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Parallel mesh simplification using embedded tree collapsing

机译:使用嵌入式树折叠的并行网格简化

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We present a novel parallel algorithm for mesh simplification that can reduce an input triangle mesh with highly improved performance. To take full advantage of the GPU comprising many computing cores, we enable collapsing of connected edges to be processed at one time by breaking data dependency in the update of the mesh data structure. Our solution is a lazy update method, which temporarily stores edge update information in a table and then updates the mesh data with it in the next step. Thanks to the lazy update method, we can more freely choose a large number of edges in the form of small trees for collapsing. The constructed trees are split to satisfy an error constraint, prevent normal flipping, and preserve the mesh topology. In experiments performed on several test models of various scales, we found that our algorithm consistently outperformed the prior GPU algorithm of Papageorgiou and Platis (Vis Comput 31(2):235-244, 2015) by a factor of 10 or higher.
机译:我们提出了一种新颖的并行算法来简化网格,可以减少输入三角形网格,从而大大提高性能。为了充分利用包含许多计算核心的GPU,我们通过打破网格数据结构更新中的数据依赖关系,使连接边缘的折叠一次得以处理。我们的解决方案是一种惰性更新方法,该方法将边缘更新信息临时存储在表中,然后在下一步中使用它更新网格数据。由于采用了惰性更新方法,我们可以自由选择小树形式的大量边缘进行折叠。分割构造的树,以满足错误约束,防止法线翻转,并保留网格拓扑。在各种规模的几个测试模型上进行的实验中,我们发现我们的算法始终比Papageorgiou和Platis的现有GPU算法(Vis Comput 31(2):235-244,2015)始终高出10倍或更高。

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