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dc.contributor.authorLlort Sánchez, Germán
dc.contributor.authorGonzález García, Juan
dc.contributor.authorServat, Harald
dc.contributor.authorGiménez Lucas, Judit
dc.contributor.authorLabarta Mancho, Jesús José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2014-10-08T14:48:38Z
dc.date.created2010
dc.date.issued2010
dc.identifier.citationLlort, G. [et al.]. On-line detection of large-scale parallel application's structure. A: IEEE International Parallel and Distributed Processing Symposium. "IEEE International Symposium on Parallel & Distributed Processing: IPDPS 2010: Atlanta, Georgia, USA: 19-23 April 2010". Atlanta, GA: Institute of Electrical and Electronics Engineers (IEEE), 2010, p. 1-10.
dc.identifier.isbn978-1-4244-6441-8
dc.identifier.urihttp://hdl.handle.net/2117/24309
dc.description.abstractWith larger and larger systems being constantly deployed, trace-based performance analysis of parallel applications has become a daunting task. Even if the amount of performance data gathered per single process is small, traces rapidly become unmanageable when merging together the information collected from all processes. In general, an e cient analysis of such a large volume of data is subject to a previous ltering step that directs the analyst's attention towards what is meaningful to understand the observed application behavior. Furthermore, the iterative nature of most scienti c applications usually ends up producing repetitive information. Discarding irrelevant data aims at reducing both the size of traces, and the time required to perform the analysis and deliver results. In this paper, we present an on-line analysis framework that relies on clustering techniques to intelligently select the most relevant information to understand how does the application behave, while keeping the trace volume at a reasonable size.
dc.format.extent10 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures distribuïdes
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshParallel programming (Computer science)
dc.subject.lcshCluster analysis
dc.subject.otherParallel processing
dc.subject.otherPattern clustering
dc.titleOn-line detection of large-scale parallel application's structure
dc.typeConference report
dc.subject.lemacProgramació en paral·lel (Informàtica)
dc.subject.lemacAnàlisi de conglomerats
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1109/IPDPS.2010.5470350
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5470350
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac15017093
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorLlort, G.; González, J.; Servat, H.; Gimenez, J.; Labarta, J.
local.citation.contributorIEEE International Parallel and Distributed Processing Symposium
local.citation.pubplaceAtlanta, GA
local.citation.publicationNameIEEE International Symposium on Parallel & Distributed Processing: IPDPS 2010: Atlanta, Georgia, USA: 19-23 April 2010
local.citation.startingPage1
local.citation.endingPage10


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