Data Processing Apparatus Region Prediction for Frame Buffer Optimization
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Solution Overview
Problem
Current data processing methods for generating output data, such as graphics outputs, consume significant processing power and memory bandwidth, especially when generating high-resolution frames at high rates, and there is a need to reduce resource usage without compromising quality.
Innovation Solution
A method and apparatus that predict whether a region of output data for a current frame will be similar to a region of output data from a previous frame, allowing for the reuse of previous data instead of regenerating it, thereby reducing processing and memory bandwidth requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all regions of output data are regenerated for each current frame, then output quality and completeness are maintained, but processing power consumption and memory bandwidth usage increase significantly
Solution Approach 1:
The output frame is divided into multiple tiles or regions, allowing the system to process and compare only specific regions rather than the entire frame. This segmentation enables selective regeneration of only those regions that have changed, reducing overall processing power consumption while maintaining complete output quality.
Solution Approach 2:
Instead of regenerating the entire frame, the system performs partial action by regenerating only the portions of the frame that have changed. The unchanged regions are identified through comparison with the previous frame and are not regenerated, thus reducing processing power consumption without compromising output quality.
2Reliability
If all regions of output data are written to frame buffer for each current frame, then data completeness is ensured, but memory bandwidth consumption increases significantly
Solution Approach 1:
The frame buffer writing process is segmented by region. Only the tiles or regions that have changed are written to the frame buffer, while unchanged regions are excluded from the write operation. This segmentation dramatically reduces memory bandwidth consumption while ensuring that all necessary updated data is complete.
Solution Approach 2:
The system performs partial writing to the frame buffer by writing only the changed regions rather than the entire frame. This partial action reduces the quantity of data transferred to memory, thereby reducing memory bandwidth consumption while maintaining data completeness for the updated portions.
3Use of energy by moving object
If processing resources are reduced to lower power consumption, then energy efficiency improves, but output quality may deteriorate
Solution Approach 1:
The system uses feedback by comparing the current frame with the previous frame to identify changed regions. This feedback mechanism allows the system to make intelligent decisions about which regions require regeneration, ensuring that output quality is maintained for changed areas while reducing processing resources for unchanged areas, thereby improving energy efficiency without sacrificing quality.
Solution Approach 2:
The system changes the processing parameter from regenerating the entire frame to regenerating only changed regions. This parameter change is dynamically determined through frame comparison, allowing the system to adjust processing resources based on actual content changes, thus improving energy efficiency while maintaining output quality where necessary.
4Productivity
If high-resolution frames are generated at high rates, then productivity and output quality are improved, but processing power consumption and memory bandwidth usage increase significantly
Solution Approach 1:
By segmenting the frame into tiles and processing them independently, the system can efficiently handle high-resolution frames at high rates. Each tile can be processed and compared separately, allowing for parallel processing and reducing the overall processing power consumption while maintaining high productivity and output quality.
Data Source
AI summary
A data processing apparatus comprises processing circuitry configured to predict whether a region of output data to be generated by the apparatus for a current set of output data will be similar to a region of output data generated and stored in memory for a previous set of output data. When it is predicted that the new region of output data will be similar to the previous region of output data, the new region of output data is prevented from being generated and the previous region of output data is used for the current set of output data instead. The data processing apparatus can provide a way to avoid generating areas of sets of output data that are static from one set of output data to the next.


