Computational Grids lend themselves well to parameter sweep applications,which consist of independent tasks, each of which calculates results for a separate point in parameter space. However, it is possible for a parameter space to become so large as to pose prohibitive system requirements. In these cases, user-directed steering promises to reduce overall computation time. In this paper, we address an interesting challenge posed by these user-directed searches: how should compute resources be allocated to application tasks as the overall computation is being steered by the user? We present a model for user-directed searches, and then propose a number of resource allocation strategies and evaluate them in simulation. We find that prioritizing the assignments of tasks to compute resources throughout the search can lead to substantial performance improvements. We present experimental results obtained with software developed as part of the Virtual Instrument project, and discuss the impact of our findings on future Virtual Instrument implementations.
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