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Old 03-12-12, 09:00 AM   #1
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Post GPU accelerated Convex Hull Computation

Abstract:
We present a hybrid algorithm to compute convex hull of points in three and higher dimensional spaces. Our formulation uses a GPU-based interior point filter to cull away many of the points that do not belong to the boundary. The convex hull of remaining points is computed on the CPU. The GPU-based filter proceeds in an incremental manner and computes a pseudo-hull that is contained inside the convex hull of the original points. The pseudo-hull computation involves only localized operations and therefore, maps well to GPU architectures. Furthermore, the underlying approach extends to high dimensional point sets and deforming points. In practice, our culling filter can reduce the number of candidate points by two orders of magnitude. We have implemented the hybrid algorithm on commodity GPUs, and evaluated its performance on several large point sets. In practice, the GPU-based filtering algorithm can cull up to 85M interior points per second on NVIDIA GeForce GTX 580 and the hybrid algorithm improves the overall performance of convex hull computation by 10-27 times (for static point sets) and 22-46 times (for deforming point sets).

(Min Tang, Jie-yi Zhao, Ruofeng Tong, and Dinesh Manocha: 'GPU accelerated Convex Hull Computation', accepted by SMI'2012. [WWW] [PREPRINT])



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