[Numpy-discussion] performance solving system of equations in numpy and MATLAB

[Gregory Lee]

Hi,

I just ran both on the same hardware and got a slightly faster computation
with numpy:

Matlab R2012a:  16.78 s  (best of 3)
numpy (python 3.4, numpy 1.10.1, anaconda accelerate (MKL)):  14.8 s  (best
of 3)

The difference could because my Matlab version is a few years old, so it's
MKL would be less up to date.

Greg

On Thu, Dec 17, 2015 at 9:29 AM, Andy Ray Terrel <andy.terrel at gmail.com>
wrote:

>
>
> On Thu, Dec 17, 2015 at 5:52 AM, Sturla Molden <sturla.molden at 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
>>
>>
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>
>
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