Pypar 2.0alpha update - Simple and efficient MPI binding for Python.

Ole Nielsen ole.moller.nielsen at gmail.com
Fri Jul 6 15:50:57 CEST 2007


pypar 2.0alpha released on sourceforge.
Pypar is a simple and efficient MPI binding for Python
Copyright (C) 2001-2007 Ole M. Nielsen
-------------------------------------------------------

This is to announce an upgrade of pypar, ver 2.0 alpha -
a simple and efficient Python binding to MPI for parallel
programming using Python.

Version 1.0 was announced on this mailing list on 7th of February 2002
http://mail.python.org/pipermail/python-announce-list/2002-February/001228.html.

Pypar has been used in many projects over the years but it became
clear that relying on the
Numeric was becoming a liability and many developers requested an
upgrade to numpy.
The update to version 2.0alpha signifies
1: Porting pypar to numpy instead of the discontinued Numeric module
2: Moving pypar to sourceforge: http://sourceforge.net/projects/pypar/
3: Numerous improvements and optimisations added over the past years

Version 2.0alpha has been tested on a few platforms, but I haven't been able to
verify that it installs everywhere. The purpose of this post is to
encourage existing and new
users of pypar to try the new release and to get back to me with
questions, feedback and patches
that will allow pypar to run on as many platforms as possible.

I am looking forward to hear from you
Ole M. Nielsen
Canberra, Australia
Ole.Moller.Nielsen at gmail.com

	

Background:
-----------
The use of multi processor computers is becoming increasingly
common and they appear in many forms: Desktop computers with more
than one processor sharing memory, clusters of PC's connected with
fast networks known as Beowulf clusters, and high-end super computers
all make use of parallelism. Even playstations have been connected to
form computational networks (http://arrakis.ncsa.uiuc.edu/ps2/cluster.php).
To efficiently use these machines in a portable way one must be able to
control communication among programs running in parallel.
One such standard is the Message Passing Interface (MPI) for
inter-processor communication.

Python and MPI:
---------------
There are a number of other Python bindings to MPI that are
more comprehensive than pypar (PyMPI, Scientific Python).
However, pypar stands out by not requiring the Python interpreter to be
modified, by being very easy to install and by
by shielding the user from many details involving data types and
MPI parameters without sacrificing the full bandwidth provided by the
underlying MPI implementation.

Download:
---------
Pypar can be downloaded from

  http://sourceforge.net/projects/pypar


Credentials:
------------
Pypar was developed by Ole Nielsen at the Australian National
University in 2001 for use in the APAC Data Mining Expertise Program
and has been published under the GNU Public License
(http://www.gnu.org/licenses/gpl.txt)

Contact:
  Ole.Moller.Nielsen at gmail.com <Ole.Nielsen at anu.edu.au>

<P><A HREF="http://sourceforge.net/projects/pypar"
<http://datamining.anu.edu.au/pypar>>Pypar 2.0alpha</A> -
A simple and efficient MPI binding for Python.  (07-July-07)
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