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作 者:张晓蓉 陈浩[1,2] 陈呈 李学俊 吴亚东[3] ZHANG Xiaorong;CHEN Hao;CHEN Cheng;LI Xuejun;WU Yadong(Southwest University of Science and Technology,Mianyang 621010;Institute of Computational Aerodynamics,China Aerodynamics Research and Development Center,Mianyang 621010;Sichuan University of Science and Engineering,Zigong 643000)
机构地区:[1]西南科技大学,绵阳621010 [2]中国空气动力研究与发展中心计算空气动力研究所,绵阳621010 [3]四川轻化工大学,自贡643000
出 处:《计算机与数字工程》2024年第8期2245-2251,2278,共8页Computer & Digital Engineering
基 金:国家数值风洞工程项目(编号:NNW2019ZT6-A17);国家自然科学基金项目(编号:61872304,61802320)资助。
摘 要:流线是矢量场可视化最具表现力的方法之一。随着计算机硬件和计算方法的发展,流场数据规模日趋增大,传统的流线算法在数据加载与积分计算存在瓶颈,导致算法效率低。开源的vtk-m算法库中提供的流线算法将积分任务划分为基本任务单元,理论上可调用海量线程并行处理,算法性能虽有提升,但在实践研究中发现并行效率低。针对这一问题,提出了基于动态结点树的并行流线可视化优化算法。主要通过粗粒度和细粒度两次划分,并行构建动态结点树对数据进行组织管理,利用索引关系缩小积分备选区域,实现对网格单元的快速定位;其次使用数据属性抽取与种子点任务并行执行等方法在算法其他环节进行优化,减小程序内存需求并提高对计算资源的利用率。在不同规模数据集下的实验结果表明优化后算法的有效性。Streamlines are one of the most illuminating techniques to achieve fundamental goal of scientific insight from resulting numerical simulations.Due to the large scale of the flow field data,the traditional streamline algorithm is inefficient,resulting in a slow visualization process.Although the performance of the streamline algorithm provided in the open source vtk-m has been improved,the parallel efficiency is low under multithreading.To solve this problem,a parallel streamline visualization optimization algorithm based on dynamic node tree is proposed.Mainly through two divisions of coarse-grained and fine-grained,parallel construction of dynamic node tree to organize and manage data,and the index structure is established to conveniently narrow the alternative areas in the integration process.To reduce memory requirements of streamline integration by the methods of data blocks attribute extraction and employ parallel execution of seed integral tasks to leverage multi-core computing resources.The experimental results under different scale data sets show the effectiveness of the optimized algorithm.
分 类 号:TP399[自动化与计算机技术—计算机应用技术]
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