pipeline.c 6.4 KB

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  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2012, 2013, 2014 CNRS
  4. * Copyright (C) 2012, 2014, 2016 Université de Bordeaux
  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. /*
  18. * This examples shows how to submit a pipeline to StarPU with limited buffer
  19. * use, and avoiding submitted all the tasks at once.
  20. *
  21. * This is a dumb example pipeline, depicted here:
  22. *
  23. * x--\
  24. * >==axpy-->sum
  25. * y--/
  26. *
  27. * x and y produce vectors full of x and y values, axpy multiplies them, and sum
  28. * sums it up. We thus have 3 temporary buffers
  29. */
  30. #include <starpu.h>
  31. #include <stdint.h>
  32. #include <semaphore.h>
  33. #include <common/blas.h>
  34. #ifdef STARPU_USE_CUDA
  35. #include <cublas.h>
  36. #endif
  37. #define FPRINTF(ofile, fmt, ...) do { if (!getenv("STARPU_SSILENT")) {fprintf(ofile, fmt, ## __VA_ARGS__); }} while(0)
  38. /* Vector size */
  39. #ifdef STARPU_QUICK_CHECK
  40. #define N 16
  41. #else
  42. #define N 1048576
  43. #endif
  44. /* Number of iteration buffers, and thus overlapped pipeline iterations */
  45. #define K 16
  46. /* Number of concurrently submitted pipeline iterations */
  47. #define C 64
  48. /* Number of iterations */
  49. #define L 256
  50. /* X / Y codelets */
  51. void pipeline_cpu_x(void *descr[], void *args)
  52. {
  53. float x;
  54. float *val = (float *) STARPU_VECTOR_GET_PTR(descr[0]);
  55. int n = STARPU_VECTOR_GET_NX(descr[0]);
  56. int i;
  57. starpu_codelet_unpack_args(args, &x);
  58. for (i = 0; i < n ; i++)
  59. val[i] = x;
  60. }
  61. static struct starpu_perfmodel pipeline_model_x =
  62. {
  63. .type = STARPU_HISTORY_BASED,
  64. .symbol = "pipeline_model_x"
  65. };
  66. static struct starpu_codelet pipeline_codelet_x =
  67. {
  68. .cpu_funcs = {pipeline_cpu_x},
  69. .cpu_funcs_name = {"pipeline_cpu_x"},
  70. .nbuffers = 1,
  71. .modes = {STARPU_W},
  72. .model = &pipeline_model_x
  73. };
  74. /* axpy codelets */
  75. void pipeline_cpu_axpy(void *descr[], void *arg)
  76. {
  77. float *x = (float *) STARPU_VECTOR_GET_PTR(descr[0]);
  78. float *y = (float *) STARPU_VECTOR_GET_PTR(descr[1]);
  79. int n = STARPU_VECTOR_GET_NX(descr[0]);
  80. STARPU_SAXPY(n, 1., x, 1, y, 1);
  81. }
  82. #ifdef STARPU_USE_CUDA
  83. void pipeline_cublas_axpy(void *descr[], void *arg)
  84. {
  85. float *x = (float *) STARPU_VECTOR_GET_PTR(descr[0]);
  86. float *y = (float *) STARPU_VECTOR_GET_PTR(descr[1]);
  87. int n = STARPU_VECTOR_GET_NX(descr[0]);
  88. starpu_cublas_set_stream();
  89. cublasSaxpy(n, 1., x, 1, y, 1);
  90. cudaStreamSynchronize(starpu_cuda_get_local_stream());
  91. }
  92. #endif
  93. static struct starpu_perfmodel pipeline_model_axpy =
  94. {
  95. .type = STARPU_HISTORY_BASED,
  96. .symbol = "pipeline_model_axpy"
  97. };
  98. static struct starpu_codelet pipeline_codelet_axpy =
  99. {
  100. .cpu_funcs = {pipeline_cpu_axpy},
  101. .cpu_funcs_name = {"pipeline_cpu_axpy"},
  102. #ifdef STARPU_USE_CUDA
  103. .cuda_funcs = {pipeline_cublas_axpy},
  104. #endif
  105. .nbuffers = 2,
  106. .modes = {STARPU_R, STARPU_RW},
  107. .model = &pipeline_model_axpy
  108. };
  109. /* sum codelet */
  110. void pipeline_cpu_sum(void *descr[], void *_args)
  111. {
  112. float *x = (float *) STARPU_VECTOR_GET_PTR(descr[0]);
  113. int n = STARPU_VECTOR_GET_NX(descr[0]);
  114. float y;
  115. y = STARPU_SASUM(n, x, 1);
  116. FPRINTF(stderr,"CPU finished with %f\n", y);
  117. }
  118. #ifdef STARPU_USE_CUDA
  119. void pipeline_cublas_sum(void *descr[], void *arg)
  120. {
  121. float *x = (float *) STARPU_VECTOR_GET_PTR(descr[0]);
  122. int n = STARPU_VECTOR_GET_NX(descr[0]);
  123. float y;
  124. starpu_cublas_set_stream();
  125. y = cublasSasum(n, x, 1);
  126. cudaStreamSynchronize(starpu_cuda_get_local_stream());
  127. FPRINTF(stderr,"CUBLAS finished with %f\n", y);
  128. }
  129. #endif
  130. static struct starpu_perfmodel pipeline_model_sum =
  131. {
  132. .type = STARPU_HISTORY_BASED,
  133. .symbol = "pipeline_model_sum"
  134. };
  135. static struct starpu_codelet pipeline_codelet_sum =
  136. {
  137. .cpu_funcs = {pipeline_cpu_sum},
  138. .cpu_funcs_name = {"pipeline_cpu_sum"},
  139. #ifdef STARPU_USE_CUDA
  140. .cuda_funcs = {pipeline_cublas_sum},
  141. #endif
  142. .nbuffers = 1,
  143. .modes = {STARPU_R},
  144. .model = &pipeline_model_sum
  145. };
  146. int main(void)
  147. {
  148. int ret = 0;
  149. int k, l, c;
  150. starpu_data_handle_t buffersX[K], buffersY[K], buffersP[K];
  151. sem_t sems[C];
  152. ret = starpu_init(NULL);
  153. if (ret == -ENODEV)
  154. exit(77);
  155. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  156. starpu_cublas_init();
  157. /* Initialize the K temporary buffers. No need to allocate it ourselves
  158. * Since it's the X and Y kernels which will fill the initial values. */
  159. for (k = 0; k < K; k++)
  160. {
  161. starpu_vector_data_register(&buffersX[k], -1, 0, N, sizeof(float));
  162. starpu_vector_data_register(&buffersY[k], -1, 0, N, sizeof(float));
  163. starpu_vector_data_register(&buffersP[k], -1, 0, N, sizeof(float));
  164. }
  165. /* Initialize way to wait for the C previous concurrent stages */
  166. for (c = 0; c < C; c++)
  167. sem_init(&sems[c], 0, 0);
  168. /* Submits the l pipeline stages */
  169. for (l = 0; l < L; l++)
  170. {
  171. float x = l;
  172. float y = 2*l;
  173. /* First wait for the C previous concurrent stages */
  174. if (l >= C)
  175. {
  176. starpu_do_schedule();
  177. sem_wait(&sems[l%C]);
  178. }
  179. /* Now submit the next stage */
  180. ret = starpu_task_insert(&pipeline_codelet_x,
  181. STARPU_W, buffersX[l%K],
  182. STARPU_VALUE, &x, sizeof(x),
  183. STARPU_TAG_ONLY, (starpu_tag_t) (100*l),
  184. 0);
  185. if (ret == -ENODEV) goto enodev;
  186. STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_insert x");
  187. ret = starpu_task_insert(&pipeline_codelet_x,
  188. STARPU_W, buffersY[l%K],
  189. STARPU_VALUE, &y, sizeof(y),
  190. STARPU_TAG_ONLY, (starpu_tag_t) (100*l+1),
  191. 0);
  192. if (ret == -ENODEV) goto enodev;
  193. STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_insert y");
  194. ret = starpu_task_insert(&pipeline_codelet_axpy,
  195. STARPU_R, buffersX[l%K],
  196. STARPU_RW, buffersY[l%K],
  197. STARPU_TAG_ONLY, (starpu_tag_t) l,
  198. 0);
  199. if (ret == -ENODEV) goto enodev;
  200. STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_insert axpy");
  201. ret = starpu_task_insert(&pipeline_codelet_sum,
  202. STARPU_R, buffersY[l%K],
  203. STARPU_CALLBACK_WITH_ARG, (void (*)(void*))sem_post, &sems[l%C],
  204. STARPU_TAG_ONLY, (starpu_tag_t) l,
  205. 0);
  206. if (ret == -ENODEV) goto enodev;
  207. STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_insert sum");
  208. }
  209. starpu_task_wait_for_all();
  210. enodev:
  211. for (k = 0; k < K; k++)
  212. {
  213. starpu_data_unregister(buffersX[k]);
  214. starpu_data_unregister(buffersY[k]);
  215. starpu_data_unregister(buffersP[k]);
  216. }
  217. starpu_shutdown();
  218. return (ret == -ENODEV ? 77 : 0);
  219. }