[Numpy-discussion] performance matrix multiplication vs. matlab
david at ar.media.kyoto-u.ac.jp
Fri Jun 5 13:48:45 EDT 2009
Eric Firing wrote:
> The eigen web site indicates that eigen achieves high performance
> without all the compilation difficulty of atlas. Does eigen have enough
> functionality to replace atlas in numpy?
No, eigen does not provide a (complete) BLAS/LAPACK interface. I don't
know if that's even a goal of eigen (it started as a project for KDE, to
support high performance core computations for things like spreadsheet
But even then, it would be a huge undertaking. For all its flaws, LAPACK
is old, tested code, with a very stable language (F77). Eigen is:
- not mature.
- heavily expression-template-based C++, meaning compilation takes
ages + esoteric, impossible to decypher compilation errors. We have
enough build problems already :)
- SSE dependency harcoded, since it is setup at build time. That's
going backward IMHO - I would rather see a numpy/scipy which can load
the optimized code at runtime.
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