Behind the Scenes of Distributed Training and Why Your GPU Wiring Matters as Much as Your Strategy

TL;DR

Training large models on a single GPU can be inefficient due to time and space constraints. Distributed Data Parallel (DDP) and Fully Sharded Data Parallel (FSDP) are two strategies to address these issues.

Key Takeaways

• Use DDP for models fitting within GPU memory limits.
• Opt for FSDP when training larger models to avoid memory issues.
• Consider ZeRO stages for a balance between memory and communication.
• Assess GPU wiring to optimize data transfer speeds.