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dc.contributor.authorLopez, Victor
dc.contributor.authorRamirez Miranda, Guillem
dc.contributor.authorGarcia Gasulla, Marta
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2021-07-13T16:41:55Z
dc.date.available2021-07-13T16:41:55Z
dc.date.issued2021
dc.identifier.citationLopez, V.; Ramirez Miranda, G.; Garcia Gasulla, M. TALP: A Lightweight Tool to Unveil Parallel Efficiency of Large-scale Executions. A: HPDC: High-Performance Parallel and Distributed Computing. "In Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy (PERMAVOST '21): 25 June, 2021: Virtual Event Sweden". New York, NY, USA: Association for Computing Machinery, 2021, p. 3-10. ISBN 978-1-4503-8387-5. DOI doi.org/10.1145/3452412.3462753.
dc.identifier.isbn978-1-4503-8387-5
dc.identifier.urihttp://hdl.handle.net/2117/349221
dc.description.abstractThis paper presents the design, implementation, and application of TALP, a lightweight, portable, extensible, and scalable tool for online parallel performance measurement. The efficiency metrics reported by TALP allow HPC users to evaluate the parallel efficiency of their executions, both post-mortem and at runtime. The API that TALP provides allows the running application or resource managers to collect performance metrics at runtime. This enables the opportunity to adapt the execution based on the metrics collected dynamically. The set of metrics collected by TALP are well defined, independent of the tool, and consolidated. We extend the collection of metrics with two additional ones that can differentiate between the load imbalance originated from the intranode or internode imbalance. We evaluate the potential of TALP with three parallel applications that present various parallel issues and carefully analyze the overhead introduced to determine its limitations.
dc.description.sponsorshipThis work is partially supported by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology (TIN2015-65316-P), by the Generalitat de Catalunya (2017-SGR-1414), and by the European POP CoE (GA n. 824080).
dc.format.extent8 p.
dc.language.isoeng
dc.publisherAssociation for Computing Machinery
dc.subjectÀrees temàtiques de la UPC::Informàtica::Programació
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures paral·leles
dc.subject.lcshSupercomputers
dc.subject.lcshHigh performance computing
dc.subject.lcshParallel computer programs
dc.subject.lcshDistributed computing systems, Heterogeneous
dc.subject.otherPerformance and optimization
dc.subject.otherPerformance Monitoring
dc.titleTALP: A Lightweight Tool to Unveil Parallel Efficiency of Large-scale Executions
dc.typeConference lecture
dc.subject.lemacSupercomputadors
dc.identifier.doidoi.org/10.1145/3452412.3462753
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://dl.acm.org/doi/10.1145/3452412.3462753?sid=SCITRUS
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/824080/EU/Performance Optimisation and Productivity 2/POP2
local.citation.contributorHPDC: High-Performance Parallel and Distributed Computing
local.citation.pubplaceNew York, NY, USA
local.citation.publicationNameIn Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy (PERMAVOST '21): 25 June, 2021: Virtual Event Sweden
local.citation.startingPage3
local.citation.endingPage10


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