With the increasing popularity of Data Center (DCs), the energy efficiency issue is becoming more important than before. Due to their complex nature, the analysis and in particular the measurement of DCs’ energy efficiency is articulated and open issue. Therefore, the analysis of energy efficiency in DCs, through a set of globally accepted metrics, is an ongoing challenge. In particular, the area of productivity metrics is not complete explored and existing proposed metrics none provides a direct measure of the useful work in a DC. To this end, this paper study and analyses the relationship between the power consumption by server’ workload and the relative number of cores used. In details, through the ENEA-HPC’DC facility, we analyse the real data collected during one year to understand the link between workload’ power consumption and cores. In this way, we present to advance beyond the state of the art of the productivity metrics, and in the meantime, a step forward regarding server performance and power management since through the statistical data analysis provides the behaviour of server energy consumption. © Springer International Publishing AG, part of Springer Nature 2019.

An HPC-data center case study on the power consumption of workload

Quintiliani, A.;Chinnici, M
2019

Abstract

With the increasing popularity of Data Center (DCs), the energy efficiency issue is becoming more important than before. Due to their complex nature, the analysis and in particular the measurement of DCs’ energy efficiency is articulated and open issue. Therefore, the analysis of energy efficiency in DCs, through a set of globally accepted metrics, is an ongoing challenge. In particular, the area of productivity metrics is not complete explored and existing proposed metrics none provides a direct measure of the useful work in a DC. To this end, this paper study and analyses the relationship between the power consumption by server’ workload and the relative number of cores used. In details, through the ENEA-HPC’DC facility, we analyse the real data collected during one year to understand the link between workload’ power consumption and cores. In this way, we present to advance beyond the state of the art of the productivity metrics, and in the meantime, a step forward regarding server performance and power management since through the statistical data analysis provides the behaviour of server energy consumption. © Springer International Publishing AG, part of Springer Nature 2019.
9783319756042
Energy efficiency;Energy metrics;HPC;Computer applications;Data center
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/3764
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