Energy Efficiency trends in HPC: what high-energy and astrophysicists need to know

Estela Suarez ^1,2,3* Jorge Amaya ⁴ Martin Frank ⁵ Oliver Freyermuth ⁶ Maria Girone ⁷ Bartosz Kostrzewa ⁸ Susanne Pfalzner ¹

• ¹ Jülich Supercomputing Center, Institute for Advanced Simulation, Julich Research Center, Helmholtz Association of German Research Centers (HZ), Jülich, Germany
• ² SiPEARL GmbH, Duisburg, Lower Saxony, Germany
• ³ Institute of Computer Science, University of Bonn, Bonn, North Rhine-Westphalia, Germany
• ⁴ European Space Agency (Germany), Darmstadt, Hesse, Germany
• ⁵ Karlsruhe Institute of Technology (KIT), Karlsruhe, Baden-Württemberg, Germany
• ⁶ Physikalisches Institut, University of Bonn, Bonn, Germany
• ⁷ European Organization for Nuclear Research (CERN), Geneva, Geneva, Switzerland
• ⁸ Department of Physics and Astronomy, University of Bonn, Bonn, North Rhine-Westphalia, Germany

The growing energy demands of High Performance Computing (HPC) systems have made energy efficiency a critical concern for system developers and operators. However, HPC users are generally less aware of how these energy concerns influence the design, deployment, and operation of supercomputers even though they experience the consequences. This paper examines the implications of HPC's energy consumption, providing an overview of current trends aimed at improving energy efficiency. We describe how hardware innovations such as energyefficient processors, novel system architectures, power management techniques, and advanced scheduling policies do have a direct impact on how applications need to be programmed and executed on HPC systems. For application developers, understanding how these new systems work and how to analyse and report the performances of their own software is critical in the dialog with HPC system designers and administrators. The paper aims to raise awareness about energy efficiency among users, particularly in the high energy physics and astrophysics domains, offering practical advice on how to analyse and optimise applications to reduce their energy consumption without compromising on performance.