6774

A 3D Convex Hull Algorithm for Graphics Hardware

Mingcen Gao, Thanh-Tung Cao, Tiow-Seng Tan, Zhiyong Huang
National University of Singapore
National University of Singapore, Technical Report, 2011
@article{gao20113d,

   title={A 3D Convex Hull Algorithm for Graphics Hardware},

   author={Gao, M. and Cao, T.T. and Tan, T.S. and Huang, Z.},

   year={2011}

}

Download Download (PDF)   View View   Source Source   Source codes Source codes

Package:

851

views

This report presents a novel approach, termed gHull, to compute the convex hull for a given point set in R3 using the graphics processing units (GPUs). While the 2D problem can easily and efficiently be solved in the GPU, there is no known obvious, classical parallel solution that works well in the GPU for the 3D problem. Our novel parallel approach exploits the relationship between the 3D Voronoi diagram and the 3D convex hull so as to maximize the parallelism available in the GPU to compute the answer from the former rather than directly. Our implementation of the approach using the CUDA programming model on nVidia GPUs shows that it is robust and efficient. Our experiment shows that gHull runs up to 10x faster than the fastest CPU convex hull software, QuickHull, on inputs with millions of points.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

142 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1221 peoples are following HGPU @twitter

Featured events

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: