Analytical Energy Model Parametrized by Workload, Clock Frequency and Number of Active Cores for Share-Memory High-Performance Computing Applications

Analytical Energy Model Parametrized by Workload, Clock Frequency and Number of Active Cores for Share-Memory High-Performance Computing Applications

Energy consumption is crucial in high-performance computing (HPC), especially to enable the next exascale generation. Hence, modern systems implement various hardware and software features for power management. Nonetheless, due to numerous different implementations, we can always push the limits of...

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Bibliographic Details
Main Authors: Vitor Ramos Gomes da Silva, Carlos Valderrama, Pierre Manneback, Samuel Xavier-de-Souza
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Energies
Subjects:
energy model
dynamic frequency and voltage scaling
dynamic power management
high performance computing
Online Access:https://www.mdpi.com/1996-1073/15/3/1213

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https://www.mdpi.com/1996-1073/15/3/1213

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