Ray Deep Dives
Multi-model composition with Ray Serve deployment graphs
Ray Summit 2022
In this talk, we aim to show how to leverage the programmable and general-purpose distributed computing ability of Ray to facilitate the authoring, orchestrating, scaling, and deployment of complex serving graphs as a DAG under one set of APIs, like a microservice. Learn how you can program multiple models dynamically on your laptop as if you're writing a local Python script, deploy to production at scale, and upgrade individually.
About Simon
Simon Mo is a software engineer working on Ray Serve at Anyscale. Before Anyscale, he was a student at UC Berkeley participating in research at the RISELab. He focuses on studying and building systems for machine learning, in particular, how to make ML model serving systems more efficient, ergonomic, and scalable.
Simon Mo
Software Engineer, Anyscale
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