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GPU-Assisted Computation of Centroidal Voronoi Tessellation

机译:GPU辅助的质心Voronoi细分计算

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Centroidal Voronoi tessellations (CVT) are widely used in computational science and engineering. The most commonly used method is Lloyd's method, and recently the L-BFGS method is shown to be faster than Lloyd's method for computing the CVT. However, these methods run on the CPU and are still too slow for many practical applications. We present techniques to implement these methods on the GPU for computing the CVT on 2D planes and on surfaces, and demonstrate significant speedup of these GPU-based methods over their CPU counterparts. For CVT computation on a surface, we use a geometry image stored in the GPU to represent the surface for computing the Voronoi diagram on it. In our implementation a new technique is proposed for parallel regional reduction on the GPU for evaluating integrals over Voronoi cells.
机译:质心Voronoi镶嵌(CVT)在计算科学和工程中广泛使用。最常用的方法是劳埃德(Lloyd)方法,最近显示L-BFGS方法比劳埃德(Lloyd)方法计算CVT的速度更快。但是,这些方法在CPU上运行,对于许多实际应用而言仍然太慢。我们介绍了在GPU上实现这些方法以在2D平面和曲面上计算CVT的技术,并展示了这些基于GPU的方法在其CPU同类产品上的显着提速。对于表面上的CVT计算,我们使用存储在GPU中的几何图像来表示表面,以在其上计算Voronoi图。在我们的实现中,提出了一种新技术,用于在GPU上进行并行区域约简,以评估Voronoi单元上的积分。

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