20 citations · 24 across the 6 of their papers we have counts for
6 papers
SmartGen: Seamless Disaggregated LLM Inference with Selective KV Cache Transfer
Xuchuan Luo, Jiacheng Shen, Xin Wang +1
Disaggregating the prefill and decoding stages of large language model (LLM) inference into two separate sets of nodes is widely adopted in today's LLM serving systems. However, su…
EdgeFlow: Fast Cold Starts for LLMs on Mobile Devices
Yongsheng Yan, Jiacheng Shen, Xuchuan Luo +1
Deploying large language models (LLMs) on mobile devices is an emerging trend to enable data privacy and offline accessibility of LLM applications. Modern mobile neural processing…
CIDER: Boosting Memory-Disaggregated Key-Value Stores with Pessimistic Synchronization
Yuxuan Du, Xuchuan Luo, Xin Wang +2
Memory-disaggregated key-value (KV) stores suffer from a severe performance bottleneck due to their I/O redundancy issues. A huge amount of redundant I/Os are generated when synchr…
Ditto: An Elastic and Adaptive Memory-Disaggregated Caching System
Jiacheng Shen, Pengfei Zuo, Xuchuan Luo +5
In-memory caching systems are fundamental building blocks in cloud services. However, due to the coupled CPU and memory on monolithic servers, existing caching systems cannot elast…
FUSEE: A Fully Memory-Disaggregated Key-Value Store (Extended Version)
Jiacheng Shen, Pengfei Zuo, Xuchuan Luo +4
Distributed in-memory key-value (KV) stores are embracing the disaggregated memory (DM) architecture for higher resource utilization. However, existing KV stores on DM employ a sem…
Muffin: Testing Deep Learning Libraries via Neural Architecture Fuzzing
Jiazhen Gu, Xuchuan Luo, Yangfan Zhou +1
Deep learning (DL) techniques are proven effective in many challenging tasks, and become widely-adopted in practice. However, previous work has shown that DL libraries, the basis o…