Building a Production-Grade Multi-Node Training Pipeline with PyTorch DDP

Scaling deep learning training across multiple machines is a common bottleneck, which can be effectively solved using PyTorch's DistributedDataParallel (DDP) framework. The DDP approach works by launching an identical model copy on each GPU, where gradients are automatically averaged across all processes during the backward pass to keep