Hi, I have been trying to use Pypy to speed up the Krakatau decompiler ( https://github.com/Storyyeller/Krakatau). It is a large, pure Python application with several compute intensive parts, so I thought it would work well. Unfortunately, there is no clear speedup, and Pypy requires several times as much memory as well, making it unusual for larger inputs.
For example, decompiling a quarter of ASM, I got the following results (execution time, memory usage) cpython 64 - 62.5s, 102.6kb cpython 32 - 69.2s, 54.5kb pypy 2.1.0 - 106.5s, 277.8kb pypy 2.2.1 - 109.2s, 194.6kb Sometimes, 2.2.1 is faster than 2.1.0, but they're both clearly much worse than CPython. These tests were performed on Windows 7 64bit using the prebuilt 32bit binaries of Pypy. I tested the 32bit version of CPython too, to see if the problem was a lack of 64bit support. However, CPython 32bit also vastly outperformed Pypy. Execution time was measured using time.time(). Memory usage was measured by watching the Windows Resource Manager and recording the peak Private value. Similar patterns were seen in Working Set, etc. I thought the increased memory usage at least might be explained by constant overhead from compiled code or from it not running long enough to trigger full garbage collection. However, Pypy continues to use several times as much memory on much larger examples. Does anyone know what could be going on here? Pypy isn't normally slower than CPython. Is there a way for me to tell what the problem is?
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