[Octave-bug-tracker] [bug #41453] norm is really slow for sparse matrices

[Massimiliano Fasi]

Follow-up Comment #10, bug #41453 (project octave):

Thank you for your feedback. Yes, I know that EIG computes all the eigenvalues
of the matrix and is hence not the best choice, as we need just the largest
one. Of course, that could be easily done with eigs. Nevertheless, we cannot
call eigs from the file I am modifying, and I agree that the best choice would
be using an ARPACK call, as you suggested. Reading a bit of source code, I
think I've spotted the function I should use, that is defined in
liboctave/numeric/eigs-base.cc, but I'm facing some troubles, as there are
many parameters to call and I can't really understand how it works. I am
working on it, but I don't know wether I 'll be able to get there in a
reasonable amount of time.

I have tested my implementation with the current implementation in Octave. In
particular, I compared 


norm(A)


with


norm(full(A))


getting that the latter is up to five time faster than the former. Of course,
that's not good, but it should be better than the factor 1000 we had at the
beginning.

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