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dc.contributor.authorPratas, F.en
dc.contributor.authorTrancoso, Pedroen
dc.contributor.authorSousa, L.en
dc.contributor.authorStamatakis, A.en
dc.contributor.authorShi, G.en
dc.contributor.authorKindratenko, V.en
dc.creatorPratas, F.en
dc.creatorTrancoso, Pedroen
dc.creatorSousa, L.en
dc.creatorStamatakis, A.en
dc.creatorShi, G.en
dc.creatorKindratenko, V.en
dc.date.accessioned2019-11-13T10:42:05Z
dc.date.available2019-11-13T10:42:05Z
dc.date.issued2012
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54885
dc.description.abstractCurrently, we are facing a situation where applications exhibit increasing computational demands and where a large variety of parallel processor systems are available. In this paper we focus on exploiting fine-grain parallelism for three applications with distinct characteristics: a Bioinformatics application (MrBayes), a Molecular Dynamics application (NAMD), and a database application (TPC-H). We assess, side-by-side, the performance of the three applications on general-purpose multi-core processors, the Cell Broadband Engine (Cell/BE), and Graphics Processing Units (GPU). Our results indicate that application performance depends on the characteristics of the parallel architectures and on the computational requirements of the core functions of the respective applications. For MrBayes the best overall performance is achieved on general-purpose multi-core processors, for NAMD on the Cell/BE, and for TPC-H on GPUs. © 2011 Elsevier B.V. All rights reserved.en
dc.sourceParallel Computingen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84862697881&doi=10.1016%2fj.parco.2011.08.002&partnerID=40&md5=bfeb3cdac4c28baacdd3f123198f6d3c
dc.subjectParallel architecturesen
dc.subjectParallel processing systemsen
dc.subjectMolecular dynamicsen
dc.subjectComputer graphicsen
dc.subjectMicroprocessor chipsen
dc.subjectMulti-core processoren
dc.subjectBioinformaticsen
dc.subjectProgram processorsen
dc.subjectPerformance evaluationen
dc.subjectMulti coreen
dc.subjectDatabase workloaden
dc.subjectDatabase workloadsen
dc.subjectFine grain parallelismen
dc.subjectFine-grain parallelismen
dc.subjectMulti-core aceleratorsen
dc.subjectMulti-core processorsen
dc.subjectScientific workloadsen
dc.titleFine-grain parallelism using multi-core, Cell/BE, and GPU systemsen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.parco.2011.08.002
dc.description.volume38
dc.description.issue8
dc.description.startingpage365
dc.description.endingpage390
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :13</p>en
dc.source.abbreviationParallel Computen
dc.contributor.orcidTrancoso, Pedro [0000-0002-2776-9253]
dc.gnosis.orcid0000-0002-2776-9253


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