Special issue on energy reduction techniques for exa-scale computing: theory and practice

Special issue on energy reduction techniques for exa-scale computing: theory and practice 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 shajulin@sxcce.edu.in Michael Gerndt gerndt@in.tum.de Siegfried Benkner siegfried.benkner@univie.ac.at 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: http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computing Springer Journals

Special issue on energy reduction techniques for exa-scale computing: theory and practice

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer-Verlag GmbH Austria
Subject
Computer Science; Computer Science, general; Information Systems Applications (incl.Internet); Computer Communication Networks; Software Engineering; Artificial Intelligence (incl. Robotics); Computer Appl. in Administrative Data Processing
ISSN
0010-485X
eISSN
1436-5057
D.O.I.
10.1007/s00607-017-0570-9
Publisher site
See Article on Publisher Site

Abstract

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 shajulin@sxcce.edu.in Michael Gerndt gerndt@in.tum.de Siegfried Benkner siegfried.benkner@univie.ac.at 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:

Journal

ComputingSpringer Journals

Published: Jul 28, 2017

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