Speeding Up Variable-Length Training with Dynamic Context Parallelism and NVIDIA Megatron Core

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...

Jan 29, 2026 - 00:30

Speeding Up Variable-Length Training with Dynamic Context Parallelism and NVIDIA Megatron Core

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... A decorative image.

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…

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