Computing (2017) 99:725–726 DOI 10.1007/s00607-017-0570-9 EDITORIAL Special issue on energy reduction techniques for exa-scale computing: theory and practice 1 2 Shajulin Benedict · Michael Gerndt · Siegfried Benkner Published online: 28 July 2017 © Springer-Verlag GmbH Austria 2017 Keywords AutoTuning · Energy Efﬁciency · Energy Prediction · Tools 1 Introduction Recently, exa-scale computing has received much attention among the hardware and software designers although exa-scale machine will ﬁrst become available in the 2020s. In fact, these machines are supposed to have hierarchical memory structures, highly scalable architectures with many accelerated nodes and a high performance IO sys- tem. Application and tool developers are rapidly developing solutions to address the known possible exa-scale challenges such as poor scalability, increased energy con- sumption, improper mapping of applications to hardware, and so forth. This special issue addresses the recent trends and technologies involved in reducing the energy consumption of scientiﬁc applications on future exa-scale systems. B Shajulin Benedict email@example.com Michael Gerndt firstname.lastname@example.org Siegfried Benkner email@example.com HPCCLoud Research Laboratory, SXCCE, Anna University, Nagercoil 629003, India Chair for Computer Architecture, Technische Universitaet Muenchen, Munich, Germany Research Group Scientiﬁc Computing, University of Vienna, Vienna, Austria 123 726 S. Benedict et al. 2 The special issue:
Computing – Springer Journals
Published: Jul 28, 2017
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