Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project

Energy efficiency has emerged as a central challenge for modern high-performance computing (HPC) systems, where escalating computational demands and architectural complexity have led to significant energy footprints. This paper presents the collective experience of the EuroHPC JU Center of Excellence in Exascale CFD (CEEC) in measuring, analyzing, and optimizing energy consumption across major European HPC systems. We briefly review key methodologies and tools for energy measurement as well as define metrics for reporting results. Through case studies using representative CFD applications (waLBerla, FLEXI/GALÆXI, Neko, and NekRS), we evaluate energy-to-solution and time-to-solution on diverse architectures, including CPU- and GPU-based partitions of LUMI, MareNostrum5, MeluXina, and JUWELS Booster. Our results highlight the advantages of accelerators and mixed-precision techniques for reducing energy consumption while maintaining computational accuracy. Finally, we advocate the need to facilitate energy measurements on HPC systems in order to raise awareness, teach the community, and take actions toward more sustainable exascale computing.

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Publication Details

Published
2026-01-22
DOI
https://doi.org/10.1145/3784828.3785161
Citations
1
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
97.47
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Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project

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1 citations
Parallel Computing and Optimization Techniques
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article

Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project

Roman Iakymchuk, Samuel Kemmler, Dimitrios Papageorgiou, Ioannis Kavroulakis, Yanxiang Chen, Kajol Kulkarni, Anna Schwartz, Gülçin Gedik
article en
1 citations

Abstract

Energy efficiency has emerged as a central challenge for modern high-performance computing (HPC) systems, where escalating computational demands and architectural complexity have led to significant energy footprints. This paper presents the collective experience of the EuroHPC JU Center of Excellence in Exascale CFD (CEEC) in measuring, analyzing, and optimizing energy consumption across major European HPC systems. We briefly review key methodologies and tools for energy measurement as well as define metrics for reporting results. Through case studies using representative CFD applications (waLBerla, FLEXI/GALÆXI, Neko, and NekRS), we evaluate energy-to-solution and time-to-solution on diverse architectures, including CPU- and GPU-based partitions of LUMI, MareNostrum5, MeluXina, and JUWELS Booster. Our results highlight the advantages of accelerators and mixed-precision techniques for reducing energy consumption while maintaining computational accuracy. Finally, we advocate the need to facilitate energy measurements on HPC systems in order to raise awareness, teach the community, and take actions toward more sustainable exascale computing.

University of Stuttgart (DE), Federal Institute For Materials Research and Testing (DE), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Aristotle University of Thessaloniki (GR), Umeå University (SE)
Affordable and clean energy
Openalex Percentile: Top 1%
Parallel Computing and Optimization Techniques
97.47
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