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Online energy-efficient fair scheduling for heterogeneous multi-cores considering shared resource contention

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Abstract

Heterogeneous multi-core processors (HMP) are dual-objective hardware platforms which integrate both high-performance and low power consumption processors. Investigation of simultaneous fairness and energy efficiency could widen their applicability and reveal their strengths. This paper proposes a scheduling framework considering energy efficiency, shared resource contention, and fairness for heterogeneous multi-core processors. The presented framework is implemented and evaluated on a real HMP platform. The obtained experimental results via SPEC CPU2006 benchmark indicate that the proposed framework surpasses Linux and four other schedulers in terms of fairness (58% on average) and energy efficiency (37% on average). The source code of the proposed framework and the opponent algorithms are available online at https://github.com/baghers/CEEF.

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Authors and Affiliations

  1. Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Bagher Salami, Hamid Noori & Mahmoud Naghibzadeh

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  1. Bagher Salami
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  2. Hamid Noori
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  3. Mahmoud Naghibzadeh
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Correspondence to Hamid Noori.

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Salami, B., Noori, H. & Naghibzadeh, M. Online energy-efficient fair scheduling for heterogeneous multi-cores considering shared resource contention. J Supercomput 78, 7729–7748 (2022). https://doi.org/10.1007/s11227-021-04159-8

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