Intel® MKL version 2020 Update 4 is now available

[Gennady_F_Intel]

Intel® Math Kernel Library (Intel® MKL) is a highly optimized, extensively threaded, and thread-safe library of mathematical functions for engineering, scientific, and financial applications that require maximum performance.

Intel MKL 2020 Update 4 packages are now ready for download.

Intel MKL is available as part of the Intel® Parallel Studio XE and Intel® System Studio. Please visit the Intel® Math Kernel Library Product Page.

Please see What's new in Intel MKL 2020 and MKL 2020 Update 4 follow this link

[Towie__Ewan]

Hi,

I'm trying to download MKL 2020U4 but I keep getting directed to the oneAPI download which forces me to 2021U1.

Can anyone give me a weblink that will let me download older versions of the library?

Thanks,

Ewan

[Gennady_F_Intel]

could you please try to reach 2020 u4 via this page - https://software.intel.com/content/www/us/en/develop/articles/free-ipsxe-tools-and-libraries.html

[jeremybouny]

Hi,
I have the exact same issue. It is not possible to download 2020 u4 or any other older version through this link.
When opening "Download libraries now", it is reporting me "you need a serial number to register for this product" while it is clearly stated in the page you linked "Free Intel Performance Libraries for Everyone".

[Webb]

Trying to get MKL from intel.com is a Kafkaesque nightmare, and I haven't been able to get pytorch to build using the new oneAPI MKL.

Save yourself a lot of trouble and instead use conda or pip to download the MKL. Currently, you must use conda if you need also need the mkl dnn library, or you may use pip if you don't.

Examples:

1. install miniconda https://docs.conda.io/en/latest/miniconda.html
2. set up and activate a conda environment (instructions at the above link)
3.
conda install -c conda-forge mkl mkl-devel mkl-include intel-openmp blas=2.108=mkl blas-devel=3.9.0=8_mkl libblas=3.9.0=8_mkl libcblas=3.9.0=8_mkl liblapack=3.9.0=8_mkl liblapacke=3.9.0=8_mkl
conda install intel-openmp

or

pip install mkl intel-openmp
(doesn't include mkl dnn)

[Webb]

[ignore]

[jeremybouny]

Thank you for the answer,

I finally succeeded in downloading MKL thanks to conda, a bit similarly to what you proposed. This is the only location where it is seems to have all the correct versions.

Conda is quite intrusive, it is not really cool to have to download it just to download the correct MKL packages. However, it is working well.

# optional: force a specific OS download: win-64, osx-64, linux-64
set CONDA_SUBDIR=win-64
# download MKL package into a folder
conda create --prefix <path_to_a_directory> -c intel mkl-devel=<version> -y

[Webb]

One correction: I said pip MKL doesn't have MKL DNN but anaconda MKL does. That's wrong: anaconda MKL doesn't have MKL DNN either. opeAPI has it, and that's what my build was linking to, even though, strangely, it could initially use oneAPI for the rest of MKL. I did finally get pytorch to build with only oneAPI, although the fastest/easiest seems to be to use oneAPI for MKL DNN and anaconda MKL for all other MKL libraries. But I'll look through my bash history and see if I can piece together how to build pytorch using only oneAPI, no anaconda.