Affiliations: Parallel Processing Research Group, University of
Greenwich, London SE10 9LS, UK. E-mail: {c.ierotheou, s.johnson, p.leggett,
m.cross, e.w.evans}@gre.ac.uk | NAS Systems Division, NASA Ames Research Center,
Moffett Field, CA, USA. E-mail: {hjin, frumkin}@nas.nasa.gov,
[email protected]
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.
