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) 2016,2017 CNRS
  4. * Copyright (C) 2016 Université de Bordeaux
  5. * Copyright (C) 2016 Bérangère Subervie
  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 <stdbool.h>
  19. #include <starpu.h>
  20. #include "../helper.h"
  21. /* Run a series of independent tasks with homogeneous execution time and independent data */
  22. #define TIME 0.010
  23. #ifdef STARPU_QUICK_CHECK
  24. #define TASK_COEFFICIENT 20
  25. #define MARGIN 0.20
  26. #else
  27. #define TASK_COEFFICIENT 100
  28. #define MARGIN 0.10
  29. #endif
  30. #define SECONDS_SCALE_COEFFICIENT_TIMING_NOW 1000000
  31. #define NB_FLOAT 4000000
  32. void wait_homogeneous(void *descr[], void *_args)
  33. {
  34. (void)descr;
  35. (void)_args;
  36. starpu_sleep(TIME);
  37. }
  38. double cost_function(struct starpu_task *t, struct starpu_perfmodel_arch *a, unsigned i)
  39. {
  40. (void)t; (void)a; (void)i;
  41. return TIME * 1000000;
  42. }
  43. static struct starpu_perfmodel perf_model =
  44. {
  45. .type = STARPU_PER_ARCH,
  46. .arch_cost_function = cost_function,
  47. };
  48. static struct starpu_codelet cl =
  49. {
  50. .cpu_funcs = { wait_homogeneous },
  51. .cuda_funcs = { wait_homogeneous },
  52. .opencl_funcs = { wait_homogeneous },
  53. .cpu_funcs_name = { "wait_homogeneous" },
  54. .nbuffers = 1,
  55. .modes = {STARPU_RW},
  56. .flags = STARPU_CODELET_SIMGRID_EXECUTE,
  57. .model = &perf_model,
  58. };
  59. int main(int argc, char *argv[])
  60. {
  61. int ret;
  62. ret = starpu_initialize(NULL, &argc, &argv);
  63. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  64. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  65. unsigned nb_tasks, nb_workers;
  66. double begin_time, end_time, time_m, time_s, speed_up, expected_speed_up, percentage_expected_speed_up;
  67. bool check, check_sup;
  68. 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);
  69. nb_tasks = nb_workers*TASK_COEFFICIENT;
  70. /* We consider a vector of float that is initialized just as any of C
  71. * data */
  72. float *vector[nb_tasks];
  73. starpu_data_handle_t vector_handle[nb_tasks];
  74. unsigned i,j;
  75. for (j = 0; j < nb_tasks; j++)
  76. {
  77. vector[j] = malloc(NB_FLOAT * sizeof(float));
  78. #ifndef STARPU_SIMGRID
  79. for (i = 0; i < NB_FLOAT; i++)
  80. vector[j][i] = (i+1.0f);
  81. #endif
  82. /* Tell StaPU to associate the "vector" vector with the "vector_handle"
  83. * identifier. When a task needs to access a piece of data, it should
  84. * refer to the handle that is associated to it.
  85. * In the case of the "vector" data interface:
  86. * - the first argument of the registration method is a pointer to the
  87. * handle that should describe the data
  88. * - the second argument is the memory node where the data (ie. "vector")
  89. * resides initially: STARPU_MAIN_RAM stands for an address in main memory, as
  90. * opposed to an adress on a GPU for instance.
  91. * - the third argument is the adress of the vector in RAM
  92. * - the fourth argument is the number of elements in the vector
  93. * - the fifth argument is the size of each element.
  94. */
  95. starpu_vector_data_register(&vector_handle[j], STARPU_MAIN_RAM, (uintptr_t)vector[j], NB_FLOAT, sizeof(vector[0][0]));
  96. }
  97. begin_time = starpu_timing_now();
  98. /*execution des tasks*/
  99. for (i=0; i<nb_tasks; i++)
  100. {
  101. starpu_task_insert(&cl, STARPU_RW, vector_handle[i], 0);
  102. starpu_data_wont_use(vector_handle[i]);
  103. }
  104. starpu_task_wait_for_all();
  105. end_time = starpu_timing_now();
  106. for (j = 0; j < nb_tasks; j++)
  107. starpu_data_unregister(vector_handle[j]);
  108. /*on determine si le temps mesure est satisfaisant ou pas*/
  109. time_m = (end_time - begin_time)/SECONDS_SCALE_COEFFICIENT_TIMING_NOW; //pour ramener en secondes
  110. time_s = nb_tasks * TIME;
  111. speed_up = time_s/time_m;
  112. expected_speed_up = nb_workers;
  113. percentage_expected_speed_up = 100 * (speed_up/expected_speed_up);
  114. check = speed_up >= ((1 - MARGIN) * expected_speed_up);
  115. check_sup = speed_up <= ((1 + MARGIN) * expected_speed_up);
  116. 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);
  117. starpu_shutdown();
  118. for (j = 0; j < nb_tasks; j++)
  119. free(vector[j]);
  120. //test reussi ou test echoue
  121. if (check && check_sup)
  122. {
  123. return EXIT_SUCCESS;
  124. }
  125. else
  126. {
  127. return EXIT_FAILURE;
  128. }
  129. }