parallel_independent_homogeneous_tasks_data.c 4.8 KB

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  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2016-2021 Université de Bordeaux, CNRS (LaBRI UMR 5800), Inria
  4. * Copyright (C) 2016 Bérangère Subervie
  5. *
  6. * StarPU is free software; you can redistribute it and/or modify
  7. * it under the terms of the GNU Lesser General Public License as published by
  8. * the Free Software Foundation; either version 2.1 of the License, or (at
  9. * your option) any later version.
  10. *
  11. * StarPU is distributed in the hope that it will be useful, but
  12. * WITHOUT ANY WARRANTY; without even the implied warranty of
  13. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
  14. *
  15. * See the GNU Lesser General Public License in COPYING.LGPL for more details.
  16. */
  17. #include <stdbool.h>
  18. #include <starpu.h>
  19. #include "../helper.h"
  20. /* Run a series of independent tasks with homogeneous execution time and independent data */
  21. #define TIME 0.010
  22. #ifdef STARPU_QUICK_CHECK
  23. #define TASK_COEFFICIENT 20
  24. #define MARGIN 0.20
  25. #else
  26. #define TASK_COEFFICIENT 100
  27. #define MARGIN 0.10
  28. #endif
  29. #define SECONDS_SCALE_COEFFICIENT_TIMING_NOW 1000000
  30. #define NB_FLOAT 4000000
  31. void wait_homogeneous(void *descr[], void *_args)
  32. {
  33. (void)descr;
  34. (void)_args;
  35. starpu_sleep(TIME);
  36. }
  37. double cost_function(struct starpu_task *t, struct starpu_perfmodel_arch *a, unsigned i)
  38. {
  39. (void)t; (void)a; (void)i;
  40. return TIME * 1000000;
  41. }
  42. static struct starpu_perfmodel perf_model =
  43. {
  44. .type = STARPU_PER_ARCH,
  45. .arch_cost_function = cost_function,
  46. };
  47. static struct starpu_codelet cl =
  48. {
  49. .cpu_funcs = { wait_homogeneous },
  50. .cuda_funcs = { wait_homogeneous },
  51. .opencl_funcs = { wait_homogeneous },
  52. .cpu_funcs_name = { "wait_homogeneous" },
  53. .nbuffers = 1,
  54. .modes = {STARPU_RW},
  55. .flags = STARPU_CODELET_SIMGRID_EXECUTE,
  56. .model = &perf_model,
  57. };
  58. int main(int argc, char *argv[])
  59. {
  60. int ret;
  61. ret = starpu_initialize(NULL, &argc, &argv);
  62. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  63. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  64. unsigned nb_tasks, nb_workers;
  65. double begin_time, end_time, time_m, time_s, speed_up, expected_speed_up, percentage_expected_speed_up;
  66. bool check, check_sup;
  67. nb_workers = starpu_worker_get_count_by_type(STARPU_CPU_WORKER) + starpu_worker_get_count_by_type(STARPU_CUDA_WORKER) + starpu_worker_get_count_by_type(STARPU_OPENCL_WORKER);
  68. nb_tasks = nb_workers*TASK_COEFFICIENT;
  69. /* We consider a vector of float that is initialized just as any of C
  70. * data */
  71. float *vector[nb_tasks];
  72. starpu_data_handle_t vector_handle[nb_tasks];
  73. unsigned i,j;
  74. for (j = 0; j < nb_tasks; j++)
  75. {
  76. vector[j] = malloc(NB_FLOAT * sizeof(float));
  77. #ifndef STARPU_SIMGRID
  78. for (i = 0; i < NB_FLOAT; i++)
  79. vector[j][i] = (i+1.0f);
  80. #endif
  81. /* Tell StaPU to associate the "vector" vector with the "vector_handle"
  82. * identifier. When a task needs to access a piece of data, it should
  83. * refer to the handle that is associated to it.
  84. * In the case of the "vector" data interface:
  85. * - the first argument of the registration method is a pointer to the
  86. * handle that should describe the data
  87. * - the second argument is the memory node where the data (ie. "vector")
  88. * resides initially: STARPU_MAIN_RAM stands for an address in main memory, as
  89. * opposed to an adress on a GPU for instance.
  90. * - the third argument is the adress of the vector in RAM
  91. * - the fourth argument is the number of elements in the vector
  92. * - the fifth argument is the size of each element.
  93. */
  94. starpu_vector_data_register(&vector_handle[j], STARPU_MAIN_RAM, (uintptr_t)vector[j], NB_FLOAT, sizeof(vector[0][0]));
  95. }
  96. begin_time = starpu_timing_now();
  97. /*execution des tasks*/
  98. for (i=0; i<nb_tasks; i++)
  99. {
  100. starpu_task_insert(&cl, STARPU_RW, vector_handle[i], 0);
  101. starpu_data_wont_use(vector_handle[i]);
  102. }
  103. starpu_task_wait_for_all();
  104. end_time = starpu_timing_now();
  105. for (j = 0; j < nb_tasks; j++)
  106. starpu_data_unregister(vector_handle[j]);
  107. /*on determine si le temps mesure est satisfaisant ou pas*/
  108. time_m = (end_time - begin_time)/SECONDS_SCALE_COEFFICIENT_TIMING_NOW; //pour ramener en secondes
  109. time_s = nb_tasks * TIME;
  110. speed_up = time_s/time_m;
  111. expected_speed_up = nb_workers;
  112. percentage_expected_speed_up = 100 * (speed_up/expected_speed_up);
  113. check = speed_up >= ((1 - MARGIN) * expected_speed_up);
  114. check_sup = speed_up <= ((1 + MARGIN) * expected_speed_up);
  115. printf("measured time = %f seconds\nsequential time = %f seconds\nspeed up = %f\nnumber of workers = %u\nnumber of tasks = %u\nexpected speed up = %f\npercentage of expected speed up %.2f%%\n", time_m, time_s, speed_up, nb_workers, nb_tasks, expected_speed_up, percentage_expected_speed_up);
  116. starpu_shutdown();
  117. for (j = 0; j < nb_tasks; j++)
  118. free(vector[j]);
  119. //test reussi ou test echoue
  120. if (check && check_sup)
  121. {
  122. return EXIT_SUCCESS;
  123. }
  124. else
  125. {
  126. return EXIT_FAILURE;
  127. }
  128. }