dc.contributor.author | Lopez, Victor |
dc.contributor.author | Ramirez Miranda, Guillem |
dc.contributor.author | Garcia Gasulla, Marta |
dc.contributor.other | Barcelona Supercomputing Center |
dc.date.accessioned | 2021-07-13T16:41:55Z |
dc.date.available | 2021-07-13T16:41:55Z |
dc.date.issued | 2021 |
dc.identifier.citation | Lopez, 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.isbn | 978-1-4503-8387-5 |
dc.identifier.uri | http://hdl.handle.net/2117/349221 |
dc.description.abstract | This 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.sponsorship | This 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.extent | 8 p. |
dc.language.iso | eng |
dc.publisher | Association for Computing Machinery |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Programació |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures paral·leles |
dc.subject.lcsh | Supercomputers |
dc.subject.lcsh | High performance computing |
dc.subject.lcsh | Parallel computer programs |
dc.subject.lcsh | Distributed computing systems, Heterogeneous |
dc.subject.other | Performance and optimization |
dc.subject.other | Performance Monitoring |
dc.title | TALP: A Lightweight Tool to Unveil Parallel Efficiency of Large-scale Executions |
dc.type | Conference lecture |
dc.subject.lemac | Supercomputadors |
dc.identifier.doi | doi.org/10.1145/3452412.3462753 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://dl.acm.org/doi/10.1145/3452412.3462753?sid=SCITRUS |
dc.rights.access | Open Access |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/824080/EU/Performance Optimisation and Productivity 2/POP2 |
local.citation.contributor | HPDC: High-Performance Parallel and Distributed Computing |
local.citation.pubplace | New York, NY, USA |
local.citation.publicationName | In Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy (PERMAVOST '21): 25 June, 2021: Virtual Event Sweden |
local.citation.startingPage | 3 |
local.citation.endingPage | 10 |