Managing Large-Scale Scientific Computing in Ensemble Prediction Using BPEL

Abstract

The development of large-scale parallel scientific computing applications has put forward more urgent demands for powerful computing capacities and complex process managing technologies. Meanwhile, the scientific experiment processes become more and more complicated which makes it becomes a hard work for e-scientists to control the experiment analysis processes by hand. In this paper, we provide a scientific workflow system called EPSWFlow for the escientists in climate domain for services composition and workflow orchestration. In order to integrate the large number of the existing legacy applications into the system, we provide a service wrapping method and a unified interface for the workflow users to access to the services. The workflow system can process the experiment process dynamically and manage the heterogeneous grid resources transparently.