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.

中文翻译：

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共享内存多处理器上的并行数据分布管理

在基于代理的模拟研究的背景下，识别两组 d 维轴平行矩形之间的交叉点的问题经常出现。为此，高级架构 (HLA) 规范——模拟器间互操作性的标准框架——包括数据分布管理 (DDM) 服务，其职责是报告一组订阅和更新区域之间的所有交集。DDM 服务的核心算法是 CPU 密集型的，可以极大地受益于现代多核处理器的强大计算能力。在本文中，我们针对 DDM 问题提出了两种并行解决方案，它们可以在共享内存多处理器上有效运行。第一个解决方案基于一种数据结构（间隔树），它允许并发计算订阅和更新区域之间的交集。第二种解决方案基于基于排序匹配算法的新颖并行扩展，其顺序版本被认为是 DDM 问题的最有效解决方案之一。对所提出算法的广泛实验评估证实了它们在利用共享内存架构中的多个执行单元方面的有效性。