4 papers
CANS: Accelerating Multiuser Collaborative Edge Inference via Cooperative Autodidactic NeuroSurgeon
Zheshun Wu, Ziyang Zhang, Changyao Lin +2
Recently, mobile edge computing (MEC)-enabled collaborative deep neural network (DNN) inference has emerged as a promising approach for delivering intelligent services to resource-…
E4: Energy-Efficient DNN Inference for Edge Video Analytics Via Early-Exit and DVFS
Ziyang Zhang, Yang Zhao, Ming-Ching Chang +2
Deep neural network (DNN) models are increasingly popular in edge video analytic applications. However, the compute-intensive nature of DNN models pose challenges for energy-effici…
DVFO: Learning-Based DVFS for Energy-Efficient Edge-Cloud Collaborative Inference
Ziyang Zhang, Yang Zhao, Huan Li +2
Due to limited resources on edge and different characteristics of deep neural network (DNN) models, it is a big challenge to optimize DNN inference performance in terms of energy c…
BCEdge: SLO-Aware DNN Inference Services with Adaptive Batching on Edge Platforms
Ziyang Zhang, Huan Li, Yang Zhao +2
As deep neural networks (DNNs) are being applied to a wide range of edge intelligent applications, it is critical for edge inference platforms to have both high-throughput and low-…