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dc.contributorLabarta Mancho, Jesús José
dc.contributor.authorMartínez Vera, Juan Francisco
dc.date.accessioned2018-06-30T21:41:08Z
dc.date.available2018-06-30T21:41:08Z
dc.date.issued2018-04-16
dc.identifier.urihttp://hdl.handle.net/2117/118762
dc.description.abstractApplication structure detection problem have been typical solved by means of sequential pattern mining techniques but they present to be difficultly scalable. In this thesis we propose a new approach for HPC apps facing this problem as a classification problem such that scalability can be improved.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshPattern recognition systems
dc.subject.lcshComputer simulation
dc.subject.lcshCluster analysis
dc.subject.othercomputació d'alt rendiment
dc.subject.otherclustering
dc.subject.otherescalabilitat
dc.subject.otherminat de patrons seqüencials
dc.subject.othereïnes per l'analisi del rendiment
dc.subject.otherMPI
dc.subject.otherreconeixement de patrons
dc.subject.otheraplicacions HPC
dc.subject.otherhigh perfomance computing
dc.subject.otherHPC applications
dc.subject.othersequential pattern mining
dc.subject.otherscalability
dc.subject.otherapplication structure detection
dc.subject.otherperformance analysis tools
dc.subject.otherdetecció d'estructura d'aplicacions
dc.titleInferring program structure from execution traces
dc.typeMaster thesis
dc.subject.lemacReconeixement de formes (Informàtica)
dc.subject.lemacSimulació per ordinador
dc.subject.lemacAnàlisi de conglomerats
dc.identifier.slug131665
dc.rights.accessOpen Access
dc.date.updated2018-04-30T04:00:25Z
dc.audience.educationlevelMàster
dc.audience.mediatorFacultat d'Informàtica de Barcelona
dc.contributor.covenanteeBarcelona Supercomputing Center


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