parallel_redux_heterogeneous_tasks_data.c 6.3 KB

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  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2016 Bérangère Subervie
  4. *
  5. * StarPU is free software; you can redistribute it and/or modify
  6. * it under the terms of the GNU Lesser General Public License as published by
  7. * the Free Software Foundation; either version 2.1 of the License, or (at
  8. * your option) any later version.
  9. *
  10. * StarPU is distributed in the hope that it will be useful, but
  11. * WITHOUT ANY WARRANTY; without even the implied warranty of
  12. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
  13. *
  14. * See the GNU Lesser General Public License in COPYING.LGPL for more details.
  15. */
  16. #include <stdbool.h>
  17. #include <starpu.h>
  18. #include "../helper.h"
  19. /* Run a series of tasks with heterogeneous execution time and redux data */
  20. #define TIME 0.010
  21. #ifdef STARPU_QUICK_CHECK
  22. #define TASK_COEFFICIENT 20
  23. #define MARGIN 0.20
  24. #else
  25. #define TASK_COEFFICIENT 100
  26. #define MARGIN 0.10
  27. #endif
  28. #define TIME_CUDA_COEFFICIENT 10
  29. #define TIME_OPENCL_COEFFICIENT 5
  30. #define SECONDS_SCALE_COEFFICIENT_TIMING_NOW 1000000
  31. #define NB_FLOAT 400000
  32. void wait_CPU(void *descr[], void *_args)
  33. {
  34. (void)descr;
  35. (void)_args;
  36. starpu_sleep(TIME);
  37. }
  38. void wait_CUDA(void *descr[], void *_args)
  39. {
  40. (void)descr;
  41. (void)_args;
  42. starpu_sleep(TIME/TIME_CUDA_COEFFICIENT);
  43. }
  44. void wait_OPENCL(void *descr[], void *_args)
  45. {
  46. (void)descr;
  47. (void)_args;
  48. starpu_sleep(TIME/TIME_OPENCL_COEFFICIENT);
  49. }
  50. double cost_function(struct starpu_task *t, struct starpu_perfmodel_arch *a, unsigned i)
  51. {
  52. (void) t; (void) i;
  53. STARPU_ASSERT(a->ndevices == 1);
  54. if (a->devices[0].type == STARPU_CPU_WORKER)
  55. {
  56. STARPU_ASSERT(a->devices[0].ncores == 1);
  57. return TIME * 1000000;
  58. }
  59. else if (a->devices[0].type == STARPU_CUDA_WORKER)
  60. {
  61. return TIME/TIME_CUDA_COEFFICIENT * 1000000;
  62. }
  63. else if (a->devices[0].type == STARPU_OPENCL_WORKER)
  64. {
  65. return TIME/TIME_OPENCL_COEFFICIENT * 1000000;
  66. }
  67. STARPU_ASSERT(0);
  68. return 0.0;
  69. }
  70. static struct starpu_perfmodel perf_model =
  71. {
  72. .type = STARPU_PER_ARCH,
  73. .arch_cost_function = cost_function,
  74. };
  75. static struct starpu_codelet cl =
  76. {
  77. .cpu_funcs = { wait_CPU },
  78. .cuda_funcs = { wait_CUDA },
  79. .opencl_funcs = { wait_OPENCL },
  80. .cpu_funcs_name = { "wait_CPU" },
  81. .nbuffers = 1,
  82. .modes = {STARPU_REDUX},
  83. .flags = STARPU_CODELET_SIMGRID_EXECUTE,
  84. .model = &perf_model,
  85. .name = "cl",
  86. };
  87. static struct starpu_perfmodel perf_model_init =
  88. {
  89. .type = STARPU_PER_ARCH,
  90. .arch_cost_function = cost_function,
  91. };
  92. static struct starpu_codelet cl_init =
  93. {
  94. .cpu_funcs = { wait_CPU },
  95. .cuda_funcs = { wait_CUDA },
  96. .opencl_funcs = { wait_OPENCL },
  97. .cpu_funcs_name = { "wait_CPU" },
  98. .nbuffers = 1,
  99. .modes = {STARPU_RW},
  100. .flags = STARPU_CODELET_SIMGRID_EXECUTE,
  101. .model = &perf_model_init,
  102. .name = "init",
  103. };
  104. static struct starpu_perfmodel perf_model_redux =
  105. {
  106. .type = STARPU_PER_ARCH,
  107. .arch_cost_function = cost_function,
  108. };
  109. static struct starpu_codelet cl_redux =
  110. {
  111. .cpu_funcs = { wait_CPU },
  112. .cuda_funcs = { wait_CUDA },
  113. .opencl_funcs = { wait_OPENCL },
  114. .cpu_funcs_name = { "wait_CPU" },
  115. .nbuffers = 2,
  116. .modes = {STARPU_RW, STARPU_R},
  117. .flags = STARPU_CODELET_SIMGRID_EXECUTE,
  118. .model = &perf_model_redux,
  119. .name = "redux",
  120. };
  121. int main(int argc, char *argv[])
  122. {
  123. int ret;
  124. ret = starpu_initialize(NULL, &argc, &argv);
  125. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  126. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  127. unsigned nb_tasks, nb_workers_CPU, nb_workers_CUDA, nb_workers_OPENCL;
  128. double begin_time, end_time, time_m, time_s, speed_up, expected_speed_up, percentage_expected_speed_up;
  129. bool check, check_sup;
  130. nb_workers_CPU = starpu_worker_get_count_by_type(STARPU_CPU_WORKER);
  131. nb_workers_CUDA = starpu_worker_get_count_by_type(STARPU_CUDA_WORKER);
  132. nb_workers_OPENCL = starpu_worker_get_count_by_type(STARPU_OPENCL_WORKER);
  133. nb_tasks = (nb_workers_CPU + nb_workers_CUDA + nb_workers_OPENCL)*TASK_COEFFICIENT;
  134. /* We consider a vector of float that is initialized just as any of C
  135. * data */
  136. float *vector;
  137. starpu_data_handle_t vector_handle;
  138. unsigned i;
  139. vector = calloc(NB_FLOAT, sizeof(float));
  140. #ifndef STARPU_SIMGRID
  141. for (i = 0; i < NB_FLOAT; i++)
  142. vector[i] = (i+1.0f);
  143. #endif
  144. /* Tell StaPU to associate the "vector" vector with the "vector_handle"
  145. * identifier. When a task needs to access a piece of data, it should
  146. * refer to the handle that is associated to it.
  147. * In the case of the "vector" data interface:
  148. * - the first argument of the registration method is a pointer to the
  149. * handle that should describe the data
  150. * - the second argument is the memory node where the data (ie. "vector")
  151. * resides initially: STARPU_MAIN_RAM stands for an address in main memory, as
  152. * opposed to an adress on a GPU for instance.
  153. * - the third argument is the adress of the vector in RAM
  154. * - the fourth argument is the number of elements in the vector
  155. * - the fifth argument is the size of each element.
  156. */
  157. starpu_vector_data_register(&vector_handle, STARPU_MAIN_RAM, (uintptr_t)vector, NB_FLOAT, sizeof(vector[0]));
  158. starpu_data_set_reduction_methods(vector_handle, &cl_redux, &cl_init);
  159. begin_time = starpu_timing_now();
  160. /*execution des tasks*/
  161. for (i=0; i<nb_tasks; i++)
  162. starpu_task_insert(&cl, STARPU_REDUX, vector_handle, 0);
  163. starpu_data_wont_use(vector_handle);
  164. starpu_task_wait_for_all();
  165. end_time = starpu_timing_now();
  166. starpu_data_unregister(vector_handle);
  167. /*on determine si le temps mesure est satisfaisant ou pas*/
  168. time_m = (end_time - begin_time)/SECONDS_SCALE_COEFFICIENT_TIMING_NOW; //pour ramener en secondes
  169. time_s = nb_tasks * TIME;
  170. speed_up = time_s/time_m;
  171. expected_speed_up = nb_workers_CPU + TIME_CUDA_COEFFICIENT*nb_workers_CUDA + TIME_OPENCL_COEFFICIENT*nb_workers_OPENCL;
  172. percentage_expected_speed_up = 100 * (speed_up/expected_speed_up);
  173. check = speed_up >= ((1 - MARGIN) * expected_speed_up);
  174. check_sup = speed_up <= ((1 + MARGIN) * expected_speed_up);
  175. printf("measured time = %f seconds\nsequential time = %f seconds\nspeed up = %f\nnumber of workers CPU = %u\nnumber of workers CUDA = %u\nnumber of workers OPENCL = %u\nnumber of tasks = %u\nexpected speed up = %f\npercentage of expected speed up %.2f%%\n", time_m, time_s, speed_up, nb_workers_CPU, nb_workers_CUDA, nb_workers_OPENCL, nb_tasks, expected_speed_up, percentage_expected_speed_up);
  176. starpu_shutdown();
  177. free(vector);
  178. //test reussi ou test echoue
  179. if (check && check_sup)
  180. {
  181. return EXIT_SUCCESS;
  182. }
  183. else
  184. {
  185. return EXIT_FAILURE;
  186. }
  187. }