Today's PHP is a fast and efficient high-level application programming language. Modern additions to the core and ecosystem have allowed PHP engineers to achieve levels of performance that were unthinkable in the past. In this talk, we'll survey some of those improvements and demonstrate how we applied them to build the fastest and most advanced Machine Learning library for the PHP language, Rubix ML. You'll learn how to identify similar opportunities in your own codebase and how to benchmark particular areas of code so that you can refactor for performance. In the process, we'll touch on new features of PHP 7.4 such as Foreign Function Interface (FFI), explain concurrency frameworks like Amp, React PHP, and Swoole, and introduce a language that looks suspiciously like PHP called Zephir that lets you port performance-crucial code to a PHP extension with no sweat.
About The Speaker
Andrew DalPino is a software engineer, ML engineer, and the author and maintainer of the open-source Machine Learning library for PHP called Rubix ML. He has created several businesses on the foundation of PHP and is currently on a mission to democratize Machine Learning technology by bringing it to as many languages as possible. He is also an amateur roboticist and once took a two year hiatus from engineering to throw concerts and travel as a festival journalist.
Speaker: Andrew DalPino
6:30 - 6:45 :: Food and Introduction
6:45 - 7:45 :: Main Presentation
7:45 - 8:00 :: Q&A and Networking
Food and drinks are always provided!
If you're interested in submitting a talk: https://bit.ly/CPUG-Submit-Talk
Or find us on social media
- Rubix ML - https://rubixml.com
- Amp - https://amphp.org
- React PHP - https://reactphp.org
- Swoole - https://www.swoole.co.uk
- Zephir lang - https://zephir-lang.com