一种基于共享存储的并行层次兴趣匹配算法  

A Shared Memory Based Parallel Hierarchical Interest Matching Algorithm

作　　者：唐文杰 程俊玮 姚益平[1] 朱峰 Tang Wenjie;Cheng Junwei;Yao Yiping;Zhu Feng(College of Systems Engineering,National University of Defense Technology,Changsha 410073,China)

机构地区：[1]国防科技大学系统工程学院,湖南长沙410073

出　　处：《系统仿真学报》2021年第5期1086-1094,共9页Journal of System Simulation

基　　金：国家自然科学基金(61702527,61903368)。

摘　　要：兴趣匹配在分布式仿真中扮演着重要的角色。然而,在大规模仿真场景中,仿真实体数量大且区域变化频繁,导致兴趣匹配的计算量很大,严重影响仿真性能。另一方面,多核处理器的普及也促使从并行视角来提升兴趣匹配算法的性能。针对上述问题,提出了一种并行层次兴趣匹配算法,将订阅区域映射到一棵满二叉树中,由更新区域并行地与二叉树进行匹配,并利用二叉树相邻节点的区域关联关系来剔除不必要的计算。实验结果表明:并行层次兴趣匹配算法具有较好的可扩展性,且能够有效提升兴趣匹配的效率。Interest matching plays an important role in distributed simulation.However,because of huge number of simulation entities and frequent change of regions,interest matching consumes tremendous computation in large scale simulations.The ubiquity of multicore urges us to improve the performance of interest matching by parallelization.A shared memory based parallel hierarchical interest matching algorithm is propose to solve the problem.It maps subscribe regions into a full binary tree,and compares update regions with the tree in parallel.Due to the associative relationship between adjacent nodes,unnecessary comparisons can be eliminated.The experimental results demonstrate that the proposed algorithm has good scalability and can effectively improve the efficiency of interest matching.

关 键 词：兴趣匹配 并行算法 分布式仿真 基于排序的匹配 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]