Originally published at: Speeding Up Variable-Length Training with Dynamic Context Parallelism and NVIDIA Megatron Core | NVIDIA Technical Blog
This post introduces Dynamic Context Parallelism (Dynamic-CP), a scheduling approach in NVIDIA Megatron-Core used for LLM post-training or DiT pre-training. It dynamically selects the CP size per microbatch to efficiently handle variable-length sequences, achieving up to 1.48x speedup on real-world datasets. In large-scale model training, an often-overlooked bottleneck arises from the sequence-length variability in real-world…