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Scientific Computing with Free GNU / Linux Software
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7. Programming Systems for GNU/Linux
This section deals with links to tutorials and documents for installing
Linux on a PC, getting started with Linux, and then going a step further --
to optimize your PC for processing power, using multiple processors (Symmetric
Muliti Processing - SMP); making a cheap, upgradeable Supercomputing Linux cluster
and finally links to software to do parallel programming on Linux.
7.1. The GNU/Linux Workstation
As with most documentation related to GNU/Linux, the Linux Documentation project's home page is a priceless source. You might first want to read The Linux Installation HOWTO. For those who want to install Linux along with Windows might want to browse
through The Linux + Windows HOWTO. When installing Linux make sure that you choose to install all documentation.
After installing Linux, a good, comprehensive document to getting started with
using Linux is The Rute Users Tutorial and Exposition which is a beginners guide to Linux and UNIX like systems. I'd like to give
a less intimidating (size-wise) link to a small beginners guide, but U will
find this useful after taking the plunge. You might also want to go through
The Linux System Administrator's Guide and to check out The Linux Administration Made Easy (LAME) guide It attempts to describe day-to-day administration and maintenance issues commonly
faced by Linux system administrators.
7.2. Parallel Processing and Symmetric Multiprocessing: Supercomputing
It is possible to get large volume number crunching without spending millions
of rupees on a supercomputer. You only need to link together (by some high speed
network) the requisite number of CPUs, with GNU/LINUX as the underlying OS.
Add some freely available message passing software and a effective parallel
processing number crunching machine is made. Such clusters are called "Beowulf
clusters". The other advantages of such a cluster other than building costs
is, up-gradation costs are minimal. The two best resources for Linux cluster
builders are
These sites are upgraded frequently with useful information for cluster builders.
7.2.1. Parallel computing document links
You will also want to read this excellent article on Linux Clustering Software (and the large variety of links it provides) by Joe Greenseid. I hope to go
through the links and include them subsequently in this HOWTO.
Other free document links for parallel processing are:
7.2.2. Parallel processing software for Linux
Now after reading the above documents, you have an idea of parallel processing.
Parallel program libraries are the core of parallel processing on a Linux
cluster. There are various free implementations of parallel processing libraries.
Since parallel processing is all about performance, these libraries have
some very nice functional tools to analyze your parallel program performance.
Given below is a set of links to these parallel program libraries and tools.
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Message Passing Interface: MPI is a standard specification of message passing libraries. The above document
gives a lot of links to documents on the standard, etc.. A MPI implementation
for Linux mpich is also available at that site. There are a lot of documents for Learning to use MPI .
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Local Area Multicomputer - LAM: LAM (Local Area Multicomputer) is an MPI programming environment and development
system for heterogeneous computers on a network. With LAM, a dedicated
cluster or an existing network computing infrastructure can act as one
parallel computer solving one problem. LAM features extensive debugging
support in the application development cycle and peak performance for
production applications. LAM features a full implementation of the MPI
communication standard. You can download the sources (tar-zipped, rpm)
or binaries from here A host of MPI tutorial links and also a `getting started with LAM' tutorial
is available here
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Parallel Virtual Machine : As the PVM home page describes, it is a software package that permits a heterogeneous
collection of Unix and/or NT computers hooked together by a network
to be used as a single large parallel computer. Thus large computational
problems can be solved more cost effectively by using the aggregate
power and memory of many computers. The software is very portable. The
source, which is available free thru netlib, has been compiled on everything
from laptops to CRAYs.
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Ganglia: Ganglia is an open source cluster monitoring and execution environment developed
at the University of California, Berkeley Computer Science Division.
As the above link describes it, "Ganglia is as simple to install and
use on a 16-node cluster as it is to use on a 512-node cluster as has
been proven by its use on multiple 500+ node clusters". It not only
can link nodes in a cluster, but also link clusters to other clusters.
Scientific Computing with Free Linux Software
Table of Contents
0. Home
1. Preamble
2. Introduction
3. Code Development Tools
3.1. Programming Languages
3.2. Debugging Tools
3.3. Version Control Tools
3.4. Integrated Development Environments
4. Mathematics Packages
5. Numerical Methods and Libraries
6. Graphics and Visualization
7. Programming systems for GNU/Linux
8. Word-Processing and Poster presenting tools on Linux
9. Free Database Management Systems for Linux
10. Linux in the laboratory
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