Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project
Kajol Kulkarni, Samuel Kemmler, Anna Schwarz, Gulcin Gedik, Yanxiang Chen, Dimitrios Papageorgiou, Ioannis Kavroulakis, Roman Iakymchuk

TL;DR
This paper shares European HPC systems' energy consumption experiences, emphasizing measurement methodologies, case studies, and the benefits of accelerators and mixed-precision techniques for energy efficiency.
Contribution
It provides a comprehensive overview of energy measurement practices and case studies across European HPC systems, highlighting strategies for energy reduction and sustainability.
Findings
Accelerators and mixed-precision techniques reduce energy consumption.
Energy measurement is crucial for sustainable HPC development.
Case studies demonstrate energy savings across diverse architectures.
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/GAL{\AE}XI, 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…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Cloud Computing and Resource Management · Big Data and Digital Economy
