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On the Limitations of Analyzing Worst-Case Dynamic Energy of Processing

2018; Association for Computing Machinery; Volume: 17; Issue: 3 Linguagem: Inglês

10.1145/3173042

1558-3465

Jeremy Morse, Steve Kerrison, Kerstin Eder,

Embedded Systems Design Techniques

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.