A Scalable Strategy for the Parallelization of Multiphysics Unstructured Mesh-Iterative Codes on Distributed-Memory Systems

Authors:
Kevin Mcmanus;Mark Cross;Chris Walshaw;Steve Johnson;Peter Leggett
Affiliations:
Centre for Numerical Modelling and Process Analysis, University of Greenwich, London;Centre for Numerical Modelling and Process Analysis, University of Greenwich, London;Centre for Numerical Modelling and Process Analysis, University of Greenwich, London;Centre for Numerical Modelling and Process Analysis, University of Greenwich, London;Centre for Numerical Modelling and Process Analysis, University of Greenwich, London
Venue:
International Journal of High Performance Computing Applications
Year:
2000

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Abstract

Realizing scalable performance on high performance computing systems is not straightforward for single-phenomenon codes (such as computational fluid dynamics [CFD]). This task is magnified considerably when the target software involves the interactions of a range of phenomena that have distinctive solution procedures involving different discretization methods. The problems of addressing the key issues of retaining data integrity and the ordering of the calculation procedures are significant. A strategy for parallelizing this multiphysics family of codes is described for software exploiting finite-volume discretization methods on unstructured meshes using iterative solution procedures. A mesh partitioning-based SPMD approach is used. However, since different variables use distinct discretization schemes, this means that distinct partitions are required; techniques for addressing this issue are described using the mesh-partitioning tool, JOSTLE. In this contribution, the strategy is tested for a variety of test cases under a wide range of conditions (e.g., problem size, number of processors, asynchronous/synchronous communications, etc.) using a variety of strategies for mapping the mesh partition onto the processor topology.