Author: Antonio Cuni <anto.c...@gmail.com> Branch: extradoc Changeset: r5532:2403b934d742 Date: 2015-04-16 17:52 +0200 http://bitbucket.org/pypy/extradoc/changeset/2403b934d742/
Log: merge diff --git a/talk/ep2015/performance-abstract.txt b/talk/ep2015/performance-abstract.txt --- a/talk/ep2015/performance-abstract.txt +++ b/talk/ep2015/performance-abstract.txt @@ -1,20 +1,25 @@ -================================== -PyPy performance (not) for dummies -================================== +============================================== +Python and PyPy performance (not) for dummies +============================================== +[[The talk will be given by Antonio Cuni and Maciej Fijalkowski, +both long time PyPy core developers and expert in the area of +Python performance.]] -Abstract ---------- +In this talk we would like to have a short introduction on how Python +programs are compiled and executed, with a special attention towards +just in time compilation done by PyPy. PyPy is the most advanced Python +interpreter around and while it should generally just speed up your programs +there is a wide range of performance that you can get out of PyPy, ranging from +slightly faster than CPython to C speeds, depending on how you write your +programs. -PyPy is the fastest Python interpreter around, and its JIT can optimize most -of your Python programs without problems. However, there are techniques to -improve the performances even further and squeeze the most out of PyPy. In -this talk we will see: +We will split the talk in two parts. In the first part we will explain +how things work and what can and what cannot be optimized as well as describe +the basic heuristics of JIT compiler and optimizer. In the next part we will +do a survey of existing tools for looking at performance of Python programs +with specific focus on PyPy. -- the general principles behind the PyPy JIT - -- how to profile programs to find the bottlenecks - -- how to examine the code generated by the JIT - -- how to write JIT-friendly programs +As a result of this talk, an audience member should be better equipped with +tools how to write new software and improve existing software with performance +in mind. _______________________________________________ pypy-commit mailing list pypy-commit@python.org https://mail.python.org/mailman/listinfo/pypy-commit
