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Parallel Sort-Based Matching for Data Distribution Management on Shared-Memory Multiprocessors



In this paper we consider the problem of identifying intersections between two sets of d-dimensional axis-parallel rectangles. This is a common problem that arises in many agent-based simulation studies, and is of central importance in the context of High Level Architecture (HLA), where it is at the core of the Data Distribution Management (DDM) service. Several realizations of the DDM service have been proposed; however, many of them are either inefficient or inherently sequential. These are serious limitations since multicore processors are now ubiquitous, and DDM algorithms – being CPU-intensive – could benefit from additional computing power. We propose a parallel version of the Sort-Based Matching algorithm for shared-memory multiprocessors. Sort-Based Matching is one of the most efficient serial algorithms for the DDM problem, but is quite difficult to parallelize due to data dependencies. We describe the algorithm and compute its asymptotic running time; we complete the analysis by assessing its performance and scalability through extensive experiments on two commodity multicore systems based on a dual socket Intel Xeon processor, and a single socket Intel Core i7 processor.


  • Data Distribution Management; High Level Architecture; Parallel Algorithms; Sort-Based Matching


Best Paper Award: IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2017), oct 18—20, 2017, Rome, Italy.



  • All the source code and the scripts used in the paper (plus the raw data obtained by the experiments) is available for download.
parallelsbm-paper.1579249383.txt.gz · Last modified: 2020/01/17 08:23 by gda

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