Abstract

Scientific applications often perform complex computational analyses that consume and produce large data sets. We are concerned with data placement policies that distribute data in ways that are advantageous for application execution, for example, by placing data sets so that they may be staged into or out of computations efficiently or by replicating them for improved performance and reliability. In particular, we propose to study the relationship between data placement services and workflow management systems. In this paper, we explore the interactions between two services used in large-scale science today. We evaluate the benefits of prestaging data using the Data Replication Service versus using the native data stage-in mechanisms of the Pegasus workflow management system. We use the astronomy application, Montage, for our experiments and modify it to study the effect of input data size on the …

Date

September 19, 2007

Authors

Ann Chervenak, Ewa Deelman, Miron Livny, Mei-Hui Su, Rob Schuler, Shishir Bharathi, Gaurang Mehta, Karan Vahi

Conference

2007 8th IEEE/ACM International Conference on Grid Computing

Pages

267-274

Publisher

IEEE