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Issue title: Automatic Application Tuning for HPC Architectures
Article type: Research Article
Authors: Schöne, Robert; | Treibig, Jan | Dolz, Manuel F. | Guillen, Carla | Navarrete, Carmen | Knobloch, Michael | Rountree, Barry
Affiliations: Center for Information Services and High Performance Computing (ZIH), Technische Universität Dresden, Dresden, Germany. E-mail: [email protected] | Erlangen Regional Computing Center, University Erlangen-Nuremberg, Erlangen, Germany. E-mail: [email protected] | Department of Informatics, Universität Hamburg, Hamburg, Germany. E-mail: [email protected] | Leibniz Rechenzentrum (LRZ) Bayerischen Akademie der Wissenschaften, München, Germany. E-mails: {carla.guillen, carmen.navarrete}@lrz.de | Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, Jülich, Germany. E-mail: [email protected] | Center for Applied Scientific Computation, Lawrence Livermore National Laboratory, Livermore, CA, USA. E-mail: [email protected]
Note: [] Corresponding author: Robert Schöne, Center for Information Services and High Performance Computing (ZIH), Technische Universität Dresden, 01062 Dresden, Germany. E-mail: [email protected]
Abstract: Energy costs nowadays represent a significant share of the total costs of ownership of High Performance Computing (HPC) systems. In this paper we provide an overview on different aspects of energy efficiency measurement and optimization. This includes metrics that define energy efficiency and a description of common power and energy measurement tools. We discuss performance measurement and analysis suites that use these tools and provide users the possibility to analyze energy efficiency weaknesses in their code. We also demonstrate how the obtained power and performance data can be used to locate inefficient resource usage or to create a model to predict optimal operation points. We further present interfaces in these suites that allow an automated tuning for energy efficiency and how these interfaces are used. We finally discuss how a hard power limit will change our view on energy efficient HPC in the future.
Keywords: Energy efficiency, energy and performance measurement, HPC, high performance computing, energy optimization tools, energy models, energy-efficiency tuning
DOI: 10.3233/SPR-140393
Journal: Scientific Programming, vol. 22, no. 4, pp. 273-283, 2014
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