As a general rule I wouldn't worry too much about test speed. Speed is extremely dependent on exact workloads. And this is doubly so for test suites -- production workloads tend to do a small number of normal things over and over, while a good test suite never does the same thing twice and spends most of its time exercising weird edge conditions. So unless your actual workload is running the numpy test suite :-), it's probably not worth trying to track down.
And yeah, numpy does not in general do automatic multithreading -- the only automatic multithreading you should see is when using linear algebra functions (matrix multiply, eigenvalue calculations, etc.) that dispatch to the BLAS. -n On Wed, Jun 29, 2016 at 12:07 AM, Ralf Gommers <ralf.gomm...@gmail.com> wrote: > > > On Wed, Jun 29, 2016 at 3:27 AM, Chris Barker - NOAA Federal > <chris.bar...@noaa.gov> wrote: >> >> >>> >>> Now the user is writing back to say, "my test code is fast now, but >>> numpy.test() is still about three times slower than <some other server we >>> don't manage>". When I watch htop as numpy.test() executes, sure enough, >>> it's using one core >> >> >>> * if numpy.test() is supposed to be using multiple cores, why isn't it, >>> when we've established with other test code that it's now using multiple >>> cores? >> >> >> Some numpy.linalg functions (like np.dot) will be using multiple cores, >> but np.linalg.test() takes only ~1% of the time of the full test suite. >> Everything else will be running single core. So your observations are not >> surprising. >> >> >> Though why it would run slower on one box than another comparable box is a >> mystery... > > > Maybe just hardware config? I see a similar difference between how long the > test suite runs on TravisCI vs my linux desktop (the latter is slower, > surprisingly). > > Ralf > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > -- Nathaniel J. Smith -- https://vorpus.org _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
