A Block Iteration with Parallelization Method for the Greedy Selection in Radial Basis Functions Based Mesh Deformation
A Block Iteration with Parallelization Method for the Greedy Selection in Radial Basis Functions Based Mesh Deformation
复制标题
基于径向基函数的网格变形贪婪选择的并行化分块迭代方法
DOI：
10.3390/app9061141
复制
发表时间：
2019
影响因子：
2.7
通讯作者：
Yang Canqun
中科院分区：
文献类型：
--
作者：
Zhao Ran;Li Chao;Guo Xiaowei;Fan Sijiang;Wang Yi;Yang Canqun
贪心算法是基于径向基函数的网格变形中重要的点选择方法之一。然而，在大规模网格中，传统的贪婪选择会产生昂贵的时间消耗和性能损失。为了加快点选择的计算速度，本文提出了一种并行化的块迭代方法。通过块迭代法，将贪心选择的三个步骤的计算复杂度都从O （n 3）降低到O （n 2）。此外，贪婪选择中两步的并行化将边界点划分为子核，有效地加快了过程。以三维波动鱼、ONERA M6机翼和三维超空泡水翼3种典型模型为例进行了验证，结果表明，该方法的性能比传统方法提高了17.41倍。
Greedy algorithm is one of the important point selection methods in the radial basis function based mesh deformation. However, in large-scale mesh, the conventional greedy selection will generate expensive time consumption and result in performance penalties. To accelerate the computational procedure of the point selection, a block iteration with parallelization method is proposed in this paper. By the block iteration method, the computational complexities of three steps in the greedy selection are all reduced from O ( n 3 ) to O ( n 2 ) . In addition, the parallelization of two steps in the greedy selection separates boundary points into sub-cores, efficiently accelerating the procedure. Specifically, three typical models of three-dimensional undulating fish, ONERA M6 wing and three-dimensional Super-cavitating Hydrofoil are taken as the test cases to validate the proposed method and the results show that it improves 17.41 times performance compared to the conventional method.