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cs.DC2026
CascadeEP: Asynchronous Expert Execution for MoE Prefill under Attention Imbalance
Jin Qin, Tiancheng Hu, Shiyan Wang +12
Mixture-of-experts (MoE) serving commonly deploys data and expert parallelism (DEP): attention replicas run distinct request batches while routed experts are sharded across an expe…
cs.DC2026
HYPIC: Accelerating Hybrid-Attention LLM Serving with Position-Independent Caching
Yifei Liu, Juntong Wu, Yang Liu +4
In retrieval-augmented generation and agentic LLM serving, prompts are assembled from independent segments into long contexts, making the prefill stage dominate per-request cost. T…
cs.DC2026
Hummingbird: SLO-Oriented GPU Preemption at Microsecond-scale
Tiancheng Hu, Chenxi Wang, Ting Cao +9
Existing GPU-sharing techniques, including spatial and temporal sharing, aim to improve utilization but face challenges in simultaneously ensuring SLO adherence and maximizing effi…