[cctbxbb] Install OpenBLAS or MKL in base

[Billy Poon]

Hi Pascal,

It depends on what you mean by useable. I outlined some steps for building
and running DIALS at https://github.com/cctbx/cctbx_project/issues/85, but
those steps will work for Phenix and CCTBX as well. Most tests will pass,
but there are still missing dependencies and there is no Windows support.
So most things should run, but I have not tested on multiple operating
systems yet. Also, the workflow for compiling development builds and
release installers still needs to be worked out.

Does openblas need to be installed by default? If so, testing the builds on
different operating systems (especially CentOS 5 and 32-bit oses) are the
time-consuming steps.

--
Billy K. Poon
Research Scientist, Molecular Biophysics and Integrated Bioimaging
Lawrence Berkeley National Laboratory
1 Cyclotron Road, M/S 33R0345
Berkeley, CA 94720
Tel: (510) 486-5709
Fax: (510) 486-5909
Web: https://phenix-online.org


On Thu, Jun 21, 2018 at 2:40 AM Pascal <pascal22p at parois.net> wrote:

> Hi,
>
> What is the state of this preliminary work? Is it somehow useable?
>
> I am wondering if I should look into including openblas in bootstrap or
> make use of the conda branch.
>
> How much work and how easy would it be to include openblas in bootsrap?
> Basically I just need to download the archive, run make and make install
> into base.
>
> Regards,
> Pascal
>
> On 20/06/18 18:54, Billy Poon wrote:
>
> Hi Luc,
>
> Also, we are exploring the use of conda for installing the dependencies
> instead of compiling from scratch. There is some preliminary work in
> https://github.com/cctbx/conda_build for dependencies and the
> "conda_compiler" branch in cctbx_project for building. The
> "cctbx_dependencies" conda package already installs mkl and it would be
> easy to install openblas.
>
> This should be ready in a few months once some other details (e.g.
> building releases, filling in missing dependencies) are worked out.
>
> --
> Billy K. Poon
> Research Scientist, Molecular Biophysics and Integrated Bioimaging
> Lawrence Berkeley National Laboratory
> 1 Cyclotron Road, M/S 33R0345
> Berkeley, CA 94720
> Tel: (510) 486-5709
> Fax: (510) 486-5909
> Web: https://phenix-online.org
>
>
> On Wed, Jun 20, 2018 at 9:48 AM Nigel Moriarty <nwmoriarty at lbl.gov> wrote:
>
>> Luc
>>
>> I like the idea. I may be able to convince a new collaborator to drop
>> FORTRAN in favour of the cctbx.
>>
>> Cheers
>>
>> Nigel
>>
>> ---
>> Nigel W. Moriarty
>> Building 33R0349, Molecular Biophysics and Integrated Bioimaging
>> Lawrence Berkeley National Laboratory
>> Berkeley, CA 94720-8235
>> Phone : 510-486-5709     Email : NWMoriarty at LBL.gov
>> Fax   : 510-486-5909       Web  : CCI.LBL.gov
>>
>> On Wed, Jun 20, 2018 at 5:13 AM, Luc Bourhis <luc_j_bourhis at mac.com>
>> wrote:
>>
>>> Hi,
>>>
>>> years ago, I had wrote on this discussion list about a project of mine
>>> to dramatically accelerate scitbx.lstbx by using optimised BLAS libraries.
>>> That work had been dormant on a branch but now we are planning to move
>>> forward with the help of Pascal Parlois who will do the actual coding in
>>> the coming months. In order for this new code to be exercised by nightly
>>> tests, we, the smtbx people, need to write code so that that optimised BLAS
>>> library is installed during bootstrap. Right now, as a stopgap, I used
>>> conda to install either OpenBLAS and MKL but that won’t do with the cctbx
>>> philosophy.
>>>
>>> There are basically two choices: either OpenBLAS or MKL. When I started
>>> this project, I chose OpenBLAS because MKL was not freely redistributable,
>>> and I had got the green light to install it as needed. However now MKL has
>>> become completely free, thus becoming a possible choice. MKL is more
>>> performant on Intel but OpenBLAS is better on AMD (OpenBLAS actually runs
>>> on pretty much any processor out there but we don’t care in the context of
>>> cctbx): c.f. Julia people conclusions
>>> <https://discourse.julialang.org/t/openblas-is-faster-than-intel-mkl-on-amd-hardware-ryzen/8033>
>>> Now I realise that most of you may not care one way or another!?! But we
>>> won’t move forward before we got the green light…
>>>
>>> Note that I am taking about installing a BLAS usable from C++ here, not
>>> getting a BLAS-accelerated numpy. The latter could be an alternative
>>> though. But that would require to modify the bootstrap code to compile a
>>> MKL- or OpenBLAS-enabled numpy anyway.
>>>
>>> Best wishes,
>>>
>>> Luc J Bourhis
>>>
>>>
>>> _______________________________________________
>>> cctbxbb mailing list
>>> cctbxbb at phenix-online.org
>>> http://phenix-online.org/mailman/listinfo/cctbxbb
>>>
>>>
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