Author: Armin Rigo <[email protected]>
Branch: extradoc
Changeset: r4748:bea7ab7c8bbc
Date: 2012-09-06 11:58 +0200
http://bitbucket.org/pypy/extradoc/changeset/bea7ab7c8bbc/

Log:    Updates

diff --git a/talk/googlezurich2012/abstract.rst 
b/talk/googlezurich2012/abstract.rst
--- a/talk/googlezurich2012/abstract.rst
+++ b/talk/googlezurich2012/abstract.rst
@@ -10,13 +10,14 @@
 
 The speed comes from a custom Just-in-Time compiler (JIT).  It is the
 first Virtual Machine to have a JIT generated automatically from the
-interpreter of the language, which makes it complete by construction.
-The JIT itself is a tracing JIT, roughly similar to SpiderMonkey.
+interpreter of the language, which makes it correct and complete by
+construction.  The JIT itself is a tracing JIT, roughly similar to
+SpiderMonkey.
 
 * most Python benchmarks run much faster than with CPython or Psyco
 * the real-world PyPy compiler toolchain itself (200 KLocs) runs twice as fast
 * supports x86 (32 or 64 bit), ARM (v7), and soon POWER64
-* full compatibility with  CPython (more than Jython/IronPython)
+* full compatibility with CPython (more than Jython/IronPython)
 * ctypes, CFFI and C++ support to call C/C++ libraries from Python (fast)
 * supports Stackless Python (in-progress)
 * integrates existing CPython C extensions (slowly)
@@ -24,9 +25,8 @@
 In this talk we will see examples of what PyPy is best at (pure Python
 code that runs for a while), what compatibility issues you may run into
 (very few), how to use CPython C extension modules (you can more or
-less, but it's slow right now), as well as dig a bit below the surface
-and use some tools to view the x86 machine code that was produced by the
-JIT.
+less, but it's slow), as well as dig a bit below the surface and use
+some tools to view the x86 machine code that was produced by the JIT.
 
 I will end the talk with an overview of Software Transactional Memory
 (STM) and how it promizes to give a PyPy without the Global Interpreter
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