期刊
ADVANCED SCIENCE
卷 8, 期 12, 页码 -出版社
WILEY
DOI: 10.1002/advs.202100707
关键词
climate change; computational research; green computing
资金
- University of Cambridge MRC DTP [MR/S502443/1]
- La Trobe University Postgraduate Research Scholarship - Baker Heart and Diabetes Institute
- La Trobe University Postgraduate Research Scholarship - La Trobe University Full-Fee Research Scholarship
- UK Medical Research Council [MR/L003120/1]
- NIHR Cambridge Biomedical Research Centre [BRC-1215-20014]
- British Heart Foundation [RG/13/13/30194, RG/18/13/33946]
- Health Data Research UK - 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
- Wellcome
- Munz Chair of Cardiovascular Prediction and Prevention
- Victorian Government'sOperational Infrastructure Support (OIS) program
This study presents a methodological framework and tool to estimate the carbon footprint of computational tasks and quantifies the greenhouse gas emissions of algorithms used in certain fields. The aim is to raise awareness and facilitate greener computation practices.
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 Algorithms () is developed, which enables a user to estimate and report the carbon footprint of their computation. The tool easily integrates with computational processes as it requires minimal information and does not interfere with existing code, while also accounting for a broad range of hardware configurations. Finally, the GHG emissions of algorithms used for particle physics simulations, weather forecasts, and natural language processing are quantified. Taken together, this study develops a simple generalizable framework and freely available tool to quantify the carbon footprint of nearly any computation. Combined with recommendations to minimize unnecessary CO2 emissions, the authors hope to raise awareness and facilitate greener computation.
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