Accelerate ND-Parallel: A guide to Efficient Multi-GPU Training
Accelerate ND-Parallel guides how to combine multiple parallelism strategies (data, fully sharded data, tensor, context) for multi-GPU training. It provides concrete config examples (dp_shard_size, dp_replicate_size, cp_size, tp_size) and an FSDP plugin, plus Axolotl integration and end-to-end training scripts to minimize inter-device communication at scale. The article also discusses how to compose strategies for large models and points to ready configs and docs.