49 citations · 164 across the 10 of their papers we have counts for
22 papers
ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference
Wangsong Yin, Daliang Xu, Mengwei Xu +2
On-device running Large Language Models (LLMs) is nowadays a critical enabler towards preserving user privacy. We observe that the attention operator falls back from the special-pu…
Elastic On-Device LLM Service
Wangsong Yin, Rongjie Yi, Daliang Xu +3
On-device Large Language Models (LLMs) are transforming mobile AI, catalyzing applications like UI automation without privacy concerns. Nowadays the common practice is to deploy a…
From Cloud to Edge: A First Look at Public Edge Platforms
Mengwei Xu, Zhe Fu, Xiao Ma +7
Public edge platforms have drawn increasing attention from both academia and industry. In this study, we perform a first-of-its-kind measurement study on a leading public edge plat…
An Empirical Study on Deployment Faults of Deep Learning Based Mobile Applications
Zhenpeng Chen, Huihan Yao, Yiling Lou +4
Deep Learning (DL) is finding its way into a growing number of mobile software applications. These software applications, named as DL based mobile applications (abbreviated as mobi…
VM Matters: A Comparison of WASM VMs and EVMs in the Performance of Blockchain Smart Contracts
Shuyu Zheng, Haoyu Wang, Lei Wu +2
WebAssemly is an emerging runtime for Web applications and has been supported in almost all browsers. Recently, WebAssembly is further regarded to be a the next-generation environm…
Hierarchical Federated Learning through LAN-WAN Orchestration
Jinliang Yuan, Mengwei Xu, Xiao Ma +3
Federated learning (FL) was designed to enable mobile phones to collaboratively learn a global model without uploading their private data to a cloud server. However, exiting FL pro…