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[Getfem-users] collaboration between GMM and KDE/Eigen


From: Benoît Jacob
Subject: [Getfem-users] collaboration between GMM and KDE/Eigen
Date: Sun, 21 Jan 2007 23:01:31 +0100
User-agent: KMail/1.9.5

Hello,

This mail is to propose a collaboration between the GMM project and parts of 
the KDE project.

Several subprojects of KDE (kde.org) have identified a common need for linear 
algebra functionality. After having considered the existing linear algebra 
libraries, we found that we needed to start a new one, which we called Eigen 
(eigen.tuxfamily.org). Like GMM, Eigen is a C++ template library.

More recently, a new need has appeared in Krita (koffice.org/krita), that 
Eigen can't currently fulfill: sparse matrices and vectors.

Since we see no point in reinventing the wheel, we would like to reuse 
existing code for that. After examining the existing libraries, we found that 
GMM was the most interesting one from our point of view.

However, using GMM as an external dependency is not optimal for 
us, for several reasons:
- additional dependencies are frowned upon by distribution packagers
- we are only interested in a small subset of GMM, and GMM doesn't cover all 
of our needs
- we wouldn't like KDE to depend on two different incompatible linear algebra 
libraries, especially as there is much feature overlap between them.

So the best solution for us would be, if you allowed us to copy GMM code 
directly into Eigen. Eigen is licensed under the GPL plus an exception 
allowing any software to use it (much like the GNU C++ STL license, except 
that our exception is more liberal). This is very similar in spirit to the 
LGPL used by GMM. Of course, if we copy GMM code into Eigen, we will preserve 
the GMM authors's copyright lines. But the license will become the 
GPL+exception license used by Eigen.

So do you allow us to copy GMM code into Eigen? If yes, we'd probably have a 
few questions to ask about the GMM source code.

Conversely, we are planning to implement sparse algorithms that aren't yet 
available in GMM, namely sparse least squares:

http://www.stanford.edu/group/SOL/software/lsqr.html

We'd then be happy to back-port them to GMM if you're interested. This way, 
our collaboration would be reciprocal :)

Cheers,
Benoit Jacob and Ben Schleimer

PS. Please reply-to-all as we're not subscribed to this mailing list.

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