Abstract: This is an introductory and hands-on guided tutorial of Ray, which provides powerful yet easy-to-use abstractions for implementing distributed systems in Python. This tutorial includes a brief talk to provide an overview of concepts in Ray Core, why you should use Ray for distributing Python and machine learning workloads, and a brief discussion on Ray’s library ecosystem.
Primarily, the tutorial will focus on Ray Core APIs to write remote functions and actors. Attendees will walk away with an understanding of why distributed computing is a necessity today, the common design patterns for writing distributed Python applications in Ray, and a basic understanding of how Ray works under hood.
Bio: Stephanie is a final-year PhD student at UC Berkeley and a software engineer at Anyscale. She is interested in abstractions for distributed computing and problems in fault tolerance. Towards this end, she is also a maintainer for the open-source project Ray, which provides a simple, universal API for building distributed applications in Python.
