Common Open Source High Productivity Languages

High productivity languages have recently become an important part of scientific computing and visualization. Leading high productivity languages include the commercially available MATLAB, open source Python (with its scientific computing add-ons) and open source Octave. Each of these high productivity languages forms an integral part of a standard library that includes text processing, file I/O, data compression, and a host of capabilities ranging from basic numerical linear algebra to complex data visualization.

BC Policy: LS2_10-02
Date of Policy: 1st November 2011
First Update: 15th July 2011
Second Update: 22nd September 2011

The main objective of this policy is to provide the following common open source high productivity languages environment across all LinkSCEEM-2 resources:

Package/Tool	Description	Compliance level	Reference
Python	General Purpose Scripting Language	MUST	http://python.org/
NumPy	Numerical Arrays and Linear Algebra in Python	MUST	http://numpy.scipy.org/
PyMPI	Python Message Passing Interface	MUST	http://pympi.sourceforge.net/
SciPy	Scientific Python	MUST	http://www.scipy.org/
Octave	MATLAB Clone	MUST	http://www.gnu.org/software/octave/
Matplotlib	Scientific 2-D and 3-D Plotting	SHOULD	http://matplotlib.sourceforge.net/
NAG	Numerical library /Numerical Algorithms Group	SHOULD	http://www.nag.co.uk/
R	R language	SHOULD	http://www.r-project.org/

These high productivity languages environment will be supplemented with other open source productivity languages as they become available on allocated systems.

There are two key sources which MAY be used to provide support to the scripting language Python and its scientific add-ons NumPy, PyMPI and SciPy. These are:

Computational Science Environment (CSE). The CSE is an integrated production level environment developed at ARL DSRC. CSE consists of open source tools, libraries as well as Python support (Python, NumPy, SciPy and PyMPI). All CSE components are assembled in an extensible framework that handles software dependencies at compile and runtime.
Parallel Tools Runtime Environment (PToolsRTE). The PToolsRTE is a collection of Python, NumPy, PyMPI, SciPy and related packages, including Matplotlib, developed by ParaTools, Inc. PToolsRTE provides a hybrid binary and source distribution where a majority of the components are pre-packaged in a binary form and a minimal number of platform and compiler specific components are built on the target system. This simplifies the complexity of software installation and the runtime environment can be easily installed on external systems to provide a consistent Python based environment for developing and deploying scientific packages that rely on a common runtime environment.

Both the CSE and PToolsRTE MAY be made available on HPC systems. The CSE package is being maintained by the ARL CSE Team, while the PToolsRTE is being maintained through PETTT.

User Documentation

LS2_10-02

Common Open Source High Productivity Languages