On the limitations of analysing worst-case dynamic energy of processing

Jeremy Morse; Steve Kerrison; Kerstin Eder

doi:10.1145/3173042

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arXiv · 1603.02580

On the limitations of analysing worst-case dynamic energy of processing

Jeremy Morse·Steve Kerrison·Kerstin Eder

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Abstract

This paper examines dynamic energy consumption caused by data during software execution on deeply embedded microprocessors, which can be significant on some devices. In worst-case energy consumption analysis, energy models are used to find the most costly execution path. Taking each instruction's worst case energy produces a safe but overly pessimistic upper bound. Algorithms for safe and tight bounds would be desirable. We show that finding exact worst-case energy is NP-hard, and that tight bounds cannot be approximated with guaranteed safety. We conclude that any energy model targeting tightness must either sacrifice safety or accept overapproximation proportional to data-dependent energy.

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Jeremy Morse, Steve Kerrison, Kerstin Eder. 2016-03-07. On the limitations of analysing worst-case dynamic energy of processing. https://doi.org/10.1145/3173042

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