Integrated Data and Task Management for Scientific Applications

Authors:
Jarek Nieplocha;Sriram Krishamoorthy;Marat Valiev;Manoj Krishnan;Bruce Palmer;P. Sadayappan
Affiliations:
Pacific Northwest National Laboratory, Richland, USA WA 99352;Pacific Northwest National Laboratory, Richland, USA WA 99352;Pacific Northwest National Laboratory, Richland, USA WA 99352;Pacific Northwest National Laboratory, Richland, USA WA 99352;Pacific Northwest National Laboratory, Richland, USA WA 99352;The Ohio State University, Columbus, USA OH 43210
Venue:
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Year:
2008

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Abstract

Several emerging application areas require intelligent management of distributed data and tasks that encapsulate execution units for collection of processors or processor groups. This paper describes an integration of data and task parallelism to address the needs of such applications in context of the Global Array (GA) programming model. GA provides programming interfaces for managing shared arrays based on non-partitioned global address space programming model concepts. Compatibility with MPI enables the scientific programmer to benefit from performance and productivity advantages of these high level programming abstractions using standard programming languages and compilers.