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Getting Started with Distributed Training at Scale

Ready to move beyond single-GPU limits and master distributed systems? Join us for a webinar where ML and platform engineers will explore how to scale model training from a single node to a massive cluster using PyTorch and Ray.

In this virtual session you will learn:

  • What is distributed Training ? And do we need it ?

  • Introduction to Distributed Data Parallel (DDP)

  • Utilize advanced DDP techniques with ZeRO-1, ZeRO-2, ZeRO-3, and FSDP.

  • Introduction to Ray and how you can use Ray Train to train models at scale

  • Training a model at scale using Ray Train and PyTorch at scale

This session is more than a demo. You’ll leave with a working understanding of Ray, a reusable project you can build on, and a clear view of how Ray and Anyscale work together to accelerate AI development.

Ready to try Anyscale?

Access Anyscale today to see how companies using Anyscale and Ray benefit from rapid time-to-market and faster iterations across the entire AI lifecycle.