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@ARTICLE{Suarez:1039782,
author = {Suarez, Estela and Bockelmann, Hendryk and Eicker, Norbert
and Eitzinger, Jan and El Sayed Mohamed, Salem and Fieseler,
Thomas and Frank, Martin and Frech, Peter and Giesselmann,
Pay and Hackenberg, Daniel and Hager, Georg and Herten,
Andreas and Ilsche, Thomas and Koller, Bastian and Laure,
Erwin and Manzano, Cristina and Oeste, Sebastian and Ott,
Michael and Reuter, Klaus and Schneider, Ralf and Thust, Kay
and von St. Vieth, Benedikt},
title = {{E}nergy-aware operation of {HPC} systems in {G}ermany},
journal = {Frontiers in high performance computing},
volume = {3},
issn = {2813-7337},
address = {Beijing},
publisher = {Frontiers Media SA},
reportid = {FZJ-2025-01793},
pages = {1520207},
year = {2025},
abstract = {High Performance Computing (HPC) systems are among the most
energy-intensive scientific facilities, with electric power
consumption reaching and often exceeding 20 Megawatts per
installation. Unlike other major scientific infrastructures
such as particle accelerators or high-intensity light
sources, which are few around the world, the number and size
of supercomputers are continuously increasing. Even if every
new system generation is more energy efficient than the
previous one, the overall growth in size of the HPC
infrastructure, driven by a rising demand for computational
capacity across all scientific disciplines, and especially
by Artificial Intelligence (AI) workloads, rapidly drives up
the energy demand. This challenge is particularly
significant for HPC centers in Germany, where high
electricity costs, stringent national energy policies, and a
strong commitment to environmental sustainability are key
factors. This paper describes various state-of-the-art
strategies and innovations employed to enhance the energy
efficiency of HPC systems within the national context. Case
studies from leading German HPC facilities illustrate the
implementation of novel heterogeneous hardware
architectures, advanced monitoring infrastructures,
high-temperature cooling solutions, energy-aware scheduling,
and dynamic power management, among other optimisations. By
reviewing best practices and ongoing research, this paper
aims to share valuable insight with the global HPC
community, motivating the pursuit of more sustainable and
energy-efficient HPC architectures and operations.},
cin = {JSC},
ddc = {004},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5121 - Supercomputing $\&$ Big Data Facilities (POF4-512) /
5122 - Future Computing $\&$ Big Data Systems (POF4-512) /
ATML-X-DEV - ATML Accelerating Devices (ATML-X-DEV)},
pid = {G:(DE-HGF)POF4-5121 / G:(DE-HGF)POF4-5122 /
G:(DE-Juel-1)ATML-X-DEV},
typ = {PUB:(DE-HGF)16},
doi = {10.3389/fhpcp.2025.1520207},
url = {https://juser.fz-juelich.de/record/1039782},
}