Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915598735245312 |
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| author | Kulkarni, Kajol Kemmler, Samuel Schwarz, Anna Gedik, Gulcin Chen, Yanxiang Papageorgiou, Dimitrios Kavroulakis, Ioannis Iakymchuk, Roman |
| author_facet | Kulkarni, Kajol Kemmler, Samuel Schwarz, Anna Gedik, Gulcin Chen, Yanxiang Papageorgiou, Dimitrios Kavroulakis, Ioannis Iakymchuk, Roman |
| contents | 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 metrics 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_03029 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project Kulkarni, Kajol Kemmler, Samuel Schwarz, Anna Gedik, Gulcin Chen, Yanxiang Papageorgiou, Dimitrios Kavroulakis, Ioannis Iakymchuk, Roman Distributed, Parallel, and Cluster Computing 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 metrics 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. |
| title | Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2511.03029 |