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.
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Baumann, R.C.: Radiation-induced soft errors in advanced semiconductor technologies. IEEE Trans. Device Mater. Reliab. 5(3), 305–316 (2005)
Sudo, T., Sasaki, H., Drewniak, J.L.: Electromagnetic interference (emi) of system-on-package (sop). IEEE Trans. Adv. Packag. 27(2), 304–314 (2004)
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)
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)
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)
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)
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)
McPherson, J.W.: Reliability challenges for 45nm and beyond. In: ACM Design Automation Conference (2006)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
Tosun, S.: Energy- and reliability-aware task scheduling onto heterogeneous MPSoC architectures. J. Supercomput. 62, 265–289 (2012)
Moulik, S., Chaudhary, R., Das, Z.: Hears: a heterogeneous energy-aware real-time scheduler. Microprocess. Microsyst. 72, 102939 (2020)
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)
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)
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)
Quan, G., Chaturvedi, V.: Feasibility analysis for temperature-constraint hard real-time periodic tasks. IEEE Trans. Ind. Inform. 6(3), 329–339 (2010)
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)
Deverge, J., Puaut, I.: Safe measurement-based wcet estimation. In: WCET (2007)
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This work is founded by China Scholarship Council (CSC).
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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
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DOI: https://doi.org/10.1007/s10766-022-00724-7