[Numpy-discussion] MKL and OpenBLAS
sturla.molden at gmail.com
Thu Feb 6 05:10:32 EST 2014
I just thought i'd mention this:
Why not use Eigen? It has a full BLAS implementation and passes the BLAS
test suite, and is generelly faster than MKL except on Core i7. Also, Eigen
requires no build process, just include the header files.
Yes, Eigen is based on C++, but OpenBLAS is parially coded in assembly.
Whatever language is used internally in the BLAS implementation should be
of no concern to NumPy.
BTW: The performance of OpenBLAS is far behind Eigen, MKL and ACML, but
better than ATLAS and Accelerate.
"Dinesh Vadhia" <dineshbvadhia at hotmail.com> wrote:
> This conversation gets discussed often with Numpy developers but since
> the requirement for optimized Blas is pretty common these days, how about
> distributing Numpy with OpenBlas by default? People who don't want
> optimized BLAS or OpenBLAS can then edit the site.cfg file to add/remove.
> I can never remember if Numpy comes with Atlas by default but either
> way, if using MKL is not feasible because of its licensing issues then
> Numpy has to be re-compiled with OpenBLAS (for example). Why not make it
> easier for developers to use Numpy with an in-built optimized Blas.
> Btw, just in case some folks from Intel are listening: how about
> releasing MKL binaries for all platforms for developers to do with it
> what they want ie. free. You know it makes sense!
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