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Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

Zhi Ma

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Book Open access Sep 2026

OmniPipe: Efficient, Flexible and Scalable Pipeline Parallelism for Large Model Training

OmniPipe is proposed, a flexible bidirectional multi-pipeline parallelism scheme for unified dense and MoE LLM training that minimizes the pipeline bubble ratio while effectively overlapping EP communication with computation, enabled by the flexible and scalable parallelism scheme of bidirectional pipelines.

Jun Li, Zhi Ma, Shi-Gang Li · 0 citations
#large language models Book Open access Sep 2026

OmniPipe: Efficient, Flexible and Scalable Pipeline Parallelism for Large Model Training

Mixture-of-Experts (MoE) has become the de facto architecture for scaling large language models, offering expanded capacity with manageable compute. Pipeline parallelism (PP) is indispensable for distributed MoE training, but state-of-the-art PP schemes face three major limitations: large pipeline bubbles, high per-sta...

Jun Li, Zhi Ma, Shigang Li · 0 citations
Book Open access Jul 2026

Dynamo-MoE: Accelerating Sparse Large Model Inference with Dynamic Parallelization

Dynamo-MoE, an out-of-box MoE inference framework to bridge the performance gap by dynamic parallelization strategies, integrates a novel load balancing approach based on token sorting and on-demand expert loading to solve the workload imbalance issue in the scenario of high workload.

Jiahao Chen, Shigang Li, Rongtian Fu et al. · 0 citations

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