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dc.contributor.authorSchuchart, Joseph
dc.contributor.authorGerndt, Michael
dc.contributor.authorKjeldsberg, Per Gunnar
dc.contributor.authorLysaght, Michael
dc.contributor.authorHorák, David
dc.contributor.authorŘíha, Lubomír
dc.contributor.authorGocht, Andreas
dc.contributor.authorSourouri, Mohammed
dc.contributor.authorKumaraswamy, Madhura
dc.contributor.authorChowdhury, Anamika
dc.contributor.authorJahre, Magnus
dc.contributor.authorDiethelm, Kai
dc.contributor.authorBouizi, Othman
dc.contributor.authorMian, Umbreen Sabir
dc.contributor.authorKružík, Jakub
dc.contributor.authorSojka, Radim
dc.contributor.authorBeseda, Martin
dc.contributor.authorKannan, Venkatesh
dc.contributor.authorBendifallah, Zakaria
dc.contributor.authorHackenberg, Daniel
dc.contributor.authorNagel, Wolfgang E.
dc.date.accessioned2017-11-10T08:45:25Z
dc.date.available2017-11-10T08:45:25Z
dc.date.issued2017
dc.identifier.citationComputing. 2017, vol. 99, issue 8, p. 727-745.cs
dc.identifier.issn0010-485X
dc.identifier.issn1436-5057
dc.identifier.urihttp://hdl.handle.net/10084/121390
dc.description.abstractEnergy efficiency is an important aspect of future exascale systems, mainly due to rising energy cost. Although High performance computing (HPC) applications are compute centric, they still exhibit varying computational characteristics in different regions of the program, such as compute-, memory-, and I/O-bound code regions. Some of today's clusters already offer mechanisms to adjust the system to the resource requirements of an application, e.g., by controlling the CPU frequency. However, manually tuning for improved energy efficiency is a tedious and painstaking task that is often neglected by application developers. The European Union's Horizon 2020 project READEX (Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing) aims at developing a tools-aided approach for improved energy efficiency of current and future HPC applications. To reach this goal, the READEX project combines technologies from two ends of the compute spectrum, embedded systems and HPC, constituting a split design-time/runtime methodology. From the HPC domain, the Periscope Tuning Framework (PTF) is extended to perform dynamic auto-tuning of fine-grained application regions using the systems scenario methodology, which was originally developed for improving the energy efficiency in embedded systems. This paper introduces the concepts of the READEX project, its envisioned implementation, and preliminary results that demonstrate the feasibility of this approach.cs
dc.language.isoencs
dc.publisherSpringercs
dc.relation.ispartofseriesComputingcs
dc.relation.urihttps://doi.org/10.1007/s00607-016-0532-7cs
dc.rights© The Author(s) 2017. This article is published with open access at Springerlink.com.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectautomatic tuningcs
dc.subjectenergy efficiencycs
dc.subjectdynamic behaviourcs
dc.subjectdynamic tuningcs
dc.subjectparallel computingcs
dc.titleThe READEX formalism for automatic tuning for energy efficiencycs
dc.typearticlecs
dc.identifier.doi10.1007/s00607-016-0532-7
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/671657/EU//READEX
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume99cs
dc.description.issue8cs
dc.description.lastpage745cs
dc.description.firstpage727cs
dc.identifier.wos000407442300002


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© The Author(s) 2017. This article is published with open access at Springerlink.com.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © The Author(s) 2017. This article is published with open access at Springerlink.com.