{"title":"Is container-based technology a winner for high performance scientific applications?","authors":"Theodora Adufu, Jieun Choi, Yoonhee Kim","doi":"10.1109/APNOMS.2015.7275379","DOIUrl":null,"url":null,"abstract":"High Performance Computing (HPC) applications require systems with environments for maximum use of limited resources to facilitate efficient computations. However, these systems are faced with a large trade-off between efficient resource allocation and minimum execution times for the applications executed on them. Also, deploying applications in newer environments is exacting. To alleviate this challenge, container-based systems are recently being deployed to reduce the trade-off. In this paper, we investigate container-based technology as an efficient virtualization technology for running high performance scientific applications. We select Docker as the container-based technology for our test bed. We execute autodock3, a molecular modeling simulation software mostly used for Protein-ligand docking, in Docker containers and VMs created using OpenStack. We compare the execution times of the docking process in both Docker containers and in VMs.","PeriodicalId":269263,"journal":{"name":"2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"55","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APNOMS.2015.7275379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 55
Abstract
High Performance Computing (HPC) applications require systems with environments for maximum use of limited resources to facilitate efficient computations. However, these systems are faced with a large trade-off between efficient resource allocation and minimum execution times for the applications executed on them. Also, deploying applications in newer environments is exacting. To alleviate this challenge, container-based systems are recently being deployed to reduce the trade-off. In this paper, we investigate container-based technology as an efficient virtualization technology for running high performance scientific applications. We select Docker as the container-based technology for our test bed. We execute autodock3, a molecular modeling simulation software mostly used for Protein-ligand docking, in Docker containers and VMs created using OpenStack. We compare the execution times of the docking process in both Docker containers and in VMs.