Supporting Dynamic Data and Processor Repartitioning for Irregular Applications

Recent research has shown that both system utilization and application throughput improves in parallel programming environments where resources allocated to applications can be reconfigured dynamically at run-time. We have implemented the Distributed Resource Management System (DRMS) that supports the program development and execution of reconfigurable applications in time-varying resource environments. This paper describes DRMS support for writing reconfigurable irregular applications. We use a sparse Cholesky factorization algorithm as a model irregular application. We present, for this application, performance levels achieved by the DRMS dynamic data redistribution primitives. The results show that the cost for dynamic data redistribution between different processor configurations for irregular data are comparable to those for regular data.

By: Jose E. Moreira, Kalluri Eswar, Ravi B. Konuru and Vijay K. Naik

Published in: RC20426 in 1996


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