Skip to main content

Advertisement

Springer Nature Link
Log in

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

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Zhuravlev S, Saez JC, Blagodurov S, Fedorova A, Prieto M (2012) Survey of scheduling techniques for addressing shared resources in multicore processors. ACM Comput Surv 45(1):1–28

    Article  Google Scholar 

  2. Garcia-Garcia A, Saez JC, Prieto-Matias M (2018) Contention-Aware Fair Scheduling for Asymmetric Single-ISA Multicore Systems. IEEE Trans Comput 67(12):1703–1719

    Article  MathSciNet  Google Scholar 

  3. Srikantaiah S, Das R, Mishra AK, Das CR, Kandemir M (2009) A case for integrated processor-cache partitioning in chip multiprocessors. In: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, pp 1–12

  4. Delaluz V, Sivasubramaniam A, Kandemir M, Vijaykrishnan N, Irwin MJ (2002) Scheduler-based DRAM energy management. In: Design Automation Conference (DAC), pp 697–702

  5. Lukefahr A, Padmanabha S, Das R, Dreslinski Jr R, Wenisch TF, Mahlke S (2014) Heterogeneous microarchitectures trump voltage scaling for low-power cores. In: Parallel architectures and compilation Techniques (PACT), pp 237–250

  6. Sarma S, Muck T, Bathen LA, Dutt N, Nicolau A (2015) SmartBalance: a sensing-driven linux load balancer for energy efficiency of heterogeneous MPSoCs. In: Design Automation Conference (DAC), pp 1–6

  7. Mück TR, Ghaderi Z, Dutt ND, Bozorgzadeh E (2017) Exploiting heterogeneity for aging-aware load balancing in mobile platforms. IEEE Trans Multi-Scale Comput Syst 3(1):25–35

    Article  Google Scholar 

  8. Van Craeynest K, Jaleel A, Eeckhout L, Narvaez P, Emer J (2012) Scheduling heterogeneous multi-cores through performance impact estimation (PIE). In: International Symposium on Computer Architecture (ISCA), pp 213–224

  9. Delimitrou C, Kozyrakis C (2013) Paragon: QoS-Aware Scheduling for Heterogeneous Datacenters. In: Architectural support for programming languages and operating systems (ASPLOS), pp 77–88

  10. Kim M, Kim K, Geraci JR, Hong S (2014) Utilization-aware load balancing for the energy efficient operation of the big. LITTLE processor. In: Design, Automation & Test in Europe (DATE), pp 1–4

  11. Bhat G, Singla G, Unver AK, Ogras UY (2018) Algorithmic optimization of thermal and power management for heterogeneous mobile platforms. IEEE Trans Very Large Scale Integr (VLSI) Syst, 26(3): 544–557

  12. Roy SK, Devaraj R, Sarkar A, Maji K, Sinha S (2020) Contention-aware optimal scheduling of real-time precedence-constrained task graphs on heterogeneous distributed systems. J Syst Archit 105(1):101706

    Article  Google Scholar 

  13. Feliu J, Sahuquillo J, Petit S, Duato J (2017) Perf&Fair: a progress-aware scheduler to enhance performance and fairness in SMT multicores. IEEE Trans Comput 66(5):905–911

    Article  MathSciNet  Google Scholar 

  14. Van Craeynest K, Akram S, Heirman W, Jaleel A, Eeckhout L (2013) Fairness-aware scheduling on single-ISA heterogeneous multi-cores. In: Parallel Architectures and Compilation Techniques (PACT), pp 177–187

  15. Ankit T, Chaudhari K, Shah M (2020) A comprehensive survey on energy-efficient power management techniques. Procedia Comput Sci 167(1):1189–1199

    Google Scholar 

  16. Salami B, Noori H, Naghibzadeh M (2020) Fairness-aware energy efficient scheduling on heterogeneous multi-core processors. IEEE Trans Computs, pp 1–1

  17. Li T, Brett P, Knauerhase R, Koufaty D, Reddy D, Hahn S (2010) Operating system support for overlapping-ISA heterogeneous multi-core architectures. In: High Performance Computer Architecture (HPCA), pp 1–12

  18. Becchi M, Crowley P (2006) Dynamic thread assignment on heterogeneous multiprocessor architectures. In: Computing Frontiers (CF), pp 29–40

  19. Kim C, Huh J (2018) Exploring the design space of fair scheduling supports for asymmetric multicore systems. IEEE Trans Comput 67(8):1136–1152

    Article  MathSciNet  Google Scholar 

  20. Tian K, Jiang Y, and Shen X (2009) A study on optimally co-scheduling jobs of different lengths on chip multiprocessors. In: Computing Frontiers (CF), pp 41–50

  21. Zhuravlev S, Blagodurov S, Fedorova A (2010) Addressing shared resource contention in multicore processors via scheduling. ACM Sigplan Notices 45(3):129–142

    Article  Google Scholar 

  22. Moreno IS Yang R, Xu J, Wo T (2013) Improved energy-efficiency in cloud datacenters with interference-aware virtual machine placement. In: International Symposium on Autonomous Decentralized Systems (ISADS), pp 1–8

  23. Kim YG, Kim M, Kong J, Chung SW (2020) An Adaptive Thermal Management Framework for Heterogeneous Multi-Core Processors. IEEE Trans Comput 69(6):894–906

    Article  Google Scholar 

  24. Jain PN, Surve SK (2020) A review on shared resource contention in multicores and its mitigating techniques. Int J High Perform Syst Archit 9(1):20–48

    Article  Google Scholar 

  25. da Silva J, Leao L, Petrucci V, Gamatié A, Pereira F (2020) Mapping computations in heterogeneous multicore systems with statistical regression on inputs. In: Brazilian Symposium on Computing Systems Engineering (SBESC)

  26. Singh AK, Dey S, McDonald-Maier K, Basireddy KR, Merrett GV, Al-Hashimi BM (2020) Dynamic energy and thermal management of multi-core mobile platforms: A survey. IEEE Des Test 37(5):25–33

    Article  Google Scholar 

  27. Pasricha S, Ayoub R, Kishinevsky M, Mandal SK, Ogras UY (2020) A survey on energy management for mobile and IoT devices. IEEE Des Test

  28. Ortega C, Alvarez L, Casas M, Bertran R, Buyuktosunoglu A, Eichenberger AE, Bose P, Moreto M (2020) Intelligent adaptation of hardware knobs for improving performance and power consumption. IEEE Trans Comput

  29. Rodgers JL, Nicewander WA (1988) Thirteen ways to look at the correlation coefficient. Am Stat 42(1):59–66

    Article  Google Scholar 

  30. Petrucci V, Loques O, Mossé D, Melhem R, Gazala NA, Gobriel S (2015) Energy-efficient thread assignment optimization for heterogeneous multicore systems. ACM Trans Embedded Comput Syst TECS 14(1):1–26

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Bagher Salami, Hamid Noori & Mahmoud Naghibzadeh

Authors
  1. Bagher Salami
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Hamid Noori
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Mahmoud Naghibzadeh
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Hamid Noori.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-021-04159-8

Keywords