The parawise expert assistant – widening accessibility to efficient and scalable tool generated OpenMP code

Authors:
Stephen Johnson;Emyr Evans;Haoqiang Jin;Constantinos Ierotheou
Affiliations:
Parallel Processing Research Group, University of Greenwich, London, UK;Parallel Processing Research Group, University of Greenwich, London, UK;NAS Division, NASA Ames Research Center, Moffet Field;Parallel Processing Research Group, University of Greenwich, London, UK
Venue:
WOMPAT'04 Proceedings of the 5th international conference on OpenMP Applications and Tools: shared Memory Parallel Programming with OpenMP
Year:
2004

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Abstract

Despite the apparent simplicity of the OpenMP directive shared memory programming model and the sophisticated dependence analysis and code generation capabilities of the ParaWise/CAPO tools, experience shows that a level of expertise is required to produce efficient parallel code. In a real world application the investigation of a single loop in a generated parallel code can soon become an in-depth inspection of numerous dependencies in many routines. The additional understanding of dependencies is also needed to effectively interpret the information provided and supply the required feedback. The ParaWise Expert Assistant has been developed to automate this investigation and present questions to the user about, and in the context of, their application code. In this paper, we demonstrate that knowledge of dependence information and OpenMP are no longer essential to produce efficient parallel code with the Expert Assistant. It is hoped that this will enable a far wider audience to use the tools and subsequently, exploit the benefits of large parallel systems.