14 citations · 39 across the 9 of their papers we have counts for
4 papers · 1 filter
Prefill-as-a-Service: KVCache of Next-Generation Models Could Go Cross-Datacenter
Ruoyu Qin, Weiran He, Yaoyu Wang +5
Prefill-decode (PD) disaggregation has become the standard architecture for large-scale LLM serving, but in practice its deployment boundary is still determined by KVCache transfer…
TENT: A Declarative Slice Spraying Engine for Performant and Resilient Data Movement in Disaggregated LLM Serving
Feng Ren, Ruoyu Qin, Teng Ma +16
Modern GPU clusters rely on complex, heterogeneous interconnects. As large language model (LLM) serving shifts toward agentic reasoning, KVCache becomes a first-class mobile asset,…
Seer: Online Context Learning for Fast Synchronous LLM Reinforcement Learning
Ruoyu Qin, Weiran He, Weixiao Huang +7
Reinforcement Learning (RL) has emerged as a critical technique for advancing modern Large Language Models (LLMs), yet existing synchronous RL systems face severe performance bottl…
Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving
Ruoyu Qin, Zheming Li, Weiran He +4
Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI. It features a KVCache-centric disaggregated architecture that separates the prefill and de…