August 2015
Intermediate to advanced
384 pages
7h 42m
Chinese
Content preview from 高效能PYTHON程式設計
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矩陣與向量計算
|
125
比較範例 6-15 與 6-10 的效能數據，可以看到，移除不必要的配置讓程式碼提升效能
29%，部分是因為減少快取未命中（cache miss）的數量，但主要是來自缺頁異常（page
fault）的削減。
範例
6-15
搭配就地記憶體操作的
numpy
版本的效能數據
$ perf stat -e cycles,stalled-cycles-frontend,stalled-cycles-backend,instructions,\
cache-references,cache-misses,branches,branch-misses,task-clock,faults,\
minor-faults,cs,migrations -r 3 python diffusion_numpy_memory.py
Performance counter stats for 'python diffusion_numpy_memory.py' (3 runs):
7,864,072,570 cycles # 3.330 GHz
3,055,151,931 stalled-cycles-frontend # 38.85% frontend cycles idle
1,368,235,506 stalled-cycles-backend # 17.40% backend cycles idle
13,257,488,848 instructions # 1.69 insns ...
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