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dc.contributor.authorSchulz, Christian Ferdinand
dc.contributor.authorHasle, Geir
dc.contributor.authorBrodtkorb, André R.
dc.contributor.authorHagen, Trond Runar
dc.date.accessioned2017-09-18T05:27:06Z
dc.date.available2017-09-18T05:27:06Z
dc.date.created2013-04-02T14:36:19Z
dc.date.issued2013
dc.identifier.citationEURO Journal on Transportation and Logistics. 2013, 2 (1-2), 159-186.nb_NO
dc.identifier.issn2192-4376
dc.identifier.urihttp://hdl.handle.net/11250/2454986
dc.description.abstractIn many cases there is still a large gap between the performance of current optimization technology and the requirements of real-world applications. As in the past, performance will improve through a combination of more powerful solution methods and a general performance increase of computers. These factors are not independent. Due to physical limits, hardware development no longer results in higher speed for sequential algorithms, but rather in increased parallelism. Modern commodity PCs include a multi-core CPU and at least one GPU, providing a low-cost, easily accessible heterogeneous environment for high-performance computing. New solution methods that combine task parallelization and stream processing are needed to fully exploit modern computer architectures and profit from future hardware developments. This paper is the second in a series of two. Part I gives a tutorial style introduction to modern PC architectures and GPU programming. Part II gives a broad survey of the literature on parallel computing in discrete optimization targeted at modern PCs, with special focus on routing problems. We assume that the reader is familiar with GPU programming, and refer the interested reader to Part I. We conclude with lessons learnt, directions for future research, and prospects.
dc.language.isoengnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleGPU Computing in Discrete Optimization Part II: Survey Focused on Routing Problemsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionsubmittedVersion
dc.description.versionacceptedVersion
dc.source.pagenumber159-186nb_NO
dc.source.volume2nb_NO
dc.source.journalEURO Journal on Transportation and Logisticsnb_NO
dc.source.issue1-2nb_NO
dc.identifier.doi10.1007/s13676-013-0026-0
dc.identifier.cristin1021700
dc.relation.projectNorges forskningsråd: 217108nb_NO
dc.relation.projectNorges forskningsråd: 205298nb_NO
dc.relation.projectNorges forskningsråd: 192905nb_NO
dc.relation.projectNorges forskningsråd: 227071nb_NO
cristin.unitcode7401,90,11,0
cristin.unitnameAnvendt matematikk
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.fulltextpostprint
cristin.qualitycode1


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