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Approximating WCET and energy consumption for fast multi-objective memory allocation
Citation Link: https://doi.org/10.15480/882.4375
Publikationstyp
Research Report
Publikationsdatum
2022-06
Sprache
German
Author
Institut
Start Page
162
End Page
172
Citation
RTNS 2022: Proceedings of the 30th International Conference on Real-Time Networks and Systems: 162-172 (2022)
Contribution to Conference
Publisher DOI
Scopus ID
2-s2.0-85132374209
Peer Reviewed
true
Worst-Case Execution Time (WCET) is the most important design criterion in the domain of hard real-time systems. Most embedded systems also need to satisfy additional design criteria like, e.g., energy consumption. Performing WCET and energy analyses statically at compile-time can be time-consuming. Consequently, minimizing WCET and energy consumption of the code at the compiler level using multi-objective optimization can be a time-consuming process. In this paper, we propose an approximation model to quickly approximate the WCET and energy consumption of the code at compile-time. Instead of using traditional WCET and energy analyses, we exploit this approximation model to perform ScratchPad Memory (SPM) allocation-based multi-objective optimization. Furthermore, we solve the multi-objective optimization problem using metaheuristic algorithms and explore the trade-offs between WCET and energy consumption. Using the proposed approximation model, we achieved, on average, a 94.12% reduction in compilation time and maintained the quality of the Pareto optimal solutions while performing the multi-objective optimization. Furthermore, the approximation error while using the proposed approximation model was in an acceptable range of 2% - 4% on average.
Schlagworte
Multi-objective optimization
Hard real-time systems,
Approxima- tion
Metaheuristic algorithms,
SPM allocation
DDC Class
600: Technik
Funding Organisations