Large (52%) Performance Gains #37
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Drasticly imporves Performance by avoiding repeated calls to numpy.flip() by saving a flipped version of the repeatadly flipped array. This turn getVisibleHistory() into a single line Method, so it was placed inline to avoid the function call for further performance gains. Performance gains: reduced the time needed to run a 10 (9 examples + mine) Strategy tournament repeatatly (100 times) from 12.84s to 6.161. (52%)
EFHIII
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May 23, 2021
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I get some performance gains, however they are far from the 52% gain stated, running in a environment with 48 strategies (1128 rounds per tournament), for me the time taken to run 10 tournaments is:
One thing that has a lot of impact in the overall time is the performance of the strategies themselves, in my case I have a few strategies that take quite some time when compared with the examples. In any case, in the context of the tournament code, there is a measurable improvement in the execution time with this change. |
zebarnabe
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May 27, 2021
Cache by hash as well as modification time
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