Pinterest's ML Evolution: Distributed Training with Ray | Ray Summit 2024
Автор: Anyscale
Загружено: 2024-10-18
Просмотров: 1661
Pinterest's success hinges on its advanced recommender systems, which power key products like Homefeed, Related Pins, and Ads. In this session, Saurabh Vishwas Joshi and Jiun-Yu Lee from Pinterest's ML Platform team reveal how they've harnessed Ray to optimize data loading for their data-intensive recommender model training.
The presenters detail Pinterest's journey in leveraging Ray and the Ray Data ecosystem to decompose and orchestrate massive workloads across thousands of training jobs. They discuss the challenges faced, including memory pinning and multi-threaded collate, and the innovative solutions implemented to scale data-loading beyond trainer nodes. Learn how these optimizations have significantly boosted training throughput and how Pinterest is addressing new challenges through internal abstractions and open-source contributions.
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