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dc.contributor.authorServat, Harald
dc.contributor.authorLlort, German
dc.contributor.authorGonzález, Juan
dc.contributor.authorGiménez Lucas, Judit
dc.contributor.authorLabarta Mancho, Jesús José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherBarcelona Supercomputing Center
dc.identifier.citationServat, H., Llort, G., González, J., Giménez, J., Labarta, J. Bio-inspired call-stack reconstruction for performance analysis. A: Euromicro International Conference on Parallel, Distributed, and Network-Based Processing. "24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2016: 17-19 February 2016 Heraklion, Crete, Greece: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 82-90.
dc.description.abstractThe correlation of performance bottlenecks and their associated source code has become a cornerstone of performance analysis. It allows understanding why the efficiency of an application falls behind the computer's peak performance and enabling optimizations on the code ultimately. To this end, performance analysis tools collect the processor call-stack and then combine this information with measurements to allow the analyst comprehend the application behavior. Some tools modify the call-stack during run-time to diminish the collection expense but at the cost of resulting in non-portable solutions. In this paper, we present a novel portable approach to associate performance issues with their source code counterpart. To address it, we capture a reduced segment of the call-stack (up to three levels) and then process the segments using an algorithm inspired by multi-sequence alignment techniques. The results of our approach are easily mapped to detailed performance views, enabling the analyst to unveil the application behavior and its corresponding region of code. To demonstrate the usefulness of our approach, we have applied the algorithm to several first-time seen in-production applications to describe them finely, and optimize them by using tiny modifications based on the analyses.
dc.description.sponsorshipWe thankfully acknowledge Mathis Bode for giving us access to the Arts CF binaries, and Miguel Castrillo and Kim Serradell for their valuable insight regarding Nemo. We would like to thank Forschungszentrum Jülich for the computation time on their Blue Gene/Q system. This research has been partially funded by the CICYT under contracts No. TIN2012-34557 and TIN2015-65316-P.
dc.format.extent9 p.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
dc.subject.otherPerformance analysis
dc.subject.otherMulti-sequence alignment
dc.subject.otherCall-stack analysis
dc.titleBio-inspired call-stack reconstruction for performance analysis
dc.typeConference report
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
local.citation.authorServat, H.; Llort, G.; González, J.; Giménez, J.; Labarta, J.
local.citation.contributorEuromicro International Conference on Parallel, Distributed, and Network-Based Processing
local.citation.publicationName24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2016: 17-19 February 2016 Heraklion, Crete, Greece: proceedings

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