Very interesting. If that really working it will be game changer. Can it build Scipy, scikit-learn, matplotlib now? Pandas already working i think.
On Fri, Feb 13, 2015 at 8:16 PM, Matti Picus <matti.pi...@gmail.com> wrote: > I am close to releasing a blog post about numpy.linalg > > https://gist.github.com/mattip/25680e68fe7e2856fe0c > > Note the benchmark section, this is not a typo. Here's how I got to the > conclusion that cpyext is faster than python+cffi. > > I installed numpy from the pypy/numpy repo on a nightly after 2.5.0 > > pip install git+https://bitbucket.org/pypy/numpy.git > > I then benchmarked the two pypy methods of calling numpy.linalg.inv() via > this script which simply calls linalg.inv() for different sized ndarray. > > https://gist.github.com/mattip/a7b22dc237fb09a46758 > > $pypy inverse.py 10 > UserWarning: npy_clear_floatstatus, npy_set_floatstatus_invalid not found > warn('npy_clear_floatstatus, npy_set_floatstatus_invalid not found') > after 999999, for n= 10, time=20.64, 20.64 msec/1000 loops > > and > > $USE_CPYEXT=yes pypy inverse.py 10 > after 999999, for n= 10, time= 8.52, 8.52 msec/1000 loops > > Any thoughts? Comments on the blog post? > Matti > > _______________________________________________ > pypy-dev mailing list > pypy-dev@python.org > https://mail.python.org/mailman/listinfo/pypy-dev _______________________________________________ pypy-dev mailing list pypy-dev@python.org https://mail.python.org/mailman/listinfo/pypy-dev
