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Multi-Node Training

Sixteen GPUs across two machines, one training loop — if the network can keep up.

Key Insight​

This project runs FSDP across 2 nodes of 8 GPUs each, launched with torchrun, aiming for over 70% MFU. Once a job spans machines, the hard part shifts from the model to the network and the orchestration between nodes.

Why This Matters​

Real pretraining spans many machines, where slow links and straggler GPUs — not the model — decide throughput. Keeping utilization high across nodes is the difference between a run that finishes in days and one that drags on for weeks.