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From Anton Chernov <mecher...@gmail.com>
Subject Re: Remove MKLML as dependency
Date Wed, 19 Sep 2018 09:12:45 GMT
MKLML is super easy to install since it's distributed with the MKL-DNN
package on GitHub [1] and this for all desktop platforms (Linux, Windows
and MacOS). Currently, I don't see a way how MKL could be automatically
installed on a Windows CI host for example. It also has the advantage of
being smaller than the whole MKL library, which is good for distribution,
while still having enough functionality it it.

I would rather be in favour of keeping it.

The unfortunate situation with the fact that MKLML is downloaded for every
cmake build will hopefully get resolved when #11148 PR [2] will be merged.

Best regards,
Anton

[1] https://github.com/intel/mkl-dnn/releases
[2] https://github.com/apache/incubator-mxnet/pull/11148


ср, 19 сент. 2018 г. в 8:31, Lv, Tao A <tao.a.lv@intel.com>:

> If you just want to test the performance, I think you need link MKL for
> BLAS and MKL-DNN for NN. Also MKL-DNN should link MKL for better
> performance.
>
> Here are some ways for you to install full MKL library if you don't have
> one:
> 1. Register and download from intel website:
> https://software.intel.com/en-us/mkl
> 2. Apt-get/yum: currently it need configure Intel’s repositories.
>         a.
> https://software.intel.com/en-us/articles/installing-intel-free-libs-and-python-yum-repo
>         b.
> https://software.intel.com/en-us/articles/installing-intel-free-libs-and-python-apt-repo
> 3. pip install mkl / mkl-devel: ‘mkl’ package has the runtime and
> ‘mkl-devel’ includes everything with the headers
>         a.
> https://software.intel.com/en-us/articles/installing-the-intel-distribution-for-python-and-intel-performance-libraries-with-pip-and
> 4. conda install: also has mkl and mkl-devel
>         a. https://anaconda.org/intel/mkl
>         b. https://anaconda.org/intel/mkl-devel
>
> If you want to redistribute MKL with MXNet, you may need take care of the
> license issue. Currently, MKL is using ISSL (
> https://software.intel.com/en-us/license/intel-simplified-software-license
> ).
>
> -----Original Message-----
> From: Zai, Alexander [mailto:alexzai@amazon.com.INVALID]
> Sent: Wednesday, September 19, 2018 12:49 PM
> To: dev@mxnet.incubator.apache.org
> Subject: Re: Remove MKLML as dependency
>
> Will test it out tomorrow.
>
> On the side, what is the best way to test MKL build for MXnet. MKL is
> licensed?
>
> Best,
> Alex
>
> On 9/18/18, 7:50 PM, "Lv, Tao A" <tao.a.lv@intel.com> wrote:
>
>     Hi Alex,
>
>     Thanks for bringing this up.
>
>     The original intention of MKLML is to provide a light and
> easy-to-access library for ML/DL community. It's released with MKL-DNN
> under Apache-2.0 license.
>
>     AFAIK, MKL-DNN still relies on it for better performance. So I'm
> afraid there will be a performance regression in MKL pip packages if MKLML
> is simply removed.
>
>     Have you ever tried the build without MKLML and how does the
> performance look like?
>
>     -tao
>
>     -----Original Message-----
>     From: Alex Zai [mailto:azai91@gmail.com]
>     Sent: Wednesday, September 19, 2018 4:49 AM
>     To: dev@mxnet.incubator.apache.org
>     Subject: Remove MKLML as dependency
>
>     On our build from source page we have a list of blas libraries that
> are recommended:
>     https://mxnet.incubator.apache.org/install/build_from_source.html
>
>     MKL-DNN
>     MKL
>     MKLML
>     Apple Accelerate
>     OpenBlas
>
>     MKLML is a subset of MKL (https://github.com/intel/mkl-dnn/issues/102)
>     and therefore MKLML users can just use MKL instead. Does anyone see an
> issue with me removing this? It would simplify out doc page and build file.
>
>     Alex
>
>
>

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