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dc.contributor.author | Pons-Escat, Lucía | es_ES |
dc.contributor.author | Sahuquillo Borrás, Julio | es_ES |
dc.contributor.author | Petit Martí, Salvador Vicente | es_ES |
dc.contributor.author | Pons Terol, Julio | es_ES |
dc.date.accessioned | 2023-12-22T07:14:13Z | |
dc.date.available | 2023-12-22T07:14:13Z | |
dc.date.issued | 2022-09-01 | es_ES |
dc.identifier.isbn | 978-1-4503-9733-9 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/201062 | |
dc.description.abstract | [EN] Current server processors have redistributed the cache hierarchy space over previous generations. The private L2 cache has been made larger and the shared last level caches (LLC) smaller but designed as non-inclusive to reduce the number of replicated blocks. As a result, the new organization shrinks the per-core cache area. Cache management in this organization becomes more critical than in inclusive caches due to two main reasons: there is less storage capacity per core both in the L3 and when considering the sum of L2 and L3 cache sizes, and there is higher L2-L3 traffic especially when running high cache-demanding applications. This paper focuses on minimizing L3 cache pollution to make a more efficient use of the limited space. Three main types of pollution are identified and measured: useless prefetches, bad speculated loads, and poor locality. This paper proposes Cache-Poll, a pollution-aware management policy that concentrates on limiting the cache space to polluting and L3 insensitive applications, allowing critical applications occupy more space. Unlike state-of-the-art work on non-inclusive caches, Cache-Poll is able to improve performance in an Intel Xeon Scalable processor even when running heavy cache-demanding workloads, consisting of 12-application workloads, as many applications as cores in the processor. Results show that Cache-Poll improves fairness and turnaround time by 44% and 24%, respectively, over the Linux OS, while even improving performance up to 3.5%. | es_ES |
dc.description.sponsorship | This work has been supported by the Spanish Ministerio de Universidades under the grant FPU18/01948 and by Spanish Ministerio de Universidades and European ERDF under grant RTI2018-098156-BC51. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Association for Computing Machinery | es_ES |
dc.relation.ispartof | ICPP '22: Proceedings of the 51st International Conference on Parallel Processing | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Cache partitioning | es_ES |
dc.subject | Intel CAT | es_ES |
dc.subject | Non-inclusive cache | es_ES |
dc.subject | Multicore processor | es_ES |
dc.subject | Cache pollution | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | Cache-Poll: Containing Pollution in Non-Inclusive Caches Through Cache Partitioning | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.type | Capítulo de libro | es_ES |
dc.identifier.doi | 10.1145/3545008.3545083 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098156-B-C51/ES/TECNOLOGIAS INNOVADORAS DE PROCESADORES, ACELERADORES Y REDES, PARA CENTROS DE DATOS Y COMPUTACION DE ALTAS PRESTACIONES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/ //FPU18%2F01948//AYUDA PREDOCTORAL FPU-PONS ESCAT. PROYECTO: GESTION EFICIENTE DE RECURSOS COMPARTIDOS EN HIGH-PERFORMANCE COMPUTING Y CLOUD COMPUTING/ | es_ES |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica | 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 | Pons-Escat, L.; Sahuquillo Borrás, J.; Petit Martí, SV.; Pons Terol, J. (2022). Cache-Poll: Containing Pollution in Non-Inclusive Caches Through Cache Partitioning. Association for Computing Machinery. 1-11. https://doi.org/10.1145/3545008.3545083 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.conferencename | 51th International Conference on Parallel Processing (ICPP 2022) | es_ES |
dc.relation.conferencedate | Agosto 29-Septiembre 01,2022 | es_ES |
dc.relation.conferenceplace | Online | es_ES |
dc.relation.publisherversion | https://doi.org/10.1145/3545008.3545083 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 11 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | S\480629 | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |