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Particle-in-Cell algorithms on DEEP: The iPiC3D case study

dc.contributor.authorJakobs, Anna
dc.contributor.authorZitz, Anke
dc.contributor.authorEicker, Norbert
dc.contributor.authorLapenta, Giovanni
dc.date.accessioned2017-06-29T14:30:51Z
dc.date.available2017-06-29T14:30:51Z
dc.date.issued2015
dc.description.abstractThe DEEP (Dynamical Exascale Entry Platform) project aims to provide a first implementation of a novel architecture for heterogeneous high-performance computing. This architecture consists of a standard HPC Cluster and – tightly coupled – a cluster of many-core processors called Booster. This concept offers application developers the opportunity to run different parts of their program on the best fitting part of the machine striving for an optimal overall performance. In order to take advantage of this architecture applications require some adaption. To provide optimal support to the application developers the DEEP concept includes a high-level programming model that helps to separate a given program to the Cluster and Booster parts of the DEEP System. This paper presents the adaption work required for a Particle-in-Cell space weather application developed by KULeuven (Katholieke Universiteit Leuven) done in the course of the DEEP project. It discusses all crucial steps of the work starting with a scalability analysis of the different parts of the program, their performance projections for the Cluster and the Booster leading to the separation decisions for the application and finally the actual implementation work. In addition to that some performance results are presented.en
dc.identifier.pissn0177-0454
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V., Fachgruppe PARS
dc.relation.ispartofPARS-Mitteilungen: Vol. 32, Nr. 1
dc.titleParticle-in-Cell algorithms on DEEP: The iPiC3D case studyen
dc.typeText/Journal Article
gi.citation.publisherPlaceBerlin

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