CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU
In the calculating of convex hulls for point sets, a preprocessing procedure that is to filter the input points by discarding non-extreme points is commonly used to improve the computational efficiency. We previously proposed a quite straightforward preprocessing approach for accelerating 2D conv...
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Stefan cel Mare University of Suceava
2015-05-01
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Online Access: | http://dx.doi.org/10.4316/AECE.2015.02005 |
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doaj-1b4ad6c6d2434b3ba94984136d96d5ad2020-11-24T22:55:58ZengStefan cel Mare University of SuceavaAdvances in Electrical and Computer Engineering1582-74451844-76002015-05-01152354410.4316/AECE.2015.02005CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPUMEI, G.XU, N.In the calculating of convex hulls for point sets, a preprocessing procedure that is to filter the input points by discarding non-extreme points is commonly used to improve the computational efficiency. We previously proposed a quite straightforward preprocessing approach for accelerating 2D convex hull computation on the GPU. In this paper, we extend that algorithm to being used in 3D cases. The basic ideas behind these two preprocessing algorithms are similar: first, several groups of extreme points are found according to the original set of input points and several rotated versions of the input set; then, a convex polyhedron is created using the found extreme points; and finally those interior points locating inside the formed convex polyhedron are discarded. Experimental results show that: when employing the proposed preprocessing algorithm, it achieves the speedups of about 4x on average and 5x to 6x in the best cases over the cases where the proposed approach is not used. In addition, more than 95 percent of the input points can be discarded in most experimental tests.http://dx.doi.org/10.4316/AECE.2015.02005computational geometrycomputer aided engineeringmulticore processingparallel algorithmsparallel programming |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
MEI, G. XU, N. |
spellingShingle |
MEI, G. XU, N. CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU Advances in Electrical and Computer Engineering computational geometry computer aided engineering multicore processing parallel algorithms parallel programming |
author_facet |
MEI, G. XU, N. |
author_sort |
MEI, G. |
title |
CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU |
title_short |
CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU |
title_full |
CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU |
title_fullStr |
CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU |
title_full_unstemmed |
CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU |
title_sort |
cudapre3d: an alternative preprocessing algorithm for accelerating 3d convex hull computation on the gpu |
publisher |
Stefan cel Mare University of Suceava |
series |
Advances in Electrical and Computer Engineering |
issn |
1582-7445 1844-7600 |
publishDate |
2015-05-01 |
description |
In the calculating of convex hulls for point sets, a preprocessing procedure that is to filter
the input points by discarding non-extreme points is commonly used to improve the computational
efficiency. We previously proposed a quite straightforward preprocessing approach for accelerating
2D convex hull computation on the GPU. In this paper, we extend that algorithm to being used in
3D cases. The basic ideas behind these two preprocessing algorithms are similar: first, several
groups of extreme points are found according to the original set of input points and several
rotated versions of the input set; then, a convex polyhedron is created using the found
extreme points; and finally those interior points locating inside the formed convex polyhedron
are discarded. Experimental results show that: when employing the proposed preprocessing algorithm,
it achieves the speedups of about 4x on average and 5x to 6x in the best cases over the cases where
the proposed approach is not used. In addition, more than 95 percent of the input points can be
discarded in most experimental tests. |
topic |
computational geometry computer aided engineering multicore processing parallel algorithms parallel programming |
url |
http://dx.doi.org/10.4316/AECE.2015.02005 |
work_keys_str_mv |
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