International JavaScript Conference (iJS) New York.
NumPy is a foundational component of the PyData ecosystem, providing a high-performance numerical library on which countless image processing, machine learning, and data analytics tools are built in Python. Is it possible to bring the same power, performance, and robustness to JavaScript? In this talk, I’ll discuss our journey in trying to build such a library. I’ll dive deep into the weeds of performance profiling, hidden classes, cache-oblivious iteration, hardware optimization, and much more. I’ll show benchmarks showcasing how well JavaScript stacks up against the competition. And I’ll conclude by discussing where we go from here. So is it possible? Come to my talk to find out, as the answer may surprise you.
$ git clone https://github.com/kgryte/talks-ijs-new-york-2021.gitand
$ npm installFrom the top-level directory,
$ python -m http.server 9000and, in your browser, navigate to
http://127.0.0.1:9000
Copyright © 2021. Athan Reines.