Intel Math Kernel Library (MKL)

[Oceania2018]

Performance-sensitive algorithms can be swapped with alternative implementations by the concept of providers like Intel MKL.
https://software.intel.com/en-us/performance-libraries

[dotChris90]

Intels MKL library implement the LAPACK interfaces - so it would be logical to think about a layer with different LAPACK providers - in other words - a strategy pattern. Let users decide which LAPACK provider they want to use.

It will be not much work since LAPACK usual means --> all interfaces are the same. So the PInvoke class would be the same - just the native lib is different.

As fdncred already said. :)

[Oceania2018]

Sounds great.

[fdncred]

This is exactly what I was saying in #145 when I mentioned and linked to Armadillo.

[dotChris90]

@fdncred sorry yes i know but I want to mention it here at this place ;)

[Oceania2018]

@dotChris90 Please add MKL as a new provider when you have a chance.

[dotChris90]

yes. but after seeing Intel website I think we go strategy that mkl provider expects the lib installed. on their site they said u have to registry etc..... So.... I don't wanna quarrel with them. in case we simple copy their DLLs and publish them with NumSharp.... think Intel will be not happy.

so installation must be done manually by user.

At moment not sure what is most comfortable way to change providers.

My suggestion is that static numpy class has a static property lapack provider which is an enum.

The static lapack class will check this enum and will call the specific static lapack provider classes.

The user can change provider global. I think most comfortable.

[fdncred]

@dotChris90, I'll research this a bit because other people, namely microsoft, point to dlls such as this https://docs.microsoft.com/en-us/cognitive-toolkit/setup-mkl-on-windows.

Now that I look closer, this one ls mklml and is opensource by intel. Perhaps that is different.

[fdncred]

Check this out. Intel allows one to redistribute MKL. It's in the license.
https://software.intel.com/en-us/mkl/license-faq

And here is the full license.
https://software.intel.com/en-us/license/intel-simplified-software-license

[fdncred]

Here's a few Github projects that wrap MKL in C#. May be easier just to use something that already exists.
https://github.com/DNRY/CSIntelPerfLibs
https://github.com/Rafka86/SharpMKL
https://github.com/Proxem/BlasNet

[dotChris90]

@fdncred much thanks for investigation. This makes the situation much better. 👍