[pypy-dev] PyPy 1.6 released

Sat Aug 20 08:15:08 CEST 2011

On Fri, Aug 19, 2011 at 23:52 +0200, Maciej Fijalkowski wrote:
> On Fri, Aug 19, 2011 at 7:35 PM, holger krekel <holger at merlinux.eu> wrote:
> > Congrats also from here!
> >
> > On the plus side pytest's own test suite passes all tests, even some which
> > are marked as "expected-to-fail" with cpython-2.7.  On the minus side,
> > the whole test run is still 2-3 times slower compared to cpython which is slightly worse than with pypy-1.5. of course there is not too much to JIT but
> > still a bit of a dissappointing result.
> 
> Well, yes, but also we have no good answer to this. I think the reason
> why it got slower is because we compile functions now as well (which
> takes extra time). Test suites are hard I fear :(

Maybe worth a small note because i guess test suites are often run to test pypy.

FWIW if i run the test suite with --jit off it takes 117 seconds instead of
72 with JIT (cpython takes about 25 seconds).  So maybe one question is
why pypy-no-jit is already 4-5 times slower to begin with.

Holger

> >
> > best,
> > holger
> >
> > On Thu, Aug 18, 2011 at 19:30 +0200, Maciej Fijalkowski wrote:
> >> ========================
> >> PyPy 1.6 - kickass panda
> >> ========================
> >>
> >> We're pleased to announce the 1.6 release of PyPy. This release brings a lot
> >> of bugfixes and performance improvements over 1.5, and improves support for
> >> Windows 32bit and OS X 64bit. This version fully implements Python 2.7.1 and
> >> has beta level support for loading CPython C extensions.  You can download it
> >> here:
> >>
> >>     http://pypy.org/download.html
> >>
> >> What is PyPy?
> >> =============
> >>
> >> PyPy is a very compliant Python interpreter, almost a drop-in replacement for
> >> CPython 2.7.1. It's fast (`pypy 1.5 and cpython 2.6.2`_ performance comparison)
> >> due to its integrated tracing JIT compiler.
> >>
> >> This release supports x86 machines running Linux 32/64 or Mac OS X.  Windows 32
> >> is beta (it roughly works but a lot of small issues have not been fixed so
> >> far).  Windows 64 is not yet supported.
> >>
> >> The main topics of this release are speed and stability: on average on
> >> our benchmark suite, PyPy 1.6 is between **20% and 30%** faster than PyPy 1.5,
> >> which was already much faster than CPython on our set of benchmarks.
> >>
> >> The speed improvements have been made possible by optimizing many of the
> >> layers which compose PyPy.  In particular, we improved: the Garbage Collector,
> >> the JIT warmup time, the optimizations performed by the JIT, the quality of
> >> the generated machine code and the implementation of our Python interpreter.
> >>
> >> .. _`pypy 1.5 and cpython 2.6.2`: http://speed.pypy.org
> >>
> >>
> >> Highlights
> >> ==========
> >>
> >> * Numerous performance improvements, overall giving considerable speedups:
> >>
> >>   - better GC behavior when dealing with very large objects and arrays
> >>
> >>   - **fast ctypes:** now calls to ctypes functions are seen and optimized
> >>     by the JIT, and they are up to 60 times faster than PyPy 1.5 and 10 times
> >>     faster than CPython
> >>
> >>   - improved generators(1): simple generators now are inlined into the caller
> >>     loop, making performance up to 3.5 times faster than PyPy 1.5.
> >>
> >>   - improved generators(2): thanks to other optimizations, even generators
> >>     that are not inlined are between 10% and 20% faster than PyPy 1.5.
> >>
> >>   - faster warmup time for the JIT
> >>
> >>   - JIT support for single floats (e.g., for ``array('f')``)
> >>
> >>   - optimized dictionaries: the internal representation of dictionaries is now
> >>     dynamically selected depending on the type of stored objects, resulting in
> >>     faster code and smaller memory footprint.  For example, dictionaries whose
> >>     keys are all strings, or all integers. Other dictionaries are also smaller
> >>     due to bugfixes.
> >>
> >> * JitViewer: this is the first official release which includes the JitViewer,
> >>   a web-based tool which helps you to see which parts of your Python code have
> >>   been compiled by the JIT, down until the assembler. The `jitviewer`_ 0.1 has
> >>   already been release and works well with PyPy 1.6.
> >>
> >> * The CPython extension module API has been improved and now supports many
> >>   more extensions. For information on which one are supported, please refer to
> >>   our `compatibility wiki`_.
> >>
> >> * Multibyte encoding support: this was of of the last areas in which we were
> >>   still behind CPython, but now we fully support them.
> >>
> >> * Preliminary support for NumPy: this release includes a preview of a very
> >>   fast NumPy module integrated with the PyPy JIT.  Unfortunately, this does
> >>   not mean that you can expect to take an existing NumPy program and run it on
> >>   PyPy, because the module is still unfinished and supports only some of the
> >>   numpy API. However, barring some details, what works should be
> >>   blazingly fast :-)
> >>
> >> * Bugfixes: since the 1.5 release we fixed 53 bugs in our `bug tracker`_, not
> >>   counting the numerous bugs that were found and reported through other
> >>   channels than the bug tracker.
> >>
> >> Cheers,
> >>
> >> Hakan Ardo, Carl Friedrich Bolz, Laura Creighton, Antonio Cuni,
> >> Maciej Fijalkowski, Amaury Forgeot d'Arc, Alex Gaynor,
> >> Armin Rigo and the PyPy team
> >>
> >> .. _`jitviewer`:
> >> http://morepypy.blogspot.com/2011/08/visualization-of-jitted-code.html
> >> .. _`bug tracker`: https://bugs.pypy.org
> >> .. _`compatibility wiki`: https://bitbucket.org/pypy/compatibility/wiki/Home
> >> _______________________________________________
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> >> pypy-dev at python.org
> >> http://mail.python.org/mailman/listinfo/pypy-dev
> >>
> >
> 