pnumpy 1.0.6

A very lightweight implementation of distributed arrays

pnumpy
======

$Id: README 26 2014-02-16 20:07:08Z pletzer $

"Parallel computing in N dimensions made easy"

pnumpy is a very lightweight implementation of distributed arrays,
which runs on architectures ranging from multi-core laptops to large
MPI clusters. pnumpy is based on numpy and mpi4py and supports arrays in
any number of dimensions. Processes can access remote data using a "get"
method. This can be used to access neighbor ghost data but is more
flexible as it allows to access data from any process--not necessarily
a neighboring one. pnumpy is designed to work seamlessly with numpy's
slicing operators ufunc, etc., making it easy to transition your code
from using numpy arrays to pnumpy arrays.

Getting pnumpy
--------------

Stable versions of pnumpy can be accessed and installed using

$ [sudo] pip install pnumpy

or

$ [sudo] easy_install pnumpy

The latest source version can be accessed anonymously from the sourceforge site
using the command:

$ svn co https://svn.code.sf.net/p/pnumpy/code/trunk pnumpy

Building pnumpy by hand
-----------------------

pnumpy needs python 2.x, mpi4py, and numpy. To install pnumpy type:

$ [sudo] python setup.py install

or

$ python setup.py install --prefix=<install_directory>

if you wish to install pnumpy under install_directory (make sure
to set the PYTHONPATH environment variable to
<install_directory/lib/python<version>/site-packages).

Documentation
-------------

Please visit https://sourceforge.net/p/pnumpy/wiki/Home/ for examples showing
how to use pnumpy.

Testing
-------

$ cd tests
$ mpiexec -n 4 python testDistArray.py (or any other test)

Contact
-------

Send email to Alexander Pletzer (alexander _at_ gokliya _dot_ net) for bug
reports, questions, and request for additional features.