Texture Map Pixel Pairing Optimization for Anisotropic Filtering
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Solution Overview
Problem
Conventional graphics processors experience decreased texture filtering performance when using anisotropic filtering or high bit-count texels, as they struggle to efficiently process and cache texels, leading to reduced performance and increased latency.
Innovation Solution
The solution involves pairing texel reads based on the alignment of the major axis of anisotropy in pixel space and processing them in a sequence to improve texel locality, thereby enhancing the texture cache hit rate and reducing conflicts, which allows for more efficient filtering and caching of texels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If anisotropic filtering is used to produce higher quality images, then image quality is improved, but texture filtering performance decreases
Solution Approach 1:
The patent segments the texel processing into paired reads organized by the major axis of anisotropy alignment. By dividing the filtering operation into sequential pairs of texel reads rather than processing all texels independently, the system achieves better cache locality and reduces conflicts, thereby maintaining high image quality while improving filtering performance.
Solution Approach 2:
The patent introduces a new organizational dimension for texel reads based on the alignment of the major axis of anisotropy in pixel space. This dimensional reorganization transforms the traditional random-access pattern into a structured sequential pattern that optimizes cache utilization, resolving the contradiction between filtering quality and processing performance.
2Measurement precision
If the number of bits per texel component is increased to produce higher quality images, then image quality is improved, but texture filtering performance decreases
Solution Approach 1:
The patent applies segmentation to high bit-count texel processing by organizing reads into pairs based on major axis alignment. This structured approach improves cache hit rates and reduces conflicts, enabling efficient processing of high bit-depth texels while maintaining image quality.
Solution Approach 2:
The patent changes the parameter of texel read organization from conventional independent reads to paired reads aligned with the major axis of anisotropy. This parameter change optimizes the processing sequence for high bit-count texels, improving both performance and quality.
3Measurement precision
If more texels are processed to produce each filtered result, then image quality is improved, but texture filtering performance decreases
Solution Approach 1:
The patent merges paired texel reads into a unified processing sequence organized by major axis alignment. This combining approach improves cache locality and reduces conflicts, allowing the system to process more texels efficiently while maintaining high filtering performance and image quality.
Data Source
AI summary
The current invention involves new systems and methods for increasing texture filtering performance by reorganizing a texture sampling order used to read and filter texels when anisotropic filtering is used. Texel read performance is improved for anisotropic filtering by reorganizing texel reads when a texel cache is used. The texel reads are paired based on a major axis alignment in pixel space. The paired texel reads for a pixel footprint may also be ordered to improve texel coherency, thereby improving a texture cache hit rate.