Edge Hardware Acceleration
Edge Hardware Acceleration is a specialized computing methodology that leverages dedicated physical devices at the network edge to enhance computational performance by offloading and accelerating specific tasks closer to data sources.
120
Publications
4.3K
Citations
579
Authors
165
Institutions
Publications per year
2017–2026
114
Parents
120
Long Lu, Vinod Yegneswaran, Phillip Porras et al. · 2010 · 144 citations
Fengbin Tu, Yiqi Wang, Zihan Wu et al. · 2022 IEEE International Solid- State Circuits Conference (ISSCC) · 2022 · 129 citations
An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks
Kiran Seshadri, Berkin Akin, James Laudon et al. · 2022 · 121 citations
1–5 of 120
579
5
h-index
5
h-index
4
h-index
3
h-index
3
h-index
1–5 of 579
165
ETH Zurich
Zurich, Switzerland
5 h-index
19 publications
539 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
15 publications
592 citations

SIB Swiss Institute of Bioinformatics
Lausanne, Switzerland
4 h-index
17 publications
461 citations
Sun Moon University
Asan, South Korea
4 h-index
8 publications
261 citations
University of Zurich
Zurich, Switzerland
4 h-index
17 publications
461 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
18 publications
850 citations

Harbin Institute of Technology
Harbin, China
3 h-index
8 publications
363 citations
Kyungpook National University
Daegu, South Korea
3 h-index
8 publications
189 citations
1–8 of 165
Repository · 9 publications · 169 citations
9
h-index
8 publications · 264 citations
8
h-index
3 publications · 86 citations
3
h-index
JSA · 3 publications · 118 citations
3
h-index
JETCAS · 3 publications · 102 citations
3
h-index
1–5