Abstract
Robust and efficient Cartesian mesh generation for large-scale scene is of great significance for fluid dynamics simulation and collision detection. High-quality and large-scale mesh generation task in a personal computer is hard to achieve. In this paper, a parallel Cartesian mesh generation algorithm based on graphics processing unit (GPU) is proposed. The proposed algorithm is optimized based on the traditional ray casting method in computer graphics, and is more efficient and stable for large-scale Cartesian mesh generation. In the process of mesh generation, the geometries represented by triangular facets are transformed into a mesh composed of orthogonal hexahedrons. A parallel ray generation method is proposed to reduce the data exchange between the host memory and device memory. A parallel primitives searching method based on lattice grid is adopted to search the triangular facets for intersection calculation between rays and triangles. The parallel Cartesian mesh generation algorithm has been implemented using CUDA library. The performance of parallel Cartesian mesh generation algorithm has been promoted enormously compared with the traditional the sequential algorithm, which is shown in different numerical experiments. Through some tests, the performance of parallel algorithm is analyzed, and the results show that the parallel computing power of the GPU is fully utilized. Finally, examples of Cartesian mesh generation are presented.
Funder
National Natural Science Foundation of China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
4 articles.
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