Abstract
Computational Grids lend themselves well to parameter sweep applications, in which independent tasks calculate results for points in a parameter space. 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.
This work was supported by the National Science Foundation under Award ACI-0086092.
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Faerman, M., Birnbaum, A., Casanova, H., Berman, F. (2002). Resource Allocation for Steerable Parallel Parameter Searches. In: Parashar, M. (eds) Grid Computing — GRID 2002. GRID 2002. Lecture Notes in Computer Science, vol 2536. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36133-2_14
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DOI: https://doi.org/10.1007/3-540-36133-2_14
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