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Towards a Predictive Framework for Power Consumption of Job..:
, In:
Proceedings of the 12th International Conference on Management of Digital EcoSystems
,
Sukhija, Nitin
;
Gessinger, Alexander
;
Bautista, Elizabeth
- p. 46-47 , 2020
Link:
https://dl.acm.org/doi/10.1145/3415958.3433042
RT T1 <cTitle>Proceedings of the 12th International Conference on Management of Digital EcoSystems</cTitle>: T1 <Title>Towards a Predictive Framework for Power Consumption of Jobs in HPC Facilities</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3433042&Exemplar=1&LAN=DE A1 Sukhija, Nitin A1 Gessinger, Alexander A1 Bautista, Elizabeth PB ACM YR 2020 K1 Big Data K1 High Performance Computing K1 Machine Learning K1 Power Capping K1 Power Consumption K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Hardware K1 Power and energy K1 Power estimation and optimization K1 Enterprise level and data centers power issues SP 46 OP 47 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3415958.3433042 DO https://dl.acm.org/doi/10.1145/3415958.3433042 SF ELIB - SuUB Bremen
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