matrix_as_vector.c 6.7 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. #define LOOPS 100
  25. void vector_cpu_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  26. {
  27. STARPU_SKIP_IF_VALGRIND;
  28. float *matrix = (float *)STARPU_VECTOR_GET_PTR(descr[0]);
  29. int nx = STARPU_VECTOR_GET_NX(descr[0]);
  30. int i;
  31. float sum=0;
  32. for(i=0 ; i<nx ; i++) sum+=i;
  33. matrix[0] = sum/nx;
  34. }
  35. static
  36. void vector_cuda_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  37. {
  38. #ifdef STARPU_USE_CUDA
  39. STARPU_SKIP_IF_VALGRIND;
  40. float *matrix = (float *)STARPU_VECTOR_GET_PTR(descr[0]);
  41. int nx = STARPU_VECTOR_GET_NX(descr[0]);
  42. float sum = cublasSasum(nx, matrix, 1);
  43. sum /= nx;
  44. cudaMemcpyAsync(matrix, &sum, sizeof(matrix[0]), cudaMemcpyHostToDevice, starpu_cuda_get_local_stream());
  45. #endif /* STARPU_USE_CUDA */
  46. }
  47. void matrix_cpu_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  48. {
  49. STARPU_SKIP_IF_VALGRIND;
  50. float *matrix = (float *)STARPU_MATRIX_GET_PTR(descr[0]);
  51. int nx = STARPU_MATRIX_GET_NX(descr[0]);
  52. int ny = STARPU_MATRIX_GET_NY(descr[0]);
  53. int i;
  54. float sum=0;
  55. for(i=0 ; i<nx*ny ; i++) sum+=i;
  56. matrix[0] = sum / (nx*ny);
  57. }
  58. static
  59. void matrix_cuda_func(void *descr[], void *cl_arg STARPU_ATTRIBUTE_UNUSED)
  60. {
  61. #ifdef STARPU_USE_CUDA
  62. STARPU_SKIP_IF_VALGRIND;
  63. float *matrix = (float *)STARPU_MATRIX_GET_PTR(descr[0]);
  64. int nx = STARPU_MATRIX_GET_NX(descr[0]);
  65. int ny = STARPU_MATRIX_GET_NY(descr[0]);
  66. float sum = cublasSasum(nx*ny, matrix, 1);
  67. sum /= nx*ny;
  68. cudaMemcpyAsync(matrix, &sum, sizeof(matrix[0]), cudaMemcpyHostToDevice, starpu_cuda_get_local_stream());
  69. #endif /* STARPU_USE_CUDA */
  70. }
  71. static
  72. int check_size(int nx, struct starpu_codelet *vector_codelet, struct starpu_codelet *matrix_codelet, char *device_name)
  73. {
  74. float *matrix, mean;
  75. starpu_data_handle_t vector_handle, matrix_handle;
  76. int ret, i, loop, maxloops;
  77. double vector_timing, matrix_timing;
  78. double start;
  79. double end;
  80. starpu_malloc((void **) &matrix, nx*sizeof(matrix[0]));
  81. maxloops = LOOPS;
  82. #ifdef STARPU_HAVE_VALGRIND_H
  83. if (RUNNING_ON_VALGRIND)
  84. /* computations are skipped when running on valgrind, there is no need to have several loops */
  85. maxloops=1;
  86. #endif /* STARPU_HAVE_VALGRIND_H */
  87. start = starpu_timing_now();
  88. for(loop=1 ; loop<=maxloops ; loop++)
  89. {
  90. for(i=0 ; i<nx ; i++) matrix[i] = i;
  91. starpu_vector_data_register(&vector_handle, STARPU_MAIN_RAM, (uintptr_t)matrix, nx, sizeof(matrix[0]));
  92. ret = starpu_task_insert(vector_codelet, STARPU_RW, vector_handle, 0);
  93. starpu_data_unregister(vector_handle);
  94. if (ret == -ENODEV) goto end;
  95. }
  96. end = starpu_timing_now();
  97. vector_timing = end - start;
  98. vector_timing /= maxloops;
  99. mean = matrix[0];
  100. start = starpu_timing_now();
  101. for(loop=1 ; loop<=maxloops ; loop++)
  102. {
  103. for(i=0 ; i<nx ; i++) matrix[i] = i;
  104. starpu_matrix_data_register(&matrix_handle, STARPU_MAIN_RAM, (uintptr_t)matrix, nx/2, nx/2, 2, sizeof(matrix[0]));
  105. ret = starpu_task_insert(matrix_codelet, STARPU_RW, matrix_handle, 0);
  106. starpu_data_unregister(matrix_handle);
  107. if (ret == -ENODEV) goto end;
  108. }
  109. end = starpu_timing_now();
  110. matrix_timing = end - start;
  111. matrix_timing /= maxloops;
  112. if (mean == matrix[0])
  113. {
  114. fprintf(stderr, "%d\t%f\t%f\n", nx, vector_timing, matrix_timing);
  115. {
  116. char *output_dir = getenv("STARPU_BENCH_DIR");
  117. char *bench_id = getenv("STARPU_BENCH_ID");
  118. if (output_dir && bench_id)
  119. {
  120. char file[1024];
  121. FILE *f;
  122. sprintf(file, "%s/matrix_as_vector_%s.dat", output_dir, device_name);
  123. f = fopen(file, "a");
  124. fprintf(f, "%s\t%d\t%f\t%f\n", bench_id, nx, vector_timing, matrix_timing);
  125. fclose(f);
  126. }
  127. }
  128. ret = EXIT_SUCCESS;
  129. }
  130. else
  131. {
  132. FPRINTF(stderr, "Incorrect result nx=%7d --> mean=%7f != %7f\n", nx, matrix[0], mean);
  133. ret = EXIT_FAILURE;
  134. }
  135. end:
  136. starpu_free(matrix);
  137. return ret;
  138. }
  139. #define NX_MIN 1024
  140. #define NX_MAX 1024*1024
  141. static
  142. int check_size_on_device(uint32_t where, char *device_name)
  143. {
  144. int nx, ret;
  145. struct starpu_codelet vector_codelet;
  146. struct starpu_codelet matrix_codelet;
  147. fprintf(stderr, "# Device: %s\n", device_name);
  148. fprintf(stderr, "# nx vector_timing matrix_timing\n");
  149. starpu_codelet_init(&vector_codelet);
  150. vector_codelet.modes[0] = STARPU_RW;
  151. vector_codelet.nbuffers = 1;
  152. if (where == STARPU_CPU) vector_codelet.cpu_funcs[0] = vector_cpu_func;
  153. if (where == STARPU_CUDA) vector_codelet.cuda_funcs[0] = vector_cuda_func;
  154. if (where == STARPU_CUDA) vector_codelet.cuda_flags[0] = STARPU_CUDA_ASYNC;
  155. // if (where == STARPU_OPENCL) vector_codelet.opencl_funcs[0] = vector_opencl_func;
  156. starpu_codelet_init(&matrix_codelet);
  157. matrix_codelet.modes[0] = STARPU_RW;
  158. matrix_codelet.nbuffers = 1;
  159. if (where == STARPU_CPU) matrix_codelet.cpu_funcs[0] = matrix_cpu_func;
  160. if (where == STARPU_CUDA) matrix_codelet.cuda_funcs[0] = matrix_cuda_func;
  161. if (where == STARPU_CUDA) matrix_codelet.cuda_flags[0] = STARPU_CUDA_ASYNC;
  162. // if (where == STARPU_OPENCL) matrix_codelet.opencl_funcs[0] = matrix_opencl_func;
  163. for(nx=NX_MIN ; nx<=NX_MAX ; nx*=2)
  164. {
  165. ret = check_size(nx, &vector_codelet, &matrix_codelet, device_name);
  166. if (ret != EXIT_SUCCESS) break;
  167. }
  168. return ret;
  169. }
  170. int main(int argc, char **argv)
  171. {
  172. int ret;
  173. unsigned devices;
  174. #ifdef STARPU_USE_CUDA
  175. int cublas_version;
  176. #endif
  177. ret = starpu_init(NULL);
  178. if (ret == -ENODEV) return STARPU_TEST_SKIPPED;
  179. STARPU_CHECK_RETURN_VALUE(ret, "starpu_init");
  180. #ifdef STARPU_USE_CUDA
  181. /* cublasSasum has synchronization issues when using a non-blocking stream */
  182. cublasGetVersion(&cublas_version);
  183. if (cublas_version >= 7050)
  184. starpu_cublas_init();
  185. #endif
  186. devices = starpu_cpu_worker_get_count();
  187. if (devices)
  188. {
  189. ret = check_size_on_device(STARPU_CPU, "STARPU_CPU");
  190. if (ret) goto error;
  191. }
  192. devices = starpu_cuda_worker_get_count();
  193. if (devices)
  194. {
  195. ret = check_size_on_device(STARPU_CUDA, "STARPU_CUDA");
  196. if (ret) goto error;
  197. }
  198. devices = starpu_opencl_worker_get_count();
  199. if (devices)
  200. {
  201. ret = check_size_on_device(STARPU_OPENCL, "STARPU_OPENCL");
  202. if (ret) goto error;
  203. }
  204. error:
  205. if (ret == -ENODEV) ret=STARPU_TEST_SKIPPED;
  206. #ifdef STARPU_USE_CUDA
  207. if (cublas_version >= 7050)
  208. starpu_cublas_shutdown();
  209. #endif
  210. starpu_shutdown();
  211. STARPU_RETURN(ret);
  212. }