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Parallel Data Distribution Management on Shared-Memory Multiprocessors



The problem of identifying intersections between two sets of d-dimensional axis-parallel rectangles appears frequently in the context of agent-based simulation studies. For this reason, the High Level Architecture (HLA) specification – a standard framework for interoperability among simulators – includes a Data Distribution Management (DDM) service whose responsibility is to report all intersections between a set of subscription and update regions. The algorithms at the core of the DDM service are CPU-intensive, and could greatly benefit from the large computing power of modern multi-core processors. In this paper we propose two parallel solutions to the DDM problem that can operate effectively on shared-memory multiprocessors. The first solution is based on a data structure (the Interval Tree) that allows concurrent computation of intersections between subscription and update regions. The second solution is based on a novel parallel extension of the Sort Based Matching algorithm, whose sequential version is considered among the most efficient solutions to the DDM problem. Extensive experimental evaluation of the proposed algorithms confirm their effectiveness on taking advantage of multiple execution units in a shared-memory architecture.


  • Data Distribution Management (DDM), Parallel And Distributed Simulation (PADS), High Level Architecture (HLA), Parallel Algorithms


  • Published: “ACM Transactions on Modeling and Computer Simulation (TOMACS), Vol. 30, No. 1, Article 5. ACM, February 2020. ISSN: 1049-3301”.


  • The author's version of the article can be found on 1911.03456.


  • All the source code used in the paper is available for download.
parallelddm-paper.txt · Last modified: 2020/02/26 10:10 by gda

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