Abstract
The Deep Water Horizon well blowout on April 20th 2010 discharged between 40,000-1.2 million tons of crude oil into the Gulf of Mexico. In order to understand the fate and impact of the discharged oil, particularly on the environmentally sensitive Florida Keys region, we have implemented a multi-component application which consists of many individual tasks that utilize a distributed set of computational and data management resources. The application consists of two 3D ocean circulation models of the Gulf and South Florida and a 3D oil spill model. The ocean models used here resolve the Gulf at 2 km and the South Florida region at 900 m. This high resolution information on the ocean state is then integrated with the oil model to track the fate of approximately 10 million oil particles. These individual components execute as MPI based parallel applications on a 576 core IBM Power 5 cluster and a 5040 core Linux cluster, both operated by the Center for Computational Science, University of Miami. The data and workflow between is handled by means of a custom distributed software framework built around the Open Project for Networked Data Access Protocol (OPeNDAP). In this paper, we present this application as an example of Many Task Computing, report on the execution characteristics of this application, and discuss the challenges presented by the many task distributed workflow involving heterogeneous components. The application is a typical example from the ocean modeling and forecasting field and imposes soft timeliness and output quality constraints on top of the traditional performance requirements.