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From "Ted Dunning" <ted.dunn...@gmail.com>
Subject Re: svn commit: r721203 [1/2] - in /commons/proper/math/branches/MATH_2_0: ./ src/java/org/apache/commons/math/linear/ src/site/xdoc/ src/site/xdoc/userguide/ src/test/org/apache/commons/math/linear/
Date Thu, 27 Nov 2008 21:27:18 GMT
Luc,

Last I looked, I think I saw that commons math used a double indirect
storage format very similar to Jama.

Is there any thought to going to a higher performance layout such as used by
Colt?

On Thu, Nov 27, 2008 at 9:10 AM, <luc.maisonobe@free.fr> wrote:

> Hello,
>
> This commit is the result of weeks of work. I hope it completes an
> important feature
> to [math], computation of eigenvalues and eigenvectors for symmetric real
> matrices.
>
> The implementation is based on algorithms developed in the last 10 years or
> so. It is based partly on two reference papers and partly on LAPACK. Lapack
> is distributed under a modified-BSD license, so this is acceptable for
> [math]. I have updated the NOTICE file and taken care of the proper
> attributions in Javadoc.
>
> The current status is that we can solve eigenproblems much faster than Jama
> (see the speed gains in the commit message below). Furthermore, the
> eigenvectors are not always computed, they are computed only if needed. So
> applications that only need eigenvalues will benefit from a larger speed
> gain. This could even be improved again by allowing to compute only some
> eigenvalues, not all of them. This feature is available in the higher level
> LAPACK routine, but I didn't include it yet. I'll do it only when required,
> as this as already been a very large amount of work.
>
> If someone could test this new decomposition algorithm further, I would be
> more than happy.
>
> My next goal is now to implement Singular Value Decomposition. I will most
> probably use a method based on eigen decomposition as this seems to be now
> the prefered way since dqd/dqds and MRRR algorithms are available.
>
> Luc
>
> ----- luc@apache.org a écrit :
>
> > Author: luc
> > Date: Thu Nov 27 07:50:42 2008
> > New Revision: 721203
> >
> > URL: http://svn.apache.org/viewvc?rev=721203&view=rev
> > Log:
> > completed implementation of EigenDecompositionImpl.
> > The implementation is now based on the very fast and accurate dqd/dqds
> > algorithm.
> > It is faster than Jama for all dimensions and speed gain increases
> > with dimensions.
> > The gain is about 30% below dimension 100, about 50% around dimension
> > 250 and about
> > 65% for dimensions around 700.
> > It is also possible to compute only eigenvalues (and hence saving
> > computation of
> > eigenvectors, thus even increasing the speed gain).
> > JIRA: MATH-220
>
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>


-- 
Ted Dunning, CTO
DeepDyve
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