Numerical Analysis/Methods Packages

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SUMMARY

This discussion focuses on numerical analysis packages in C/C++, specifically mentioning LAPACK and its C++ counterpart, LAPACK++. Users recommend the GNU Scientific Library (GSL) and resources from Netlib for various numerical analysis functions. Optimization of these packages varies based on the intended processing type, including vector, parallel, or scalar processing. The Template Numerical Toolkit is highlighted as a modern alternative to LAPACK++.

PREREQUISITES
  • Familiarity with C/C++ programming languages
  • Understanding of numerical analysis concepts
  • Knowledge of optimization techniques in programming
  • Basic experience with libraries and package management in C/C++
NEXT STEPS
  • Explore LAPACK and its C++ version, LAPACK++
  • Investigate the GNU Scientific Library (GSL) for numerical functions
  • Learn about the Template Numerical Toolkit for advanced numerical methods
  • Research optimization techniques for vector and parallel processing in C/C++
USEFUL FOR

Software developers, numerical analysts, and researchers looking to implement efficient numerical methods in C/C++ will benefit from this discussion.

neurocomp2003
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Any body use or know of any good numerical analysis packages in C/C++.
something like LAPACK. and are they easy to use.
 
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Here is a good library of numerical analysis functions:

http://www.gnu.org/software/gsl/

If you want to learn how numberical analysis is done in C this is a good resource:

http://www.library.cornell.edu/nr/cbookcpdf.html
 
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thanks i alredy have thle numerical recipesin C(waiting on C++) just wondering if there were some other ones, or if people have used cLAPACK. I'll look into gsl but it seems only for linux =[ and I'm coding in windows platform(like the vc6 interface too much.

i'll also look at the netlib site...thanks...thats the one my compphys text(landau) suggested...have you guys used these packages...are they pretty optimized?
 
Yes, I've used/use several programs from netlib and have never had any problems with any of them (including several routines from LAPACK-fortran version). As for optimization it depends on what you mean by "optimized". The code can be optimized for vector processing, parallel processing, or scalar processing. Check the header of the given code you want for specifics.
 
You may know of this, but there's a version of LAPACK for C++ called LAPACK++, but this is being superseeded by the Template Numerical Toolkit, available at http://math.nist.gov/tnt/.
 
With respect to degree of "optimization" of netlib packages typically exceed my own workings by a fair margin, as problem free as it comes.

Usually access via our neighboring organization who have their things pretty good straightened and sorted out:

http://www.csc.fi/math_topics/FTP/index.html
http://www.csc.fi/math_topics/Software.html
 
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