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.