Title | ||
---|---|---|
Work in Progress: Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework |
Abstract | ||
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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 Yuan | 1 | 9 | 3.80 |
Dong Peiyan | 2 | 4 | 3.12 |
Mengshu Sun | 3 | 3 | 3.21 |
Wei Niu | 4 | 24 | 11.21 |
Zhengang Li | 5 | 15 | 7.27 |
Yuxuan Cai | 6 | 2 | 2.05 |
Jun Liu | 7 | 0 | 0.34 |
Weiwen Jiang | 8 | 95 | 16.21 |
Xue Lin | 9 | 86 | 14.97 |
Bin Ren | 10 | 82 | 18.03 |
Xulong Tang | 11 | 5 | 4.79 |
Yanzhi Wang | 12 | 1082 | 136.11 |