_______________________________________________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 BioimagingLawrence Berkeley National Laboratory1 Cyclotron Road, M/S 33R0345Berkeley, CA 94720Tel: (510) 486-5709Fax: (510) 486-5909
On Wed, Jun 20, 2018 at 9:48 AM Nigel Moriarty <nwmoriarty@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 BioimagingLawrence Berkeley National Laboratory
Berkeley, CA 94720-8235
Phone : 510-486-5709 Email : NWMoriarty@LBL.gov
Fax : 510-486-5909 Web : CCI.LBL.gov
On Wed, Jun 20, 2018 at 5:13 AM, Luc Bourhis <luc_j_bourhis@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 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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