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Green Algorithms: Quantifying the Carbon Footprint of Computation

Advanced science, 2021-06, Vol.8 (12), p.2100707-n/a [Peer Reviewed Journal]

2021 The Authors. Advanced Science published by Wiley‐VCH GmbH ;2021 The Authors. Advanced Science published by Wiley‐VCH GmbH. ;2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2198-3844 ;EISSN: 2198-3844 ;DOI: 10.1002/advs.202100707 ;PMID: 34194954

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  • Title:
    Green Algorithms: Quantifying the Carbon Footprint of Computation
  • Author: Lannelongue, Loïc ; Grealey, Jason ; Inouye, Michael
  • Subjects: Air travel ; Algorithms ; Carbon footprint ; Carbon sequestration ; climate change ; computational research ; Computer centers ; Cost control ; Digital currencies ; Emissions ; Energy consumption ; Environmental impact ; Estimates ; Genomes ; green computing ; Particle physics ; Radiation ; Simulation ; Software ; Supercomputers ; Weather forecasting
  • Is Part Of: Advanced science, 2021-06, Vol.8 (12), p.2100707-n/a
  • Description: 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 (www.green‐algorithms.org) 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. The Green Algorithms framework estimates the carbon footprint of computation in a simple and reliable way. It is shown that many research activities have substantial footprints and the freely available online app (www.green‐algorithms.org) empowers researchers to assess the impact of their own work, alongside a list of simple ways to reduce it.
  • Publisher: Germany: John Wiley & Sons, Inc
  • Language: English
  • Identifier: ISSN: 2198-3844
    EISSN: 2198-3844
    DOI: 10.1002/advs.202100707
    PMID: 34194954
  • Source: Open Access: PubMed Central
    Open Access: Wiley Blackwell Open Access Journals
    ProQuest Central
    DOAJ Directory of Open Access Journals
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