Supporting Dynamic Data and Processor Repartitioning for Irregular Applications

Recent research has shown that dynamic reconfiguration of resources allocated to parallel applications can improve both system utilization and application throughput. Distributed Resource Management System (DRMS) is a parallel programming environment that supports development and execution of reconfigurable applications on a dynamically varying set of resources. This paper describes DRMS support for developing reconfigurable irregular applications, using a sparse Cholesky factorization as a model application. We present performance levels achieved by DRMS redistribution primitives, which show that the cost of dynamic data redistribution between different processor configurations for irregular data are comparable to those for regular data.

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