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.h.... 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@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@gmail.com <P>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)