Dinanath Sulakhe, Alex Rodriguez, M. Wilde, Ian T Foster, N. Maltsev
{"title":"Using multiple grid resources for bioinformatics applications in GADU","authors":"Dinanath Sulakhe, Alex Rodriguez, M. Wilde, Ian T Foster, N. Maltsev","doi":"10.1109/CCGRID.2006.182","DOIUrl":null,"url":null,"abstract":"During the past decade, the scientific community has witnessed the rapid accumulation of gene sequence data and data related to physiology and biochemistry of organisms. Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. GADU is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run a job simultaneously on different grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual data system that helps in using heterogeneous grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid","PeriodicalId":419226,"journal":{"name":"Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGRID.2006.182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
During the past decade, the scientific community has witnessed the rapid accumulation of gene sequence data and data related to physiology and biochemistry of organisms. Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. GADU is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run a job simultaneously on different grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual data system that helps in using heterogeneous grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid