May 12, 2022 · Backend Development

Practical Guide to PyTorch Distributed Training: DP, DDP, Groups, and IO Considerations

This guide explains PyTorch’s distributed training, contrasting single‑node DataParallel with multi‑node DistributedDataParallel, detailing essential parameters, group communication setup, proper use of DistributedSampler for data loading, handling IO bottlenecks, and avoiding common pitfalls such as memory imbalance, unsynchronized buffers, and unused‑parameter errors.

DDPDataParallelDistributed Training

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Practical Guide to PyTorch Distributed Training: DP, DDP, Groups, and IO Considerations