10885

GPU-Based Sparse Voxel Octree Raytracing for Rendering of Procedurally Generated Terrain

Chris Goosen
University of Cape Town, Department of Computer Science
University of Cape Town, 2013
@article{goosen2013gpu,

   title={GPU-BASED SPARSE VOXEL OCTREE RAYTRACING FOR RENDERING OF PROCEDURALLY GENERATED TERRAIN},

   author={Goosen, Chris and Gain, James},

   year={2013}

}

Download Download (PDF)   View View   Source Source   

618

views

Within the field of Computer Graphics, there have been two competing approaches to doing rendering, namely rasterisation and raytracing. Rasterisation became, and has been, the dominant of the two methods for realtime rendering for a long period of time. With recent developments in graphics hardware, however, raytracing is starting to gain popularity once again. At the same time, the need for procedurally generated content, and particularly procedurally generated terrain, is growing. In this thesis, we propose a rendering system, which makes use of raytracing into a sparse voxel octree structure, to render procedurally generated terrain. We develop both a CPU implementation of our system and a GPU implementation and examine the performance benefits that we get by migrating our system to the GPU. In doing so, we evaluate the viability of raytracing into a sparse voxel octree as an alternative to rasterisation. While our system is not yet ready to replace rasterisation, it suggests that sparse voxel octree raytracers may yet be a viable alternative.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

230 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1427 peoples are following HGPU @twitter

* * *

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: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • 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: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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 © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: