matrix_as_vector.c 6.8 KB

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  1. /* StarPU --- Runtime system for heterogeneous multicore architectures.
  2. *
  3. * Copyright (C) 2012, 2013, 2014 CNRS
  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 <starpu.h>
  17. #include "../helper.h"
  18. #ifdef STARPU_USE_CUDA
  19. # include <cublas.h>
  20. #endif
  21. /*
  22. * Compare the efficiency of matrix and vector interfaces
  23. */
  24. #ifdef STARPU_QUICK_CHECK
  25. #define LOOPS 10
  26. #elif !defined(STARPU_LONG_CHECK)
  27. #define LOOPS 30
  28. #else
  29. #define LOOPS 100
  30. #endif
  31. void vector_cpu_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  32. {
  33. STARPU_SKIP_IF_VALGRIND;
  34. float *matrix = (float *)STARPU_VECTOR_GET_PTR(descr[0]);
  35. int nx = STARPU_VECTOR_GET_NX(descr[0]);
  36. int i;
  37. float sum=0;
  38. for(i=0 ; i<nx ; i++) sum+=i;
  39. matrix[0] = sum/nx;
  40. }
  41. static
  42. void vector_cuda_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  43. {
  44. #ifdef STARPU_USE_CUDA
  45. STARPU_SKIP_IF_VALGRIND;
  46. float *matrix = (float *)STARPU_VECTOR_GET_PTR(descr[0]);
  47. int nx = STARPU_VECTOR_GET_NX(descr[0]);
  48. float sum = cublasSasum(nx, matrix, 1);
  49. sum /= nx;
  50. cudaMemcpyAsync(matrix, &sum, sizeof(matrix[0]), cudaMemcpyHostToDevice, starpu_cuda_get_local_stream());
  51. #endif /* STARPU_USE_CUDA */
  52. }
  53. void matrix_cpu_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  54. {
  55. STARPU_SKIP_IF_VALGRIND;
  56. float *matrix = (float *)STARPU_MATRIX_GET_PTR(descr[0]);
  57. int nx = STARPU_MATRIX_GET_NX(descr[0]);
  58. int ny = STARPU_MATRIX_GET_NY(descr[0]);
  59. int i;
  60. float sum=0;
  61. for(i=0 ; i<nx*ny ; i++) sum+=i;
  62. matrix[0] = sum / (nx*ny);
  63. }
  64. static
  65. void matrix_cuda_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  66. {
  67. #ifdef STARPU_USE_CUDA
  68. STARPU_SKIP_IF_VALGRIND;
  69. float *matrix = (float *)STARPU_MATRIX_GET_PTR(descr[0]);
  70. int nx = STARPU_MATRIX_GET_NX(descr[0]);
  71. int ny = STARPU_MATRIX_GET_NY(descr[0]);
  72. float sum = cublasSasum(nx*ny, matrix, 1);
  73. sum /= nx*ny;
  74. cudaMemcpyAsync(matrix, &sum, sizeof(matrix[0]), cudaMemcpyHostToDevice, starpu_cuda_get_local_stream());
  75. #endif /* STARPU_USE_CUDA */
  76. }
  77. static
  78. int check_size(int nx, struct starpu_codelet *vector_codelet, struct starpu_codelet *matrix_codelet, char *device_name)
  79. {
  80. float *matrix, mean;
  81. starpu_data_handle_t vector_handle, matrix_handle;
  82. int ret, i, loop, maxloops;
  83. double vector_timing, matrix_timing;
  84. double start;
  85. double end;
  86. starpu_malloc((void **) &matrix, nx*sizeof(matrix[0]));
  87. maxloops = LOOPS;
  88. #ifdef STARPU_HAVE_VALGRIND_H
  89. if (RUNNING_ON_VALGRIND)
  90. /* computations are skipped when running on valgrind, there is no need to have several loops */
  91. maxloops=1;
  92. #endif /* STARPU_HAVE_VALGRIND_H */
  93. start = starpu_timing_now();
  94. for(loop=1 ; loop<=maxloops ; loop++)
  95. {
  96. for(i=0 ; i<nx ; i++) matrix[i] = i;
  97. starpu_vector_data_register(&vector_handle, STARPU_MAIN_RAM, (uintptr_t)matrix, nx, sizeof(matrix[0]));
  98. ret = starpu_task_insert(vector_codelet, STARPU_RW, vector_handle, 0);
  99. starpu_data_unregister(vector_handle);
  100. if (ret == -ENODEV) goto end;
  101. }
  102. end = starpu_timing_now();
  103. vector_timing = end - start;
  104. vector_timing /= maxloops;
  105. mean = matrix[0];
  106. start = starpu_timing_now();
  107. for(loop=1 ; loop<=maxloops ; loop++)
  108. {
  109. for(i=0 ; i<nx ; i++) matrix[i] = i;
  110. starpu_matrix_data_register(&matrix_handle, STARPU_MAIN_RAM, (uintptr_t)matrix, nx/2, nx/2, 2, sizeof(matrix[0]));
  111. ret = starpu_task_insert(matrix_codelet, STARPU_RW, matrix_handle, 0);
  112. starpu_data_unregister(matrix_handle);
  113. if (ret == -ENODEV) goto end;
  114. }
  115. end = starpu_timing_now();
  116. matrix_timing = end - start;
  117. matrix_timing /= maxloops;
  118. if (mean == matrix[0])
  119. {
  120. fprintf(stderr, "%d\t%f\t%f\n", nx, vector_timing, matrix_timing);
  121. {
  122. char *output_dir = getenv("STARPU_BENCH_DIR");
  123. char *bench_id = getenv("STARPU_BENCH_ID");
  124. if (output_dir && bench_id)
  125. {
  126. char file[1024];
  127. FILE *f;
  128. sprintf(file, "%s/matrix_as_vector_%s.dat", output_dir, device_name);
  129. f = fopen(file, "a");
  130. fprintf(f, "%s\t%d\t%f\t%f\n", bench_id, nx, vector_timing, matrix_timing);
  131. fclose(f);
  132. }
  133. }
  134. ret = EXIT_SUCCESS;
  135. }
  136. else
  137. {
  138. FPRINTF(stderr, "Incorrect result nx=%7d --> mean=%7f != %7f\n", nx, matrix[0], mean);
  139. ret = EXIT_FAILURE;
  140. }
  141. end:
  142. starpu_free(matrix);
  143. return ret;
  144. }
  145. #define NX_MIN 1024
  146. #define NX_MAX 1024*1024
  147. static
  148. int check_size_on_device(uint32_t where, char *device_name)
  149. {
  150. int nx, ret;
  151. struct starpu_codelet vector_codelet;
  152. struct starpu_codelet matrix_codelet;
  153. fprintf(stderr, "# Device: %s\n", device_name);
  154. fprintf(stderr, "# nx vector_timing matrix_timing\n");
  155. starpu_codelet_init(&vector_codelet);
  156. vector_codelet.modes[0] = STARPU_RW;
  157. vector_codelet.nbuffers = 1;
  158. if (where == STARPU_CPU) vector_codelet.cpu_funcs[0] = vector_cpu_func;
  159. if (where == STARPU_CUDA) vector_codelet.cuda_funcs[0] = vector_cuda_func;
  160. if (where == STARPU_CUDA) vector_codelet.cuda_flags[0] = STARPU_CUDA_ASYNC;
  161. // if (where == STARPU_OPENCL) vector_codelet.opencl_funcs[0] = vector_opencl_func;
  162. starpu_codelet_init(&matrix_codelet);
  163. matrix_codelet.modes[0] = STARPU_RW;
  164. matrix_codelet.nbuffers = 1;
  165. if (where == STARPU_CPU) matrix_codelet.cpu_funcs[0] = matrix_cpu_func;
  166. if (where == STARPU_CUDA) matrix_codelet.cuda_funcs[0] = matrix_cuda_func;
  167. if (where == STARPU_CUDA) matrix_codelet.cuda_flags[0] = STARPU_CUDA_ASYNC;
  168. // if (where == STARPU_OPENCL) matrix_codelet.opencl_funcs[0] = matrix_opencl_func;
  169. for(nx=NX_MIN ; nx<=NX_MAX ; nx*=2)
  170. {
  171. ret = check_size(nx, &vector_codelet, &matrix_codelet, device_name);
  172. if (ret != EXIT_SUCCESS) break;
  173. }
  174. return ret;
  175. }
  176. int main(int argc, char **argv)
  177. {
  178. int ret;
  179. unsigned devices;
  180. #ifdef STARPU_USE_CUDA
  181. int cublas_version;
  182. #endif
  183. ret = starpu_init(NULL);
  184. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  185. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  186. #ifdef STARPU_USE_CUDA
  187. /* cublasSasum has synchronization issues when using a non-blocking stream */
  188. cublasGetVersion(&cublas_version);
  189. if (cublas_version >= 7050)
  190. starpu_cublas_init();
  191. #endif
  192. devices = starpu_cpu_worker_get_count();
  193. if (devices)
  194. {
  195. ret = check_size_on_device(STARPU_CPU, "STARPU_CPU");
  196. if (ret) goto error;
  197. }
  198. devices = starpu_cuda_worker_get_count();
  199. if (devices)
  200. {
  201. ret = check_size_on_device(STARPU_CUDA, "STARPU_CUDA");
  202. if (ret) goto error;
  203. }
  204. devices = starpu_opencl_worker_get_count();
  205. if (devices)
  206. {
  207. ret = check_size_on_device(STARPU_OPENCL, "STARPU_OPENCL");
  208. if (ret) goto error;
  209. }
  210. error:
  211. if (ret == -ENODEV) ret=STARPU_TEST_SKIPPED;
  212. #ifdef STARPU_USE_CUDA
  213. if (cublas_version >= 7050)
  214. starpu_cublas_shutdown();
  215. #endif
  216. starpu_shutdown();
  217. STARPU_RETURN(ret);
  218. }