A Green(er) World for A.I.

Dan Zhao, Nathan C. Frey, Joseph McDonald, Matthew Hubbell, David Bestor, Michael Jones, Andrew Prout, Vijay Gadepally, Siddharth Samsi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As research and practice in artificial intelligence (A.I.) grow in leaps and bounds, the resources necessary to sustain and support their operations also grow at an increasing pace. While innovations and applications from A.I. have brought significant advances, from applications to vision and natural language to improvements to fields like medical imaging and materials engineering, their costs should not be neglected. As we embrace a world with ever-increasing amounts of data as well as research & development of A.I. applications, we are sure to face an ever-mounting energy footprint to sustain these computational budgets, data storage needs, and more. But, is this sustainable and, more importantly, what kind of setting is best positioned to nurture such sustainable A.I. in both research and practice? In this paper, we outline our outlook for Green A.I. - a more sustainable, energy-efficient and energy-aware ecosystem for developing A.I. across the research, computing, and practitioner communities alike - and the steps required to arrive there. We present a bird's eye view of various areas for potential changes and improvements from the ground floor of AI's operational and hardware optimizations for datacenter/HPCs to the current incentive structures in the world of A.I. research and practice, and more. We hope these points will spur further discussion, and action, on some of these issues and their potential solutions.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages742-750
Number of pages9
ISBN (Electronic)9781665497473
DOIs
StatePublished - 2022
Externally publishedYes
Event36th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022 - Virtual, Online, France
Duration: May 30 2022Jun 3 2022

Publication series

NameProceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022

Conference

Conference36th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022
Country/TerritoryFrance
CityVirtual, Online
Period05/30/2206/3/22

Keywords

  • energy efficiency
  • Green AI
  • sustainable AI

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