Corner Table Generation for Faster Triangle Mesh Compression
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Solution Overview
Problem
Existing CPU and GPU architectures lack specialized acceleration capability for efficient mesh encoding and decoding, particularly in the creation of corner tables required for mesh compression in graphics processing, which is processing intensive due to the traversal of arbitrarily ordered and linked mesh elements.
Innovation Solution
An apparatus and process for accelerating corner table creation, which is essential for mesh encoding, by utilizing specialized hardware logic and algorithms to efficiently identify and store opposite corner indices in a data structure, thereby optimizing mesh compression operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing CPU and GPU architectures are used for mesh compression, then general-purpose processing capability is maintained, but processing intensity and time consumption increase significantly
Solution Approach 1:
The patent segments the mesh compression task into two distinct phases: a CPU phase for generating corner tables (using specialized hardware logic) and a GPU phase for actual mesh encoding/decoding. This segmentation allows each phase to be optimized independently, with the corner table creation being performed more efficiently through specialized hardware assistance.
Solution Approach 2:
The patent introduces corner tables as an intermediary data structure that pre-stores opposite corner indices for mesh elements. By creating this intermediate representation beforehand, the actual mesh compression process can proceed faster without repeatedly traversing the mesh structure, thus reducing overall processing time.
2Productivity
If specialized hardware logic is added for corner table creation, then processing efficiency improves, but device complexity increases
Solution Approach 1:
The patent designs the specialized hardware logic to serve multiple functions: it not only creates corner tables but also supports the overall mesh compression workflow. This multi-functionality reduces the need for separate dedicated components, thereby limiting the increase in device complexity while maintaining efficiency improvements.
Solution Approach 2:
The specialized hardware logic performs corner table creation as a preliminary action before the main mesh compression process. By preparing the corner table data structure in advance using efficient hardware-assisted algorithms, the subsequent compression operations can proceed more rapidly without requiring complex real-time computations.
3Manufacturing precision
If mesh models with millions of triangles are processed, then photo-realism and resolution requirements are met, but storage and transmission efficiency decrease
Solution Approach 1:
The patent performs preliminary processing by generating corner tables that store compressed representations of mesh connectivity information. This pre-computation enables subsequent mesh encoding to achieve higher compression ratios, thereby reducing the quantity of data needed for storage and transmission while preserving the original high-resolution mesh structure.
Solution Approach 2:
The patent extracts and stores only the essential connectivity information (opposite corner indices) in the corner table structure, separating this metadata from the full mesh geometry data. This extraction allows for efficient compression of the connectivity information while maintaining the complete triangle mesh for rendering, thus reducing overall data size without losing resolution.
Data Source
AI summary
Corner table creation for graphics processing is described. An example of an apparatus includes corner data generator circuitry, including a circuit to generate a plurality of vertex-corner lists for a plurality of portions of a triangle mesh, wherein a vertex-corner list for a portion includes an index for a vertex, a count of corners for the vertex, and a list of corners associated with the vertex, and a circuit to receive the vertex-corner lists and generate one or more edge hash maps, each edge hash map including corner indices for edges of the triangle mesh.