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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Chicago |
| Country | United States |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2026 |
| Duration | 729 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2442555 |
The environmental impact of computing has raised concerns worldwide as the growth of both Artificial Intelligence (AI) and Cloud Computing continues to accelerate. These trends are exacerbated by the slowing energy-efficiency improvement of computing technology. Organizations that procure and operate computing equipment are increasingly viewed as accountable for the carbon-emissions impact, water use, and other environmental costs of computing.
Yet today, there are few clear reporting standards for what can be practically done with a reasonable effort. In short, while the need is clear, there is a lack of clear pathways and practices. The project will develop recommendations for effective climate impact reporting at scientific research computing centers, with an accompanying community engagement plan to ensure broad adoption.
The project proposes to analyze existing proposals and practices for reporting on the environmental damage caused by large-scale research computing. The study will explore and develop a range of methodologies for assessing carbon footprint (embodied, operational, and after-use) and other environmental impacts such as water use. The initial focus will be on facilities operated by academic institutions and government-funded centers.
An important part of the study includes the engagement of the community that operates such systems to understand the effort required to produce rigorous reporting and the tradeoff between effort and accuracy. The plan is to engage the academic computing community collaboratively to create realistic, implementable reporting options. The project's hypothesis is that broad adoption of the proposed reporting methods, and accessibility to the accompanying data used in reporting, will lead to procurement, operation, and disposal practices that reduce environmental damage from scientific research computing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Chicago
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