Delta Color Compression for GPU Texture Bandwidth
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Solution Overview
Problem
Existing compression methods for textures and surfaces in graphics processing units (GPUs) are not well-suited, limiting GPU performance due to memory or cache bandwidth constraints.
Innovation Solution
A system and method for compressing pixel data by shifting M-bit pixel components into N-bit containers, converting them, and using delta color compression (DCC) to create a compressed block, which is then stored and decompressed as needed, optimizing storage and bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing compression methods are used for textures and surfaces, then storage space and bandwidth utilization are reduced, but GPU performance is limited due to memory or cache bandwidth constraints
Solution Approach 1:
The patent transforms pixel data from RGB color space to YCbCr color space, changing the parameter representation of color information. This transformation enables separate processing of luma (Y) and chroma (CbCr) components, allowing for more efficient compression strategies that prioritize bandwidth-critical luma data while compressing chroma data more aggressively, thereby improving GPU performance without excessive quality loss
Solution Approach 2:
The patent divides pixel data into separate components (luma Y and chroma CbCr) and processes them differently. By segmenting the compression approach based on component type and predicting which components will change between frames, the system optimizes bandwidth utilization while maintaining GPU performance for visually critical elements
2Quantity of substance
If textures are compressed to reduce storage space and bandwidth, then memory bandwidth is reduced, but the quality of original textures and surfaces may be degraded
Solution Approach 1:
The patent changes the color representation parameters from RGB to YCbCr, separating luminance and chrominance information. This allows the system to compress chroma components more aggressively while preserving luma quality, as the human visual system is more sensitive to brightness changes than color changes, thereby maintaining perceived texture quality at lower bandwidth costs
Solution Approach 2:
The patent applies different compression qualities to different pixel components and different regions of texture data. By predicting which pixels and components are likely to change between frames and prioritizing those for higher quality transmission, the system maintains local quality where it matters most while reducing overall bandwidth utilization
Data Source
AI summary
Systems, apparatuses, and methods for compressing pixel data are disclosed. In one embodiment, if a block of pixel data is equal to a constant value, a processor compresses the block down to a metadata value which specifies the constant value for the entire block of pixel data. The processor also detects if the constant value is equal to a video specific typical minimum or maximum value. In another embodiment, the processor receives a plurality of M-bit pixel components which are most significant bit aligned in N-bit containers. Next, the processor shifts the M-bit pixel components down into least significant bit locations of the N-bit containers. Then, the processor converts the N-bit containers into M-bit containers. Next, the processor compresses the M-bit containers to create a compressed block of pixel data which is then stored in a memory subsystem.