Two-Stage Primitive Setup for Graphics Pipeline Efficiency
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Solution Overview
Problem
Current graphics processing systems incur unnecessary processing and resource usage by determining and calculating primitive setup information for all primitives, even if they are not required for rendering, due to the lack of efficient culling and interpolation equation calculation strategies.
Innovation Solution
Implementing a two-stage primitive setup process where only the necessary information is calculated, with a first stage determining if a primitive should be processed further based on edge equations and early culling tests, and a second stage determining further information like barycentric equations only if the primitive passes these tests, thereby reducing unnecessary calculations and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all primitives are processed with complete primitive setup information calculated, then rendering accuracy is maintained, but processing time and resource usage increase unnecessarily
Solution Approach 1:
The patent applies preliminary action by performing early culling tests using simplified edge equations before calculating complete primitive setup information. This allows the system to identify and eliminate primitives that will not contribute to the final render output before investing resources in full processing, thus maintaining accuracy for visible primitives while reducing overall processing time.
Solution Approach 2:
The patent segments the primitive processing into distinct stages: first calculating only edge equations for culling tests, then conditionally calculating additional setup information like barycentric equations only for primitives that pass the culling tests. This segmentation allows the system to process primitives differently based on their visibility, maintaining accuracy where needed while reducing unnecessary processing.
2Reliability
If complete primitive setup information is calculated for all primitives, then rendering quality is preserved, but power consumption and memory bandwidth increase
Solution Approach 1:
The system performs preliminary culling tests using minimal edge equation calculations before committing to full primitive setup information calculation. This preliminary action consumes minimal power and identifies which primitives actually require full processing, thereby preserving rendering quality for visible elements while significantly reducing overall power consumption by avoiding unnecessary calculations for culled primitives.
Solution Approach 2:
The patent applies local quality by providing different levels of processing detail to different primitives based on their visibility. Visible primitives receive complete setup information for high-quality rendering, while invisible primitives receive minimal processing or are culled entirely. This differentiated approach maintains rendering quality where it matters while reducing power consumption through selective processing.
3Productivity
If early culling tests are implemented, then processing efficiency improves, but device complexity increases due to additional processing stages
Solution Approach 1:
The patent segments the processing pipeline into distinct stages: an early culling stage that uses only edge equations, and a subsequent rendering stage that processes primitives with complete setup information. This segmentation improves efficiency by eliminating invisible primitives early, while the added complexity is managed by reusing the same edge equation calculations across stages rather than duplicating full processing logic.
Solution Approach 2:
The edge equations serve multiple functions: they are used both for the early culling tests and as part of the complete primitive setup information for rendering. This multi-functionality reduces the need for separate calculation routines, thereby improving processing efficiency while minimizing the increase in device complexity since the same computational structures serve dual purposes.
Data Source
AI summary
Operating a graphics processing pipeline that includes processing stages including a rasteriser that rasterises input primitives to generate graphics fragments to be processed, each graphics fragment having one or more sampling points associated with it, and a renderer that processes fragments generated by the rasteriser to generate output fragment data for output to a render output, comprising the following steps: (i) determining first information to test whether at least a part of a primitive should be processed further; (ii) using at least some of the first information to decide whether to process at least a part of the primitive further; and if it is decided that at least a part of the primitive is to be processed further: (iii) determining further information to be used in further processing of the primitive; and (iv) further processing at least a part of the primitive using the determined further information.