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
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/168885
Título:
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Phase-Aware Cache Partitioning to Target Both Turnaround Time and System Performance
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Autor:
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Pons-Escat, Lucía
Sahuquillo Borrás, Julio
Selfa, Vicent
Petit Martí, Salvador Vicente
Pons Terol, Julio
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Entidad UPV:
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Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
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Fecha difusión:
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Resumen:
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[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, ...[+]
[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.
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Palabras clave:
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System performance
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Interference
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Throughput
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Measurement
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Heuristic algorithms
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Program processors
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Multicore processing
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Cache memories
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Multi-core multiprocessors
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Memory structures
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Memory hierarchy
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Performance
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Derechos de uso:
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Reserva de todos los derechos
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Fuente:
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IEEE Transactions on Parallel and Distributed Systems. (issn:
1045-9219
)
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DOI:
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10.1109/TPDS.2020.2996031
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Editorial:
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Institute of Electrical and Electronics Engineers
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Versión del editor:
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https://doi.org/10.1109/TPDS.2020.2996031
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Código del Proyecto:
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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/
info:eu-repo/grantAgreement/GVA//AICO%2F2019%2F317/
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Descripción:
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© 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.
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Agradecimientos:
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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.
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Tipo:
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Artículo
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