Progressive Multisample Anti-aliasing Bandwidth Reduction
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Solution Overview
Problem
Current data processing systems, particularly graphics processing units (GPUs), face challenges in efficiently processing graphics data and managing bandwidth, especially when implementing techniques like multi-sampling anti-aliasing (MSAA) that require storing multiple samples per pixel.
Innovation Solution
The implementation of a graphics processing unit (GPU) that uses lossless compression techniques for multisample render targets, storing samples in an interleaved manner to enhance efficiency, and progressive MSAA plane allocation to reduce bandwidth consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple samples per pixel are stored for multi-sampling anti-aliasing, then image quality is improved, but bandwidth consumption increases
Solution Approach 1:
The patent divides the multisample render target into multiple planes (e.g., even samples and odd samples separated into different planes). This segmentation allows independent compression and processing of each plane, reducing overall bandwidth consumption while maintaining the ability to reconstruct high-quality images through progressive allocation of planes based on actual rendering needs.
2Loss of energy
If lossless compression techniques are applied to multisample render targets, then bandwidth consumption is reduced, but processing complexity increases
Solution Approach 1:
The patent performs preliminary organization of multisample data into separate planes before compression. By pre-separating samples into even and odd planes and organizing them systematically, the compression process becomes more efficient and manageable, reducing the actual processing complexity during runtime while still achieving bandwidth reduction through lossless compression.
Data Source
AI summary
One embodiment provides a graphics processor comprising an interface to a system interconnect and a graphics processor coupled to the interface, the graphics processor comprising circuitry configured to compact sample data for multiple sample locations of a pixel, map the multiple sample locations to memory locations that store compacted sample data, the memory locations in a memory of the graphics processor, apply lossless compression to the compacted sample data, and update a compression control surface associated with the memory locations, the compression control surface to specify a compression status for the memory locations