This contains my bachelors thesis and associated tex files, code snippets and maybe more. Topic: Data Movement in Heterogeneous Memories with Intel Data Streaming Accelerator
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

185 lines
3.3 KiB

  1. {
  2. "count": 12,
  3. "list": [
  4. {
  5. "affinity": {
  6. "nnode_dst": 12,
  7. "nnode_src": 0,
  8. "node": 0
  9. },
  10. "task": {
  11. "batching": {
  12. "batch_size": 0,
  13. "batch_submit": false
  14. },
  15. "iterations": 10,
  16. "size": 1073741824
  17. }
  18. },
  19. {
  20. "affinity": {
  21. "nnode_dst": 12,
  22. "nnode_src": 0,
  23. "node": 0
  24. },
  25. "task": {
  26. "batching": {
  27. "batch_size": 0,
  28. "batch_submit": false
  29. },
  30. "iterations": 10,
  31. "size": 1073741824
  32. }
  33. },
  34. {
  35. "affinity": {
  36. "nnode_dst": 12,
  37. "nnode_src": 0,
  38. "node": 0
  39. },
  40. "task": {
  41. "batching": {
  42. "batch_size": 0,
  43. "batch_submit": false
  44. },
  45. "iterations": 10,
  46. "size": 1073741824
  47. }
  48. },
  49. {
  50. "affinity": {
  51. "nnode_dst": 12,
  52. "nnode_src": 0,
  53. "node": 0
  54. },
  55. "task": {
  56. "batching": {
  57. "batch_size": 0,
  58. "batch_submit": false
  59. },
  60. "iterations": 10,
  61. "size": 1073741824
  62. }
  63. },
  64. {
  65. "affinity": {
  66. "nnode_dst": 12,
  67. "nnode_src": 0,
  68. "node": 0
  69. },
  70. "task": {
  71. "batching": {
  72. "batch_size": 0,
  73. "batch_submit": false
  74. },
  75. "iterations": 10,
  76. "size": 1073741824
  77. }
  78. },
  79. {
  80. "affinity": {
  81. "nnode_dst": 12,
  82. "nnode_src": 0,
  83. "node": 0
  84. },
  85. "task": {
  86. "batching": {
  87. "batch_size": 0,
  88. "batch_submit": false
  89. },
  90. "iterations": 10,
  91. "size": 1073741824
  92. }
  93. },
  94. {
  95. "affinity": {
  96. "nnode_dst": 12,
  97. "nnode_src": 0,
  98. "node": 0
  99. },
  100. "task": {
  101. "batching": {
  102. "batch_size": 0,
  103. "batch_submit": false
  104. },
  105. "iterations": 10,
  106. "size": 1073741824
  107. }
  108. },
  109. {
  110. "affinity": {
  111. "nnode_dst": 12,
  112. "nnode_src": 0,
  113. "node": 0
  114. },
  115. "task": {
  116. "batching": {
  117. "batch_size": 0,
  118. "batch_submit": false
  119. },
  120. "iterations": 10,
  121. "size": 1073741824
  122. }
  123. },
  124. {
  125. "affinity": {
  126. "nnode_dst": 12,
  127. "nnode_src": 0,
  128. "node": 0
  129. },
  130. "task": {
  131. "batching": {
  132. "batch_size": 0,
  133. "batch_submit": false
  134. },
  135. "iterations": 10,
  136. "size": 1073741824
  137. }
  138. },
  139. {
  140. "affinity": {
  141. "nnode_dst": 12,
  142. "nnode_src": 0,
  143. "node": 0
  144. },
  145. "task": {
  146. "batching": {
  147. "batch_size": 0,
  148. "batch_submit": false
  149. },
  150. "iterations": 10,
  151. "size": 1073741824
  152. }
  153. },
  154. {
  155. "affinity": {
  156. "nnode_dst": 12,
  157. "nnode_src": 0,
  158. "node": 0
  159. },
  160. "task": {
  161. "batching": {
  162. "batch_size": 0,
  163. "batch_submit": false
  164. },
  165. "iterations": 10,
  166. "size": 1073741824
  167. }
  168. },
  169. {
  170. "affinity": {
  171. "nnode_dst": 12,
  172. "nnode_src": 0,
  173. "node": 0
  174. },
  175. "task": {
  176. "batching": {
  177. "batch_size": 0,
  178. "batch_submit": false
  179. },
  180. "iterations": 10,
  181. "size": 1073741824
  182. }
  183. }
  184. ],
  185. "path": "sw"
  186. }