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Parallel Data Distribution Management on Shared-memory Multiprocessors

机译：共享内存多处理器上的并行数据分发管理

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摘要

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 article, 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.
机译：识别两组d维轴平行矩形之间的交集的问题在基于代理的模拟研究中经常出现。因此，高级体系结构（HLA）规范（模拟器之间互操作性的标准框架）包括数据分发管理（DDM）服务，该服务负责报告一组订阅和更新区域之间的所有交集。 DDM服务的核心算法占用大量CPU，并且可以从现代多核处理器的强大计算能力中受益匪浅。在本文中，我们为DDM问题提出了两个并行解决方案，它们可以在共享内存多处理器上有效运行。第一种解决方案基于数据结构（间隔树），该数据结构允许并发计算订阅区域和更新区域之间的交集。第二种解决方案基于“基于排序的匹配”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共享内存体系结构中利用多个执行单元的有效性。

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