Author: Antonio Cuni <[email protected]>
Branch: extradoc
Changeset: r5526:92dbb3dfe86f
Date: 2015-04-13 18:08 +0200
http://bitbucket.org/pypy/extradoc/changeset/92dbb3dfe86f/

Log:    abstract for my EP talk

diff --git a/talk/ep2015/performance-abstract.txt 
b/talk/ep2015/performance-abstract.txt
new file mode 100644
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+==================================
+PyPy performance (not) for dummies
+==================================
+
+
+Abstract
+---------
+
+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
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