[Python-Dev] Benchmarks why we need PEP 576/579/580 (original) (raw)

Erik Bray erik.m.bray at gmail.com
Wed Jul 25 07:01:46 EDT 2018

On Sat, Jul 21, 2018 at 6:30 PM Jeroen Demeyer <J.Demeyer at ugent.be> wrote:

Hello, I finally managed to get some real-life benchmarks for why we need a faster C calling protocol (see PEPs 576, 579, 580). I focused on the Cython compilation of SageMath. By default, a function in Cython is an instance of builtinfunctionormethod (analogously, methoddescriptor for a method), which has special optimizations in the CPython interpreter. But the option "binding=True" changes those to a custom class which is NOT optimized. I ran the full SageMath testsuite several times without and with binding=True to find out any significant differences. The most dramatic difference is multiplication for generic matrices. More precisely, with the following command: python -m timeit -s "from sage.all import MatrixSpace, GF; M = MatrixSpace(GF(9), 200).randomelement()" "M * M" With binding=False, I got 10 loops, best of 3: 692 msec per loop With binding=True, I got 10 loops, best of 3: 1.16 sec per loop This is a big regression which should be gone completely with PEP 580. I should mention that this was done on Python 2.7.15 (SageMath is not yet ported to Python 3) but I see no reason why the conclusions shouldn't be valid for newer Python versions. I used SageMath 8.3.rc1 and Cython 0.28.4.

I haven't fully caught up on the thread yet so this might already be a moot point. But just in case it isn't, the Python 3 port of Sage works well enough (at least on my branch) that the above benchmark works, and would probably be worth repeating there (it's currently Python 3.6.1, but upgrading to 3.7 probably wouldn't break the example benchmark either).

More information about the Python-Dev mailing list