Harvesting energy consumption on European HPC systems: Sharing Experience from the CEEC project
Addressing energy-efficiency bottlenecks in European exascale HPC systems, this study conducts empirical power measurements and optimizations for representative CFD applications—waLBerla, FLEXI/GALÆXI, Neko, and NekRS—across heterogeneous platforms including LUMI, MareNostrum5, MeluXina, and JUWELS Booster. Methodologically, we propose an accelerator-native adaptation framework coupled with a mixed-precision (FP16/FP32) co-optimization strategy, and establish a unified cross-platform energy-efficiency evaluation metric. Experimental results demonstrate that GPU acceleration combined with judicious mixed-precision arithmetic achieves 30–50% energy reduction while preserving numerical accuracy, thereby significantly improving the energy efficiency (FLOPS/W). Our contributions include a reproducible, portable energy-optimization paradigm for HPC, validated across diverse architectures and application kernels. This work advances sustainable exascale computing by bridging algorithmic, hardware, and system-level energy-aware design principles.