Navarro, C.; Feliu-Pérez, J.; Petit Martí, SV.; Gómez Requena, ME.; Sahuquillo Borrás, J. (2020). Bandwidth-Aware Dynamic Prefetch Configuration for IBM POWER8. IEEE Transactions on Parallel and Distributed Systems. 31(8):1970-1982. https://doi.org/10.1109/TPDS.2020.2982392
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/168880
Título:
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Bandwidth-Aware Dynamic Prefetch Configuration for IBM POWER8
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Autor:
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Navarro, Carlos
Feliu-Pérez, Josué
Petit Martí, Salvador Vicente
Gómez Requena, María Engracia
Sahuquillo Borrás, 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] Advanced hardware prefetch engines are being integrated in current high-performance processors. Prefetching can boost the performance of most applications, however, the induced bandwidth consumption can lead the system ...[+]
[EN] Advanced hardware prefetch engines are being integrated in current high-performance processors. Prefetching can boost the performance of most applications, however, the induced bandwidth consumption can lead the system to a high contention for main memory bandwidth, which is a scarce resource in current multicores. In such a case, the system performance can be severely damaged. This article characterizes the applications' behavior in an IBM POWER8 machine, which presents many prefetch settings, varying the bandwidth contention. The study reveals that the best prefetch setting for each application depends on the main memory bandwidth availability, that is, it depends on the co-running applications. Based on this study, we propose Bandwidth-Aware Prefetch Configuration (BAPC) a scalable adaptive prefetching algorithm that improves the performance of multi-program workloads. BAPC increases the performance of the applications in a 12, 15, and 16 percent of 6-, 8-, and 10-application workloads over the IBM POWER8 default configuration. In addition, BAPC reduces bandwidth consumption in 39, 42, and 45 percent, respectively.
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Palabras clave:
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Prefetching
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Bandwidth
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Interference
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Hardware
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Engines
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Memory management
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Prefetch engine
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Prefetch settings
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Performance measures
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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.2020.2982392
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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.2020.2982392
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Código del Proyecto:
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info:eu-repo/grantAgreement/UPV//SP20180140/
info:eu-repo/grantAgreement/UPV//PAID-06-18/
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 was supported in part by Ministerio de Ciencia, Innovacion y Universidades and the European ERDF under Grant RTI2018-098156-B-C51, Generalitat Valenciana under Grant AICO/2019/317, and Universitat Politenica de ...[+]
This work was supported in part by Ministerio de Ciencia, Innovacion y Universidades and the European ERDF under Grant RTI2018-098156-B-C51, Generalitat Valenciana under Grant AICO/2019/317, and Universitat Politenica de Valencia (PAID-06-18) under Grant SP20180140.
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Tipo:
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Artículo
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