COBRA-HPA: a block generating tool to perform hybrid program analysis

Huybrechts, Thomas; Bock, Yorick De; Li, Haoxuan; Hellinckx, Peter

doi:10.1504/ijguc.2019.098211

Cited by 6 publications

(7 citation statements)

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“…The current implementation provides insights for embedded developers in three categories: WCRC analysis, scheduler optimisation [16] and design pattern-based performance optimisation for multi-core processors. In previous research, we implemented the hybrid methodology to estimate the WCET on embedded devices [15]. The results showed a reduction in effort while keeping sound WCET predictions.…”

Section: Worst-case Resource Analysismentioning

confidence: 99%

“…The third approach, we use in our research [15], is the hybrid methodology, which is a combination of the analysis techniques above. By splitting the code into smaller components, or 'hybrid blocks', we are able to create a balance between the computational complexity and accuracy.…”

Section: Worst-case Resource Analysismentioning

confidence: 99%

“…The research on hybrid WCRC analysis has been integrated within the Code Behaviour fRAmework (COBRA) tool which we developed. This framework is a collection of tools to examine the behaviour of code on different computing platforms [15]. The current implementation provides insights for embedded developers in three categories: WCRC analysis, scheduler optimisation [16] and design pattern-based performance optimisation for multi-core processors.…”

Section: Worst-case Resource Analysismentioning

confidence: 99%

“…Nevertheless, this list can be further expanded and improved on in future research by employing feature engineering techniques [37,38], such as correlation analysis between features and feature extraction strategies [39]. In the hybrid analysis methodology [15], the WCEC of each block is first determined by empirical analysis on the physical hardware and then statically combined. However, we aim to reduce the analysis effort by replacing the physical measurements with a machine learning estimation layer.…”

Section: Machine Learningmentioning

confidence: 99%

“…A set of software tools have been developed to facilitate the analysis process. All tools are now integrated as the Hybrid Program Analyser (HPA) addition to the COBRA framework [15].…”

Section: Cobra Frameworkmentioning

confidence: 99%

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Automated Testbench for Hybrid Machine Learning-Based Worst-Case Energy Consumption Analysis on Batteryless IoT Devices

et al. 2021

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Batteryless Internet-of-Things (IoT) devices need to schedule tasks on very limited energy budgets from intermittent energy harvesting. Creating an energy-aware scheduler allows the device to schedule tasks in an efficient manner to avoid power loss during execution. To achieve this, we need insight in the Worst-Case Energy Consumption (WCEC) of each schedulable task on the device. Different methodologies exist to determine or approximate the energy consumption. However, these approaches are computationally expensive and infeasible to perform on all type of devices; or are not accurate enough to acquire safe upper bounds. We propose a hybrid methodology that combines machine learning-based prediction on small code sections, called hybrid blocks, with static analysis to combine the predictions to a final upper bound estimation for the WCEC. In this paper, we present our work on an automated testbench for the Code Behaviour Framework (COBRA) that measures and profiles the upper bound energy consumption on the target device. Next, we use the upper bound measurements of the testbench to train eight different regression models that need to predict these upper bounds. The results show promising estimates for three regression models that could potentially be used for the methodology with additional tuning and training.

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Section: Worst-case Resource Analysismentioning

confidence: 99%

Section: Worst-case Resource Analysismentioning

confidence: 99%

Section: Worst-case Resource Analysismentioning

confidence: 99%

Section: Machine Learningmentioning

confidence: 99%

“…A set of software tools have been developed to facilitate the analysis process. All tools are now integrated as the Hybrid Program Analyser (HPA) addition to the COBRA framework [15].…”

Section: Cobra Frameworkmentioning

confidence: 99%

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