Blog coverage of speed.pypy.org
If you want to read a detailed analysis about why speed.pypy.org is cool, head over to Saveen Reddy's blog at the MSDN.
The PyPy blogposts
Create a guest post via a PR to the source repo
Recent Posts
- M1 support for PyPy
- Implementing a Toy Optimizer
- How is PyPy Tested?
- PyPy v7.3.9 security release
- PyPy v7.3.8: release of python 2.7, 3.7, 3.8, and 3.9
- Natural Language Processing for Icelandic with PyPy: A Case Study
- Error Message Style Guides of Various Languages
- PyPy v7.3.7: bugfix release of python 3.7 and 3.8
- PyPy v7.3.6: release of python 2.7, 3.7, and 3.8
- Better JIT Support for Auto-Generated Python Code
Archives
Tags
- arm (2)
- casestudy (1)
- cli (1)
- compiler (1)
- cpyext (4)
- CPython (3)
- ep2008 (1)
- extension modules (2)
- gc (1)
- GraalPython (1)
- hpy (1)
- Heptapod (1)
- jit (19)
- jython (1)
- kcachegrind (1)
- numpy (24)
- parser (1)
- profiling (4)
- pypy (6)
- pypy3 (16)
- PyQt4 (1)
- release (54)
- releasecffi (3)
- releaserevdb (1)
- releasestm (1)
- revdb (1)
- roadmap (2)
- RPyC (1)
- speed (6)
- sponsors (7)
- sprint (3)
- stm (14)
- sun (1)
- Smalltalk (1)
- Squeak (1)
- unicode (1)
- valgrind (1)
Comments
First of all congratulations for the great work, I can say I am a newbie in Python world but I follow with interest this project. I tryed the release with the JIT compiler with also the parallel python module and the speed gain is sensible. I compared also the performance with psyco on 3 or 4 benchmarks and it seems that the time for the execution is usually more or less the same. Do you think there will be the possibility again for a massive speed improvement in future releases or the level of max performance is not so far? How much faster could it be in the future?
Thanks,
Paolo
Question:
According to the Computer Language Benchmarks Game, there are three benchmarks that perform way slower in Pypy against Python 3 ( see here: https://shootout.alioth.debian.org/u32/benchmark.php?test=all&lang=pypy&lang2=python3 ).
Those are:
1) reverse-complement
2) regex-dna
3) pidgits
I know that regex-dna performs slower because regex haven't been optimized yet, but what's the reason for the other two? Do they use regex too?
@Luis pidigits is about using gmpy for cpython vs longs for pypy. It's a bit apples vs oranges. That said, CPython's longs are still faster than pypy's so we definitely can improve. This are needs some love :)
Reverse complement is string benchmark and I did not look but it might be that the speed of str.translate is suboptimal.
Cheers,
fijal, hiding