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Green Algorithms: Quantifying the Carbon Footprint of Computation
Loïc Lannelongue1,2,3, Jason Grealey4,5, Michael Inouye1,2,3,4,6,7,8
1Cambridge Baker Systems Genomics Initiative Department of Public Health and Primary Care University of Cambridge Cambridge CB1 8RN UK.
Summary
This study presents a framework and online tool, Green Algorithms, to estimate the carbon footprint of computational tasks. It quantifies greenhouse gas emissions from computing to promote greener practices.
Area of Science:
- Environmental Science
- Computer Science
- Computational Science
Background:
- Climate change impacts societies, economies, and health globally.
- High-performance computing, while vital for scientific advancement, contributes significantly to greenhouse gas (GHG) emissions.
- The environmental impact of large-scale computation is often underappreciated.
Purpose of the Study:
- To develop a standardized and reliable methodological framework for estimating the carbon footprint of computational tasks.
- To create accessible metrics for contextualizing GHG emissions from computation.
- To raise awareness and facilitate greener computing practices.
Main Methods:
- Developed a methodological framework to estimate the carbon footprint of any computational task.
- Defined metrics for contextualizing GHG emissions.
- Created a freely available online tool, Green Algorithms (www.green-algorithms.org), for users to estimate and report computation carbon footprints.
- Integrated the tool with computational processes requiring minimal information and accounting for diverse hardware.
Main Results:
- Quantified the GHG emissions of algorithms used in particle physics simulations, weather forecasts, and natural language processing.
- Demonstrated a generalizable framework and tool for quantifying the carbon footprint of diverse computational tasks.
- The Green Algorithms tool requires minimal input and integrates seamlessly with existing computational workflows.
Conclusions:
- A simple, generalizable framework and tool have been developed to quantify the carbon footprint of most computations.
- The study provides recommendations to minimize unnecessary CO2 emissions.
- The aim is to increase awareness and promote environmentally sustainable computation.
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