When Climate Meets Machine Learning: Edge to Cloud ML Energy Efficiency

A large portion of current cloud and edge workloads feature Machine Learning (ML) tasks, thereby requiring a deep understanding of their energy efficiency. While the holy grail for judging the quality of a ML model has largely been testing accuracy, and only recently its resource usage, neither of t...

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Bibliographic Details

Published in:	2021 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED) p. 1
Main Author:	Marculescu, Diana
Format:	Conference Proceeding
Language:	English
Published:	IEEE 26.07.2021
Subjects:	Clouds Energy efficiency Hardware hardware-aware ML Machine learning Measurement Mobile handsets model compression neural architecture search quantization Runtime
Online Access:	Get full text
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