VINKLER, Marek, Jiří BITTNER, Vlastimil HAVRAN and Michal HAPALA. Massively Parallel Hierarchical Scene Processing with Applications in Rendering. Computer Graphics Forum. Wiley, 2013, vol. 32, No 8, p. 13-25. ISSN 0167-7055. Available from: https://dx.doi.org/10.1111/cgf.12140.
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Basic information
Original name Massively Parallel Hierarchical Scene Processing with Applications in Rendering
Authors VINKLER, Marek (203 Czech Republic, guarantor, belonging to the institution), Jiří BITTNER (203 Czech Republic), Vlastimil HAVRAN (203 Czech Republic) and Michal HAPALA (203 Czech Republic).
Edition Computer Graphics Forum, Wiley, 2013, 0167-7055.
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 Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL URL
Impact factor Impact factor: 1.595
RIV identification code RIV/00216224:14330/13:00069069
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1111/cgf.12140
UT WoS 000327433800002
Keywords (in Czech) paralelní algoritmy; CUDA; akcelerační datové struktury; sledování paprsku; BVH
Keywords in English parallel algorithms; CUDA; acceleration data structures; ray tracing; BVH
Tags best1
Tags International impact, Reviewed
Changed by Changed by: RNDr. Marek Vinkler, Ph.D., učo 172521. Changed: 19/1/2014 16:14.
Abstract
We present a novel method for massively parallel hierarchical scene processing on the GPU, which is based on sequential decomposition of the given hierarchical algorithm into small functional blocks. The computation is fully managed by the GPU using a specialized task pool which facilitates synchronization and communication of processing units. We present two applications of the proposed approach: construction of the bounding volume hierarchies and collision detection based on divide-and-conquer ray tracing. The results indicate that using our approach we achieve high utilization of the GPU even for complex hierarchical problems which pose a challenge for massive parallelization. The results indicate that using our approach we achieve high utilization of the GPU even for complex hierarchical problems which pose a challenge for massive parallelization.
Links
LG13010, research and development projectName: Zastoupení ČR v European Research Consortium for Informatics and Mathematics (Acronym: ERCIM-CZ)
Investor: Ministry of Education, Youth and Sports of the CR
MUNI/A/0750/2012, interní kód MUName: Vyzkum FI v oblastech aplikovane informatiky (Acronym: FI_Apl_Inf_2013)
Investor: Masaryk University, Category A
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