Author: Maciej Fijalkowski <fij...@gmail.com> Branch: extradoc Changeset: r5527:1e9cb1d73547 Date: 2015-04-14 13:31 +0200 http://bitbucket.org/pypy/extradoc/changeset/1e9cb1d73547/
Log: rework the abstract 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 +1,21 @@ -================================== -PyPy performance (not) for dummies -================================== +==================================== +Python performance (not) for dummies +==================================== +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. -Abstract ---------- +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. -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: - -- 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
