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

Morse, Jeremy, Kerrison, Steven, and Eder, Kerstin (2018) On the limitations of analyzing worst-case dynamic energy of processing. ACM Transactions on Embedded Computing Systems, 17 (3). 59.

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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.

Item ID: 71228
Item Type: Article (Research - C1)
ISSN: 1558-3465
Keywords: Hardware, Power and energy, Power estimation and optimization, Chip-level power issues
Copyright Information: © ACM 2018. This is the author’s version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Embedded Computing Systems, Vol. 17, No 3 (February 2018). http://dx.doi.org/10.1145/3173042.
Funders: European Union Seventh Framework Programme (EU FP7)
Projects and Grants: ENTRA: Whole-Systems ENergy TRAnsparency (318337), ICT-Energy (611004)
Date Deposited: 23 May 2022 05:08
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4612 Software engineering > 461207 Software quality, processes and metrics @ 25%
46 INFORMATION AND COMPUTING SCIENCES > 4613 Theory of computation > 461302 Computational complexity and computability @ 50%
40 ENGINEERING > 4009 Electronics, sensors and digital hardware > 400903 Digital processor architectures @ 25%
SEO Codes: 17 ENERGY > 1701 Energy efficiency > 170199 Energy efficiency not elsewhere classified @ 34%
22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220404 Computer systems @ 33%
28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 33%
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