CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU

被引:6
|
作者
Mei, Gang [1 ,2 ]
Xu, Nengxiong [1 ]
机构
[1] China Univ Geosci Beijing, Sch Engn & Technol, Beijing 100083, Peoples R China
[2] Univ Freiburg, Inst Earth & Environm Sci, D-79104 Freiburg, Germany
基金
中国博士后科学基金;
关键词
computational geometry; computer aided engineering; multicore processing; parallel algorithms; parallel programming;
D O I
10.4316/AECE.2015.02005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:35 / 44
页数:10
相关论文
共 50 条
  • [1] CudaPre2D: A Straightforward Preprocessing Approach for Accelerating 2D Convex Hull Computations on the GPU
    Mei, Gang
    Guo, Sixu
    [J]. 2018 26TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, AND NETWORK-BASED PROCESSING (PDP 2018), 2018, : 726 - 732
  • [2] gHull: A GPU Algorithm for 3D Convex Hull
    Gao, Mingcen
    Thanh-Tung Cao
    Nanjappa, Ashwin
    Tan, Tiow-Seng
    Huang, Zhiyong
    [J]. ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2013, 40 (01):
  • [3] CudaHull: Fast parallel 3D convex hull on the GPU
    Stein, Ayal
    Geva, Eran
    El-Sana, Jihad
    [J]. COMPUTERS & GRAPHICS-UK, 2012, 36 (04): : 265 - 271
  • [4] CudaCHPre2D: A straightforward preprocessing approach for accelerating 2D convex hull computations on the GPU
    Qin, Jiayu
    Mei, Gang
    Cuomo, Salvatore
    Guo, Sixu
    Li, Yixuan
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2020, 32 (10):
  • [5] PARALLEL IMPLEMENTATION OF 3D CONVEX-HULL ALGORITHM
    DAY, AM
    [J]. COMPUTER-AIDED DESIGN, 1991, 23 (03) : 177 - 188
  • [6] An evaluation of GPU filters for accelerating the 2D convex hull
    Carrasco, Roberto
    Ferrada, Hector
    Navarro, Cristobal A.
    Hitschfeld, Nancy
    [J]. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2024, 184
  • [7] RELATIVE 3D POSITIONING AND 3D CONVEX-HULL COMPUTATION FROM A WEAKLY CALIBRATED STEREO PAIR
    ROBERT, L
    FAUGERAS, OD
    [J]. IMAGE AND VISION COMPUTING, 1995, 13 (03) : 189 - 196
  • [8] 2D grey-level convex hull computation:: A discrete 3D approach
    Nyström, I
    Borgefors, G
    di Baja, GS
    [J]. IMAGE ANALYSIS, PROCEEDINGS, 2003, 2749 : 763 - 770
  • [9] PATCH PEELING FROM 3D CONVEX HULL
    Pivee, Bostjan
    Zalik, Borut
    [J]. 10TH INTERNATIONAL MULTIDISCIPLINARY SCIENTIFIC GEOCONFERENCE: SGEM 2010, VOL I, 2010, : 1085 - 1092
  • [10] THE PARALLEL 3D CONVEX HULL PROBLEM REVISITED
    Amato, Nancy M.
    Preparata, Franco P.
    [J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL GEOMETRY & APPLICATIONS, 1992, 2 (02) : 163 - 173