Workload decomposition strategies for hierarchical distributed-shared memory parallel systems and their implementation with integration of high-level parallel languages

In this paper we address the issue of workload decomposition in programming hierarchical distributed‐shared memory parallel systems. The workload decomposition we have devised consists of a two‐stage procedure: a higher‐level decomposition among the computational nodes; and a lower‐level one among t...

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Bibliographic Details
Published in:Concurrency and computation 2002-08, Vol.14 (11), p.933-956
Main Authors: Briguglio, Sergio, Di Martino, Beniamino, Vlad, Gregorio
Format: Article
Language:English
Subjects:
clusters of symmetric multiprocessors
distributed-shared memory parallel systems
High-Performance Fortran
OpenMP
workload balancing
workload decomposition
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Summary:In this paper we address the issue of workload decomposition in programming hierarchical distributed‐shared memory parallel systems. The workload decomposition we have devised consists of a two‐stage procedure: a higher‐level decomposition among the computational nodes; and a lower‐level one among the processors of each computational node. By focusing on porting of a case study particle‐in‐cell application, we have implemented the described work decomposition without large programming effort by using and integrating the high‐level language extensions High‐Performance Fortran and OpenMP. Copyright © 2002 John Wiley & Sons, Ltd.
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.702