Author: Armin Rigo <ar...@tunes.org>
Branch: extradoc
Changeset: r5050:b29cb4d623f0
Date: 2013-09-13 15:47 +0200
http://bitbucket.org/pypy/extradoc/changeset/b29cb4d623f0/
Log: Restart, putting more focus on STM and less on the Status of PyPy
part
diff --git a/talk/pycon2014/abstract.rst b/talk/pycon2014/abstract.rst
new file mode 100644
--- /dev/null
+++ b/talk/pycon2014/abstract.rst
@@ -0,0 +1,34 @@
+Software Transactional Memory with PyPy
+=======================================
+
+Description
+-----------
+
+PyPy is a fast alternative Python implementation. Software
+Transactional Memory is a current academic research topic. Put the two
+together --brew for a couple of years-- and we obtain a version of PyPy
+that runs on multiple cores, without the infamous Global Interpreter
+Lock (GIL). It has been freshly released in beta, including integration
+with the Just-in-Time compiler.
+
+The talk will also include a "general status of PyPy" part.
+
+
+Audience
+--------
+
+
+Objectives
+----------
+
+
+Detailed abstract
+-----------------
+
+
+Outline
+-------
+
+
+Additional notes
+----------------
diff --git a/talk/pycon2014/talk.rst b/talk/pycon2014/talk.rst
deleted file mode 100644
--- a/talk/pycon2014/talk.rst
+++ /dev/null
@@ -1,15 +0,0 @@
-The status of PyPy
-==================
-
-PyPy is an alternative Python interpreter. It is seriously fast, but
-progress purely in that direction is reaching limits. Instead, it is
-growing support for a larger part of the Python ecosystem: a long list
-of common libraries are going from "unsupported" to "badly supported" to
-"well supported". We also have beta Python 3 support. In short, try
-PyPy today :-)
-
-On the research front, Transactional Memory seems to work as a way to
-run programs on multiple cores. It is coming along, fully integrated
-with the JIT compiler. We will show various examples, including
-versions of event libraries (like Twisted, Tornado, greenlet...) that
-run existing non-multithreaded programs on multiple cores.
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