Hi Yash Is your software open source? I'm happy to check it out for you
I think the c-level profiling for vmprof is relatively new, you would need to use pypy nightly in order to get that level of insight. Additionally, we're working on cpyext improvements *right now* stay tuned. If there is a good case for speeding up numpy, we can get it a lot faster than it is right now and seek some funding for that. Neural networks might be one of those! Best regards, Maciej Fijalkowski On Fri, Mar 3, 2017 at 2:31 AM, Singh, Yashwardhan <yashwardhan.si...@intel.com> wrote: > Hi Everyone, > > I am using numpy on pypy to train a deep neural network. For my workload > numpy on pypy is taking twice the time to train as numpy on Cpython. I am > using Numpy via cpyext. > > I read in the documentation, "Performance-wise, the speed is mostly the same > as CPython's NumPy (it is the same code); the exception is that interactions > between the Python side and NumPy objects are mediated through the slower > cpyext layer (which hurts a few benchmarks that do a lot of > element-by-element array accesses, for example)." Is there any way in which > I can profile my application to see how much additional overhead cypext > layer is adding or is it the numpy via pypy which is slowing down the > things. I have tried vmprof, but I couldn't figure out from it how much time > cpyext layer is taking. > > Any help will be highly appreciated. > > Regards > Yash > > _______________________________________________ > 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
