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.

150 lines
2.5 KiB

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