Variable Rate Shading GPU Sampling Rate Parameter Map
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current computer graphics systems face inefficiencies in processing power and memory usage due to constant sampling rates across the entire frame, especially with increasing pixel density and display resolution, particularly in mobile devices like the HOLOLENS holographic headset, necessitating more efficient graphics processing methods.
Innovation Solution
The implementation of variable rate shading, where the graphics processing unit (GPU) determines map coordinates and lookup values to calculate fragment-specific sampling rate parameters, allowing for dynamic adjustment of shading rates across different regions of an image, from coarse to full subpixel resolution, based on factors like level of detail, screen-space position, and object complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If constant sampling rate is used across entire frame, then image fidelity is maintained, but processing power and memory usage increase significantly
Solution Approach 1:
The patent applies local quality by varying the sampling rate differently across different regions of the image. High sampling rates are used in regions requiring fine detail (such as text or complex patterns) while lower sampling rates are applied to simpler regions. This is achieved through a sampling rate parameter (SRP) map that assigns different SRP values to different screen regions, allowing the system to maintain image fidelity where needed while reducing processing power consumption overall.
Solution Approach 2:
The patent segments the image into multiple screen-space regions, each with its own sampling rate parameter. The frame buffer is divided into tiles or blocks, and each region can have independently controlled sampling rates. This segmentation allows the system to process different parts of the image at different computational costs, resolving the contradiction between maintaining overall image fidelity and reducing total processing power requirements.
2Manufacturing precision
If constant sampling rate is used across entire frame, then image quality is maintained, but memory usage increases
Solution Approach 1:
The system uses local quality by implementing region-specific sampling rates through an SRP map. Instead of allocating memory for high-precision pixel data across the entire frame, the system only allocates and processes high-precision data in regions where it is actually needed. This reduces overall memory usage while maintaining image quality in critical areas.
Solution Approach 2:
The frame buffer and associated data structures are segmented into regions corresponding to different sampling rates. The SRP map divides the screen into tiles or blocks, and memory is allocated and processed accordingly for each segment. This segmentation strategy reduces total memory requirements compared to maintaining uniform high-precision data for the entire frame.
3Productivity
If variable sampling rate is implemented, then processing efficiency improves, but device complexity increases
Solution Approach 1:
The system performs preliminary action by pre-computing and storing the SRP map before the actual rendering process. The SRP map is generated in advance based on the image content or scene representation, and this pre-computed map is then used during rendering to efficiently determine sampling rates for different regions. This preliminary computation simplifies the rendering process itself, as the sampling rate decisions are already made, reducing the complexity of real-time processing.
Solution Approach 2:
The SRP map acts as an intermediary between the scene representation and the actual pixel rendering process. Instead of complex real-time calculations during rendering, the system uses the pre-computed SRP map as an intermediate data structure that guides the sampling process. This intermediary approach simplifies the rendering pipeline by separating the sampling rate determination from the actual shading and rendering operations.
Data Source
AI summary
Methods and devices for rendering graphics in a computer system include a graphical processing unit (GPU) with a flexible, dynamic, application-directed mechanism for varying the rate at which fragment shading is performed for rendering an image to a display. In particular, the described aspects include determining, at a rasterization stage, map coordinates based on coarse scan converting a primitive of an object, the map coordinates indicating a location on a sampling rate parameter (SRP) map of a fragment within the primitive of the object, and identifying a lookup value for the fragment within the primitive of the object based at least on map coordinates, and calculating a respective fragment variable SRP value for the fragment within the primitive of the object based at least on the lookup value.