Table of Contents Author Guidelines Submit a Manuscript
Scientific Programming
Volume 22, Issue 4, Pages 273-283
http://dx.doi.org/10.3233/SPR-140393

Tools and Methods for Measuring and Tuning the Energy Efficiency of HPC Systems

Robert Schöne,1 Jan Treibig,2 Manuel F. Dolz,3 Carla Guillen,4 Carmen Navarrete,4 Michael Knobloch,5 and Barry Rountree6

1Center for Information Services and High Performance Computing (ZIH), Technische Universität Dresden, Dresden, Germany
2Erlangen Regional Computing Center, University Erlangen-Nuremberg, Erlangen, Germany
3Department of Informatics, Universität Hamburg, Hamburg, Germany
4Leibniz Rechenzentrum (LRZ) Bayerischen Akademie der Wissenschaften, München, Germany
5Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, Jülich, Germany
6Center for Applied Scientific Computation, Lawrence Livermore National Laboratory, Livermore, CA, USA

Copyright © 2014 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.