On Fri, Aug 19, 2011 at 23:52 +0200, Maciej Fijalkowski wrote: > On Fri, Aug 19, 2011 at 7:35 PM, holger krekel <hol...@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 > >> _______________________________________________ > >> pypy-dev mailing list > >> pypy-dev@python.org > >> http://mail.python.org/mailman/listinfo/pypy-dev > >> > > > _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
