2026-07-26T02:16:07Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:18438 2024-03-06T10:32:12Z ddc:004 open_access

EnergyAnalyzer: Using Static WCET Analysis Techniques to Estimate the Energy Consumption of Embedded Applications Wegener, Simon Nikov, Kris K. Nunez-Yanez, Jose Eder, Kerstin Energy Modelling Static Analysis Gaisler LEON3 ARM Cortex-M0 This paper presents EnergyAnalyzer, a code-level static analysis tool for estimating the energy consumption of embedded software based on statically predictable hardware events. The tool utilises techniques usually used for worst-case execution time (WCET) analysis together with bespoke energy models developed for two predictable architectures - the ARM Cortex-M0 and the Gaisler LEON3 - to perform energy usage analysis. EnergyAnalyzer has been applied in various use cases, such as selecting candidates for an optimised convolutional neural network, analysing the energy consumption of a camera pill prototype, and analysing the energy consumption of satellite communications software. The tool was developed as part of a larger project called TeamPlay, which aimed to provide a toolchain for developing embedded applications where energy properties are first-class citizens, allowing the developer to reflect directly on these properties at the source code level. The analysis capabilities of EnergyAnalyzer are validated across a large number of benchmarks for the two target architectures and the results show that the statically estimated energy consumption has, with a few exceptions, less than 1% difference compared to the underlying empirical energy models which have been validated on real hardware. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Simon Wegener and Kris K. Nikov and Jose Nunez-Yanez and Kerstin Eder 2023 Is Part Of OASIcs, Volume 114, 21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.WCET.2023.9 urn:nbn:de:0030-drops-184380 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2023.9 eng https://creativecommons.org/licenses/by/4.0/legalcode