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DTSTART;TZID=America/Denver:20231114T110000
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UID:submissions.supercomputing.org_SC23_sess169_pap128@linklings.com
SUMMARY:Clover: Toward Sustainable AI with Carbon-Aware Machine Learning I
 nference Service
DESCRIPTION:Baolin Li (Northeastern University); Siddharth Samsi and Vijay
  Gadepally (Massachusetts Institute of Technology (MIT), Lincoln Laborator
 y); and Devesh Tiwari (Northeastern University)\n\nThis paper presents a s
 olution to the challenge of mitigating carbon emissions from hosting large
 -scale machine learning (ML) inference services. ML inference is critical 
 to modern technology products, but it is also a significant contributor to
  carbon footprint. We introduce, Clover, a carbon-friendly ML inference se
 rvice runtime system that balances performance, accuracy, and carbon emiss
 ions through mixed-quality models and GPU resource partitioning. Our exper
 imental results demonstrate that Clover is effective in substantially redu
 cing carbon emissions while maintaining high accuracy and meeting service 
 level agreement (SLA) targets.\n\nTag: Cloud Computing, Distributed Comput
 ing, Energy Efficiency, Green Computing, Programming Frameworks and System
  Software, State of the Practice, Sustainability\n\nRegistration Category:
  Tech Program Reg Pass\n\nSession Chair: Marco Aldinucci (University of To
 rino, Italy; CINI HPC-KTT Laboratory)\n\n
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