[Python-Dev] Benchmarks why we need PEP 576/579/580
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:
> 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 builtin_function_or_method (analogously,
> method_descriptor 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).random_element()" "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
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