Multi-Objective Optimization for the Compiler of Real-Time Systems based on Flower Pollination Algorithm

Jadhav, Shashank; Falk, Heiko

doi:10.1145/3323439.3323977

Cited by 4 publications

(6 citation statements)

References 12 publications

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“…5: Repair individuals from the population if necessary. 6: Evaluate initial population using Equations ( 5) and (12). 7: while Stopping criteria is not reached do 8:…”

Section: Discussionmentioning

confidence: 99%

“…Evaluate individual using Equations ( 5) and (12) Update to next generation using Selection operator. 12: end while 13: return Approximated Pareto-optimal solutions.…”

Section: Discussionmentioning

confidence: 99%

“…Muts et al [17] proposed a function-inlining-based multi-objective optimization. Jadhav et al [12] proposed a compiler-level multiobjective optimization framework using FPA.…”

Section: Related Workmentioning

confidence: 99%

“…We evaluate these individuals using the WCET and energy analyzers integrated within the compiler, and then we collect the related data for these individuals. Eventually, we use this data to approximate the WCET and energy objective using equations ( 5) and (12).…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

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Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation

Jadhav

Falk

2022

Proceedings of the 30th International Conference on Real-Time Networks and Systems

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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 timeconsuming 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 multiobjective 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. CCS CONCEPTS• Computer systems organization → Embedded systems; • Software and its engineering → Compilers; • Computing methodologies → Modeling methodologies; • Mathematics of computing → Discrete optimization.

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“…5: Repair individuals from the population if necessary. 6: Evaluate initial population using Equations ( 5) and (12). 7: while Stopping criteria is not reached do 8:…”

Section: Discussionmentioning

confidence: 99%

“…Evaluate individual using Equations ( 5) and (12) Update to next generation using Selection operator. 12: end while 13: return Approximated Pareto-optimal solutions.…”

Section: Discussionmentioning

confidence: 99%

“…Muts et al [17] proposed a function-inlining-based multi-objective optimization. Jadhav et al [12] proposed a compiler-level multiobjective optimization framework using FPA.…”

Section: Related Workmentioning

confidence: 99%

Section: Multi-objective Optimizationmentioning

confidence: 99%

See 2 more Smart Citations

Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation

Jadhav

Falk

2022

Proceedings of the 30th International Conference on Real-Time Networks and Systems

Self Cite

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“…The CSL layer gathers information about the code structure, e.g., tasks and their parameters, and the associated ETS code points of interests (POIs). The collected POIs are then sent to the multi-criteria optimising compiler (implemented in the WCET-aware C compiler WCC [2]- [4]), that applies a set of multi-objective optimisations [5] regarding energy usage, timing control, and security risks. To do this, WCC employs three plug-in tools, each of which targets a distinct non-functional property.…”

Section: A the Teamplay Methodology For Predictable Architecturesmentioning

confidence: 99%

The TeamPlay Project: Analysing and Optimising Time, Energy, and Security for Cyber-Physical Systems

Rouxel,

Brown,

Ebeid

et al. 2023

2023 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE)

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Non-functional properties, such as energy, time, and security (ETS) are becoming increasingly important in Cyber-Physical Systems (CPS) programming. This article describes TeamPlay, a research project funded under the EU Horizon 2020 programme between January 2018 and June 2021. TeamPlay aimed to provide the system designer with a toolchain for developing embedded applications where ETS properties are first-class citizens, allowing the developer to reflect directly on energy, time and security properties at the source code level. In this paper we give an overview of the TeamPlay methodology, introduce the challenges and solutions of our approach and summarise the results achieved. Overall, applying our TeamPlay methodology led to an improvement of up to 18% performance and 52% energy usage over traditional approaches.

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An Improved Flower Pollination Algorithm for Global Numerical Optimization

Yang

et al. 2020

2020 19th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)

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Multi-Objective Optimization for the Compiler of Real-Time Systems based on Flower Pollination Algorithm

Cited by 4 publications

References 12 publications

Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation

Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation

The TeamPlay Project: Analysing and Optimising Time, Energy, and Security for Cyber-Physical Systems

An Improved Flower Pollination Algorithm for Global Numerical Optimization

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