Parallel BVH Rebuilding with Bottom-Up Node Clustering
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Solution Overview
Problem
Existing ray tracing systems face inefficiencies in building bounding volume hierarchies, which are crucial for accelerating ray-triangle intersection tests, leading to suboptimal performance in rendering complex scenes.
Innovation Solution
A method is introduced to generate a new bounding volume hierarchy (BVH) by traversing an initial BVH in a bottom-up manner, combining nodes based on a threshold number of uncombined descendants, and utilizing parallel processing to enhance efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sequential methods are used to build bounding volume hierarchies, then the BVH structure can be constructed with reasonable accuracy, but the construction time becomes excessively long for complex scenes
Solution Approach 1:
The patent divides the BVH construction process into multiple independent levels (root level, intermediate levels, leaf levels) that can be processed in parallel. Each level's bounding volumes are constructed independently based on geometric criteria, allowing simultaneous processing across different hierarchical levels without interfering with each other.
Solution Approach 2:
The patent performs preliminary geometric analysis and classification of scene objects before actual BVH construction. Objects are pre-categorized by their spatial properties and geometric characteristics, enabling faster decision-making during the parallel construction phase and reducing computation time during the critical path.
2Productivity
If parallel processing is implemented to speed up BVH construction, then construction time is reduced, but synchronization and coordination between parallel threads become complex
Solution Approach 1:
The patent segments the scene into multiple independent spatial regions or object groups that can be processed by different parallel threads. Each thread handles a specific subset of objects or a specific hierarchical level, eliminating the need for complex inter-thread synchronization since the segments are inherently independent.
Solution Approach 2:
Each parallel processing thread independently determines its own work load and progression through the BVH construction without requiring centralized coordination. Threads autonomously select objects to process, compute bounding volumes, and advance to the next task based on local geometric criteria, reducing synchronization overhead.
3Manufacturing precision
If the BVH is built with high precision to minimize ray-triangle intersections, then rendering accuracy improves, but the construction complexity and time increase
Solution Approach 1:
The patent applies different levels of bounding volume precision to different regions of the scene based on local geometric characteristics. Dense regions with many intersecting objects receive tighter, more accurate bounding volumes, while sparse regions use coarser approximations, optimizing the trade-off between precision and construction complexity locally rather than uniformly across the entire scene.
Solution Approach 2:
The patent dynamically adjusts bounding volume parameters (such as tightness factors, subdivision thresholds, and geometric tolerance levels) based on the local density and complexity of objects in each region. This adaptive parameter adjustment achieves high precision where needed while maintaining simpler construction processes in less demanding areas.
Data Source
AI summary
Techniques herein involve generating a bounding volume hierarchy in a fast and accurate manner. The techniques begin with a quickly built initial BVH and traverse that initial BVH in a bottom-up manner to generate a new BVH. The algorithm begins at the bottom level, setting the bottom-most primitive nodes as nodes in the new BVH and follows the initial BVH up, collecting uncombined nodes from lower levels to higher nodes. When the algorithm has collected a threshold number of such nodes at a node of the initial BVH, the algorithm builds a new subtree for that node by combining the threshold number of such nodes, and adds that new subtree to the new BVH. This algorithm is efficiently parallelizable by immediately switching from the traversal phase to the combining phase and using all work-items of a wavefront for such combining.