If OpenBLAS is looking like the easiest to support solution, then no objections here. (If 0.2.17 is genuinely working well, then maybe we want to switch to it on Windows too. I know Xianyi disabled some of the problematic kernels for us -- maybe that's enough. Mostly I just don't want to end up in the situation where we're trying to support a bunch of differently broken builds on different platforms.)

On Mar 28, 2016 2:34 PM, "Matthew Brett" <matthew.brett@gmail.com> wrote:

Hi,

Olivier Grisel and I are working on building and testing manylinux
wheels for numpy and scipy.

We first thought that we should use ATLAS BLAS, but Olivier found that
my build of these could be very slow [1].  I set up a testing grid [2]
which found test errors for numpy and scipy using ATLAS wheels.

On the other hand, the same testing grid finds no errors or failures
[3] using latest OpenBLAS (0.2.17) and running tests for:

numpy
scipy
scikit-learn
numexpr
pandas
statsmodels

This is on the travis-ci ubuntu VMs.

Please do test on your own machines with something like this script [4]:

source test_manylinux.sh

We have worried in the past about the reliability of OpenBLAS, but I
find these tests reassuring.

Are there any other tests of OpenBLAS that we should run to assure
ourselves that it is safe to use?

Matthew

[1] https://github.com/matthew-brett/manylinux-builds/issues/4#issue-143530908
[2] https://travis-ci.org/matthew-brett/manylinux-testing/builds/118780781
[3] I disabled a few pandas tests which were failing for reasons not
related to BLAS.  Some of the statsmodels test runs time out.
[4] https://gist.github.com/matthew-brett/2fd9d9a29e022c297634
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