[B! JIT] syanbiã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

syanbi id:syanbi

JITã«é–¢ã™ã‚‹syanbiã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (6)

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PyPyã®è«–æ–‡ã¤ã¶ã‚„ã
Ryotaro Ikeda @chlere ä»Šå›žã¯language-specificãªç‰¹å¾´é‡ã‚’ã„ã‹ã«ã—ã¦Meta-Tracingã§æ‰±ã†ã‹ã«ã¤ã„ã¦è¿°ã¹ã‚‰ã‚Œã¦ã„ã¾ã™ (via : http://t.co/miqpebaã€€)ã€€#pypy Ryotaro Ikeda @chlere Pythonã§ç°¡å˜ã«VMã‚’ä½œã‚ŠãŸã„ï¼->RPythonã§ä½œã‚Œã‚‹PyPyã¨ã„ã†FWã‚’ä½œã‚Šã¾ã—ãŸï¼->JITã¯è¨€èªžã®å®Ÿè£…ã«å¯„ã‚‰ãªã„ã‚ˆã†ã«RPythonãã®ã‚‚ã®ã‚’å¯¾è±¡ã«ã—ã¡ã‚ƒã†ã‚ˆï¼->ã‚ã‚Œã€ãƒ‡ãƒ¼ã‚¿ãƒ¢ãƒ‡ãƒ«ã®éƒ¨åˆ†ã«ã‚‚JITãŒå…¥ã‚Šè¾¼ã‚€ã‹ã‚‰ã™ã’ãƒ¼æ—©ããªã£ã¡ã‚ƒã£ãŸ ï¼ˆã„ã¾ã“ã“ï¼‰ã€€#pypy
syanbi 2011/11/03
pypy

python

JIT
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ãã¾ãŽ @kumagi Pythonã®JITã‚³ãƒ³ãƒ‘ã‚¤ãƒ©ã‚’å®Ÿè£…ã™ã‚‹ã ã‘ãªã‚‰å®Ÿè£…ã«ç”¨ã„ã‚‹è¨€èªžã¯Pythonã§ã‚ã‚‹å¿…è¦ã¯ç„¡ã„ã‚ã‘ã ã‘ã‚Œã©ã€Rubiniusã¨ã„ã„ãã®è¨€èªžã®å‡¦ç†ç³»ã‚’ãã®è¨€èªžè‡ªèº«ã§ä½œã‚‹ã“ã¨ã®æ„ç¾©ã£ã¦å…·ä½“çš„ã«ä½•ãŒã‚ã‚‹ã‚“ã§ã™ã‹ï¼Ÿå®Ÿè¡Œã®ç‚ºã«CPythonã‚„CRubyã‚’åˆ¥ã«å¿…è¦ã¨ã™ã‚‹ã¨è€ƒãˆã‚‹ã¨æ¬ ç‚¹ã—ã‹â€¦ï¼Ÿ 2011-11-02 13:28:05 ã½ã‚“ã“ã¤ @ponkotuy pypyã¯Pythonã®å®Ÿè¡Œç’°å¢ƒã‚’Pythonã§ä½œã£ã¦ã‚‹ã€‚ã‚ã‚‹è¨€èªžã®å®Ÿè¡Œç’°å¢ƒã‚’ãã®è¨€èªžãã®ã‚‚ã®ã§å®Ÿè£…ã™ã‚‹ã“ã¨ã¯æ„ç¾©ãŒã‚ã‚‹ã€ã£ã¦è¨€ã£ã¦ãŸãªã€pypyã§ã¯ [Mimas] 2011-11-02 13:30:28
syanbi 2011/11/02
Python

programming

JIT

pypy
ãƒªãƒ³ã‚¯
A JIT for Regular Expression Matching
This is part 2 of a series, see Part 1 for an introduction. In this post I want to describe how the JIT generator of the PyPy project can be used to turn the elegant but not particularly fast regular expression matcher from the first part into a rather fast implementation. In addition, I will show some speed measurements against various regular expression implementations. Again, note the disclaime
syanbi 2010/06/10
pypy

JIT

python
ãƒªãƒ³ã‚¯
PEP 3146 â€“ Merging Unladen Swallow into CPython | peps.python.org
PEP 3146 â€“ Merging Unladen Swallow into CPython Author: Collin Winter <collinwinter at google.com>, Jeffrey Yasskin <jyasskin at google.com>, Reid Kleckner <rnk at mit.edu> Status: Withdrawn Type: Standards Track Created: 01-Jan-2010 Python-Version: 3.3 Post-History: Table of Contents PEP Withdrawal Abstract Rationale, Implementation Alternatives Performance Benchmarks Performance vs CPython 2.6.4
syanbi 2010/04/25
python

JIT
ãƒªãƒ³ã‚¯
PyPy 1.2 Released
The latest news from Google on open source releases, major projects, events, and student outreach programs. PyPy is a reimplementation of Python in Python, using advanced techniques to try to attain better performance than CPython. Many years of hard work have finally paid off. Our speed results often beat CPython, ranging from being slightly slower, to speedups of up to 2x on real application cod
syanbi 2010/04/07
python

JIT
ãƒªãƒ³ã‚¯
First results of the JIT
Hi all, Just a quick note to tell you that we are progressing on the JIT front. Here are the running times of the richards benchmark on my laptop: 8.18 seconds with CPython 2.5.2; 2.61 seconds with pypy-c-jit (3x faster than CPython); 1.04 seconds if you ignore the time spent making assem bler (8x faster than CPython); 1.59 seconds on Psyco, for reference (5x faster that CPython). Yes, as this tabl
syanbi 2009/09/28
pypy

JIT
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