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dc.contributor.authorPostigo Díaz, Daniel
dc.contributor.authorHerreros Cerro, David
dc.contributor.authorBarón, Eloy
dc.contributor.authorCamarero Coterillo, Cristobal 
dc.contributor.authorFuentes Saez, Pablo 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2024-10-15T17:31:10Z
dc.date.available2024-10-15T17:31:10Z
dc.date.issued2024
dc.identifier.isbn979-8-4007-0648-6
dc.identifier.otherPID2019-105660RB-C22es_ES
dc.identifier.otherTED2021-131176B-I00es_ES
dc.identifier.otherPID2022-136454NB-C21es_ES
dc.identifier.urihttps://hdl.handle.net/10902/34259
dc.description.abstractA hotspot traffic pattern of communications can be a common phenomenon in HPC topologies that causes significant and lasting network performance degradation. This performance deterioration remains persistent over time, intensifying its impact even after the cessation of the detrimental traffic injection into the network. To understand its causes and effects, we analyze the network behavior under different hotspot traffic scenarios and compare the performance on various topologies. We examine both the performance drop due to traffic flows with endpoint contention, and the recovery process of the network after this phenomenon has occurred, if swift action is taken to mitigate it. Our results show that some topologies are more resilient to hotspot traffic than others, both to reduce the performance drop and/or to accelerate the recovery process. In particular, Flattened Butterfly is more resilient to congestion and consistently demonstrates a rapid recovery. The results of the analysis reinforce the need for mechanisms with effective and expeditious action to reduce the magnitude and duration of the performance drop. Furthermore, they highlight behavioral differences between topologies that can affect the effectiveness of mechanisms using congestion-based metrics.es_ES
dc.description.sponsorshipThis work has been supported by Grants PID2019-105660RB-C22, TED2021-131176B-I00 and PID2022-136454NB-C21 funded by MICIU/AEI/ 10.13039/501100011033nd by ERDF/EU; by the Spanish Ministry of Science and Innovation Ramón y Cajal RYC2021-033959-I, and the European HiPEAC Network of Excellence. The experiments have been executed on the Altamira HPC cluster, at the Institute of Physics of Cantabria (IFCA-CSIC).es_ES
dc.format.extent9 p.es_ES
dc.language.isoenges_ES
dc.publisherAssociation for Computing Machineryes_ES
dc.rights© 2024 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceSNTA '24: proceedings of the Seventh International Workshop on Systems and Network Telemetry and Analytics, Nueva York, Association for Computing Machinery, 2024. Pisa, 15-23es_ES
dc.subject.otherNetwork congestiones_ES
dc.subject.otherHotspot patternes_ES
dc.subject.otherEndpoint congestiones_ES
dc.subject.otherHigh-performance interconnection networkses_ES
dc.titleDefining the boundaries for endpoint congestion management in networks for high-performance computinges_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.1145/3660320.3660333es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105660RB-C22/ES/REDES DE INTERCONEXION, ACELERADORES HARDWARE Y OPTIMIZACION DE APLICACIONES/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-136454NB-C21/ES/ARQUITECTURA Y PROGRAMACION DE COMPUTADORES ESCALABLES DE ALTO RENDIMIENTO Y BAJO CONSUMO III-UC (TEAM-MATES UC)/es_ES
dc.identifier.DOI10.1145/3660320.3660333
dc.type.versionpublishedVersiones_ES


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© 2024 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.Excepto si se señala otra cosa, la licencia del ítem se describe como © 2024 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.