dc.contributor.author | Nishtala, Rajiv | |
dc.contributor.author | Petrucci, Vinicius | |
dc.contributor.author | Carpenter, Paul | |
dc.contributor.author | Själander, Magnus | |
dc.date.accessioned | 2021-03-12T13:02:20Z | |
dc.date.available | 2021-03-12T13:02:20Z | |
dc.date.created | 2020-08-14T08:02:39Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | IEEE Symposium on High-Performance Computer Architecture (HPCA). 2020, 167-179. | en_US |
dc.identifier.issn | 1530-0897 | |
dc.identifier.uri | https://hdl.handle.net/11250/2733181 | |
dc.description.abstract | Many of the important services running on data centres are latency-critical, time-varying, and demand strict user satisfaction. Stringent tail-latency targets for colocated services and increasing system complexity make it challenging to reduce the power consumption of data centres. Data centres typically sacrifice server efficiency to maintain tail-latency targets resulting in an increased total cost of ownership. This paper introduces Twig, a scalable quality-of-service (QoS) aware task manager for latency-critical services co-located on a server system. Twig successfully leverages deep reinforcement learning to characterise tail latency using hardware performance counters and to drive energy-efficient task management decisions in data centres. We evaluate Twig on a typical data centre server managing four widely used latency-critical services. Our results show that Twig outperforms prior works in reducing energy usage by up to 38% while achieving up to 99% QoS guarantee for latency-critical services. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.title | Twig: Multi-Agent Task Management for Colocated Latency-Critical Cloud Services | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | acceptedVersion | en_US |
dc.source.pagenumber | 167-179 | en_US |
dc.source.journal | IEEE Symposium on High-Performance Computer Architecture (HPCA) | en_US |
dc.identifier.doi | 10.1109/HPCA47549.2020.00023 | |
dc.identifier.cristin | 1823260 | |
dc.relation.project | Vetenskapsrådet: 2015-05159 | en_US |
dc.description.localcode | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising 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. | en_US |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 2 | |