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dc.contributor.author | Duro-Gómez, José | es_ES |
dc.contributor.author | Petit Martí, Salvador Vicente | es_ES |
dc.contributor.author | Sahuquillo Borrás, Julio | es_ES |
dc.contributor.author | Gómez Requena, María Engracia | es_ES |
dc.date.accessioned | 2018-11-09T11:53:12Z | |
dc.date.available | 2018-11-09T11:53:12Z | |
dc.date.issued | 2018-11-09 | |
dc.identifier.isbn | 978-1-5386-7877-0 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/112204 | |
dc.description.abstract | [EN] Exascale computing is the next step in high performance computing provided by systems composed of millions of interconnected processing cores. In order to guide the design and implementation of such systems, multiple workload characterization studies and system performance evaluations are required. This paper provides a workload characterization study in the context of the European Project ExaNeSt, which focuses, among others, on developing the network technology required to implement future exascale systems. In this work, we characterize different ExaNeSt applications from the computer network perspective by analyzing the distribution of messages, the dynamic bandwidth consumption, and the spatial communication patterns among cores. The analysis highlights three main observations; i) message sizes are, in general, below 50 kB; ii) communication patterns are usually bursty; and iii) spatial communication among cores concentrate in hot spots for most applications. Taking into account these observations, one can conclude that in order to unclog congested network links, an exascale network must be designed to briefly support higher-than-average bandwidths in the vicinity of key network cores. | es_ES |
dc.description.sponsorship | This work was supported by the ExaNest project, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671553, and by the Spanish Ministerio de Econom´ıa y Competitividad (MINECO) and Plan E funds under Grant TIN2015-66972-C5-1-R. | |
dc.format.extent | 7 | |
dc.language | Inglés | |
dc.publisher | IEEE Computer Society | es_ES |
dc.relation.ispartof | 2018 International Conference on High Performance Computing & Simulation (HPCS) | |
dc.rights | Reserva de todos los derechos | |
dc.subject | Workload characterization | es_ES |
dc.subject | Exascale computing | es_ES |
dc.subject | MPI | es_ES |
dc.title | Workload Characterization for Exascale Computing Networks | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.identifier.doi | 10.1109/HPCS.2018.00069 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TIN2015-66972-C5-1-R/ES/TECNICAS PARA LA MEJORA DE LAS PRESTACIONES, COSTE Y CONSUMO DE ENERGIA DE LOS SERVIDORES/ | |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/671553/EU/European Exascale System Interconnect and Storage/ | |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors | es_ES |
dc.description.bibliographicCitation | Duro-Gómez, J.; Petit Martí, SV.; Sahuquillo Borrás, J.; Gómez Requena, ME. (2018). Workload Characterization for Exascale Computing Networks. IEEE Computer Society. 383-389. https://doi.org/10.1109/HPCS.2018.00069 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.conferencename | International Conference on High Performance Computing & Simulation (HPCS) | es_ES |
dc.relation.conferencedate | July 16-20, 2018 | es_ES |
dc.relation.conferenceplace | Orléans, France | es_ES |
dc.relation.publisherversion | http://doi.org/10.1109/HPCS.2018.00069 | |
dc.description.upvformatpinicio | 383 | es_ES |
dc.description.upvformatpfin | 389 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | S\366789 | es_ES |
dc.contributor.funder | European Commission | |
dc.contributor.funder | Ministerio de Economía y Competitividad |