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Phase-Aware Cache Partitioning to Target Both Turnaround Time and System Performance

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Phase-Aware Cache Partitioning to Target Both Turnaround Time and System Performance

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dc.contributor.author Pons-Escat, Lucía es_ES
dc.contributor.author Sahuquillo Borrás, Julio es_ES
dc.contributor.author Selfa, Vicent es_ES
dc.contributor.author Petit Martí, Salvador Vicente es_ES
dc.contributor.author Pons Terol, Julio es_ES
dc.date.accessioned 2021-07-07T03:31:23Z
dc.date.available 2021-07-07T03:31:23Z
dc.date.issued 2020-11-01 es_ES
dc.identifier.issn 1045-9219 es_ES
dc.identifier.uri http://hdl.handle.net/10251/168885
dc.description © 2020 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. es_ES
dc.description.abstract [EN] The Last Level Cache (LLC) plays a key role in the system performance of current multi-cores by reducing the number of long latency main memory accesses. The inter-application interference at this shared resource, however, can lead the system to undesired situations regarding performance and fairness. Recent approaches have successfully addressed fairness and turnaround time (TT) in commercial processors. Nevertheless, these approaches must face sustaining system performance, which is challenging. This work makes two main contributions. LLC behaviors regarding cache performance, data reuse and cache occupancy, that adversely impact on the final performance are identified. Second, based on these behaviors, we propose the Critical-Phase Aware Partitioning Approach (CPA), which reduces TT while sustaining (and even improving) IPC by making an effective use of the LLC space. Experimental results show that CPA outperforms CA, Dunn and KPart state-of-the-art approaches, and improves TT (over 40 percent in some workloads) over Linux default behavior while sustaining or even improving IPC by more than 3 percent in several mixes. es_ES
dc.description.sponsorship This work has been supported in part by Ministerio de Ciencia, Innovaci~on y Universidades and the European ERDF under Grant RTI2018-098156-B-C51, and Generalitat Valenciana under Grant AICO/2019/317. es_ES
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers es_ES
dc.relation.ispartof IEEE Transactions on Parallel and Distributed Systems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject System performance es_ES
dc.subject Interference es_ES
dc.subject Throughput es_ES
dc.subject Measurement es_ES
dc.subject Heuristic algorithms es_ES
dc.subject Program processors es_ES
dc.subject Multicore processing es_ES
dc.subject Cache memories es_ES
dc.subject Multi-core multiprocessors es_ES
dc.subject Memory structures es_ES
dc.subject Memory hierarchy es_ES
dc.subject Performance es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Phase-Aware Cache Partitioning to Target Both Turnaround Time and System Performance es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/TPDS.2020.2996031 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/GVA//AICO%2F2019%2F317/ es_ES
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 Pons-Escat, L.; Sahuquillo Borrás, J.; Selfa, V.; Petit Martí, SV.; Pons Terol, J. (2020). Phase-Aware Cache Partitioning to Target Both Turnaround Time and System Performance. IEEE Transactions on Parallel and Distributed Systems. 31(11):2556-2568. https://doi.org/10.1109/TPDS.2020.2996031 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1109/TPDS.2020.2996031 es_ES
dc.description.upvformatpinicio 2556 es_ES
dc.description.upvformatpfin 2568 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 31 es_ES
dc.description.issue 11 es_ES
dc.relation.pasarela S\413469 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES


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