Alpha Block Transforms for Low-Load GUI Stream Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional GUI streaming techniques require excessive computational resources and memory on streaming devices, often maxing out the capacity of smaller devices and causing overheating due to the need to decode multiple high-resolution video streams simultaneously.
Innovation Solution
Implementing Alpha block transforms for inter-frame and intra-frame compression, leveraging GPU hardware and software specific to the streaming device, and using GPU tile-based framebuffer compression formats to reduce the computational load on CPUs by reusing unchanged block data and decoding Alpha channels directly on the GPU.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GUI streaming techniques are used to render high-resolution video streams, then video quality is improved, but computational resources and memory usage increase excessively
Solution Approach 1:
The patent segments the frame data into multiple blocks and processes them independently using parallel processing units. Each block can be decoded and rendered separately, allowing the system to handle high-resolution video streams by dividing the computational workload across multiple units simultaneously, thus maintaining video quality while reducing the computational burden on individual processing units
Solution Approach 2:
The patent implements dynamic processing where the system adapts the processing strategy based on frame characteristics. By identifying unchanged regions between frames and reusing previous processing results, the system dynamically adjusts the amount of computation required, maintaining high video quality while optimizing resource usage according to actual processing needs
2Productivity
If multiple high-resolution video streams are decoded simultaneously on streaming devices, then streaming capability is improved, but device overheating occurs due to excessive computational load
Solution Approach 1:
The patent divides the decoding and rendering process into separate parallel processing units, where different stages of processing (decoding, transforming, rendering) are handled by dedicated units. This segmentation allows multiple video streams to be processed simultaneously across different units, improving overall streaming capability while distributing thermal load across the device rather than concentrating it in a single processor
Solution Approach 2:
The patent replaces traditional CPU-based processing with specialized GPU hardware acceleration. By substituting general-purpose mechanical processing with dedicated hardware circuits designed for parallel graphics processing, the system achieves higher productivity for multiple video streams while the distributed architecture prevents single-point overheating
3Adaptability or versatility
If CPU-based decoding is used for frame data, then processing flexibility is maintained, but processing speed decreases due to CPU limitations
Solution Approach 1:
The patent replaces CPU-based software processing with GPU-based hardware processing. The decoding, transforming, and rendering operations are performed by dedicated hardware circuits in the GPU that are optimized for parallel processing of graphical data. This substitution maintains processing flexibility through programmable shader stages while achieving significant speed improvements through hardware acceleration and parallel execution
Data Source
AI summary
Systems and techniques are described for Alpha channel inter-frame and intra-frame compression. An example method includes receiving a first frame representative of a graphical user interface at a first time and a second frame representative of the graphical user interface at a second time. The example includes dividing the first frame and the second frame into respective blocks. The example includes searching the frames for at least one target block that share a common value with at least one other block in either the first frame and/or the second frame. The example includes applying at least one transform to the at least one target block that references either the common value or the at least one other block in either the first frame and/or the second frame. The example includes replacing the at least one target block with a transform block.