Variable Rate Shading Gradient Post-Processing for GPU Image Quality
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Solution Overview
Problem
Graphics Processing Units (GPUs) face challenges in processing high pixel loads for 4K and 8K digital screens, particularly with larger Variable Rate Shading (VRS) kernel sizes, as the likelihood of uniform color blocks decreases, reducing the usability of traditional VRS techniques.
Innovation Solution
Implementing a gradient post-processing method in GPUs that detects pixel blocks corresponding to predetermined kernel sizes, instantiates pixel shaders to generate shading values for corner pixels, and generates gradient outputs through interpolation, enhancing VRS usability by incorporating additional pixel shader computations for improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If larger VRS kernel sizes are used to reduce processing workload, then productivity increases, but image quality deteriorates due to decreased likelihood of uniform color blocks
Solution Approach 1:
The patent segments the VRS kernel processing into two distinct phases: a first pass that processes only corner pixels to generate gradient information, and a second pass that uses this gradient information to render all pixels in the kernel. This segmentation allows the system to maintain image quality by preserving gradient accuracy while improving productivity by reducing the number of full pixel shader computations needed per kernel.
Solution Approach 2:
The patent performs preliminary computation of gradient information at the corner pixels before processing the entire VRS kernel. By pre-calculating the gradient data from corner pixels in the first pass, the system prepares essential information that accelerates the second pass rendering, thereby improving overall processing throughput without sacrificing image quality.
2Use of energy by moving object
If traditional VRS is used with larger kernel sizes, then computational savings increase, but usability decreases due to reduced image quality
Solution Approach 1:
The patent implements a dynamic two-pass rendering approach that adapts to different VRS kernel sizes. The first pass dynamically identifies and processes corner pixels based on the specific kernel size, and the second pass dynamically applies gradient interpolation appropriate to each kernel configuration. This dynamic adaptation enables the system to maintain image quality across various kernel sizes while preserving computational savings.
3Productivity
If pixel shader computations are reduced for larger kernels, then processing efficiency improves, but image quality deteriorates
Solution Approach 1:
The patent applies local quality by treating corner pixels differently from other pixels in the VRS kernel. Corner pixels are processed with full pixel shader computations in the first pass to accurately capture gradient information, while interior pixels are rendered using gradient interpolation in the second pass. This localized differentiation ensures that critical gradient data is preserved while reducing overall computational load, thereby maintaining image quality while improving processing efficiency.
Data Source
AI summary
A system and a method are disclosed for post-processing variable pixel rate shader output using gradients in a graphics processing unit. A block of pixels is selected that corresponds to a predetermined kernel size for variable rate shading in a draw call of an application. A pixel shader run is instantiated to generate pixel shading values for at least two pixels located within the block of pixels. A gradient output is generated based on an interpolation of the pixel shading values for the at least two pixels over the block of pixels. The predetermined kernel size may include at least one of a 4×2 block of pixels, a 2×4 block of pixels, a 4×4 block of pixels, an 8×4 block of pixels, a 4×8 block of pixels, and an 8×8 block of pixels or larger. The at least two pixels may be corner pixels of the block of pixels.