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

Morse, Jeremy;Kerrison, Steven;Eder, Kerstin

Abstract

This article 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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ACM Transactions on Embedded Computing Systems

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1558-3465

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Publisher

Association for Computing Machinery

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DOI

10.1145/3173042