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Estimation of energy consumption in machine learning

descriptionPublicationkeyboard_double_arrow_right Article 01 Dec 2019 Sweden English Publisher:Elsevier BVJournal:Journal of Parallel and Distributed Computing, volume 134, pages 75-88 (issn: 0743-7315, Copyright policy )Funded by:EC | IS-ENES2, KKS | unidentified
Authors: Eva García-Martín; Crefeda Faviola Rodrigues; Graham D. Riley; Håkan Grahn;

doi: 10.1016/j.jpdc.2019.07.007

Estimation of energy consumption in machine learning

Abstract

Energy consumption has been widely studied in the computer architecture field for decades. While the adoption of energy as a metric in machine learning is emerging, the majority of research is stil ...

Country
Sweden
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Keywords

Energy consumption, Datavetenskap (datalogi), Computer Sciences, Machine learning, Green AI, Deep learning, High performance computing

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 417
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
417
Top 0.1%
Top 1%
Top 0.1%
Green
hybrid
Related to Research communities
Energy Planning
Energy Research
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