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Amine Lahouel (CERN), Laura Eve Sarah Llinares5/4/26, 5:15 PMDashboards Demos
At CERN, where particle physics meets cloud-native scale, workloads are increasingly powered by GPUs and accelerators for simulation and machine learning. These advances are incredible for science but they raise new questions around efficiency, energy, and carbon impact.
We’ll share how we’re building a metrics-driven framework, rooted in Kubernetes and CNCF tooling, to measure and improve...
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Dr Mahendra PAIPURI (CNRS)5/4/26, 5:15 PMDashboards Demos
With the rapid acceleration of ML/AI research in the last couple of years, the energy consumption of the Information and Communication Technology (ICT) domain has rapidly increased. As a major part of this energy consumption is due to users’ workloads, it is evident that users need to be aware of the energy footprint of their applications. Compute Energy & Emissions Monitoring Stack (CEEMS)...
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Navirah Kamal (University of Cambridge)5/4/26, 5:15 PMDashboards Demos
The environmental impact of research computing is largely invisible to the people generating it. Research Computing systems (e.g. HPCs) consume significant resources, yet quantifying their energy use and carbon footprint, especially at the level of individual jobs and users, remains a genuine challenge. As a result, researchers rarely have visibility into the carbon cost of their work, making...
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