +i*size]);
  227. }
  228. else
  229. {
  230. FPRINTF(stdout, ".\t");
  231. mat[j+i*size] = 0.0f; /* debug */
  232. }
  233. }
  234. FPRINTF(stdout, "\n");
  235. }
  236. #endif
  237. if (check)
  238. {
  239. FPRINTF(stderr, "compute explicit LLt ...\n");
  240. for (j = 0; j < size; j++)
  241. {
  242. for (i = 0; i < size; i++)
  243. {
  244. if (i > j)
  245. {
  246. mat[j+i*size] = 0.0f; /* debug */
  247. }
  248. }
  249. }
  250. float *test_mat = malloc(size*size*sizeof(float));
  251. STARPU_ASSERT(test_mat);
  252. SSYRK("L", "N", size, size, 1.0f,
  253. mat, size, 0.0f, test_mat, size);
  254. FPRINTF(stderr, "comparing results ...\n");
  255. #ifdef PRINT_OUTPUT
  256. for (j = 0; j < size; j++)
  257. {
  258. for (i = 0; i < size; i++)
  259. {
  260. if (i <= j)
  261. {
  262. FPRINTF(stdout, "%2.2f\t", test_mat[j +i*size]);
  263. }
  264. else
  265. {
  266. FPRINTF(stdout, ".\t");
  267. }
  268. }
  269. FPRINTF(stdout, "\n");
  270. }
  271. #endif
  272. for (j = 0; j < size; j++)
  273. {
  274. for (i = 0; i < size; i++)
  275. {
  276. if (i <= j)
  277. {
  278. float orig = (1.0f/(1.0f+i+j)) + ((i == j)?1.0f*size:0.0f);
  279. float err = abs(test_mat[j +i*size] - orig);
  280. if (err > 0.00001)
  281. {
  282. FPRINTF(stderr, "Error[%u, %u] --> %2.2f != %2.2f (err %2.2f)\n", i, j, test_mat[j +i*size], orig, err);
  283. assert(0);
  284. }
  285. }
  286. }
  287. }
  288. free(test_mat);
  289. }
  290. starpu_free(mat);
  291. }
  292. int main(int argc, char **argv)
  293. {
  294. /* create a simple definite positive symetric matrix example
  295. *
  296. * Hilbert matrix : h(i,j) = 1/(i+j+1)
  297. * */
  298. parse_args(argc, argv);
  299. if(with_ctxs || with_noctxs || chole1 || chole2)
  300. parse_args_ctx(argc, argv);
  301. int ret;
  302. ret = starpu_init(NULL);
  303. if (ret == -ENODEV)
  304. return 77;
  305. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  306. #ifdef STARPU_USE_CUDA
  307. initialize_chol_model(&chol_model_11,"chol_model_11",cpu_chol_task_11_cost,cuda_chol_task_11_cost);
  308. initialize_chol_model(&chol_model_21,"chol_model_21",cpu_chol_task_21_cost,cuda_chol_task_21_cost);
  309. initialize_chol_model(&chol_model_22,"chol_model_22",cpu_chol_task_22_cost,cuda_chol_task_22_cost);
  310. #else
  311. initialize_chol_model(&chol_model_11,"chol_model_11",cpu_chol_task_11_cost,NULL);
  312. initialize_chol_model(&chol_model_21,"chol_model_21",cpu_chol_task_21_cost,NULL);
  313. initialize_chol_model(&chol_model_22,"chol_model_22",cpu_chol_task_22_cost,NULL);
  314. #endif
  315. starpu_cublas_init();
  316. if(with_ctxs)
  317. {
  318. construct_contexts(execute_cholesky);
  319. start_2benchs(execute_cholesky);
  320. }
  321. else if(with_noctxs)
  322. start_2benchs(execute_cholesky);
  323. else if(chole1)
  324. start_1stbench(execute_cholesky);
  325. else if(chole2)
  326. start_2ndbench(execute_cholesky);
  327. else
  328. execute_cholesky(size, nblocks);
  329. starpu_cublas_shutdown();
  330. starpu_shutdown();
  331. return ret;
  332. }