Variable Bin Size Graphics Rendering Bandwidth Trade-off
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Solution Overview
Problem
Current computer graphics rendering technologies face challenges in efficiently managing memory bandwidth and rendering performance, particularly in dynamic 3D graphics applications, due to conflicting requirements between database-building and traversal phases, and the need for accurate texture mapping and antialiasing.
Innovation Solution
The solution involves allowing the database bin size to be different from the display bin size, with multiple sub-bins within a bin, enabling efficient memory usage and reduced bandwidth consumption by discarding primitives outside the current sub-bin and using an optional bounding box test to optimize primitive processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the database bin size is made large to reduce the number of bins and improve database-building efficiency, then the memory bandwidth consumption during traversal increases because more primitives need to be read and tested
Solution Approach 1:
The patent divides each database bin into multiple sub-bins, creating a hierarchical structure. This segmentation allows the system to process smaller display regions (sub-bins) while maintaining larger database bins, thus reducing the number of primitives that need to be tested during traversal without compromising database-building efficiency.
Solution Approach 2:
The patent applies different bin sizes for different purposes: larger bins for database building and smaller sub-bins for display traversal. This local differentiation optimizes each phase independently, allowing efficient database construction while minimizing memory bandwidth consumption during the traversal phase.
2Loss of energy
If the bin size is made small to reduce memory bandwidth consumption during traversal, then the database-building phase becomes less efficient due to the increased number of bins
Solution Approach 1:
By segmenting each database bin into multiple sub-bins, the system can use larger database bins for efficient database building while creating smaller sub-bins for traversal, thus resolving the contradiction between database-building efficiency and memory bandwidth consumption.
Solution Approach 2:
The patent introduces a new dimension to the bin structure by creating sub-bins within bins. This hierarchical approach allows optimization at multiple levels, enabling efficient database building at the bin level while reducing traversal costs at the sub-bin level.
3Reliability
If all primitives in a bin are read during traversal to ensure accurate rendering, then the burden of reading discarded primitives increases memory bandwidth consumption
Solution Approach 1:
By dividing bins into sub-bins, the system can limit primitive reading to only those primitives that affect the current sub-bin being processed. This segmentation ensures rendering accuracy for the visible region while minimizing the reading of discarded primitives outside the current sub-bin.
Solution Approach 2:
The patent extracts and processes only the relevant portion of primitives that affect the current sub-bin, rather than reading all primitives in the parent bin. This extraction reduces memory bandwidth consumption by eliminating unnecessary primitive reads while maintaining rendering accuracy.
Data Source
AI summary
Conflicts between the database-building and traversal phases are resolved by allowing the database bin size to be different from the display bin size. The database bin size is some multiple of the bin display bin size, and when there are multiple display bins in a database bin, each database bin is traversed multiple times for display, and the rasterizer discards primitives outside of the current display bin. This allows a trade off between memory bandwidth consumed for database building and bandwidth consumed for display, particularly when the display traversal is done multiple of times.