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Ublas : |
Subject: [ublas] eigen Vs. ublas
From: Umut Tabak (u.tabak_at_[hidden])
Date: 2011-04-10 17:56:07
Dear all,
Since most of the people are more knowledgeable and more experienced
than me here, before testing myself, it is good to ask for some advice
and directions.
I have been looking at the eigen3 matrix library which seems to have
nice documentation and examples and some interfaces to some solvers
either (however the sparse module is not that mature as ublas I guess,
not sure on what I am saying here ;) due to lack of info). The main
issue is that looking at the benchmarks page here:
http://eigen.tuxfamily.org/index.php?title=Benchmark
It seems that it outperforms ublas and gmm++, especially for vector
operations. With both I had nice experiences as a user, maybe not on
serious problems. On matrix-vector side However, I had hard time in
understanding the important differences on the benchmarks, and I guess
these are provided for dense matrices, right?
There might be mistakes in the things I wrote, ublas is also highly
optimized in many sense, so if there are users of both libraries, could
someone draw some conclusions for both, especially for sparse matrix
operations.
One more, did anyone try to interface boost sparse matrices, especially
the csr, with the Intel MKL library for matrix vector multiplications(I
remember reading sth like that some time ago here but could not find the
post), if yes what is the performance gain if any? Since I should test
some conjugate gradient type methods, these matrix-vector products are
really important for me and moreover I have never used the MKL.
Any ideas and help are highly appreciated.
Greetings,
Umut