Condor-G: A Computation Management Agent for Multi-Institutional Grids
Cluster Computing
SPICE: Simulated Pore Interactive Computing Environment
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Design and Implementation of Network Performance Aware Applications Using SAGA and Cactus
E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
Distributed Replica-Exchange Simulations on Production Environments Using SAGA and Migol
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
Proceedings of the second international workshop on Emerging computational methods for the life sciences
Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery
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The Simple API for Grid Applications (SAGA) can be used to develop a range of applications which are in turn composed of multiple sub-tasks. In particular SAGA is an effective tool for coordinating and orchestrating the many sub-tasks of such applications, whilst keeping the application agnostic to the details of the infrastructure used. Although developed primarily in the context of distributed applications, SAGA provides an equally valid approach for applications with many sub-tasks on single high-end supercomputers, such as emerging peta-scale computers. Specifically, in this paper we describe how SAGA has been used to develop applications from two types of applications: the first with loosely-coupled homogeneous sub-tasks and, applications with loosely-coupled heterogeneous sub-tasks. We also analyse and contrast the coupling and scheduling requirements of the sub-tasks for these two applications. We find that applications with multiple sub-tasks often have dynamic characteristics, and thus require support for both infrastructure-independent programming models and agile execution models. Hence attention must be paid to the practical deployment challenges along with the theoretical advances in the development of infrastructure-independent applications.