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

About this lesson

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. Thanks for watching ❤️ Stay tuned Instagram: www.instagram.com/developershutt Twitter: www.twitter.com/developershutt

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