Ray Deep Dives

Ray Train: A Production-Ready Library for Distributed Deep Learning

September 18, 3:15 PM - 3:45 PM
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With the growing complexity of deep learning models and the emergence of Large Language Models (LLMs) and generative AI, scaling training efficiently and cost-effectively has become an urgent need. Enter Ray Train, a cutting-edge library designed specifically for seamless, production-ready distributed deep learning.

In this talk, we will take a deep dive into the architecture of Ray Train, emphasizing its advanced resource scheduling and the simplicity of its APIs designed for effortless ecosystem integrations. We will cover a detailed breakdown of Ray Train's design, from its robust architecture to its exclusive features for LLM training, including Distributed Checkpointing and the seamless Ray Data Integration.


• Ray Train offers production-ready open-source solutions for large-scale distributed training.

• Ray Train seamlessly integrates into the deep learning ecosystem (such as PyTorch, Lightning, HuggingFace) with easy-to-use APIs.

• Ray Train accelerates your LLM development with built-in fault tolerance and resource management capabilities.

About Yunxuan

Yunxuan Xiao is a software engineer at Anyscale, where he works on the open-source Ray Libraries. He is passionate about scaling AI workloads and making machine learning more accessible and efficient.

Yunxuan Xiao

Software Engineer, Anyscale
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