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cs.DC2025
Kant: An Efficient Unified Scheduling System for Large-Scale AI Clusters
Lingling Zeng, Gen Zhang, Jialin Peng +3
As AI cluster sizes continue to expand and the demand for large-language-model (LLM) training and inference workloads grows rapidly, traditional scheduling systems face significant…
cs.DC2024★ 1 cited
P/D-Serve: Serving Disaggregated Large Language Model at Scale
Yibo Jin, Tao Wang, Huimin Lin +27
Serving disaggregated large language models (LLMs) over tens of thousands of xPU devices (GPUs or NPUs) with reliable performance faces multiple challenges. 1) Ignoring the diversi…