Skip to main content

Advertisement

Log in

Energy-Efficient Partial-Duplication Task Mapping Under Multiple DVFS Schemes

  • Published:
International Journal of Parallel Programming Aims and scope Submit manuscript

Abstract

On multicore platforms, reliable task execution, as well as low energy consumption, are essential. Dynamic Voltage/Frequency Scaling (DVFS) is typically used for energy savings, but with a negative impact on reliability, especially when the applied frequency is low. Using high frequencies, required to meet reliability constraints, or replicating tasks increases energy consumption. To reduce energy consumption, while enhancing reliability and satisfying real-time constraints, we propose a hybrid approach that combines distinct reliability enhancement techniques, under task-level, processor-level and system-level DVFS. Our task mapping problem jointly decides task allocation, task frequency assignment, and task duplication, under real-time and reliability constraints. This is achieved by formulating the task mapping problem as a Mixed Integer Non-Linear Programming problem, and equivalently transforming it into a Mixed Integer Linear Programming, that can be optimally solved. From the obtained results, the proposed approach achieves better energy consumption, finding solutions, when replication approaches fail.

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

Access this article

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. Baumann, R.C.: Radiation-induced soft errors in advanced semiconductor technologies. IEEE Trans. Device Mater. Reliab. 5(3), 305–316 (2005)

    Article  Google Scholar 

  2. Sudo, T., Sasaki, H., Drewniak, J.L.: Electromagnetic interference (emi) of system-on-package (sop). IEEE Trans. Adv. Packag. 27(2), 304–314 (2004)

    Article  Google Scholar 

  3. Mbrahimi, M., Evans, A., Tahoori M.B., et al.: Comprehensive analysis of alpha and neutron particle-induced soft errors in an embedded processor at nanoscales. In: IEEE/ACM Design, Automation & Test in Europe (2014)

  4. Zhu, D., Melhem, R., Mosse, D.: The effects of energy management on reliability in real-time embedded systems. In: IEEE/ACM International Conference Computer Aided Design pp. 35–40 (2004)

  5. Zhao, B., Aydin, H., Zhu, D.: On maximizing reliability of real-time embedded applications under hard energy constraint. IEEE Trans. Ind. Inform. 6(3), 316–328 (2010)

    Article  Google Scholar 

  6. Wang, S., Li, K., Mei, J., et al.: A reliability-aware task scheduling algorithm based on replication on heterogeneous computing systems. J. Grid Comput. 15(1), 23–39 (2017)

    Article  MathSciNet  Google Scholar 

  7. Haque, M.A., Aydin, H., Zhu, D.: On reliability management of energy-aware real-time systems through task replication. IEEE Trans. Parallel Distrib. Syst. 28(3), 813–825 (2017)

    Article  Google Scholar 

  8. McPherson, J.W.: Reliability challenges for 45nm and beyond. In: ACM Design Automation Conference (2006)

  9. Zhao, B., Aydin, H., Zhu, D.: Shared recovery for energy efficiency and reliability enhancements in real-time applications with precedence constraints. ACM Trans. Des. Autom. Electron. Syst. 18(2), 1–21 (2013)

    Article  Google Scholar 

  10. Xie, G., Chen, Y., Liu, Y., et al.: Resource consumption cost minimization of reliable parallel applications on heterogeneous embedded systems. IEEE Trans. Ind. Inform. 13(4), 1629–1640 (2017)

    Article  Google Scholar 

  11. Deng, Z., Cao, D., Shen, H., et al.: Reliability-aware task scheduling for energy efciency on heterogeneous multiprocessor systems. J. Super Comput. 77, 11643–11681 (2021)

    Article  Google Scholar 

  12. Xie, G., Chen, Y., Xiao, X., et al.: Energy-efficient fault-tolerant scheduling of reliable parallel applications on heterogeneous distributed embedded systems. IEEE Trans. Sustain. Comput. 3(3), 167–181 (2018)

    Article  Google Scholar 

  13. Zhou, J., Sun, J., Zhou, X., et al.: Resource management for improving soft-error and lifetime reliability of real-time MPSoCs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(12), 2215–2228 (2019)

    Article  Google Scholar 

  14. Cui, M., Mo, L., Kritikakou, A., Casseau, E.: Energy-aware Partial-Duplication Task Mapping under Real-Time and Reliability Constraints. In: Embedded Computer Systems: Architectures, Modeling, and Simulation: 20th International Conference, pp. 213–227. SAMOS, Springer (2020)

  15. Han, L., Canon, L.C., Liu, J., Robert, Y., et al.: Improved energy-aware strategies for periodic real-time tasks under reliability constraints. In: 2019 IEEE Real-Time Systems Symposium (RTSS), pp. 17–29 (2019)

  16. Zhang, L., Li, K., Xu, Y., et al.: Maximizing reliability with energy conservation for parallel task scheduling in a heterogeneous cluster. Inf. Sci. 319, 113–131 (2015)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  18. Quan, Z., Wang, Z.J., Ye, T., et al.: Task scheduling for energy consumption constrained parallel applications on heterogeneous computing systems. IEEE Trans. Parallel Distrib. Syst. 31, 1165–1182 (2020)

    Article  Google Scholar 

  19. Cao, K., Zhou, J., Cong, P., et al.: Affinity-driven modeling and scheduling for makespan optimization in heterogeneous multiprocessor systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38, 1189–1202 (2018)

    Article  Google Scholar 

  20. Xu, H., Li, R., Pan, C., et al.: Minimizing energy consumption with reliability goal on heterogeneous embedded systems. J. Parallel Distrib. Comput. 127, 44–57 (2019)

    Article  Google Scholar 

  21. Zhang, L., Li, K., Li, K., et al.: Joint optimization of energy efficiency and system reliability for precedence constrained tasks in heterogeneous systems. Int. J. Electr. Power Energy Syst. 78, 499–512 (2016)

    Article  Google Scholar 

  22. Guo, Y., Zhu, D., Aydin, H.: Reliability-aware power management for parallel real-time applications with precedence constraints. In: IEEE International Green Computing Conference , pp. 1–8 (2011)

  23. Huang, K., Jiang, X., Zhang, X., et al.: Energy-efficient fault-tolerant mapping and scheduling on heterogeneous multiprocessor real-time systems. IEEE Access 6, 57614–57630 (2018)

    Article  Google Scholar 

  24. Salehi, M., Tavana, M.K., Rehman, S., et al.: DRVS: power-efficient reliability management through dynamic redundancy and voltage scaling under variations. In: IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), pp. 225–230 (2015)

  25. Salehi, M., Ejlali, A., Al-Hashimi, B.M.: Two-phase low-energy n-modular redundancy for hard real-time multi-core systems. IEEE Trans. Distrib. Syst. 27(5), 1497–1510 (2016)

    Article  Google Scholar 

  26. Gou, C., Benoit, A., Chen, M., et al.: Reliability-aware energy optimization for throughput-constrained applications on MPSoC. In: 24th IEEE International Conference Parallel and Distributed Systems (2018)

  27. Tosun, S.: Energy- and reliability-aware task scheduling onto heterogeneous MPSoC architectures. J. Supercomput. 62, 265–289 (2012)

    Article  Google Scholar 

  28. Moulik, S., Chaudhary, R., Das, Z.: Hears: a heterogeneous energy-aware real-time scheduler. Microprocess. Microsyst. 72, 102939 (2020)

    Article  Google Scholar 

  29. Chen, G., Huang, K., Knoll, A.: Energy optimization for real-time multiprocessor system-on-chip with optimal DVFS and DPM combination. ACM Trans. Embed. Comput. Syst. 13(3), 1–21 (2014)

    Google Scholar 

  30. Skadron, K., Stan, M.R., Sankaranarayanan, K., et al.: Temperature-aware microarchitecture: modeling and implementation. ACM Tran. Archit. Code Optim. 1(1), 94–125 (2004)

    Article  Google Scholar 

  31. Rokicki, S., Pala, D., Paturel, J., et al.: What you simulate is what you synthesize: designing a processor core from c++ specifications. In: IEEE/ACM International Conference on Computer-Aided Design (2019)

  32. Quan, G., Chaturvedi, V.: Feasibility analysis for temperature-constraint hard real-time periodic tasks. IEEE Trans. Ind. Inform. 6(3), 329–339 (2010)

    Article  Google Scholar 

  33. Guthaus, M., Ringenberg, J., Ernst, D., Austin, T., Mudge, T., Brown, R.: Mibench: A free, commercially representative embedded benchmark suite. In: International Workshop on Workload Characterization. pp. 3–14 (2002)

  34. Deverge, J., Puaut, I.: Safe measurement-based wcet estimation. In: WCET (2007)

Download references

Acknowledgements

This work is founded by China Scholarship Council (CSC).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Minyu Cui.

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

Cui, M., Kritikakou, A., Mo, L. et al. Energy-Efficient Partial-Duplication Task Mapping Under Multiple DVFS Schemes. Int J Parallel Prog 50, 267–294 (2022). https://doi.org/10.1007/s10766-022-00724-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10766-022-00724-7

Keywords

Navigation