A Flexible Operational Framework for Energy Profiling of Programs

Energy has become a serious concern in the HPC ecosystem for various reasons. The level of the issue is from crucial to critical depending on the context. Considering the variety of hardware devices and the granularity of the desired measurements, addressing the problem of energy profiling clearly requires adequate support tools for measurements and (energy aware) monitoring. There are several frameworks that aim at estimating the energy consumed by a given program on a given computing system, however they mainly suffer from some short-comings related to flexibility, portability, accuracy and programmability. Thus, we propose a tool, so-named EA2P, that is reasonably flexible from both hardware and software standpoints, supporting the major parallel paradigms including GPU acceleration. The tool is publicly available at https://github.com/HPC-CRI/EA2P.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/sbac-padw64858.2024.00014
Citations
2
Primary Topic
Green IT and Sustainability
Type
article
Field-Weighted Citation Impact
0.42

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article

A Flexible Operational Framework for Energy Profiling of Programs

Petr Dokládal, Claude Tadonki, Youssef Mesri, Roblex Nana Tchakoute
2 citations
Green IT and Sustainability
0.42
article

A Flexible Operational Framework for Energy Profiling of Programs

Petr Dokládal, Claude Tadonki, Youssef Mesri, Roblex Nana Tchakoute
article en
2 citations

Abstract

Energy has become a serious concern in the HPC ecosystem for various reasons. The level of the issue is from crucial to critical depending on the context. Considering the variety of hardware devices and the granularity of the desired measurements, addressing the problem of energy profiling clearly requires adequate support tools for measurements and (energy aware) monitoring. There are several frameworks that aim at estimating the energy consumed by a given program on a given computing system, however they mainly suffer from some short-comings related to flexibility, portability, accuracy and programmability. Thus, we propose a tool, so-named EA2P, that is reasonably flexible from both hardware and software standpoints, supporting the major parallel paradigms including GPU acceleration. The tool is publicly available at https://github.com/HPC-CRI/EA2P.

Centre de Mise en Forme des Matériaux (FR), Centre de Recherche en Informatique (FR), École Nationale Supérieure des Mines de Paris (FR)
Institut national de recherche en informatique et en automatique (INRIA), Centre National de la Recherche Scientifique, College of Natural Resources and Sciences, Humboldt State University
Affordable and clean energy
Openalex Percentile: Top 36%
Green IT and Sustainability
0.42
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