This package is based on the package 'dirvish' from project 'home:dmacvicar'.

Open MPI is a project combining technologies and resources from several
other projects (FT-MPI, LA-MPI, LAM/MPI, and PACX-MPI) in order to
build the best MPI library available.

This RPM contains all the tools necessary to compile, link, and run
Open MPI jobs.

The Cython language makes writing C extensions for the Python language as
easy as Python itself. Cython is a source code translator based on the
well-known Pyrex, but supports more cutting edge functionality and
optimizations.

The Cython language is very close to the Python language (and most Python
code is also valid Cython code), but Cython additionally supports calling C
functions and declaring C types on variables and class attributes. This
allows the compiler to generate very efficient C code from Cython code.

This makes Cython the ideal language for writing glue code for external C
libraries, and for fast C modules that speed up the execution of Python
code.

MPI for Python (mpi4py) provides bindings of the Message Passing Interface (MPI) standard for the Python programming language, allowing any Python program to exploit multiple processors.

This package is constructed on top of the MPI-1/MPI-2 specification and provides an object oriented interface which closely follows MPI-2 C++ bindings. It supports point-to-point (sends, receives) and collective (broadcasts, scatters, gathers) communications of any picklable Python object as well as optimized communications of Python object exposing the single-segment buffer interface (NumPy arrays, builtin bytes/string/array objects).

NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays. NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type.

The python module pypar.py and the C-extension mpi.c
implements scalable parallelism on distributed and shared
memory architectures using the essential subset of
the Message Passing Interface (MPI) standard.

FEATURES

- Python interpreter is not modified:
Parallel python programs need only import the pypar module.

- Flexibility: Pypar allows communication of general Python objects
of any type.

- Intuitive API:
The user need only specify what to send and to which processor.
Pypar takes care of details about
data types and MPI specifics such as tags, communicators and buffers.
Receiving is analogous.

- Efficiency:
Full bandwidth of C-MPI programs is achieved for consecutive Numerical
arrays. Latency is less than twice that of pure C-MPI programs.
Test programs to verify this are included (pytiming, ctiming.c)

- Lightweight:
Pypar consists of just two files: mpiext.c and pypar.py

SciPy is open-source software for mathematics, science, and engineering. The core library is NumPy which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers.

Referencer is a Gnome application to organise documents or references, and
ultimately generate a BibTeX bibliography file.
Its features include automatic metadata retrieval, smart web links, ability to
import from BibTeX, Reference Manager and EndNote, and tagging.