research-article

Real-time KD-tree construction on graphics hardware

Authors:

Baining GuoAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 27, Issue 5

Article No.: 126, Pages 1 - 11

https://doi.org/10.1145/1409060.1409079

Published: 01 December 2008 Publication History

Abstract

We present an algorithm for constructing kd-trees on GPUs. This algorithm achieves real-time performance by exploiting the GPU's streaming architecture at all stages of kd-tree construction. Unlike previous parallel kd-tree algorithms, our method builds tree nodes completely in BFS (breadth-first search) order. We also develop a special strategy for large nodes at upper tree levels so as to further exploit the fine-grained parallelism of GPUs. For these nodes, we parallelize the computation over all geometric primitives instead of nodes at each level. Finally, in order to maintain kd-tree quality, we introduce novel schemes for fast evaluation of node split costs.

As far as we know, ours is the first real-time kd-tree algorithm on the GPU. The kd-trees built by our algorithm are of comparable quality as those constructed by off-line CPU algorithms. In terms of speed, our algorithm is significantly faster than well-optimized single-core CPU algorithms and competitive with multi-core CPU algorithms. Our algorithm provides a general way for handling dynamic scenes on the GPU. We demonstrate the potential of our algorithm in applications involving dynamic scenes, including GPU ray tracing, interactive photon mapping, and point cloud modeling.

Supplementary Material

JPG File (a126-zhou-mp4_hi.jpg)

Download
14.23 KB

MOV File (a126-zhou-mp4_hi.mov)

Download
450.87 MB

References

[1]

Carr, N. A., Hall, J. D., and Hart, J. C. 2002. The ray engine. In Proceedings of Graphics Hardware, 37--46.

Digital Library

[2]

Carr, N. A., Hoberock, J., Crane, K., and Hart, J. C. 2006. Fast GPU ray tracing of dynamic meshes using geometry images. In Proceedings of Graphics Interface, 203--209.

Digital Library

[3]

Foley, T., and Sugerman, J. 2005. Kd-tree acceleration structures for a GPU raytracer. In Graphics Hardware'05.

[4]

Goldsmith, J., and Salmon, J. 1987. Automatic creation of object hierarchies for ray tracing. IEEE CG & A 7, 5, 14--20.

[5]

Gropp, W., Lusk, E., and Skjellum, A. 1994. Using MPI: Portable Parallel Programming with the Message Passing Interface. MIT Press.

[6]

Günther, J., Wald, I., and Slusallek, P. 2004. Realtime caustics using distributed photon mapping. In Eurographics Symposium on Rendering, 111--121.

[7]

Harris, M., Owens, J., Sengupta, S., Zhang, Y., and Davidson, A., 2007. CUDPP homepage. http://www.gpgpu.org/developer/cudpp/.

[8]

Havran, V. 2001. Heuristic Ray Shooting Algorithms. PhD thesis, Czech Technical University in Prague.

[9]

Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., and Stuetzle, W. 1992. Surface reconstruction from unorganized points. In Proceedings of SIGGRAPH'92, 71--78.

[10]

Horn, D. R., Sugerman, J., Houston, M., and Hanrahan, P. 2007. Interactive k-d tree GPU raytracing. In Proceedings of Symposium on Interactive 3D graphics and Games, 167--174.

[11]

Hunt, W., Mark, W. R., and Stoll, G. 2006. Fast kd-tree construction with an adaptive error-bounded heuristic. In IEEE Symposium on Interactive Ray Tracing, 81--88.

[12]

Jensen, H. W. 2001. Realistic Image Synthesis Using Photon Mapping. AK Peters.

[13]

MacDonald, J. D., and Booth, K. S. 1990. Heuristics for ray tracing using space subdivision. Vis. Comput. 6, 3, 153--166.

Digital Library

[14]

Manku, G. S., 2002. Fast bit counting routines. http://infolab.stanford.edu/ manku/bitcount/bitcount.html.

[15]

Mount, D. M., and Arya, S., 2006. ANN: A library for approximate nearest neighbor searching. http://www.cs.umd.edu/~mount/ANN/.

[16]

Nicolaychuk, A., 2008. RivaTuner. http://www.guru3d.com/index.php?page=rivatuner.

[17]

NVIDIA, 2007. CUDA programming guide 1.0. http://developer.nvidia.com/object/cuda.html.

[18]

Pauly, M., Keiser, R., Kobbelt, L. P., and Gross, M. 2003. Shape modeling with point-sampled geometry. In Proceedings of SIGGRAPH'03, 641--650.

[19]

Pharr, M., and Humpreys, G. 2004. Physically Based Rendering: From Theory to Implementation. Morgan Kaufmann.

[20]

Popov, S., Günther, J., Seidel, H.-P., and Slusallek, P. 2006. Experiences with streaming construction of SAH KD-trees. In IEEE Symposium on Interactive Ray Tracing, 89--94.

[21]

Popov, S., Günther, J., Seidel, H.-P., and Slusallek, P. 2007. Stackless kd-tree traversal for high performance GPU ray tracing. In Eurographics'07, 415--424.

[22]

Preparata, F. P., and Shamos, M. I. 1985. Computational Geometry: An Introduction. Springer-Verlag New York, Inc.

Digital Library

[23]

Purcell, T. J., Buck, I., Mark, W. R., and Hanrahan, P. 2002. Ray tracing on programmable graphics hardware. ACM Trans. Gr. 21, 3, 703--712.

Digital Library

[24]

Purcell, T. J., Donner, C., Cammarano, M., Jensen, H. W., and Hanrahan, P. 2003. Photon mapping on programmable graphics hardware. In Graphics Hardware'03, 41--50.

[25]

Reshetov, A., Soupikov, A., and Hurley, J. 2005. Multilevel ray tracing algorithm. In SIGGRAPH '05, 1176--1185.

[26]

Sengupta, S., Harris, M., Zhang, Y., and Owens, J. D. 2007. Scan primitives for GPU computing. In Graphics Hard-ware'07, 97--106.

[27]

Shevtsov, M., Soupikov, A., and Kapustin, A. 2007. Highly parallel fast kd-tree construction for interactive ray tracing of dynamic scenes. In Eurographics'07, 395--404.

[28]

Shiue, L.-J., Jones, I., and Peters, J. 2005. A realtime GPU subdivision kernel. ACM Trans. Gr. 24, 3, 1010--1015.

Digital Library

[29]

Stoll, G. 2005. Part II: Achieving real time - optimization techniques. In SIGGRAPH 2005 Course on Interactive Ray Tracing.

[30]

Wald, I., and Havran, V. 2006. On building fast kd-trees for ray tracing, and on doing that in O(Nlog N). In Proceedings of IEEE Symposium on Interactive Ray Tracing, 61--69.

[31]

Wald, I., Slusallek, P., Benthin, C., and Wagner, M. 2001. Interactive rendering with coherent ray tracing. Computer Graphics Forum 20, 3, 153--164.

Digital Library

[32]

Wald, I., Günther, J., and Slusallek, P. 2004. Balancing considered harmful --faster photon mapping using the voxel volume heuristic. In Proceedings of Eurographics'04, 595--603.

[33]

Wald, I., Ize, T., Kensler, A., Knoll, A., and Parker, S. G. 2006. Ray tracing animated scenes using coherent grid traversal. ACM Trans. Gr. 25, 3, 485--493.

Digital Library

[34]

Wald, I., Boulos, S., and Shirley, P. 2007. Ray tracing deformable scenes using dynamic bounding volume hierarchies. ACM Trans. Gr. 26, 1, 6.

[35]

Wald, I. 2007. On fast construction of SAH based bounding volume hierarchies. In IEEE Symposium on Interactive Ray Tracing, 33--40.

Digital Library

[36]

Wang, R. Y., Pulli, K., and Popović, J. 2007. Real-time enveloping with rotational regression. ACM Trans. Gr. 26, 3, 73.

Digital Library

[37]

Yoon, S.-E., Curtis, S., and Manocha, D. 2007. Ray tracing dynamic scenes using selective restructuring. In Eurographics Symposium on Rendering.

[38]

Zhou, K., Huang, X., Xu, W., Guo, B., and Shum, H.-Y. 2007. Direct manipulation of subdivision surfaces on GPUs. ACM Trans. Gr. 26, 3, 91, 9.

Digital Library

[39]

Zwicker, M., Pfister, H., van Baar, J., and Gross, M. 2001. Surface splatting. In SIGGRAPH'01, 371--378.

[40]

Zwicker, M., Pauly, M., Knoll, O., and Gross, M. 2002. Pointshop 3d: an interactive system for point-based surface editing. In SIGGRAPH'02, 322--329.

Cited By

Geng LLee RZhang X(2025)LibRTS: A Spatial Indexing Library by Ray TracingProceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming10.1145/3710848.3710850(396-411)Online publication date: 28-Feb-2025
https://dl.acm.org/doi/10.1145/3710848.3710850
Hliš TFister IFister I(2025)Path Overlap Detection and Property Graph Construction from TCX Data for Advanced Analysis2025 IEEE 23rd World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI63904.2025.10883235(000489-000494)Online publication date: 23-Jan-2025
https://doi.org/10.1109/SAMI63904.2025.10883235
Li ZLiu HXiong CXiao WChen SZhu ZZhao G(2025)A conformal optimization framework for lightweight design of complex components using stochastic lattice structuresComputers & Structures10.1016/j.compstruc.2025.107646308(107646)Online publication date: Feb-2025
https://doi.org/10.1016/j.compstruc.2025.107646
Show More Cited By

Index Terms

Real-time KD-tree construction on graphics hardware

Recommendations

Real-time KD-tree construction on graphics hardware
SIGGRAPH Asia '08: ACM SIGGRAPH Asia 2008 papers

We present an algorithm for constructing kd-trees on GPUs. This algorithm achieves real-time performance by exploiting the GPU's streaming architecture at all stages of kd-tree construction. Unlike previous parallel kd-tree algorithms, our method builds ...
SAH KD-tree construction on GPU
HPG '11: Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics

KD-tree is one of the most efficient acceleration data structures for ray tracing. In this paper, we present a kd-tree construction algorithm that is precisely SAH-optimized and runs entirely on GPU. We construct the tree nodes in breadth-first order. ...
Simplified photon mapping for real-time caustics rendering

The objective of this paper is to adapt photon mapping for real-time simulation of caustics. High-performance algorithm adapted for the GPU and implemented on the basis of cross-platform OpenGL and OpenCL APIs is proposed. For effective rendering of ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 27, Issue 5

December 2008

552 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1409060

Issue’s Table of Contents

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2008

Published in TOG Volume 27, Issue 5

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

261
Total Citations
View Citations
4,964
Total Downloads

Downloads (Last 12 months)189
Downloads (Last 6 weeks)29

Reflects downloads up to 28 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Geng LLee RZhang X(2025)LibRTS: A Spatial Indexing Library by Ray TracingProceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming10.1145/3710848.3710850(396-411)Online publication date: 28-Feb-2025
https://dl.acm.org/doi/10.1145/3710848.3710850
Hliš TFister IFister I(2025)Path Overlap Detection and Property Graph Construction from TCX Data for Advanced Analysis2025 IEEE 23rd World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI63904.2025.10883235(000489-000494)Online publication date: 23-Jan-2025
https://doi.org/10.1109/SAMI63904.2025.10883235
Li ZLiu HXiong CXiao WChen SZhu ZZhao G(2025)A conformal optimization framework for lightweight design of complex components using stochastic lattice structuresComputers & Structures10.1016/j.compstruc.2025.107646308(107646)Online publication date: Feb-2025
https://doi.org/10.1016/j.compstruc.2025.107646
Zhang HSong TZhang GDai KWang LLiu YYang YZeng W(2025)Blending weight BSP Tree for mesh Boolean operationsComputer-Aided Design10.1016/j.cad.2025.103849182(103849)Online publication date: May-2025
https://doi.org/10.1016/j.cad.2025.103849
He ZYuan FZhou YCui BHe YLiu Y(2025)Stereo vision based broccoli recognition and attitude estimation method for field harvestingArtificial Intelligence in Agriculture10.1016/j.aiia.2025.02.002Online publication date: Feb-2025
https://doi.org/10.1016/j.aiia.2025.02.002
Deng BXu QDong XLi WWu MJu YHe Q(2024)Automatic Method for Detecting Deformation Cracks in Landslides Based on Multidimensional Information FusionRemote Sensing10.3390/rs1621407516:21(4075)Online publication date: 31-Oct-2024
https://doi.org/10.3390/rs16214075
Wang BGong BXu WShi X(2024)An efficient method for modeling and evaluating the bench terrain of open-pit minesFrontiers in Earth Science10.3389/feart.2024.135135212Online publication date: 9-May-2024
https://doi.org/10.3389/feart.2024.1351352
Xu WLin JHe DZhang F(2024)FAST-LIO2: Fast Direct LiDAR-Inertial OdometrySSRN Electronic Journal10.2139/ssrn.4675561Online publication date: 2024
https://doi.org/10.2139/ssrn.4675561
Zou JQin J(2024)Real-time volume rendering for three-dimensional fetal ultrasound using volumetric photon mappingVisual Computing for Industry, Biomedicine, and Art10.1186/s42492-024-00177-47:1Online publication date: 25-Oct-2024
https://doi.org/10.1186/s42492-024-00177-4
Bontes JGain J(2024)Redzone stream compaction: removing k items from a list in parallel O(k) timeACM Transactions on Parallel Computing10.1145/367578211:3(1-16)Online publication date: 29-Jun-2024
https://dl.acm.org/doi/10.1145/3675782
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Issue’s Table of Contents