Measuring energy
Kerrison, Steve, Buschoff, Markus, Nunez-Yanez, Jose, and Eder, Kerstin (2017) Measuring energy. In: Fagas, Giorgos, Gammaitoni, Luca, Gallagher, John P., and Douglas, Paul, (eds.) ICT - Energy Concepts for Energy Efficiency and Sustainability. IntechOpen, London, UK, pp. 59-82.
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Abstract
This chapter provides an introduction to quantifying the energy consumed by software. It is written for computer scientists, software engineers, embedded system developers and programmers who want to understand how to measure the energy consumed by the code they write in order to optimize for energy efficiency. We start with an overview of the electrical foundations of energy measurement and show how these are applied by reviewing the most commonly found energy sensing techniques. This is followed by a brief discussion of the signal processing required to obtain energy consumption data from sensing. We then present two energy measurement systems that are based on sensing techniques. Both can be used to directly measure the energy consumed by software running on embedded systems without the need to modify the hardware. As an alternative, regression-based techniques can be used to infer energy consumption based on monitoring events during program execution using counters monitors offered by the hardware. We introduce the foundations of regression analysis and illustrate how an energy model for an ARM processor can be built using linear regression. In the conclusion, we offer a wider discussion on what should be considered when selecting an energy measurement technique.
Item ID: | 68105 |
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Item Type: | Book Chapter (Scholarly Work) |
ISBN: | 978-953-51-3012-3 |
Keywords: | ICT-Energy, Measuring, Energy, Efficiency, ICT |
Copyright Information: | © 2017 The Author(s). Licensee InTech. Distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/), which permits use, distributionand reproduction for non-commercial purposes, provided the original is properly cited. |
Funders: | EU 7th Framework Programme, Technology Strategy Board UK, Energy Efficient Computing Initiative, German Research Council (DFG) Collaborative Research Center |
Projects and Grants: | ENTRA: Whole-Systems ENergy TRAnsparency (318337), MAGEEC, DFG SFB 876, project A4 |
Date Deposited: | 06 Aug 2021 04:18 |
FoR Codes: | 46 INFORMATION AND COMPUTING SCIENCES > 4612 Software engineering > 461208 Software testing, verification and validation @ 33% 40 ENGINEERING > 4009 Electronics, sensors and digital hardware > 400904 Electronic device and system performance evaluation, testing and simulation @ 34% 46 INFORMATION AND COMPUTING SCIENCES > 4606 Distributed computing and systems software > 460606 Energy-efficient computing @ 33% |
SEO Codes: | 17 ENERGY > 1701 Energy efficiency > 170199 Energy efficiency not elsewhere classified @ 34% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 33% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280110 Expanding knowledge in engineering @ 33% |
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