As AI demand grows, so do the energy and water needs of the data centers that run it, and those centers often rely on electricity from fossil-fuel power plants. Researchers at the Marlan and Rosemary Bourns College of Engineering, University of California, Riverside, propose a new framework called Federated Carbon Intelligence (FCI) to address both operational emissions and hardware health.
FCI links environmental and grid carbon-intensity data with real-time measures of individual server condition. By routing AI workloads with awareness of server temperature, age and physical wear, the system aims to lower carbon emissions while reducing hardware stress. In simulations the researchers report up to a 45 percent reduction in CO2 over five years and an increase in average server fleet life by about 1.6 years.
The method also considers embodied carbon from manufacturing new machines, so keeping servers in service longer helps lower total emissions. Published in MRS Energy and Sustainability, the study’s next step is to partner with cloud providers and test FCI in operational data centers.
Difficult words
- carbon intensity — Amount of CO2 emitted per unit of electricity.carbon-intensity
- embodied carbon — Greenhouse gas from making a product.
- workload — Computing tasks run by servers or systems.workloads
- operational — Related to normal running or daily use.
- wear — Damage or loss from regular use over time.
- fleet — A group of similar machines or vehicles.
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Discussion questions
- What challenges might data center operators face when trying to adopt a system like FCI?
- How could extending server lifespan change costs and environmental impact for cloud providers?
- Do you think linking grid carbon-intensity data to computing decisions is realistic everywhere? Why or why not?
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