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June 28, 2022Computer327 citations

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink

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DPDavid S. PattersonJGJoseph E. GonzalezUHUrs Hölzle

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Abstract

Machine learning (ML) workloads have rapidly grown, raising concerns about their carbon footprint. We show four best practices to reduce ML training energy and carbon dioxide emissions. If the whole ML field adopts best practices, we predict that by 2030, total carbon emissions from training will decline.

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Patterson et al. (2022) studied this question.

synapsesocial.com/papers/69f25a11d4c794b733abc38ehttps://doi.org/10.1109/mc.2022.3148714
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