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

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.
Takeaways:
• 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.
Find the slide deck here: drive.google.c...
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About Anyscale
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Anyscale is the AI Application Platform for developing, running, and scaling AI.
www.anyscale.com/
If you're interested in a managed Ray service, check out:
www.anyscale.c...
About Ray
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Ray is the most popular open source framework for scaling and productionizing AI workloads. From Generative AI and LLMs to computer vision, Ray powers the world’s most ambitious AI workloads.
docs.ray.io/en...
#llm#machinelearning#ray#deeplearning#distributedsystems#python #machinelearning

[@DreamsAPI]

Enjoying the talk, zooming in on your code is good for the viewers so we can connect your words to the code

[@ansha2221]

Great talk!