Am 03.03.2014 um 20:20 schrieb Julian Taylor <[email protected]>:
> hi, > > as the numpy gsoc topic page is a little short on options I was thinking > about adding two topics for interested students. But as I have no > experience with gsoc or mentoring and the ideas are not very fleshed out > yet I'd like to ask if it might make sense at all: > > > 2. vector math library integration > > some operations like powers, sin, cos etc are relatively slow in numpy > depending on the c library used. There are now a few free libraries > available that make use of modern hardware to speed these operations up, > e.g. sleef and yeppp (also mkl but I have no interest in supporting > non-free software) > It might be interesting to investigate if these libraries can be > integrated with numpy. > This also somewhat ties in with the configurable precision mode as the > vector math libraries often have different options depending on > precision and speed requirements. I have been exhuming an old package I once wrote that wraps the vectorized math functions from Intels MKL for use with numpy. I made it available at https://github.com/geggo/uvml . I don't have access to MKL anymore, so no idea whether this package still works with recent numpy. If still useful, adapting to work with other libraries should not be difficult since they all provide a similar API. For serious work other packages like numexpr, numba or theano are much better. Nevertheless some might want to pick up this approach. Gregor _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
