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Increase chunk sizes to improve performance and parallelism #4080

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opened 2023-12-08 15:54:13 +00:00 by itamarst · 0 comments
itamarst commented 2023-12-08 15:54:13 +00:00
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  1. Processing data in larger chunk sizes can reduce overhead of all the little Python function calls for each chunk.
  2. Larger chunk sizes for functions that release GIL add additional opportunities for utilizing parallelism by shifting to a thread pool. Larger chunks of work are more efficient for this scheme.
1. Processing data in larger chunk sizes can reduce overhead of all the little Python function calls for each chunk. 2. Larger chunk sizes for functions that release GIL add additional opportunities for utilizing parallelism by shifting to a thread pool. Larger chunks of work are more efficient for this scheme.
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tahoe-lafs added this to the Performance and Benchmarking milestone 2023-12-08 15:54:13 +00:00
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Reference: tahoe-lafs/trac-2024-07-25#4080
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