Abstract
We develop a distributed poly-square mapping algorithm for large-scale 2D geometric regions, which is suitable for generating huge quadrilateral meshes in parallel using computer clusters. Our approach adopts a divide-and-conquer strategy based on domain decomposition. We first partition the data into solvable subregions, balancing their size, geometry, and communication cost; then, poly-square maps will be solved on subregions; these maps are finally merged and optimized globally through a multi-pass optimization algorithm. We demonstrate that our meshing framework can handle very big and complex geometric datasets using high performance clusters efficiently and generate high-quality semi-structured quad meshes.
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