Data & AI

Distributed ML Training with FSDP

Data & AI Pipelines diagram · made in Skemio

FSDP distributed architecture displaying GPU Ranks sharding parameters and optimizer states, communicating via All-Gather and Reduce-Scatter.
FSDP distributed architecture displaying GPU Ranks sharding parameters and optimizer states, communicating via All-Gather and Reduce-Scatter.
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What it shows

  • Standard DDP replicates full model weights on every individual GPU node
  • FSDP shards parameters, gradients, and optimizer states across worker ranks
  • All-Gather restores full layer parameters just in time for forward passes

The takeaway

FSDP delivers Zero Redundancy Optimizer benefits natively in PyTorch without expensive hardware limits.

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