摘要
本文在CUDA框架下设计与实现基于GPU的晶格Boltzmann方法(LBM)的并行算法。为进一步提高计算效率,本文分别研究几种典型的优化策略对计算效率的影响,并给出了一种集多优化策略为一体的综合优化解决方案。以圆管内Poiseuille流为算例的实验表明,采用新综合优化方案设计的LBM并行算法能够获得更高的计算效率。
In this paper,a parallel algorithm for lattice Boltzmann method（LBM） is implemented based on GPU in the CUDA framework.In order to improve the efficiency of the algorithm,several typical optimization strategies are investigated,and a new comprehensive optimization solution is obtained.The results of numerical experiments on 3-D Poiseuille flows in a tube show that the LBM parallel algorithm designed with the new optimal solution is much more efficient than those from existing optimal solutions.
出处
《广西师范大学学报（自然科学版）》
CAS
北大核心
2012年第3期142-148,共7页
Journal of Guangxi Normal University:Natural Science Edition
基金
国家自然科学基金资助项目(11162002)
