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The Journal of Supercomputing

Erschienen in:

01.01.2015

Blue Gene/Q defragmentation for energy waste minimisation

verfasst von: Timothy M. Lynar, Mark D. Nelson

Erschienen in: The Journal of Supercomputing | Ausgabe 1/2015

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Abstract

In this research, we explore the defragmentation of allocated compute resources so as to conserve energy on an IBM Blue Gene/Q. We examine a real trace from a new four-rack system and explore through simulation three heuristics to minimise energy waste through defragmentation. We describe a number of heuristics for detecting when it is desirable from an energy standpoint to defragment the computing resource through checkpoint/restart. Using heuristics, we were able to gain a simulated saving of 4.36 % of total system power. When applied to all BlueGene/Qs on the Top500 list, this is the equivalent of running the average US household for 698.5 years per annum.

Vorheriger Artikel Subjective versus objective: classifying analytical models for productive heterogeneous performance prediction

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Titel: Blue Gene/Q defragmentation for energy waste minimisation
verfasst von: Timothy M. Lynar
Mark D. Nelson
Publikationsdatum: 01.01.2015
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 1/2015
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-014-1293-8

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