parallel_independent_homogeneous_tasks_data.c 4.6 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 independent tasks with homogeneous execution time and independent 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 SECONDS_SCALE_COEFFICIENT_TIMING_NOW 1000000
  29. #define NB_FLOAT 4000000
  30. void wait_homogeneous(void *descr[] STARPU_ATTRIBUTE_UNUSED, void *_args){
  31. starpu_sleep(TIME);
  32. }
  33. double cost_function(struct starpu_task *t, struct starpu_perfmodel_arch *a, unsigned i)
  34. {
  35. return TIME * 1000000;
  36. }
  37. static struct starpu_perfmodel perf_model =
  38. {
  39. .type = STARPU_PER_ARCH,
  40. .arch_cost_function = cost_function,
  41. };
  42. static struct starpu_codelet cl =
  43. {
  44. .cpu_funcs = { wait_homogeneous },
  45. .cuda_funcs = { wait_homogeneous },
  46. .opencl_funcs = { wait_homogeneous },
  47. .cpu_funcs_name = { "wait_homogeneous" },
  48. .nbuffers = 1,
  49. .modes = {STARPU_RW},
  50. .flags = STARPU_CODELET_SIMGRID_EXECUTE,
  51. .model = &perf_model,
  52. };
  53. int main(int argc, char *argv[]){
  54. int ret;
  55. ret = starpu_initialize(NULL, &argc, &argv);
  56. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  57. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  58. unsigned nb_tasks, nb_workers;
  59. double begin_time, end_time, time_m, time_s, speed_up, expected_speed_up, percentage_expected_speed_up;
  60. bool check, check_sup;
  61. 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);
  62. nb_tasks = nb_workers*TASK_COEFFICIENT;
  63. /* We consider a vector of float that is initialized just as any of C
  64. * data */
  65. float *vector[nb_tasks];
  66. starpu_data_handle_t vector_handle[nb_tasks];
  67. unsigned i,j;
  68. for (j = 0; j < nb_tasks; j++)
  69. {
  70. vector[j] = malloc(NB_FLOAT * sizeof(float));
  71. #ifndef STARPU_SIMGRID
  72. for (i = 0; i < NB_FLOAT; i++)
  73. vector[j][i] = (i+1.0f);
  74. #endif
  75. /* Tell StaPU to associate the "vector" vector with the "vector_handle"
  76. * identifier. When a task needs to access a piece of data, it should
  77. * refer to the handle that is associated to it.
  78. * In the case of the "vector" data interface:
  79. * - the first argument of the registration method is a pointer to the
  80. * handle that should describe the data
  81. * - the second argument is the memory node where the data (ie. "vector")
  82. * resides initially: STARPU_MAIN_RAM stands for an address in main memory, as
  83. * opposed to an adress on a GPU for instance.
  84. * - the third argument is the adress of the vector in RAM
  85. * - the fourth argument is the number of elements in the vector
  86. * - the fifth argument is the size of each element.
  87. */
  88. starpu_vector_data_register(&vector_handle[j], STARPU_MAIN_RAM, (uintptr_t)vector[j], NB_FLOAT, sizeof(vector[0][0]));
  89. }
  90. begin_time = starpu_timing_now();
  91. /*execution des tasks*/
  92. for (i=0; i<nb_tasks; i++){
  93. starpu_task_insert(&cl, STARPU_RW, vector_handle[i], 0);
  94. starpu_data_wont_use(vector_handle[i]);
  95. }
  96. starpu_task_wait_for_all();
  97. end_time = starpu_timing_now();
  98. for (j = 0; j < nb_tasks; j++)
  99. starpu_data_unregister(vector_handle[j]);
  100. /*on determine si le temps mesure est satisfaisant ou pas*/
  101. time_m = (end_time - begin_time)/SECONDS_SCALE_COEFFICIENT_TIMING_NOW; //pour ramener en secondes
  102. time_s = nb_tasks * TIME;
  103. speed_up = time_s/time_m;
  104. expected_speed_up = nb_workers;
  105. percentage_expected_speed_up = 100 * (speed_up/expected_speed_up);
  106. check = speed_up >= ((1 - MARGIN) * expected_speed_up);
  107. check_sup = speed_up <= ((1 + MARGIN) * expected_speed_up);
  108. printf("measured time = %f seconds\nsequential time = %f seconds\nspeed up = %f\nnumber of workers = %d\nnumber of tasks = %d\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);
  109. starpu_shutdown();
  110. for (j = 0; j < nb_tasks; j++)
  111. free(vector[j]);
  112. if (check && check_sup){ //test reussi ou test echoue
  113. return EXIT_SUCCESS;
  114. }
  115. else{
  116. return EXIT_FAILURE;
  117. }
  118. }