Agglomerative Treelet Restructuring for Dynamic BVH Construction
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Solution Overview
Problem
Existing techniques for constructing bounding volume hierarchies (BVHs) either produce low-quality BVHs quickly or high-quality BVHs slowly, failing to meet the needs of applications requiring interactive ray tracing performance in dynamic scenes.
Innovation Solution
The method involves restructuring an initial hierarchical tree data structure using agglomerative clustering to form and optimize treelets, reducing the surface area heuristic cost and achieving high-quality BVHs at interactive rates by processing multiple treelets in parallel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If CPU-based techniques are used to construct BVHs, then BVH quality is improved, but construction time increases significantly
Solution Approach 1:
The patent divides the BVH construction process into independent treelet units that can be processed in parallel. Each treelet represents a localized neighborhood of nodes that can be optimized independently, enabling GPU parallel processing while maintaining overall BVH quality
Solution Approach 2:
The patent replaces CPU-based sequential construction with GPU-based parallel processing. By substituting the processing mechanism from CPU to GPU, the system achieves both high quality BVH construction and fast construction times through massive parallelism
2Productivity
If GPU-based techniques are used to construct BVHs, then construction speed is improved, but BVH quality deteriorates
Solution Approach 1:
The patent changes the optimization parameters and cost functions used in GPU-based treelet restructure to better align with CPU-based quality metrics. By adjusting parameters such as surface area heuristic calculations and merge costs, the system achieves high quality BVHs while maintaining GPU construction speed
Solution Approach 2:
The patent performs preliminary BVH construction using fast GPU-based methods, then applies subsequent treelet restructure operations to improve quality. This preliminary action allows the system to achieve both speed and quality by separating construction from optimization phases
3Manufacturing precision
If CPU-based techniques are used, then BVH quality is high, but the technique is too slow for dynamic scenes requiring per-frame construction
Solution Approach 1:
The patent segments the BVH into treelet units that can be processed in parallel on the GPU, enabling per-frame construction for dynamic scenes while maintaining high quality through optimized treelet restructure operations
Solution Approach 2:
The patent enables dynamic BVH construction by allowing the BVH to be rebuilt every frame using GPU parallel processing. The system adapts to changing scenes by performing rapid BVH construction and restructure operations that keep pace with dynamic content changes
4Productivity
If GPU-based techniques are used, then construction speed is fast, but the technique only works for static or low-update scenes
Solution Approach 1:
The patent modifies the cost functions and optimization parameters to better handle dynamic scenes with frequent updates. By adjusting parameters to account for scene changes, the system maintains fast GPU construction speed while becoming adaptable to various scene dynamics
Data Source
AI summary
A system, method, and computer program product are provided for modifying a hierarchical tree data structure. An initial hierarchical tree data structure is received, and treelets of node neighborhoods are formed. A processor restructures the treelets using agglomerative clustering to produce an optimized hierarchical tree data structure that includes at least one restructured treelet, where each restructured treelet includes at least one internal node.