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A Graph Partitioning Algorithm for Parallel Agent-Based Road Traffic Simulation

机译:一种基于代理的道路交通仿真的曲线图分区算法

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A common approach of parallelising an agent-based road traffic simulation is to partition the road network into sub- regions and assign computations for each subregion to a logical process (LP). Inter-process communication for synchronisation between the LPs is one of the major factors that affect the performance of parallel agent-based road traffic simulation in a distributed memory environment. Synchronisation overhead, i.e., the number of messages and the communication data volume exchanged between LPs, is heavily dependent on the employed road network partitioning algorithm. In this paper, we propose Neighbour-Restricting Graph-Growing (NRGG), a partitioning algorithm which tries to reduce the required communication between LPs by minimising the number of neighbouring partitions. Based on a road traffic simulation of the city of Singapore, we show that our method not only outperforms graph partitioning methods such as METIS and Buffoon, for the synchronisation protocol used, but also is more resilient than stripe spatial partitioning when partitions are cut more finely.
机译:并行化基于代理的道路交通仿真的常见方法是将道路网络分配到子区域并将每个子区域分配给逻辑过程(LP)的计算。 LPS之间同步的过程间通信是影响分布式内存环境中并行代理的道路流量模拟的性能的主要因素之一。同步开销,即LPS之间交换的消息数量和通信数据量,严重依赖于所采用的道路网络分区算法。在本文中,我们提出了邻居限制的图形生长(NRGG),这是一种分区算法,它通过最小化相邻分区的数量来减少LPS之间所需的通信。基于新加坡市的道路交通仿真,我们表明我们的方法不仅优于Metis和Bufeoon等图形分区方法,对于所使用的同步协议,而且除了更精细的分区时也比条纹空间分区更具弹性。 。

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