Journal article

Green Algorithms: Quantifying the Carbon Footprint of Computation

Loic Lannelongue, Jason Grealey, Michael Inouye

ADVANCED SCIENCE | WILEY | Published : 2021

Abstract

Climate change is profoundly affecting nearly all aspects of life on earth, including human societies, economies, and health. Various human activities are responsible for significant greenhouse gas (GHG) emissions, including data centers and other sources of large-scale computation. Although many important scientific milestones are achieved thanks to the development of high-performance computing, the resultant environmental impact is underappreciated. In this work, a methodological framework to estimate the carbon footprint of any computational task in a standardized and reliable way is presented and metrics to contextualize GHG emissions are defined. A freely available online tool, Green Al..

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University of Melbourne Researchers

Grants

Awarded by University of Cambridge MRC DTP


Awarded by UK Medical Research Council


Awarded by NIHR Cambridge Biomedical Research Centre


Awarded by British Heart Foundation


Funding Acknowledgements

L. and J.G. contributed equally to this work. L.L. was supported by the University of Cambridge MRC DTP (MR/S502443/1). J.G. was supported by a La Trobe University Postgraduate Research Scholarship jointly funded by the Baker Heart and Diabetes Institute and a La Trobe University Full-Fee Research Scholarship. This work was supported by core funding from: the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946) and the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation, and Wellcome. M.I. was supported by the Munz Chair of Cardiovascular Prediction and Prevention. This study was supported by the Victorian Government'sOperational Infrastructure Support (OIS) program. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.