Massively Parallel Hierarchical Scene Processing with Applications in Rendering

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 synchron...

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Bibliographic Details
Published in:Computer graphics forum Vol. 32; no. 8; pp. 13 - 25
Main Authors: Vinkler, Marek, Bittner, Jiří, Havran, Vlastimil, Hapala, Michal
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.12.2013
Subjects:
acceleration data structures
Algorithms
Analysis
BVH
Computer graphics
CUDA
I.3.6 [Computer Graphics]: Methodology and Techniques-Graphics data structures and data types
I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-Ray tracing
parallel algorithms
Parallel processing
ray tracing
Studies
ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Summary: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. 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
Bibliography:Czech Science Foundation under research - No. P202/11/1883; No. P202/12/2413; No. P202/10/1435
ArticleID:CGF12140
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SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12140