PyPyの論文つぶやき
Ryotaro Ikeda @chlere 今回はlanguage-specificな特徴量をいかにしてMeta-Tracingで扱うかについて述べられています (via : http://t.co/miqpeba ) #pypy 2011-08-15 11:26:20 Ryotaro Ikeda @chlere Pythonで簡単にVMを作りたい！->RPythonで作れるPyPyというFWを作りました！->JITは言語の実装に寄らないようにRPythonそのものを対象にしちゃうよ！->あれ、データモデルの部分にもJITが入り込むからすげー早くなっちゃった （いまここ） #pypy 2011-08-15 15:59:05
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
PEP 3146 – Merging Unladen Swallow into CPython | peps.python.org
PEP 3146 – 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 Status: Withdrawn Type: Standards Track Created: 01-Jan-2010 Python-Version: 3.3 Post-History: Table of Contents PEP Withdrawal Abstract Rationale, Implementation Alternatives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
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
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 assembler (8x faster than CPython); 1.59 seconds on Psyco, for reference (5x faster that CPython). Yes, as this tabl
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言語のJITコンパイラをその言語自身で作る事の意義とは
