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Selecting Heterogeneous Cores for Diversity

Authors:

Christophe Dubach, and

Michael O'boyleAuthors Info & Claims

ACM Transactions on Architecture and Code Optimization (TACO), Volume 13, Issue 4

Article No.: 49, Pages 1 - 25

https://doi.org/10.1145/3014165

Published: 16 December 2016 Publication History

Abstract

Mobile devices with heterogeneous processors are becoming mainstream. With a heterogeneous processor, the runtime scheduler can pick the best CPU core for a given task based on program characteristics, performance requirements, and power limitations. For a heterogeneous processor to be effective, it must contain a diverse set of cores to match a range of runtime requirements and program behaviors. Selecting a diverse set of cores is, however, a non-trivial problem. Power and performance are dependent on both program features and the microarchitectural features of cores, and a selection of cores must satisfy the competing demands of different types of programs. We present a method of core selection that chooses cores at a range of power-performance points. Our algorithm is based on the observation that it is not necessary for a core to consistently have high performance or low power; one type of core can fulfill different roles for different types of programs. Given a power budget, cores selected with our method provide an average speedup of 6% on EEMBC mobile benchmarks and a 24% speedup on SPEC 2006 integer benchmarks over the state-of-the-art core selection method.

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Cited By

Ding YMishra NHoffmann HManne SHunter HAltman E(2019)Generative and multi-phase learning for computer systems optimizationProceedings of the 46th International Symposium on Computer Architecture10.1145/3307650.3326633(39-52)Online publication date: 22-Jun-2019
https://dl.acm.org/doi/10.1145/3307650.3326633
Rexha HLafond SDesnos K(2018)Energy-Efficient Actor Execution for SDF Application on Heterogeneous Architectures2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)10.1109/PDP2018.2018.00083(486-493)Online publication date: Mar-2018
https://doi.org/10.1109/PDP2018.2018.00083
Saeedi SSpink TGorgovan CWebb AClarkson JTomusk EDebrunner TKaszyk KGonzalez-De-Aledo PRodchenko ARiley GBodin BKotselidis CFranke BO'Boyle MDavison AKelly PLujan MFurber SWagstaff HNisbet ANardi LMawer JMelot NPalomar OVespa E(2018)Navigating the Landscape for Real-Time Localization and Mapping for Robotics and Virtual and Augmented RealityProceedings of the IEEE10.1109/JPROC.2018.2856739106:11(2020-2039)Online publication date: Nov-2018
https://doi.org/10.1109/JPROC.2018.2856739

Index Terms

Selecting Heterogeneous Cores for Diversity
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Heterogeneous (hybrid) systems
    2. Parallel architectures
      1. Multicore architectures

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Published In

cover image ACM Transactions on Architecture and Code Optimization

ACM Transactions on Architecture and Code Optimization Volume 13, Issue 4

December 2016

648 pages

ISSN:1544-3566

EISSN:1544-3973

DOI:10.1145/3012405

Editor:
Koen De Bosschere
Ghent University

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Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 16 December 2016

Accepted: 01 October 2016

Revised: 01 October 2016

Received: 01 May 2016

Published in TACO Volume 13, Issue 4

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Cited By

Ding YMishra NHoffmann HManne SHunter HAltman E(2019)Generative and multi-phase learning for computer systems optimizationProceedings of the 46th International Symposium on Computer Architecture10.1145/3307650.3326633(39-52)Online publication date: 22-Jun-2019
https://dl.acm.org/doi/10.1145/3307650.3326633
Rexha HLafond SDesnos K(2018)Energy-Efficient Actor Execution for SDF Application on Heterogeneous Architectures2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)10.1109/PDP2018.2018.00083(486-493)Online publication date: Mar-2018
https://doi.org/10.1109/PDP2018.2018.00083
Saeedi SSpink TGorgovan CWebb AClarkson JTomusk EDebrunner TKaszyk KGonzalez-De-Aledo PRodchenko ARiley GBodin BKotselidis CFranke BO'Boyle MDavison AKelly PLujan MFurber SWagstaff HNisbet ANardi LMawer JMelot NPalomar OVespa E(2018)Navigating the Landscape for Real-Time Localization and Mapping for Robotics and Virtual and Augmented RealityProceedings of the IEEE10.1109/JPROC.2018.2856739106:11(2020-2039)Online publication date: Nov-2018
https://doi.org/10.1109/JPROC.2018.2856739

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