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Scientific Computing with Free software on GNU/Linux HOWTO

Manoj Warrier

<m_war (at)>

Shishir Deshpande

<shishir (at)>

V. S. Ashoka

<ashok (at)>

Revision History                                                             
Revision 1.2           2004-10-19           Revised by: M. W                 
1 Correction and new additional links                                        
Revision 1.1           2004-06-21           Revised by: M. W                 
Updates and evaluated distros                                                
Revision 1.0           2003-11-18           Revised by: JP                   
Document Reviewed by LDP.                                                    
Revision 0.0           2003-10-01           Revised by: M. W                 
first draft proposed                                                         

  This document aims to show how a PC running GNU/Linux can be used for
scientific computing. It lists the various available free software and also
links on the world wide web to tutorials on getting started with the tools.

Table of Contents
1. Preamble
    1.1. Copyright and License
    1.2. Disclaimer
    1.3. Motivation
    1.4. Credits / Contributors
    1.5. Feedback
    1.6. Translations
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
    5.1. Repositories
    5.2. Other topic specific numerical libraries
6. Graphics and Visualization
7. Programming systems for GNU/Linux
    7.1. The GNU/Linux Workstation
    7.2. Parallel Processing and Symmetric Multiprocessing: Supercomputing
8. Word-Processing and Poster presenting tools on Linux
    8.1. Word Processing Tools
    8.2. Poster presentation tools
9. Free Database Management Systems for Linux
10. Linux in the laboratory

1. Preamble

1.1. Copyright and License

  This document, Scientific Computing with free software on GNU/Linux HOWTO,
is copyrighted (c) 2002 by Manoj Warrier. Permission is granted to copy,
distribute and/or modify this document under the terms of the GNU Free
Documentation License, Version 1.1 or any later version published by the Free
Software Foundation; with no Invariant Sections, with no Front-Cover Texts,
and with no Back-Cover Texts. A copy of the license is available [http://]   here

1.2. Disclaimer

  No liability for the contents of this document is accepted. Use of the
concepts, examples, links and information is entirely at your own risk. There
may be errors and inaccuracies, that could damage your system, waste your
time, etc... Proceed with caution, and although this is unlikely, the author
takes no responsibility whatsoever.

  All copyrights are held by their respective owners, unless specifically
noted otherwise. Use of a term in this document should not be regarded as
affecting the validity of any trademark or service mark. Naming of particular
products, software or brands should not be seen as endorsements

  I have not used many of the software applications to which links are
provided. There are simply too many applications that do the same thing, that
one cannot be expected to have used all of them. In a book on Scientific
Computing using GNU/Linux, one would mention ones favorite tool to carry out
a task and describe it in detail. However this is a howto providing links to
various available free tools for scientific computing and may contain links
to some software that promises much but delivers little and vice versa.

1.3. Motivation

  This howto mainly consists of the links provided at http:// which has to be disbanded due to a name conflict.
The best alternative seems to be to make it a Linux document and host it at
the LDP site. Another reason is that there seems to be many free software
applications doing the same things. We hope to provide links to the available
software thereby making it easy for the scientific community to make a choice
without spending much time.

1.4. Credits / Contributors

  In this document, I have the pleasure of acknowledging:

��*�  Linus Trovalds, Richard M. Stallman and their merry men for Linux, GNU
    and also for indirectly broadening various perspectives which were not
    really obvious.
��*�  A host of colleagues and friends from the Institute for Plasma
    Research, India for discussions at various times.
��*�  Marcel Bose, Ivan Lamouret, K. Scott Hunziker, Livine Christin, W.
    Herbert, Simon Pinches and many others for suggesting various links
    mentioned in this document.
��*�  Vasudha my wife for letting me do what I wish and egging me on with
    comments like "let us hope that you will finish at least this project"

  Shishir and Ashoka are co-authors of this document because such a
collection of links was Shishir's idea and Ashoka is always contributing by
providing links, suggestions and a second point of view. They will be helping
me maintain this HOWTO too.

1.5. Feedback

  Feedback is most certainly welcome for this document. Send your additions,
comments and criticisms to the following email address : <m_war at>.

1.6. Translations

  No translations yet.

2. Introduction

  GNU/Linux is probably the platform of choice for scientific computing.
There exists a wide variety of high level languages, debugging tools and
other code development tools for programming, numerical subroutines for
solving various types of equations, plotting and visualization packages, word
processing software which can display equations and figures and in fact
parallel programming software to construct a supercomputer with off the shelf
PC parts and some hardware. This document aims to provide a list of free
software for carrying out the above tasks and links to tutorials and other
documents on how to setup and use these software applications.

  This document does not aim to provide links to subject specific free
software available for GNU/Linux systems. It aims to show how GNU/Linux can
be used best to handle scientific computing tasks. It is hoped that people or
institutions with interest in a specific subject list, compile a list of the
free software available for that subject ... for example see Linux for
Astronomy, Linux for Biotechnology and Linux for Chemistry at The Random
Factory . Another site with a lot of links (to commercial and free)
scientific software is Scientific Applications on Linux. The [http://]   GNU Software Directory also has links to
many of the links provided in this howto plus many more topic specific
software. You may also want to check out []  
The Science and Engineering section at

  The software links provided are classified into

��*�  [./devtools.html] Code development tools
��*�  [./mathpack.html] Mathematics packages
��*�  [./numlib.html] Numerical subroutines and libraries
��*�  [./graphvis.html] Graphics and visualization
��*�  [./systems.html] GNU/Linux Systems
��*�  [./publish.html] Publishing tools
��*�  [./database.html] Databases
��*�  [./lablinux.html] Linux in the Laboratory

  Just installing GNU/Linux on your PC makes it a powerful workstation. The
various popular distributions however do not have all the tools needed to
make it the ideal scientific computing machine. This HOWTO aims to fill in
this gap by creating a list of free software useful for scientific computing.
It is assumed that people reading this document already have a PC with Linux
and the GNU utilities installed. For those who do not have such a setup and
want to install GNU-Linux can check out [./GNULinuxWS.html] GNU/Linux Systems
for links to documents on installing GNU/Linux, and also on how to get
started using GNU/Linux. Recently there has been an effort by Dirk
Eddelbuettel to create a scientific computing environment [http://] Quantian which probably is the first
GNU-Linux distribution tailored for Scientists. I checked out the latest
release and it has almost all the packages mentioned in this document and
many packages not mentioned. It is fair to say that if you have any linux
distribution in which the packages are managed by rpms or any debian based
system, you will find pre-compiled binaries of these packages and will not
have to waste much time installing them.

3. Code Development Tools

  Code development consists of mainly Programming languages, Debugging tools,
Version Management tools, Compiling tools, and Integrated Development
Environments (IDEs) where all the above are coupled as a single software

3.1. Programming Languages

  Links are provided to various compilers used in Scientific Computing like
FORTRAN, C, C++, Java and more recently Python.

��*�  GNU Compiler Collection : GNU's project to produce a world class
    optimizing compiler. It works on multiple architectures and diverse
    environments. Currently GCC contains front ends for C, C++, Objective C,
    GNU Fortran-95, Java, and Ada, as well as libraries for these languages
    (libstdc++, libgcj,..).
      For manuals on using the various GCC compilers check out [http://]   The GCC online documentation
��*�  g77 : The GCC front end for FORTRAN 77. It is a very good FORTRAN77
    compiler. It however does not have the -r8 option which compiles a
    program as double precision. This could be a good compiler design
    philosophy but in many cases gives problems when porting a code from SUN
    / DEC / HP workstations onto Linux systems. The g77 manual is available
    at The Gcc Online documentation site.
��*�  [] gfortran. I was happy to receive this
    link by mail. It was 3 years since I had migrated to using the GNU C
    compiler for scientific computing because there was no "truly free"
    FORTRAN-95 compiler available then. I thank Paul Thomas for this link.
��*�  [] g95. gfortran above and g95 are reportedly
    offshoots from the same CVS tree. Has an impressive list of programs that
    compiles and runs using this compiler.
��*�  []   fort77
    and f2c: fort77 is a perl program which invokes the f2c command (a
    Fortran to C translator) transparently, so it can be used just like a
    real Fortran compiler. Fort77 can be used to compile Fortran, C and
    assembler code and can link the code with f2c libraries. If you install
    fort77, you'll also need to install the f2c package. This does not have
    the "-r8" problem. You can download fort77 and f2c from the above link.
��*�  [] lush: An object-oriented programming
    language, which combines the flexibility of an interpretive language,
    with the efficiency of a compiled language. It has full interfaces to
    numerical libraries (GSL, LAPACK, BLAS), graphics libraries (OpenGL),
    which allows creation of graphics and 3D animations and many other
    features that sound too good to be true. I have not yet tried this out,
    but it sounds very promising.
��*�[]   Scientific Python: You may want
    to explore [] Python for your scientific computing
    needs. Python is an interpreted, interactive, object-oriented programming
    language. It has a number of extensions for numerics, plotting, data
    storage and combined with Tk lets you develop very good GUIs for your
    codes. The most exciting aspect is that it simplifies programming because
    it has modules for almost anything (vectors, tensors, transformations,
    derivatives, linear algebra, Fourier transforms, statistics, etc ...) are
    available. You can also wrap C and Fortran libraries from Python. Finally
    if you want to write a numerical scheme of your own you may find that it
    is simpler in Python. There are also interfaces to netCDF (portable
    binary files), MPI and BSPlib (parallel programming).
      You can further explore Python for Scientific computing here:
    ��+�  []  
        Scientific-Python: A collection of modules for scientific computing
        on Python. All the necessary modules can be downloaded as either a
        tar file or an RPM file from here. The maintainer Konrad HINSEN also
        has a nice tutorial on []   Scientific Computing in Python.
    ��+�  [] SciPy An open source library of scientific
        tools for Python. It includes modules for graphics and plotting,
        optimization, integration, special functions, signal and image
        processing, genetic algorithms, ODE solvers, etc.

3.2. Debugging Tools

  In this section links are given to mainly debugging tools for GCC and
FORTRAN. I understand that python has a debugging module built in though I
have not used it. The purpose of a debugger is to allow you to see what is
going on inside a program while it executes or what the program was doing
when/if it crashed.

��*�[] Ftnchek: A FORTRAN checker designed
    to detect errors in a Fortran program that a compiler usually does not.
    Therefore it is best to run ftnchek on your FORTRAN programs after it has
    compiled without errors. Its purpose is to assist the user in finding
    semantic errors. Semantic errors are legal in the Fortran language but
    are wasteful or may cause incorrect operation. An on-line [http://]   manual is available. This project
    is looking for volunteers to bringing ftnchek up to the Fortran 90
��*�gdb : All programs written in the languages supported by GCC can be
    debugged using gdb, an excellent interactive, command line debugger. You
    can compile your programs using a -g option which then compiles your code
    with debugging information inserted into the executable. It can start
    your programs, stop your programs on specified conditions and at
    specified locations, examine what happened when your program stops. In a
    large code with multiple cascading calls to various functions it can back
    trace the function calls. You can also Download the document Debugging
    with GDB and a quick reference card.
��*�[] xxgdb: It is a front end to the gdb
    debugger. Useful for beginners to gdb as it lists out the whole gdb
    commands as buttons with a area for viewing source on which one can
    include break points, etc by a click of the mouse, and another area for
    viewing the debugging results.
��*�DDD: The GNU Data Display Debugger, GNU DDD, is a graphical front-end for
    command-line debuggers such as GDB, DBX, WDB, Ladebug, JDB, XDB, the Perl
    debugger, or the Python debugger. Besides ``usual'' front-end features
    such as viewing source texts it also has a good interactive graphical
    data display, where data structures are displayed as graphs. Follow this
    link for a []   DDD manual in postscript /
    HTML / PDF format.

3.3. Version Control Tools

  It will be worth your while investing some time in learning to use one of
the version control tools below (cvs is what I use ..) if you are into any
serious code development.

��*�[]   Concurrent Versions System
    : CVS is one of the most popular version control systems running on the
    Linux operating system. Popular Linux projects like Apache, EGCS, GIMP,
    and others are using CVS to coordinate their efforts ... This is how the
    URL linked above describes their effort.
      A tutorial on CVS is available at [
    cvs-tutorial.html]   Gentoo Linux Documentation and a free CVS book is
    available [] here
��*�[]   Project Revision Control
    System : PRCS, the Project Revision Control System, is the front end to a
    set of tools that (like CVS) provide a way to deal with sets of files and
    directories as an entity, preserving coherent versions of the entire set.
    PRCS was designed primarily by Paul N. Hilfinger, with input and
    modifications by Luigi Semenzato and Josh MacDonald. PRCS is written and
    maintained by Josh MacDonald. Its purpose is similar to that of SCCS,
    RCS, and CVS, but (according to its authors, at least), it is much
    simpler than any of those systems. This page is where information on the
    latest developments in PRCS can be found.
��*�[] Gbuild : gbuild is a script written in the
    Bourne shell language to simplify package maintenance by allowing you to
    automate code update from CVS, compilation, building tar/rpms/srpms of
    your package. some external scripts which certain functions of gbuild
    depend on are written in Perl. gbuild is released under the GPL.

3.4. Integrated Development Environments

  Integrated development environments (IDEs) can be very useful for building
code and ideally come with all the above tools (i.e a compiler, a debugger
and a version control tool). In addition to that IDEs also usually provide a
makefile generator, documenting help, online help manuals, etc.

��*�[] Kdeveloper : A easy to use C/C++ IDE
    (Integrated Development Environment) for Linux. It supports KDE/Qt,
    GNOME, plain C and C++ projects. This site has a lot of documentation
    ..... a highly browsable site for software developers. Specifically,
    KDevelop manages or provides:
      All development tools needed for C++ programming like Compiler, Linker,
    automake and autoconf; KAppWizard, which generates complete, ready-to-go
    sample applications; Class generator, for creating new classes and
    integrating them into the current project; File management for sources,
    headers, documentation etc. to be included in the project; The creation
    of User-Handbooks written with SGML and the automatic generation of
    HTML-output with the KDE look and feel; Automatic HTML-based
    API-documentation for your project's classes with cross-references to the
    used libraries; Internationalization support for your application,
    allowing translators to easily add their target language to a project;
    KDevelop also includes WYSIWYG (What you see is what you get)-creation of
    user interfaces with a built-in dialog editor; Debugging your application
    by integrating KDbg; Editing of project-specific pixmaps with KIconEdit;
    The inclusion of any other program you need for development by adding it
    to the "Tools"-menu according to your individual needs.
��*�[] VDKbuilder: VDKbuilder is a tool
    that helps programmers in constructing GUI interfaces, editing,
    compiling, linking, and debugging within an integrated environment. Using
    VDKBuilder dramatically reduces developing time since all code related to
    GUI construction and signal processing is automatically generated,
    maintained and updated. It is distributed under the GNU Public License.
    Visit the site for downloading the software.

4. Mathematics Packages

  All the links below are free high level languages and Mathematics Packages
for Scientific Computation on Linux. These packages are usually like a
Mathematical Laboratory in which numerical computations can be done and
usually have their own interpreted language. They either link to a popular
(free) plotting package or have their own graphics and plotting capability.
They also provide capability to I/O files and interface with other
programming languages like C, C++, Fortran, etc ... Now a days some of them
have parallel programming capabilities. I have not included [http://] MuPAD, a good symbolic math package, since is not really free.
Check out if their most [] free license
suits you.

��*�[] Octave: An excellent package for numerical
    computations. It uses gnuplot for plotting and has a online help. It is
    also easily extensible (i.e. new functions, procedures can be written)
    either using its own language or by using dynamically loadable modules
    written in C, C++, Fortran or other languages. An extensive manual is
    available [] here. You can get a
    GNOME based front end for it []
    here. It is distributed under the GNU Public License.
��*�  [] Scilab: Another superb package
    numerical computations having a good user interface and a very good
    online click-able help. Its plotting and graphic capabilities are also
    very impressive. It also provides for easy interfacing with Fortran and
    C. It has its own [] free
��*�[]   Yorick:
    Yorick is a fast, interpreted language, designed for scientific computing
    and numerical analysis. The syntax is similar to C, but the variables
    need not be declared. It offers an interactive graphics package based on
    X windows. X-Y plots, quadrilateral meshes, filled meshes, cell arrays,
    and contours are supported. You can embed compiled routines in Yorick to
    solve problems for which the interpreter is too slow. It is also useful
    as a pre and post processor for large physical simulation programs. A
    tutorial like manual is available [
    yorick/doc/manual/yorick.html]   here. Yorick is open source software,
    copyright of the Regents of the University of California.
��*�  [] Algae: As the above link describes it,
    Algae is a interpreted language for numerical analysis. It was developed
    as a fast and versatile tool, capable of handling large problems. Algae
    consists of the programming language Algae, and algae, the interpreter.
    Its features include speed (generally much faster than octave, RLaB and
    Scilab), storage of sparse arrays and a code profiling capability (to
    check where your code spends its time). A user manual is available [http:
    //] here. It is distributed under the GNU
    General Public License.
��*�[] YACAS: As the above link describes it,
    "YACAS is an easy to use, general purpose Computer Algebra System, a
    program for symbolic manipulation of mathematical expressions. It uses
    its own programming language designed for symbolic as well as
    arbitrary-precision numerical computations". Links to documentation (user
    manual, tutorial, etc ..) is available [
    manindex.html] here. It is distributed under the GNU General Public
��*�  [] RLAB: The above link describes it thus,
    "Rlab is an interactive, interpreted scientific programming environment.
    Rlab is a very high level language intended to provide fast prototyping
    and program development, as well as easy data-visualization, and
    processing". It is distributed under the GNU General Public License. The
    author Ian Searle has written an article in [
    /] The Linux Journal titled An Introduction to Rlab which as he reminds
    us, is a bit dated, and a [
    rlab-ref.html]   Reference Manual is also available.
��*�[]   Maxima: Maxima is a symbolic
    computation program. The above link describes it as follows, "Maxima is a
    descendant of DOE Macsyma, which had its origins in the late 1960s at
    MIT. It is the only system based on that effort still publicly available
    and with an active user community, thanks to its open source nature.
    Macsyma was the first of a new breed of computer algebra systems, leading
    the way for programs such as Maple and Mathematica. This particular
    variant of Macsyma was maintained by William Schelter from 1982 until he
    passed away in 2001. In 1998 he obtained permission to release the source
    code under GPL".
��*� [] The R-Project for Statistical Computing: R
    is a language and environment for statistical computing and graphics. It
    provides a large collection of tools for statistical analysis of large
    arrays of data and also graphical facilities. R is also a complete
    effective programming language. For computationally intensive tasks, C,
    C++ and Fortran code can be linked and called at run time. A
    comprehensive set of manuals dealing with installation, introduction,
    writing extensions, etc ... is available [
    manuals.html] here. It is distributed under the GNU General Public
��*� [] gTybalt: gTybalt is a
    step towards a free computer algebra system. It is object oriented,
    allowing symbolic calculations within C++. It is efficient, in the sense
    that solutions developed with gTybalt can be compiled with a C++ compiler
    and executed independently of gTybalt. The mathematical formulae are
    visualized using TeX fonts and can easily be converted to LaTeX. I did
    not realize that it has good graphic capabilities till I checked out the
    gTybalt [] manual.
    It is distributed under the GNU General Public License.
��*�  [] JACAL: As the link
    above describes it, " JACAL is an interactive symbolic mathematics
    program. JACAL can manipulate and simplify equations, scalars, vectors,
    and matrices of single and multiple valued algebraic expressions
    containing numbers, variables, radicals, and algebraic differential, and
    holonomic functions".
��*�  [] bc: bc is an arbitrary
    precision numeric processing language. It supports interactive execution
    of statements. Click here for a []
    Manual in a variety of formats. It is GNU software and is distributed
    under the GNU General Public License.

5. Numerical Methods and Libraries

  The best thing that could happen for scientific computing with free
software on GNU/Linux is the GNU Scientific Library [http://] GSL. It however has source code only in C and people
who use FORTRAN will find that a let down. Pouncing on this opportunity it is
recommended that GSL is another reason (in addition to the GCC C compiler,
coupled with the advantages of C programming) for starting to learn to use C.
In addition to this, the two best source code repositories for Numerical
Methods and libraries are [] Netlib and [http://] GAMS. There are new numerical packages being developed
outside the usual "write a FORTRAN program, get a numerical subroutine from
INTERNET for solving the numerics" concepts. The merits and demerits of this
approach are debatable, but there exist more options like [http://] Object Oriented Numerics GSL and []
GiNaC which are exciting developments.

5.1. Repositories

��*�  [] Netlib: An amazing amount of free source code
    for Numerical Methods. Netlib is THE source code repository which
    contains an innumerable amount of source code for Numerical Methods. It
    also has an active discussion forum wherein you can submit your queries
    and stay posted for help. Netlib also has a []  
    Parallel Tools Library and a search by subject.
��*�  []   GAMS: Guide to Available Mathematical
    Software GAMS has a very useful search using which one can search for
    keywords (example: ``diffusion'' to search for a diffusion equation
    solver). However the browse by package at GAMS reveals that a lot of the
    software they provide is a link to the netlib repository.
��*�  [] Object Oriented Numerics A site devoted to
    object oriented numerics. It has a Mailing list, Extensive Links to
    freely available libraries (OO of course) and freely available tools for
    object oriented scientific computing.
��*�  [] GNU Scientific Library The GNU
    Scientific Library (GSL) is a collection of numerical routines written
    from scratch in C. It provides an Applications Programming Interface
    (API) for C programmers and also allows wrappers to be written for very
    high level languages. It covers a wide range of numerical computing
    topics, has a good manual, is widely portable and is distributed under
    the GNU General Public License.
��*�  [] GiNaC GiNaC is designed to allow the creation of
    software which need symbolic manipulations embedded in them. It extends
    C++ by a set of algebraic capabilities and is recursively named for GiNaC
    is not a Computer Algebra system. It is distributed under the terms and
    conditions of the GNU general public license (GPL).

5.2. Other topic specific numerical libraries

��*�  [] FFTW FFTW is a collection of fast C routines for
    computing the Discrete Fourier Transform in one or more dimensions. It
    includes complex, real, and parallel transforms, and can handle arbitrary
    array sizes efficiently. This package includes both the double- and
    single-precision FFTW uniprocessors and the threads libraries.
��*�  [] LAPACK LAPACK (Linear Algebra PACKage)
    is a standard library for numerical linear algebra. LAPACK provides
    routines for solving systems of simultaneous linear equations,
    least-squares solutions of linear systems of equations, eigenvalue
    problems, and singular value problems. LAPACK is coded in Fortran77 and
    is built with egcs. It is well documented and widely used (and therefore
    widely tested).
��*�  [] SuperLU SuperLU is a general
    purpose library which performs an LU decomposition for the direct
    solution of large, sparse, non-symmetric systems of linear equations on
    high performance machines. Its written in C and is callable from either C
    or Fortran.
��*�  ARPACK ARPACK is a set of Fortran77 subroutines designed to solve large
    scale eigenvalue problems. A Users Guide is available. The above link
    also gives information about a parallel version of ARPACK - PARPACK and a
    object oriented version ARPACK++.
��*�  []   Computational Fluid Dynamics
    codes This link contains a comprehensive listing of public domain,
    shareware and freeware Computational Fluid Dynamics codes links with a
    description of each CFD code.

6. Graphics and Visualization

��*�  [] Gnuplot Gnuplot is a command-line driven
    interactive function plotting utility. It handles both curves (2
    dimensions) and surfaces (3 dimensions). Surfaces can be floating in the
    3-d coordinate space, or as a contour plot. For 2-d plots, there are also
    many plot styles, including lines, points, lines with points, error bars,
    and impulses. Graphs may be labeled with arbitrary labels and arrows,
    axes labels, a title, date and time, and a key. It has multiple plotting
    capabilities too. It allows saving the graphs in various formats which
    can be included in word processors. It can be used to generate
    publication quality plots.
��*�  [] NCAR Graphics A very popular graphics package
    which is very well documented and widely used. It provides basic
    ingredients for creating complex plots as functions / routines that can
    be called from Fortran and C. There is a contributed programming
    interface to the NCAR Graphics package: NCL (NCAR Command Language). The
    programming interfaces provide access to complex graphics utilities like
    contouring, world map projections, and velocity vectors. For the most
    part, the C interface is built on top of the Fortran interface... It is
    distributed under the GNU public license. Click [
    ngdoc/ng4.2] here for going to the documentation of all its various
��*�  [] OpenDX A very good Open Source Data eXplorer.
    It can handle large amounts of data and creates great visualizations. It
    was the tool I stumbled upon when I wanted a free graphics routine to
    make 3-D plots and zoom-in, rotate, and really eXplore the output Data
    from my codes. The downside is that compiling from source is really
    challenging and getting started is a difficult. However it has excellent
    documentation distributed with it and once I started off it was the best
    tool I have ever used.
��*�  [] Gri: It is a language for scientific
    graphics programming. The claim that Gri is similar to LaTeX in the sense
    that both provide extensive power as a reward for tolerating a learning
    curve seems exciting and I for one want to check this out!! Check out the
    following [] article in
    The Linux Journal. Go to the gri home page if you are now impressed by it
    and check out download info and manuals.
��*�  [] MayaVi: A scientific data visualizer written in
    Python. It is distributed under the BSD license. The screenshots look
    promising. Check out the above link for more details.
��*�  [] PGPLOT: PGPLOT is a Fortran
    77 or C callable subroutine package for drawing scientific 2D and Simple
    3D plots. One can call these routines during runtime and redirect the
    output to a variety of devices at run time. It is well documented and the
    full documentation is available at the above site. It is Free for
    Non-Commercial Use. A user manual is available online at PGPLOT Users
��*�  [] PLplot: This is a library of
    scientific plotting functions that can be called from C, C++, FORTRAN,
    TCL, PYTHON. PLplot features as described in the above link are, "It can
    be used to create standard x-y plots, semilog plots, log-log plots,
    contour plots, 3D plots, mesh plots, bar charts and pie charts. Multiple
    graphs (of the same or different sizes) may be placed on a single page
    with multiple lines in each graph. There are almost 2000 characters in
    the extended character set. This includes four different fonts, the Greek
    alphabet and a host of mathematical, musical, and other symbols. A
    variety of output devices are supported and new devices can be easily
    added by writing a small number of device dependent routines". To
    download click [
    2915]   here .
��*�  [] Grace Grace is a WYSIWYG 2D
    plotting tool for the X Window System and Motif. Grace runs on
    practically any version of Unix. Grace is a descendant of ACE/gr, also
    known as Xmgr. It is lisenced under the GNU public license. This link
    also has a tutorial and download information.
��*�  SciGraphica SciGraphica is a application for data analysis and
    technical graphics. It fully supplies plotting features for 2D, 3D and
    polar charts. The aim is to obtain a fully-featured, cross-platform,
    user-friendly, self-growing scientific application. It is free and
    open-source, released under the GPL license.
��*�  []   Plotutils: The
    GNU plotutils package contains software for both programmers and
    technical users. Its centerpiece is libplot.a powerful C/C++ function
    library for exporting 2-D vector graphics in many file formats, both
    vector and raster. It can also do vector graphics animations. Besides
    libplot, the package contains command-line programs for plotting
    scientific data. Many of them use libplot to export graphics.
��*�  [] DISLIN DISLIN is a high-level plotting library
    for displaying data as curves, polar plots, bar graphs, pie charts,
    3D-color plots, surfaces, contours and maps.
��*�  [] ImLib3D ImLib3D is an open source C++
    library for 3D (volumetric) image processing. It contains most basic
    image processing algorithms, and some more sophisticated ones. It comes
    with an optional viewer that features multi-planar views, animations,
    vector field views and 3D (OpenGL) multi-planar.
��*�  [] Ptplot: Ptplot is a 2D
    data plotter and histogram tool implemented in Java. Ptplot can be used
    as a standalone applet or application, or it can be embedded in your own
    applet or application.

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 [
Linux+Windows-HOWTO/index.html]   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 [
linux-admin-made-easy/index.html]   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

��*�The Beowulf Project home page and
��*�  The Extreme Linux Project

These sites are upgraded frequently with useful information for cluster

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:

��*�  []   The
    Beowulf Howto : This document introduces the Beowulf Supercomputer
    architecture and provides background information on parallel programming,
    including links to other more specific documents, and web pages. But,
    before that for an understanding of parallel processing and Symmetric
    multiprocessing on Linux, check out the following:
��*�  []
    The Parallel Processing on Linux HOWTO
��*�  []   The Symmetric
    Multiprocessing HOWTO

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.

��*�  []   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 .
��*�  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 [http://] here A host of MPI tutorial links and also a
    `getting started with LAM' tutorial is available [
    tutorials/]   here
��*�  []   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.
��*�  [] 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.

8. Word-Processing and Poster presenting tools on Linux

  Those of you who do not use []   LaTeX and find
it challenging and want a WYSIWYG word processor, keep your ears tuned to 
OpenOffice which has released version 1.2 of its openoffice software. Its
tools may compare well with the best in the market.

8.1. Word Processing Tools

��*�  [] Latex: LaTeX is a high-quality
    typesetting system, with features designed for the production of
    technical and scientific documentation. LaTeX is the de facto standard
    for the communication and publication of scientific documents. [http://]   David R.Wilkin's primer
    "Getting Started with LaTeX" is a good tutorial to getting started with
    LaTeX. For those who have to live with a WYSIWYG documenting tool, check
    [] LyX. This is a front-end for latex. It isn't as
    powerful as latex proper, but helps with a good WYSIWIG.
��*�  [] Lout: A document formatting system
    similar to latex. Good features, documentation and history. Light weight
    and outputs postscript. Thanks to Emiliano Gavilan for this link.
��*�  [] Abiword: As the AbiWord home page says,
    "AbiWord is suitable for typing papers, letters, reports, memos, and so
    forth". It has won many awards and seems to be the best open source
    WYSIWYG word processor. Check out the above link to know more about it
    and download it.
��*�  [] kword: As the kword home page says,
    "KWord is a FrameMaker-like word-processing and desktop publishing
    application. KWord is capable of creating demanding and professional
    looking documents. Whether you are a corporate or home user, production
    artist or student, KWord will prove a valuable and easy to use tool for
    all your word processing and layout needs". Check out the above link to
    know more about it and download it. (you might want to know more about
    the whole []   koffice suite).

8.2. Poster presentation tools

��*�  []   KPresenter: KPresenter is the
    presentation tool of the KOffice suite of office utilities. It allows
    screen presentations with all the trappings one is used to seeing in
    costly presentation tools. It also allows honest, real scientific
    presentations where one does not have to impress the audience with non
    subject specific stuff :-). The best thing about it is the possibility of
    saving the presentation as a html file. It makes portable network
    graphics files with each presentation slide. With a smattering of
    knowledge of html files one could put in a animated image as a image link
    thereby allowing one to show movies too when necessary.
��*�  [] Xfig : Though the man page claims that
    it is a facility for the interactive generation of figures ...., It in
    fact much more than that. Other than generating figures for elucidating
    what you want to say in a poster, it helps you import and export figures
    in a variety of formats, write text in various fonts and sizes, generate
    Greek symbols and color text, Save as latex picture file or any other
    format supported by your word processor for inclusion in your
    publications, generate GIFs of each page of the poster to put on your web
    site, and finally it generates *.fig files which are small in size. The
    only thing on my wish list for xfig is the capability to edit the
    imported pictures which are not in *.fig format. Therefore for a computer
    screen projected poster presentation you need a frames capable browser
    with contents in one frame and the xfig generated posters (exported as
    *.png or *.jpg from Xfig) on the other.

9. Free Database Management Systems for Linux

  Scientific computing has two parallel data needs, one the physical values
of the data itself, and the other is Database systems to manage the data. In
this document links are provided only to database resources on the net and
free Database systems. I personally do not use databases to manipulate the
data generated by my codes. gawk, sed, and other basic Unix commands like
grep, head and tail seem sufficient to manipulate any data I generate. I
thought I should include this section for the large data generators.
Hopefully a person with experience in databases will make this section

��*�  [ ]   Free
    database list
��*�  [ ]   ACM SIGMOD: Index of
    publicly available database software.
��*�  [] MySQL: A relational Database management system.
��*�  [] PostgreSQL As the link above describes it
    ...PostgreSQL is a sophisticated Object-Relational DBMS, supporting
    almost all SQL constructs, including subselects, transactions, and
    user-defined types

10. Linux in the laboratory

  Again this is a section where I have zero experience and hope someone will
with experience will contribute towards making this document better. However,
I provide below links suggested by Sambaran Pahari and Deepak Gupta. These
links seem to be very good from my inexperienced viewpoint.

��*�  [] The Linux Lab Project A site for "Linux
    Lab Project."..everything to do with laboratory process, process control,
    automation and data acquisition on Linux. As the above link says, "The
    Linux lab project is intended to help people with development of data
    collection and process control software for LINUX. It is planned to
    provide a standardized development environment for a wide variety of
    applications from hardware support to application development".
��*�  []   Linux Parallel port drivers:
    The above link says, "If you have a parallel port device and would like
    to know if there is a Linux driver available for it --then this is the
    place to look". Sounds like a confident claim.

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