{"title":"CLITE: Efficient and QoS-Aware Co-Location of Multiple Latency-Critical Jobs for Warehouse Scale Computers","authors":"Tirthak Patel, Devesh Tiwari","doi":"10.1109/HPCA47549.2020.00025","DOIUrl":null,"url":null,"abstract":"Large-scale data centers run latency-critical jobs with quality-of-service (QoS) requirements, and throughput-oriented background jobs, which need to achieve high perfor-mance. Previous works have proposed methods which cannot co-locate multiple latency-critical jobs with multiple back-grounds jobs while: (1) meeting the QoS requirements of all latency-critical jobs, and (2) maximizing the performance of the background jobs. This paper proposes CLITE, a Bayesian Optimization-based, multi-resource partitioning technique which achieves these goals. CLITE is publicly available at https://github.com/GoodwillComputingLab/CLITE.","PeriodicalId":339648,"journal":{"name":"2020 IEEE International Symposium on High Performance Computer Architecture (HPCA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"89","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Symposium on High Performance Computer Architecture (HPCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA47549.2020.00025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 89
Abstract
Large-scale data centers run latency-critical jobs with quality-of-service (QoS) requirements, and throughput-oriented background jobs, which need to achieve high perfor-mance. Previous works have proposed methods which cannot co-locate multiple latency-critical jobs with multiple back-grounds jobs while: (1) meeting the QoS requirements of all latency-critical jobs, and (2) maximizing the performance of the background jobs. This paper proposes CLITE, a Bayesian Optimization-based, multi-resource partitioning technique which achieves these goals. CLITE is publicly available at https://github.com/GoodwillComputingLab/CLITE.