Manish Arora, Matt Skach, Wei Huang, Xudong An, Jason Mars, Lingjia Tang, D. Tullsen
{"title":"Understanding the Impact of Socket Density in Density Optimized Servers","authors":"Manish Arora, Matt Skach, Wei Huang, Xudong An, Jason Mars, Lingjia Tang, D. Tullsen","doi":"10.1109/HPCA.2019.00066","DOIUrl":null,"url":null,"abstract":"The increasing demand for computational power has led to the creation and deployment of large-scale data centers. During the last few years, data centers have seen improvements aimed at increasing computational density – the amount of throughput that can be achieved within the allocated physical footprint. This need to pack more compute in the same physical space has led to density optimized server designs. Density optimized servers push compute density significantly beyond what can be achieved by blade servers by using innovative modular chassis based designs. This paper presents a comprehensive analysis of the impact of socket density on intra-server thermals and demonstrates that increased socket density inside the server leads to large temperature variations among sockets due to inter-socket thermal coupling. The paper shows that traditional chip-level and data center-level temperature-aware scheduling techniques do not work well for thermally-coupled sockets. The paper proposes new scheduling techniques that account for the thermals of the socket a task is scheduled on, as well as thermally coupled nearby sockets. The proposed mechanisms provide 2.5% to 6.5% performance improvements across various workloads and as much as 17% over traditional temperature-aware schedulers for computation-heavy workloads. Keywords-Server; Data center; Density Optimized Server; Scheduling","PeriodicalId":102050,"journal":{"name":"2019 IEEE International Symposium on High Performance Computer Architecture (HPCA)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Symposium on High Performance Computer Architecture (HPCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA.2019.00066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The increasing demand for computational power has led to the creation and deployment of large-scale data centers. During the last few years, data centers have seen improvements aimed at increasing computational density – the amount of throughput that can be achieved within the allocated physical footprint. This need to pack more compute in the same physical space has led to density optimized server designs. Density optimized servers push compute density significantly beyond what can be achieved by blade servers by using innovative modular chassis based designs. This paper presents a comprehensive analysis of the impact of socket density on intra-server thermals and demonstrates that increased socket density inside the server leads to large temperature variations among sockets due to inter-socket thermal coupling. The paper shows that traditional chip-level and data center-level temperature-aware scheduling techniques do not work well for thermally-coupled sockets. The paper proposes new scheduling techniques that account for the thermals of the socket a task is scheduled on, as well as thermally coupled nearby sockets. The proposed mechanisms provide 2.5% to 6.5% performance improvements across various workloads and as much as 17% over traditional temperature-aware schedulers for computation-heavy workloads. Keywords-Server; Data center; Density Optimized Server; Scheduling