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Heterogeneity-Aware Resource Allocation in HPC Systems Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Hardware Performance Variation: A Comparative Study Using Lightweight Kernels

verfasst von : Hannes Weisbach, Balazs Gerofi, Brian Kocoloski, Hermann Härtig, Yutaka Ishikawa

Erschienen in: High Performance Computing

Verlag: Springer International Publishing

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Abstract

Imbalance among components of large scale parallel simulations can adversely affect overall application performance. Software induced imbalance has been extensively studied in the past, however, there is a growing interest in characterizing and understanding another source of variability, the one induced by the hardware itself. This is particularly interesting with the growing diversity of hardware platforms deployed in high-performance computing (HPC) and the increasing complexity of computer architectures in general. Nevertheless, characterizing hardware performance variability is challenging as one needs to ensure a tightly controlled software environment.
In this paper, we propose to use lightweight operating system kernels to provide a high-precision characterization of various aspects of hardware performance variability. Towards this end, we have developed an extensible benchmarking framework and characterized multiple compute platforms (e.g., Intel x86, Cavium ARM64, Fujitsu SPARC64, IBM Power) running on top of lightweight kernel operating systems. Our initial findings show up to six orders of magnitude difference in relative variation among CPU cores across different platforms.

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Vorheriges Kapitel A Novel Multi-level Integrated Roofline Model Approach for Performance Characterization
Nächstes Kapitel The Pitfalls of Provisioning Exascale Networks: A Trace Replay Analysis for Understanding Communication Performance
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Metadaten
Titel
Hardware Performance Variation: A Comparative Study Using Lightweight Kernels
verfasst von
Hannes Weisbach
Balazs Gerofi
Brian Kocoloski
Hermann Härtig
Yutaka Ishikawa
Copyright-Jahr
2018
Buch
High Performance Computing

Print ISBN: 978-3-319-92039-9

Electronic ISBN: 978-3-319-92040-5

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-92040-5_13

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