1 citations · 1 across the 4 of their papers we have counts for
4 papers
A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints
Chengyi Nie, Nian Si, Zijie Zhou
The rapid adoption of large language models (LLMs) has created significant challenges for efficient inference at scale. Unlike traditional workloads, LLM inference is constrained b…
Aladdin: Joint Placement and Scaling for SLO-Aware LLM Serving
Chengyi Nie, Rodrigo Fonseca, Zhenhua Liu
The demand for large language model (LLM) inference is gradually dominating the artificial intelligence workloads. Therefore, there is an urgent need for cost-efficient inference s…
Training DNN Models over Heterogeneous Clusters with Optimal Performance
Chengyi Nie, Jessica Maghakian, Zhenhua Liu
Adjusting batch sizes and adaptively tuning other hyperparameters can significantly speed up deep neural network (DNN) training. Despite the ubiquity of heterogeneous clusters, exi…
OpenUVR: an Open-Source System Framework for Untethered Virtual Reality Applications
Alec Rohloff, Zackary Allen, Kung-Min Lin +4
Advancements in heterogeneous computing technologies enable the significant potential of virtual reality (VR) applications. To offer the best user experience (UX), a system should…