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| Our algorithms are not always the problem, sometimes it's memory allocations that slow you down | Our algorithms are not always the problem, sometimes it's memory {de}allocations that slow you down |
Performance Enhancements Resources
Jython benchmarks (from PyPy's suite): http://freya.cs.uiuc.edu/~njriley/benchmark.html
Benchmark plots (currently broken): http://freya.cs.uiuc.edu/~njriley/plots.html
Ideas
GC Expense
Our algorithms are not always the problem, sometimes it's memory {de}allocations that slow you down
Frame creation
Frames are allocated for every Python method call, which is a GC expense. CPython (and JRuby?) recycle frame objects. Reducing the number of fields on the frame can also help (but this likely isn't possible)