Analysis of process distribution in HPC cluster using HPL

A. Rajan, B. K. Joshi, A. Rawat, R. Jha, K. Bhachavat
{"title":"Analysis of process distribution in HPC cluster using HPL","authors":"A. Rajan, B. K. Joshi, A. Rawat, R. Jha, K. Bhachavat","doi":"10.1109/PDGC.2012.6449796","DOIUrl":null,"url":null,"abstract":"Computing using parallel programming techniques running on High Performance Computing Clusters (HPCC) has become very popular for scientific applications. Evaluation of cluster performance is carried out in many different ways. Memory, interconnect bandwidth, number of cores per processor/ node and job complexity are the major parameters which affect and govern the peak computing power delivered by HPCC. In this paper we carried out experiments using High Performance Linpack (HPL) to analyze effect of job distribution among cores on same processor and among cores on distributed processors. Certain runs of HPL have also been carried out to understand effect of interconnect used for building the cluster. The distributed nature of the HPC cluster using InfiniBand interconnect has been analyzed. Results are represented in form of graphs and corresponding analysis is also included in the paper.","PeriodicalId":166718,"journal":{"name":"2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDGC.2012.6449796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Computing using parallel programming techniques running on High Performance Computing Clusters (HPCC) has become very popular for scientific applications. Evaluation of cluster performance is carried out in many different ways. Memory, interconnect bandwidth, number of cores per processor/ node and job complexity are the major parameters which affect and govern the peak computing power delivered by HPCC. In this paper we carried out experiments using High Performance Linpack (HPL) to analyze effect of job distribution among cores on same processor and among cores on distributed processors. Certain runs of HPL have also been carried out to understand effect of interconnect used for building the cluster. The distributed nature of the HPC cluster using InfiniBand interconnect has been analyzed. Results are represented in form of graphs and corresponding analysis is also included in the paper.
基于HPL的HPC集群进程分布分析
在高性能计算集群(HPCC)上使用并行编程技术进行计算已经在科学应用中变得非常流行。集群性能的评估有许多不同的方式。内存、互连带宽、每个处理器/节点的核数和作业复杂度是影响和控制HPCC峰值计算能力的主要参数。本文利用高性能Linpack (High Performance Linpack, HPL)进行了实验,分析了在同一处理器和分布式处理器上作业分配的影响。还进行了一些HPL运行,以了解用于构建集群的互连的效果。分析了采用ib互连的高性能计算集群的分布式特性。结果用图形表示,并进行了相应的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信