Author

Shiju Wang

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Preprint Sep 2026

PipeSwift: Revisiting Pipeline Parallelism for Large-Scale Completion-Oriented Agentic LLM Serving

It is shown that pipeline parallelism (PP), long overlooked because it offers little decode-latency advantage, can reduce JCT by providing a more favorable balance between prefill and decode efficiency, and PipeSwift is built, an optimized open-source pipeline-parallel runtime integrated with a tailored micro-batch par...

Shiju Wang, Fei Ren, Fang-Cheng Fu et al. · 0 citations

#artificial intelligence Preprint Sep 2025

Concertina: Data-Centric Adaptive Pipeline Parallelism for Efficient Heterogeneous Long-Context LLM Training

This paper proposes DPP, which transforms PP granularity from a static design choice into a workload-adaptive optimization space over packed, split, and hybrid chunks and further introduces a new coupling between heterogeneous pipeline scheduling and gradient checkpointing.

Shiju Wang, Yujie Wang, Fang-Cheng Fu et al. · 0 citations