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Automatic and effective multi-dimensional parallelisation of structured mesh based codes

Automatic and effective multi-dimensional parallelisation of structured mesh based codes

Evans, E.W., Johnson, S.P., Leggett, P.F. and Cross, M. (2000) Automatic and effective multi-dimensional parallelisation of structured mesh based codes. Parallel Computing, 26 (6). pp. 677-703. ISSN 0167-8191 (doi:10.1016/S0167-8191(00)00004-1)

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Abstract

The most common parallelisation strategy for many Computational Mechanics (CM) (typified by Computational Fluid Dynamics (CFD) applications) which use structured meshes, involves a 1D partition based upon slabs of cells. However, many CFD codes employ pipeline operations in their solution procedure. For parallelised versions of such codes to scale well they must employ two (or more) dimensional partitions. This paper describes an algorithmic approach to the multi-dimensional mesh partitioning in code parallelisation, its implementation in a toolkit for almost automatically transforming scalar codes to parallel form, and its testing on a range of ‘real-world’ FORTRAN codes. The concept of multi-dimensional partitioning is straightforward, but non-trivial to represent as a sufficiently generic algorithm so that it can be embedded in a code transformation tool. The results of the tests on fine real-world codes demonstrate clear improvements in parallel performance and scalability (over a 1D partition). This is matched by a huge reduction in the time required to develop the parallel versions when hand coded – from weeks/months down to hours/days.

Item Type: Article
Uncontrolled Keywords: multi-dimensional partitioning, automatic code generation; NAS parallel benchmarks results, Industrial CFD code results
Subjects: Q Science > QA Mathematics > QA76 Computer software
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Science & Engineering Group
Related URLs:
Last Modified: 14 Oct 2016 08:59
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/256

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