On Sat, Aug 6, 2016 at 9:20 AM, Benjamin Root <ben.v.r...@gmail.com> wrote: > Don't know if it is what you are looking for, but NumPy has a built-in suite > of benchmarks: > http://docs.scipy.org/doc/numpy/reference/generated/numpy.testing.Tester.bench.html
> That's the very old (now unused) benchmark runner. Numpy has had an ASV test > suite for a while, see https://github.com/numpy/numpy/tree/master/benchmarks > for how to run it. > Also, some projects have taken to utilizing the "airspeed velocity" utility > to track benchmarking stats for their projects. I know astropy utilizes it. > So, maybe their benchmarks might be a good starting point since they utilize > numpy heavily? > Cheers! > Ben Root >> On Fri, Aug 5, 2016 at 3:42 AM, Papa, Florin <florin.p...@intel.com> wrote: >> Hi, >> This is Florin Papa from the Dynamic Scripting Languages Optimizations team >> in Intel Corporation. >> Our team is working on optimizing the PyPy interpreter and part of this work >> is to find and fix incompatibilities between NumPy and PyPy. Does anyone >> have knowledge of real life workloads that use NumPy and cannot be run using >> PyPy? >> We are also interested in creating a repository with relevant benchmarks for >> real world usage of NumPy, like GUPB for CPython, but we have not found such >> workloads for NumPy. >> The approach of GUPB is interesting (the whole application part that is, the >> rest looks much more cumbersome than ASV benchmarks), but of course easier >> to create for Python than for Numpy. You'd need to find whole applications >> that spend most of their time in numpy but not in too small a set of numpy >> functions. Maybe benchmark suites of other projects aren't such a bad idea >> for that. Or spend a bit of time collecting relevant published ipython >> notebooks. >> Ralf Astropy definitely looks like a good candidate for a real life workload. Thank you also for the useful information on ASV. Regards, Florin _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
