[pypy-commit] extradoc extradoc: Improve language in abstract.

[edelsohn]

Author: edelsohn
Branch: extradoc
Changeset: r3984:b91e6cab9b06
Date: 2011-12-12 15:58 -0500
http://bitbucket.org/pypy/extradoc/changeset/b91e6cab9b06/

Log:	Improve language in abstract.

diff --git a/talk/sea2012/abstract.rst b/talk/sea2012/abstract.rst
--- a/talk/sea2012/abstract.rst
+++ b/talk/sea2012/abstract.rst
@@ -1,16 +1,17 @@
 Fast numeric in Python - NumPy and PyPy
 =======================================
 
-Python has seen a growing adoption as a new scientific processing language
-in the past few years. It has been successfully used as a glue language
-to drive various simulations implemented in either C, Fortran or the array
-manipulation language implemented in the NumPy package. Originally the main
-reason why Python was used only as a glue language is because the original
-Python implementation is relatively slow. With the recent progress in the PyPy
-project, it has been shown that while still not at C speeds, it has been
-gaining significant performance improvements the releases, bringing it
-closer and closer to C-level speeds. In this talk I would like to explore
-how to use it right now, in the near future and our plans to provide a very
-robust infrastructure for implementing numerical computations. I will also
-spend some time exploring the ideas how dynamic compilation can eventually
-outperform static compilation and how having a high-level language helps here.
+Python increasingly is being utilized as a powerful scientific
+processing language. It successfully has been used as a glue language
+to drive simulations written in C, Fortran or the array
+manipulation language provided by the NumPy package.  Originally
+Python only was used as a glue language because the original Python
+implementation was relatively slow. With the recent progress in the
+PyPy project that is showing significant performance
+improvements in each release, Python is nearing performance comparable
+to native C language implementations. In this talk I will
+describe three stages: how to use it right now, in the near future and
+our plans to provide a very robust infrastructure for implementing
+numerical computations. I also will spend some time exploring ideas
+how dynamic compilation eventually can outperform static compilation
+and how a high-level language helps accomplish this.