Towards A Power Advisor in a Devkit for Internet-of-Things Microcontrollers
Résumé
Microcontrollers (MCUs) for the Internet-of-Things (IoT) are powerful and versatile computing platforms, which may be hard to program correctly and efficiently; power performance is particularly important. We inestigate automatic methods to detect software performance anti-patterns for this class of systems, so as to help the software developer with power-related aspects. We use a virtual prototype, i.e., we execute the real object code on a simulated model of the hardware platform, given as a transaction-level model (TLM) augmented with dedicated monitors. We study two cases taken from an industrial example, and show that our method can help detect patterns that would be difficult to detect statically, even when the source code is available, because they involve the state of the hardware and the timing of operations.
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