There are several vector math libraries NumPy could use, e.g. MKL/VML, Apple Accelerate (vecLib), ACML, and probably others. They all suffer from requiring dense arrays and specific array alignments, whereas NumPy arrays have very flexible strides and flexible alignment. NumPy also has ufuncs and gufuncs as a complicating factor. There are at least two ways to proceed here. One is to only use vector math when strides and alignment allow it. The other is to build a vector math library specifically for NumPy arrays and (g)ufuncs. The latter you will most likely not be able to do in a summer. You should also consider Numba and Numexpr. They have some support for vector math libraries too. Sturla On 08/03/15 21:47, Dp Docs wrote:
Hi all, I am a CS 3rd Undergrad. Student from an Indian Institute (III T). I believe I am good in Programming languages like C/C++, Python as I have already done Some Projects using these language as a part of my academics. I really like Coding (Competitive as well as development). I really want to get involved in Numpy Development Project and want to take "Vector math library integration" as a part of my project. I want to here any idea from your side for this project. Thanks For your time for reading this email and responding back.
My IRCnickname: dp
Real Name: Durgesh Pandey.