2019
DOI: 10.1002/cpe.5229
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CudaCHPre2D: A straightforward preprocessing approach for accelerating 2D convex hull computations on the GPU

Abstract: An effective strategy for accelerating the calculation of convex hulls is to filter the input points by discarding interior points. In this paper, we present such a straightforward preprocessing approach by discarding the points locating in a convex polygon formed by 16 extreme points.Extreme points of a planar point set do not alter when all points are rotated with the same angle in the plane. Four groups of four extreme points with min or max x or y coordinates can be found for the original point set and thr… Show more

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Cited by 4 publications
(5 citation statements)
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“…At each rising clock edge, one point ID and corresponding real type x y coordinate values are read from the input point set. The coordinate values are multiplied by 2 20 and the integer values are given to the circuit by truncating the fractional part.…”
Section: Discussionmentioning
confidence: 99%
“…At each rising clock edge, one point ID and corresponding real type x y coordinate values are read from the input point set. The coordinate values are multiplied by 2 20 and the integer values are given to the circuit by truncating the fractional part.…”
Section: Discussionmentioning
confidence: 99%
“…Mei proposed a GPU-based solution [20] that utilizes a preprocessing approach to classify all points and discard those that do not belong to the convex hull in GPU. This preprocessing step resulted in a speedup of up to 6× over a Qhull implementation.…”
Section: Related Workmentioning
confidence: 99%
“…The most widely-used and efficient method for improving computational performance is eliminating interior points not candidates to the hull. However, many algorithms strongly depend on the input size, and preprocessing algorithms can significantly reduce the input size by ( ) discarding points irrelevant to the convex hull algorithm [23,24]. Mei has developed a filtering technique for computing the convex hull in 2D and 3D by first identifying 16 points on the convex hull through rotation of all points in GPU at three different angles and then discarding all points in parallel inside the polygon formed by these identified points.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Quin et al present a strategy for accelerating the calculation of convex hulls by filtering the interior points using GPUs. The key contribution is represented by the use of a complex polygon made up by many more extreme points with respect to related works, that lead to a speedup up to 14× in the best cases.…”
Section: Themes Of This Special Issuementioning
confidence: 99%