Authors
David Patterson, Joseph Gonzalez, Urs Hölzle, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R So, Maud Texier, Jeff Dean
Publication date
2022/6/28
Journal
Computer
Volume
55
Issue
7
Pages
18-28
Publisher
IEEE
Description
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.
Total citations
Scholar articles
D Patterson, J Gonzalez, U Hölzle, Q Le, C Liang… - Computer, 2022