GPU邻居搜索法在风沙流SPH算法中的应用  

APPLICATION OF GPU NEIGHBOR SEARCH ALGORITHM IN SPH ALGORITHM OF WIND-SAND FLOW

作　　者：周鹏 金阿芳[1] Zhou Peng;Jin Afang(School of Mechanical Engineering,Xinjiang University,Urumqi 830000,Xinjiang,China)

机构地区：[1]新疆大学机械工程学院,新疆乌鲁木齐830000

出　　处：《计算机应用与软件》2025年第3期221-226,267,共7页Computer Applications and Software

基　　金：国家自然科学基金项目(51968069)。

摘　　要：为了解决风沙流(Smoothed Particle Hydrodynamics,SPH)算法因粒子数目增多导致计算效率低的问题,将GPU并行计算应用在风沙流SPH算法中。分析SPH算法适合并行计算的原因,并以单元链表(Cell-Linked List,CLL)法的邻居搜索法为基础,建立SPH风沙流的并行计算模型;通过计算模型进行验证对坡面风场进行分析,得到沙粒水平速度沿高度变化规律和沙粒空间分布变化;对比不同粒子数目下四种风沙流SPH算法的计算效率,结果证明该算法可以提高计算效率。In order to solve the problem of low computational efficiency caused by the increase in the number of particles in the smoothed particle hydrodynamics(SPH)algorithm of wind-sand flow,GPU parallel computing is applied to the SPH algorithm of wind-sand flow.The reason why SPH algorithm was suitable for parallel computing was analyzed.Based on the neighbor search method of cell-linked list(CLL)method,the parallel computing model of SPH wind-sand flow was established.Through the verification of the calculation model,the slope field was analyzed,and the variation law of sand horizontal velocity along the height and the change of sand spatial distribution were obtained.The computational efficiency of the four wind-sand flow SPH algorithms under different particle numbers was compared.The results show that the proposed algorithm can improve the computational efficiency.

关 键 词：SPH算法 风沙流 并行计算 CUDA 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]