On Thu, Dec 17, 2015 at 5:52 AM, Sturla Molden <sturla.mol...@gmail.com> wrote:
> On 17/12/15 12:06, Francesc Alted wrote: > > Pretty good. I did not know that OpenBLAS was so close in performance >> to MKL. >> > > MKL, OpenBLAS and Accelerate are very close in performance, except for > level-1 BLAS where Accelerate and MKL are better than OpenBLAS. > > MKL requires the number of threads to be a multiple of four to achieve > good performance, OpenBLAS and Accelerate do not. It e.g. matters if you > have an online data acquisition and DSP system and want to dedicate one > processor to take care of i/o tasks. In this case OpenBLAS and Accelerate > are likely to perform better than MKL. > > The last time I benchmarked them MKL was much better at tall skinny matrices. > > Sturla > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion >
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