{"title":"Power and performance analysis of the Graph 500 benchmark on the Single-chip Cloud Computer","authors":"Zhiquan Lai, King Tin Lam, Cho-Li Wang, Jinshu Su","doi":"10.1109/CCIOT.2014.7062496","DOIUrl":null,"url":null,"abstract":"The concerns of data-intensiveness and energy awareness are actively reshaping the design of high-performance computing (HPC) systems nowadays. The Graph500 is a widely adopted benchmark for evaluating the performance of computing systems for data-intensive workloads. In this paper, we introduce a data-parallel implementation of Graph500 on the Intel Single-chip Cloud Computer (SCC). The SCC features a non-coherent many-core architecture and multi-domain on-chip DVFS support for dynamic power management. With our custom-made shared virtual memory programming library, memory sharing among threads is done efficiently via the shared physical memory (SPM) while the library has taken care of the coherence. We conduct an in-depth study on the power and performance characteristics of the Graph500 workloads running on this system with varying system scales and power states. Our experimental results are insightful for the design of energy-efficient many-core systems for data-intensive applications.","PeriodicalId":255477,"journal":{"name":"Proceedings of 2014 International Conference on Cloud Computing and Internet of Things","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2014 International Conference on Cloud Computing and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIOT.2014.7062496","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The concerns of data-intensiveness and energy awareness are actively reshaping the design of high-performance computing (HPC) systems nowadays. The Graph500 is a widely adopted benchmark for evaluating the performance of computing systems for data-intensive workloads. In this paper, we introduce a data-parallel implementation of Graph500 on the Intel Single-chip Cloud Computer (SCC). The SCC features a non-coherent many-core architecture and multi-domain on-chip DVFS support for dynamic power management. With our custom-made shared virtual memory programming library, memory sharing among threads is done efficiently via the shared physical memory (SPM) while the library has taken care of the coherence. We conduct an in-depth study on the power and performance characteristics of the Graph500 workloads running on this system with varying system scales and power states. Our experimental results are insightful for the design of energy-efficient many-core systems for data-intensive applications.