Name: Blobs to Clips: Efficient End-to-End Video Data Loading - Andrew Ho & Ahmad Sharif, Meta
Start: 2024-09-19T14:45:00-0700
End: 2024-09-19T15:10:00-0700

September 18-19, 2024
San Francisco, California
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Note: The schedule is subject to change.

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IMPORTANT NOTE: Timing of sessions and room locations are subject to change.

Thursday September 19, 2024 2:45pm - 3:10pm PDT

Gateway Pavilion - Cowell Theater

The PyTorch team has improved training speed by an order of magnitude for teams at Meta working on Small-to-Large-Scale MultiModal Video models. In this talk we’ll share our learnings on reducing GPU starvation by overcoming data loading challenges such as dealing with large distributed datasets, worker imbalance, compute-bottlenecks due to parallel video decoding and sampling, checkpointing, and debuggability. As part of our commitment to open-source, we are releasing a new decoding library and updating existing PyTorch libraries on GitHub, and invite feedback and contributions from the community.

Speakers

Ahmad Sharif

Software Engineer, Meta

SWE in Pytorch Content Domains Past: SWE at Google in Search, Privacy, ChromeOS

Andrew Ho

Machine Learning Engineer, Meta Platforms

We are ML Engineers at Meta on PyTorch working on multi-modal LLM dataloading

Thursday September 19, 2024 2:45pm - 3:10pm PDT
Gateway Pavilion - Cowell Theater

Breakout Sessions

Audience Intermediate

PyTorch Conference 2024

Ahmad Sharif

Andrew Ho

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