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            Chapter Globally Optimised Energy-Efficient Data Centres

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            Author(s)
            O'Sullivan, Barry
            Tsachouridis, Vassilios A.
            Rea, Susan
            Ignacio Torrens, J.
            Chen, Lydia Y.
            Vojtech Zavrel, V
            Pages, Enric
            Grimes, Diarmuid
            Townley, Jacinta
            Scherer, Thomas
            Lopez, Lara
            Pesch, Dirk
            Hensen, Jan
            Engbersen, Ton
            Language
            English
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            Abstract
            A great deal of energy in Information and Communication Technology (ICT) systems can be wasted by software, regardless of how energy-efficient the underlying hardware is. To avoid such waste, programmers need to understand the energy consumption of programs during the development process rather than waiting to measure energy after deployment. Such understanding is hindered by the large conceptual gap from hardware, where energy is consumed, to high-level languages and programming abstractions. The approaches described in this chapter involve two main topics: energy modelling and energy analysis. The purpose of modelling is to attribute energy values to programming constructs, whether at the level of machine instructions, intermediate code or source code. Energy analysis involves inferring the energy consumption of a program from the program semantics along with an energy model. Finally, the chapter discusses how energy analysis and modelling techniques can be incorporated in software engineering tools, including existing compilers, to assist the energy-aware programmer to optimise the energy consumption of code.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/175742
            Keywords
            energy modelling, energy analysis, energy transparency, energy aware, software engineering
            DOI
            10.5772/65988
            Publisher
            InTechOpen
            Publication date and place
            2017
            Classification
            Sustainability
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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