VINKLER, Marek, Vlastimil HAVRAN, Jiří BITTNER and Jiří SOCHOR. Parallel On-Demand Hierarchy Construction on Contemporary GPUs. IEEE Transactions on Visualization and Computer Graphics. USA: IEEE, 2016, vol. 22, No 7, p. 1886-1898. ISSN 1077-2626. Available from: https://dx.doi.org/10.1109/TVCG.2015.2465898.
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Basic information
Original name Parallel On-Demand Hierarchy Construction on Contemporary GPUs
Authors VINKLER, Marek (203 Czech Republic, guarantor, belonging to the institution), Vlastimil HAVRAN (203 Czech Republic), Jiří BITTNER (203 Czech Republic) and Jiří SOCHOR (203 Czech Republic, belonging to the institution).
Edition IEEE Transactions on Visualization and Computer Graphics, USA, IEEE, 2016, 1077-2626.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 2.840
RIV identification code RIV/00216224:14330/16:00089132
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1109/TVCG.2015.2465898
UT WoS 000377475200010
Keywords in English ray tracing; GPU; bounding volume hierarchies; kd-trees; lazy build
Tags best1
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 27/4/2017 05:44.
Abstract
We present the first parallel on-demand spatial hierarchy construction algorithm targeting ray tracing on many-core processors such as GPUs. The method performs simultaneous ray traversal and spatial hierarchy construction focused on the parts of the data structure being traversed. The method is based on a versatile framework built around a task pool and runs entirely on the GPU. We show that the on-demand construction can improve rendering times compared to full hierarchy construction. We evaluate our method on both object (BVH) and space (kd-tree) subdivision data structures and compare them mutually. The on-demand method is particularly beneficial for rendering large scenes with high occlusion. We also present SAH kd-tree builder that outperforms previous state-of-the-art builders running on the GPU.
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