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The semi-automatic parallelisation of scientific application codes using a computer aided parallelisation toolkit

The semi-automatic parallelisation of scientific application codes using a computer aided parallelisation toolkit

Ierotheou, C.S., Johnson, S.P., Leggett, P.F., Cross, M., Evans, E.W., Jin, H., Frumkin, M. and Yan, J. (2001) The semi-automatic parallelisation of scientific application codes using a computer aided parallelisation toolkit. Scientific Programming, 9 (2-3). pp. 163-173. ISSN 1058-9244 (Print), 1875-919X (Online)

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Abstract

The shared-memory programming model can be an effective way to achieve parallelism on shared memory parallel computers. Historically however, the lack of a programming standard using directives and the limited scalability have affected its take-up. Recent advances in hardware and software technologies have resulted in improvements to both the performance of parallel programs with compiler directives and the issue of portability with the introduction of OpenMP. In this study, the Computer Aided Parallelisation Toolkit has been extended to automatically generate OpenMP-based parallel programs with nominal user assistance. We categorize the different loop types and show how efficient directives can be placed using the toolkit's in-depth interprocedural analysis. Examples are taken from the NAS parallel benchmarks and a number of real-world application codes. This demonstrates the great potential of using the toolkit to quickly parallelise serial programs as well as the good performance achievable on up to 300 processors for hybrid message passing-directive parallelisations.

Item Type: Article
Uncontrolled Keywords: parallel programming, shared memory, OpenMP, distributed memory, message passing, CAPTools, semi-automatic parallelisation tools
Subjects: Q Science > QA Mathematics
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
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Systems Technology
Related URLs:
Last Modified: 14 Oct 2016 09:01
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/742

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