valid_model.c 4.6 KB

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  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2012-2020 Université de Bordeaux, CNRS (LaBRI UMR 5800), Inria
  4. * Copyright (C) 2013 Thibaut Lambert
  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 <starpu.h>
  18. #include <core/perfmodel/perfmodel.h>
  19. #include "../helper.h"
  20. /*
  21. * Check that measurements get recorded in the performance model
  22. */
  23. void func(void *descr[], void *arg)
  24. {
  25. (void)descr;
  26. (void)arg;
  27. }
  28. static struct starpu_perfmodel rb_model =
  29. {
  30. .type = STARPU_REGRESSION_BASED,
  31. .symbol = "valid_model_regression_based"
  32. };
  33. static struct starpu_perfmodel nlrb_model =
  34. {
  35. .type = STARPU_NL_REGRESSION_BASED,
  36. .symbol = "valid_model_non_linear_regression_based"
  37. };
  38. #if 0
  39. static struct starpu_perfmodel hb_model =
  40. {
  41. .type = STARPU_HISTORY_BASED,
  42. .symbol = "valid_model_history_based"
  43. };
  44. #endif
  45. static struct starpu_codelet mycodelet =
  46. {
  47. .cuda_funcs = {func},
  48. .opencl_funcs = {func},
  49. .cpu_funcs = {func},
  50. .cpu_funcs_name = {"func"},
  51. .nbuffers = 1,
  52. .modes = {STARPU_W}
  53. };
  54. static int submit(struct starpu_codelet *codelet, struct starpu_perfmodel *model)
  55. {
  56. int nloops = 123;
  57. int loop;
  58. starpu_data_handle_t handle;
  59. struct starpu_perfmodel lmodel;
  60. int ret;
  61. int old_nsamples, new_nsamples;
  62. struct starpu_conf conf;
  63. starpu_conf_init(&conf);
  64. conf.sched_policy_name = "eager";
  65. conf.calibrate = 1;
  66. ret = starpu_init(&conf);
  67. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  68. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  69. codelet->model = model;
  70. old_nsamples = 0;
  71. memset(&lmodel, 0, sizeof(struct starpu_perfmodel));
  72. lmodel.type = model->type;
  73. ret = starpu_perfmodel_load_symbol(codelet->model->symbol, &lmodel);
  74. if (ret != 1)
  75. {
  76. int i, impl;
  77. for(i = 0; i < lmodel.state->ncombs; i++)
  78. {
  79. int comb = lmodel.state->combs[i];
  80. for(impl = 0; impl < lmodel.state->nimpls[comb]; impl++)
  81. old_nsamples += lmodel.state->per_arch[comb][impl].regression.nsample;
  82. }
  83. }
  84. starpu_vector_data_register(&handle, -1, (uintptr_t)NULL, 100, sizeof(int));
  85. for (loop = 0; loop < nloops; loop++)
  86. {
  87. ret = starpu_task_insert(codelet, STARPU_W, handle, 0);
  88. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  89. STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");
  90. }
  91. starpu_data_unregister(handle);
  92. starpu_perfmodel_unload_model(&lmodel);
  93. starpu_shutdown(); // To force dumping perf models on disk
  94. // We need to call starpu_init again to initialise values used by perfmodels
  95. ret = starpu_init(NULL);
  96. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  97. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  98. char path[256];
  99. starpu_perfmodel_get_model_path(codelet->model->symbol, path, 256);
  100. FPRINTF(stderr, "Perfmodel File <%s>\n", path);
  101. ret = starpu_perfmodel_load_file(path, &lmodel);
  102. if (ret == 1)
  103. {
  104. FPRINTF(stderr, "The performance model for the symbol <%s> could not be loaded\n", codelet->model->symbol);
  105. starpu_shutdown();
  106. return 1;
  107. }
  108. else
  109. {
  110. int i;
  111. new_nsamples = 0;
  112. for(i = 0; i < lmodel.state->ncombs; i++)
  113. {
  114. int comb = lmodel.state->combs[i];
  115. int impl;
  116. for(impl = 0; impl < lmodel.state->nimpls[comb]; impl++)
  117. new_nsamples += lmodel.state->per_arch[comb][impl].regression.nsample;
  118. }
  119. }
  120. ret = starpu_perfmodel_unload_model(&lmodel);
  121. starpu_shutdown();
  122. if (ret == 1)
  123. {
  124. FPRINTF(stderr, "The performance model for the symbol <%s> could not be UNloaded\n", codelet->model->symbol);
  125. return 1;
  126. }
  127. if (old_nsamples + nloops == new_nsamples)
  128. {
  129. FPRINTF(stderr, "Sampling for <%s> OK %d + %d == %d\n", codelet->model->symbol, old_nsamples, nloops, new_nsamples);
  130. return EXIT_SUCCESS;
  131. }
  132. else
  133. {
  134. FPRINTF(stderr, "Sampling for <%s> failed %d + %d != %d\n", codelet->model->symbol, old_nsamples, nloops, new_nsamples);
  135. return EXIT_FAILURE;
  136. }
  137. }
  138. int main(void)
  139. {
  140. int ret;
  141. /* Use a linear regression model */
  142. ret = submit(&mycodelet, &rb_model);
  143. if (ret) return ret;
  144. /* Use a non-linear regression model */
  145. ret = submit(&mycodelet, &nlrb_model);
  146. if (ret) return ret;
  147. #ifdef STARPU_DEVEL
  148. # warning history based model cannot be validated with regression.nsample
  149. #endif
  150. #if 0
  151. /* Use a history model */
  152. ret = submit(&mycodelet, &hb_model);
  153. if (ret) return ret;
  154. #endif
  155. return EXIT_SUCCESS;
  156. }