The Sunk Carbon Fallacy: Rethinking Carbon Footprint Metrics for Effective Carbon-Aware Scheduling
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3698038.3698542.pdf
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Author(s)
Bashir, Noman
Gohil, Varun
Shahrad, Mohammad
Irwin, David
Subramanya, Anagha Belavadi
Olivetti, Elsa
Delimitrou, Christina
Date Issued
November 20, 2024
Publisher
Association for Computing Machinery
Citation
Noman Bashir, Varun Gohil, Anagha Belavadi Subramanya, Mohammad Shahrad, David Irwin, Elsa Olivetti, and Christina Delimitrou. 2024. The Sunk Carbon Fallacy: Rethinking Carbon Footprint Metrics for Effective Carbon-Aware Scheduling. In Proceedings of the 2024 ACM Symposium on Cloud Computing (SoCC '24). Association for Computing Machinery, New York, NY, USA, 542–551.
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Final published version
Abstract
The rapid increase in computing demand and corresponding energy consumption have focused attention on computing's impact on the climate and sustainability. Prior work proposes metrics that quantify computing's carbon footprint across several lifecycle phases, including its supply chain, operation, and end-of-life. Industry uses these metrics to optimize the carbon footprint of manufacturing hardware and running computing applications. Unfortunately, prior work on optimizing datacenters' carbon footprint often succumbs to the sunk cost fallacy by considering embodied carbon emissions (a sunk cost) when making operational decisions (i.e., job scheduling and placement), which leads to operational decisions that do not always reduce the total carbon footprint.
In this paper, we evaluate carbon-aware job scheduling and placement on a given set of servers for several carbon accounting metrics. Our analysis reveals state-of-the-art carbon accounting metrics that include embodied carbon emissions when making operational decisions can increase the total carbon footprint of executing a set of jobs. We study the factors that affect the added carbon cost of such suboptimal decision-making. We then use a real-world case study from a datacenter to demonstrate how the sunk carbon fallacy manifests itself in practice. Finally, we discuss the implications of our findings in better guiding effective carbon-aware scheduling in on-premise and cloud datacenters.
Description
SoCC ’24, November 20–22, 2024, Redmond, WA, USA
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1145/3698038.3698542
