Large-scale Geometric Data Processing and Structured Mesh Generation - Yu, Wuyi;Li, Xin
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This work studies the effective generation of structural mesh on large and complex geometric data. We study a general geometric computation paradigm to solve this problem via model partitioning and divide-and-conquer. To apply effective divide-and-conquer, we study two key technical components: the shape decomposition in the divide stage, and the results demonstrate the efficiency and effectiveness of our framework. The comparisons also show our algorithm outperforms existing partitioning methods in final meshing quality. We also show our pipeline scales up efficiently on HPC environment.

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Produktbeschreibung
This work studies the effective generation of structural mesh on large and complex geometric data. We study a general geometric computation paradigm to solve this problem via model partitioning and divide-and-conquer. To apply effective divide-and-conquer, we study two key technical components: the shape decomposition in the divide stage, and the results demonstrate the efficiency and effectiveness of our framework. The comparisons also show our algorithm outperforms existing partitioning methods in final meshing quality. We also show our pipeline scales up efficiently on HPC environment.
Autorenporträt
Wuyi Yu received his B.S. degree in automation from Xiamen University, China and Ph.D. degree in Computer Science from Louisiana State University. His research interests include Geometric Data Modeling/Processing, Computer Graphics, Computer-aided Design, Vision, and Visualization. Wuyi Yu is now working at Google.