Multi-dimensional Acceleration Structure Using Central and Six Grids
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Solution Overview
Problem
Conventional multi-dimensional acceleration structures, such as k-d trees and octrees, face challenges in computational complexity during data population and recursive look-up processes, which hinder efficient processing in real-time applications like video games.
Innovation Solution
A multi-dimensional acceleration structure is implemented using a central grid structure and six additional grid structures in 3D space, allowing for fast build times and look-ups by mapping entity positions to voxel grid coordinates through a linear transform and non-linear functions, eliminating the need for recursive operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a k-d tree or octree is used as an acceleration structure, then data can be organized into groups based on location, but the computational complexity in populating data into the tree increases
Solution Approach 1:
The acceleration structure is divided into a central grid structure and six additional grid structures organized around it in 3D space. Each grid structure contains a set of voxels, creating a segmented spatial organization that simplifies data population compared to traditional tree structures.
Solution Approach 2:
The patent replaces the recursive tree traversal mechanism with a direct grid-based indexing system. Instead of recursively traversing from root nodes to leaves, the system uses direct coordinate mapping to voxel grid coordinates, eliminating the recursive overhead and reducing computational complexity.
2Productivity
If a k-d tree or octree is used as an acceleration structure, then data can be organized into groups based on location, but the look-up process becomes a recursive traversal from root node which is computationally expensive
Solution Approach 1:
The recursive tree traversal mechanism is replaced with a direct grid-based indexing system. Entity positions are mapped directly to voxel grid coordinates through coordinate transformation, allowing O(1) lookup time instead of O(log n) recursive traversal.
Solution Approach 2:
The patent creates a simplified copy of the spatial organization in the form of a grid structure with fixed voxel boundaries. This grid copy allows direct address calculation from entity positions without needing to traverse the hierarchical tree structure, significantly reducing lookup time.
3Productivity
If a traditional acceleration structure is used, then data organization is achieved, but memory usage increases due to the tree structure overhead
Solution Approach 1:
The patent merges the spatial indexing function with a compact grid structure where voxels serve as both the organizational unit and the storage index. This eliminates the need for separate node structures, pointers, and hierarchical metadata that traditional trees require, reducing overall memory usage.
Solution Approach 2:
The patent changes the fundamental parameter of spatial organization from hierarchical tree nodes to flat grid voxels. This parameter change allows direct memory addressing based on grid coordinates, eliminating the memory overhead associated with tree node structures and their relationships.
Data Source
AI summary
A system and method for implementing an acceleration structure are disclosed. The method includes: determining a position of an entity; mapping the position to a 3D (three-dimensional) voxel grid coordinate in the acceleration structure, which comprises a central grid structure and six additional grid structures each comprising a set of voxels; determining a first offset value corresponding to the 3D voxel grid coordinate that corresponds to either the central grid structure or one of the six additional grid structures; and determining a second offset value corresponding to the 3D voxel grid coordinate that corresponds to a particular voxel within either the central grid structure or one of the six additional grid structures corresponding to the first offset value, wherein data corresponding to the entity is stored in memory a location based on the first offset value and the second offset value.