EPAM: A Predictive Energy Model for Mobile AI
Author:
Affiliation:
1. The University of North Carolina,Department of Electrical and Computer Engineering,Charlotte,NC,USA
2. Georgia State University,Department of Computer Science,GA,USA
3. Toyota Motor North America R&D,InfoTech Labs,Mountain View,CA,USA
Funder
NSF
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10278505/10278554/10279417.pdf?arnumber=10279417
Reference18 articles.
1. Experience
2. Where is the energy spent inside my app? Fine grained energy accounting on smartphones with eprof;pathak;Proc of ACM European Conference on Computer Systems,0
3. Towards Accurate and Reliable Energy Measurement of NLP Models
4. LEAF+AIO: Edge-assisted energyaware object detection for mobile augmented reality;wang;IEEE Trans on Mobile Computing,2022
5. DNPU: An Energy-Efficient Deep-Learning Processor with Heterogeneous Multi-Core Architecture
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