On Mar 8, 2016 11:16, "Matthew Brett" <[email protected]> wrote: > > On Tue, Mar 8, 2016 at 10:53 AM, Matthew Brett <[email protected]> wrote: > > Hi, > > > > On Tue, Mar 8, 2016 at 4:56 AM, Olivier Grisel <[email protected]> wrote: > >> If we can run all the scipy stack tests (say for instance numpy, > >> scipy, pandas, scikit-learn, scikit-image, statsmodel) with the > >> openblas built on the manylinux1 docker image using Matthew's script > >> on a variety of boxes, then I am fine with using openblas. If running > >> the tests reveals unresolved bugs / crashes in OpenBLAS, then I think > >> we should go with atlas in the short term and re-examine that decision > >> in a couple of months. > > > > At the moment, we know of > > https://github.com/xianyi/OpenBLAS/issues/783 which is not yet fixed > > in master. > > > > I see that Zhang Xianyi has set up OpenBLAS buildbot runs already: > > > > https://github.com/xianyi/OpenBLAS/issues/785 > > > > I guess we could add to those with nightly build / test runs. > > > > We need to decide what to do now though. Should we work on building > > up some heavy-duty CI to convince ourselves OpenBLAS is reliable and > > commit after that, or should we accept the risk now, on the basis that > > we will have some chance of errors / crashes? > > Specifically - if we could run the heavy-duty CI now, with some > version of OpenBLAS, where the numpy scipy scikit-learn pandas > statsmodels tests all pass, on a range of machines, would that be > enough to make us commit to OpenBLAS, both now and in the long term?
I think a lot of the people who might care about this aren't on this mailing list? -n
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