About today’s class
This week, we explore parallel and distributed computing using Ray, a framework for scaling Python applications from a laptop to a cluster. Ray enables parallelism at the task and actor level, and integrates well with the data tools we’ve been using throughout this course.
Readings
Readings for this lecture (to be completed before this class):
- What is Ray?
- Ray Basics
- Key concepts of Ray Core and the user guides for Tasks and Actors
Slides
The slides for this week are available online.
Lab
This week’s lab will introduce Ray for parallel data processing, demonstrating how to parallelize Python functions using remote tasks and actors.
Assignment
Details for this week’s assignment will be announced in class and posted to the course website.