BigMac Accelerates Multimodal Training with Nested Pipelines
The new BigMac parallel training paradigm uses a dependency-safe nested pipeline to optimize native multimodal training. By intelligently inserting encoder and generator computations into the main LLM pipeline, it significantly reduces memory bubbles and accelerates training by up to 1.9x.
2026-07-22 ~ 2026-07-24 · 2 related posts
- BigMac keeps LLM pipeline speed while capping multimodal activation memory — 小红书技术REDtech · 2026-07-22
- BigMac uses nested pipelines to speed up multimodal LLM training by up to 1.9× — 机器之心 · 2026-07-24