S. K. Kortesis

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In this paper we study the partitioning and allocation of computations associated with the numerical solution of partial differential equations (PDEs). Strategies for the mapping of such computations to parallel MIMD architectures can be applied to different levels of the solution process. We introduce and study heuristic approaches defined on the(More)
Domain decomposition methods have proved to be an efficient approach for parallel processing of partial differential equations (PDEs) on parallel architectures. Their built in course grain parallelism makes them suitable for MIMD computing as a methodology to assure that the algebraic data are generated and distributed in different processors so that the(More)
We consider the partitioning of a workload defined over a discrete geometrical data Sb"Ucture in a way that balances it across multiple processors while minimizing the communication/synchronization among them. We fannulate this problem in the contex.t of the numerical solution of partial differential equations in distributed multiprocessor hardware(More)
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