[cctbxbb] Install OpenBLAS or MKL in base

[Pascal]

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 
> <mailto: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 <http://CCI.LBL.gov>
>
>     On Wed, Jun 20, 2018 at 5:13 AM, Luc Bourhis
>     <luc_j_bourhis at mac.com <mailto: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
>
>
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