Title
Work in Progress: Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework
Abstract
Efficient deployment of Deep Neural Networks (DNNs) on edge devices (i.e., FPGAs and mobile platforms) is very challenging, especially under a recent witness of the increasing DNN model size and complexity. Although various optimization approaches have been proven to be effective in many DNNs on edge devices, most state-of-the-art work focuses on ad-hoc optimizations, and there lacks a thorough st...
Year
DOI
Venue
2021
10.1109/RTAS52030.2021.00060
2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS)
Keywords
DocType
ISSN
Neural networks,Real-time systems,Energy efficiency,Ad hoc networks,Complexity theory,Optimization,Field programmable gate arrays
Conference
1545-3421
ISBN
Citations 
PageRank 
978-1-6654-0386-3
0
0.34
References 
Authors
0
12
Name
Order
Citations
PageRank
Geng Yuan193.80
Dong Peiyan243.12
Mengshu Sun333.21
Wei Niu42411.21
Zhengang Li5157.27
Yuxuan Cai622.05
Jun Liu700.34
Weiwen Jiang89516.21
Xue Lin98614.97
Bin Ren108218.03
Xulong Tang1154.79
Yanzhi Wang121082136.11