Inside NumPy: how it works and how we can make it better

Speaker: Nathaniel Smith, BIDS Computational Fellow, University of California, Berkeley

TITLE: Inside NumPy: how it works and how we can make it better

DATE: October 19, 2017
TIME: 1:00pm to 1:30pm
LOCATION: BIDS, 190 Doe Library, UC Berkeley

ABSTRACT
NumPy and the ecosystem of libraries built on top of it together form one of the most popular numerical computing environments of all time -- but NumPy itself has a number of limitations stemming from decisions made early in its 20+ year development history. I'll review NumPy's internal architecture and outline some ideas for improving it that we plan to implement over the next few years, including better support for alternative storage formats like sparse and out-of-core arrays, richer data formats like categoricals, missing values, and values tagged with physical units, and sketch some ideas for how NumPy could better support just-in-time compilation.

SPEAKER
Nathaniel Smith is a computational fellow at BIDS, where he divides his time between computationally informed research on human cognition (esp. language processing) and on building better computational tools for researchers in general.