Performance and power modeling and prediction using MuMMI and 10 machine learning methods

Summary Energy‐efficient scientific applications require insight into how high performance computing system features impact the applications' power and performance. This insight can result from the development of performance and power models. In this article, we use the modeling and prediction...

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Veröffentlicht in:	Concurrency and computation 2023-07, Vol.35 (15), p.n/a
Hauptverfasser:	Wu, Xingfu, Taylor, Valerie, Lan, Zhiling
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Checkpointing fault tolerant applications Heat distribution Laboratories Linear algebra Machine learning modeling Modelling MuMMI Performance prediction power Power consumption prediction
Online-Zugang:	Volltext
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