Speaker
Ed Bennett
(Swansea University)
Description
Numpy is one of the most well-recognised ways to achieve good performance for numerical computation in Python. However, this performance is not guaranteed—it is possible to write Numpy code that is slower than the equivalent plain Python. In this workshop we’ll explore how to avoid these pitfalls, and in some cases obtain speedups of over 200x, while also reducing the volume of code.
