Zobrazit v EDS

An experimental comparison of software-based power meters: focus on CPU and GPU

Uloženo v:
Podrobná bibliografie
Název: An experimental comparison of software-based power meters: focus on CPU and GPU
Autoři: Jay, Mathilde, Ostapenco, Vladimir, Lefèvre, Laurent, Trystram, Denis, Orgerie, Anne-Cécile, Fichel, Benjamin
Přispěvatelé: Data Aware Large Scale Computing (DATAMOVE), Centre Inria de l'Université Grenoble Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP), Université Grenoble Alpes (UGA), Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon), Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de Lyon, Institut National de Recherche en Informatique et en Automatique (Inria), Design and Implementation of Autonomous Distributed Systems (MYRIADS), Centre Inria de l'Université de Rennes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Centre National de la Recherche Scientifique (CNRS), OVHcloud Roubaix, BATE-UGA-REG21A87, This research was partially supported by the Inria+OVHCloud FrugalCloud challenge., Grid'5000, SILECS, GRID'5000, ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019)
Zdroj: CCGrid 2023 - 23rd IEEE/ACM international symposium on cluster, cloud and internet computing ; https://inria.hal.science/hal-04030223 ; CCGrid 2023 - 23rd IEEE/ACM international symposium on cluster, cloud and internet computing, May 2023, Bangalore, India. pp.1-13, ⟨10.1109/CCGrid57682.2023.00020⟩
Informace o vydavateli: CCSD
IEEE
Rok vydání: 2023
Témata: Energy measurement, Power measurement, Software evaluation, Experimental comparison, [INFO]Computer Science [cs], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Geografické téma: Bangalore, India
Popis: International audience ; The global energy demand for digital activities is constantly growing. Computing nodes and cloud services are at the heart of these activities. Understanding their energy consumption is an important step towards reducing it. On one hand, physical power meters are very accurate in measuring energy but they are expensive, difficult to deploy on a large scale, and are not able to provide measurements at the service level. On the other hand, power models and vendor-specific internal interfaces are already available or can be implemented on existing systems. Plenty of tools, called software-based power meters, have been developed around the concepts of power models and internal interfaces, in order to report the power consumption at levels ranging from the whole computing node to applications and services. However, we have found that it can be difficult to choose the right tool for a specific need.In this work, we qualitatively and experimentally compare several software-based power meters able to deal with CPU or GPU-based infrastructures. For this purpose, we evaluate them against high-precision physical power meters while executing various intensive workloads. We extend this empirical study to highlight the strengths and limitations of each software-based power meter.
Druh dokumentu: conference object
Jazyk: English
DOI: 10.1109/CCGrid57682.2023.00020
Dostupnost: https://inria.hal.science/hal-04030223
https://inria.hal.science/hal-04030223v2/document
https://inria.hal.science/hal-04030223v2/file/_CCGrid23__An_experimental_comparison_of_software_based_power_meters__from_CPU_to_GPU.pdf
https://doi.org/10.1109/CCGrid57682.2023.00020
Rights: http://creativecommons.org/licenses/by-sa/ ; info:eu-repo/semantics/OpenAccess
Přístupové číslo: edsbas.1E584E7B
Databáze: BASE
Popis
Abstrakt:International audience ; The global energy demand for digital activities is constantly growing. Computing nodes and cloud services are at the heart of these activities. Understanding their energy consumption is an important step towards reducing it. On one hand, physical power meters are very accurate in measuring energy but they are expensive, difficult to deploy on a large scale, and are not able to provide measurements at the service level. On the other hand, power models and vendor-specific internal interfaces are already available or can be implemented on existing systems. Plenty of tools, called software-based power meters, have been developed around the concepts of power models and internal interfaces, in order to report the power consumption at levels ranging from the whole computing node to applications and services. However, we have found that it can be difficult to choose the right tool for a specific need.In this work, we qualitatively and experimentally compare several software-based power meters able to deal with CPU or GPU-based infrastructures. For this purpose, we evaluate them against high-precision physical power meters while executing various intensive workloads. We extend this empirical study to highlight the strengths and limitations of each software-based power meter.
DOI:10.1109/CCGrid57682.2023.00020