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cs.DC2026
SageSched: Efficient LLM Scheduling Confronting Demand Uncertainty and Hybridity
Zhenghao Gan, Yichen Bao, Yifei Liu +3
Efficient LLM inference scheduling is crucial for user experience. However, LLM inferences exhibit remarkable demand uncertainty (with unknown output length beforehand) and hybridi…
cs.DC2026
S-HPLB: Efficient LLM Attention Serving via Sparsity-Aware Head Parallelism Load Balance
Di Liu, Yifei Liu, Chen Chen +4
With the increasing volumes of Large Language Models (LLMs) and the expanding context lengths, attention computation has become a key performance bottleneck in LLM serving. For fas…