How GPUs Talk: A Practical Guide to Multi-GPU Training and Communication
An in-depth exploration of multi-GPU training techniques and the communication patterns that enable efficient distributed machine learning. Table of Contents 1. Why Multi-GPU Training is a communication problem 2. How GPUs are wired: intra-node and inter-node 3. Core communication patterns 4. Multi-GPU training strategies 4.1 Distributed Data Parallel (DDP) 4.2 Fully Sharded Data Parallel (FSDP) 4.3 Tensor Parallelism 4.4 Pipeline Parallelism 5. Topology-aware communication: rings, trees, and NVLink 6. Hiding communication latency 7. Conclusion When people talk about scaling deep learning, they usually mean throwing more GPUs at the problem. However, horizontal scaling can only get you so far without efficient communication strategies. ...