SCIRun: a scientific programming environment for computational steering
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
An automatic design optimization tool and its application to computational fluid dynamics
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Resource Allocation for Steerable Parallel Parameter Searches
GRID '02 Proceedings of the Third International Workshop on Grid Computing
A Symbolic Approachto Modeling Cellular Behavior
HiPC '02 Proceedings of the 9th International Conference on High Performance Computing
Selective Buddy Allocation for Scheduling Parallel Jobs on Clusters
CLUSTER '02 Proceedings of the IEEE International Conference on Cluster Computing
An Integrated Problem Solving Environment: The SCIRun Computational Steering System
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 7 - Volume 7
Nimrod: a tool for performing parametrised simulations using distributed workstations
HPDC '95 Proceedings of the 4th IEEE International Symposium on High Performance Distributed Computing
Uintah: A Massively Parallel Problem Solving Environment
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
Grid resource management: state of the art and future trends
Grid resource management: state of the art and future trends
Methods for evaluating and covering the design space during early design development
Integration, the VLSI Journal
Distributed computing in practice: the Condor experience: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Sim-X: parallel system software for interactive multi-experiment computational studies
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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This paper presents a system deployed on parallel clusters to manage a collection of parallel simulations that make up a computational study. It explores how such a system can extend traditional parallel job scheduling and resource allocation techniques to incorporate knowledge specific to the study. Using a UINTAH-based helium gas simulation code (ARCHES) and the SimX system for multi-experiment computational studies, this paper demonstrates that, by using application-specific knowledge in resource allocation and scheduling decisions, one can reduce the run time of a computational study from over 20 hours to under 4.5 hours on a 32-processor cluster, and from almost 11 hours to just over 3.5 hours on a 64-processor cluster.