A Comprehensive and Accurate Energy Model for Arm's Cortex-M0 Processor
This enables energy-aware software development for edge computing applications, though it is incremental as it builds on existing energy modeling approaches.
The paper tackles the lack of accurate and configurable energy models for embedded processors by introducing a comprehensive energy model for Arm's Cortex-M0 processor, achieving a prediction error of less than 5%.
Energy modeling can enable energy-aware software development and assist the developer in meeting an application's energy budget. Although many energy models for embedded processors exist, most do not account for processor-specific configurations, neither are they suitable for static energy consumption estimation. This paper introduces a comprehensive energy model for Arm's Cortex-M0 processor, ready to support energy-aware development of edge computing applications using either profiling- or static-analysis-based energy consumption estimation. The model accounts for the Frequency, PreFetch, and WaitState processor configurations which all have a significant impact on the execution time and energy consumption of edge computing applications. All models have a prediction error of less than 5%.