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.
Revised: October 9, 2008 |
Published: July 24, 2008
Citation
Nieplocha J., S. Krishnamoorthy, M. Valiev, M. Krishnan, B.J. Palmer, and P. Sadayappan. 2008.Integrated Data and Task Management for Scientific Applications. In Proceedings of ICCS: Lecture Notes in Computer Science, 5101, 20-31. Berlin:Springer-Verlag.PNNL-SA-59937.doi:10.1007/978-3-540-69384-0_6