How DDP works || Distributed Data Parallel || Quick explained

Discover how DDP harnesses multiple GPUs across machines to handle larger models and datasets, accelerating the training process. Learn about the gradient synchronization process and how it ensures all GPUs maintain an identical copy of the model. Understand the limitations of the Data Parallel method and how DDP overcomes them. Key takeaways include DDP’s scalability, performance, and flexibility.

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[harshwardhanfartale]

Amazing video!! Loved it and got complete understanding

[karanshingde]

Great Explanation! I have used DDP with accelerate in transformers. Along with Model it also loads whole data in respected GPUs.

[bozhang]

Thanks for this impressive video! I wonder how to make this great video. Using which tool? Many thanks!