Mixed Data Compression Integrity Bandwidth Reduction
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Solution Overview
Problem
Existing data processing technologies for System on Chip (SoC) face challenges in ensuring data integrity during compression, particularly with lossy compression methods like ASTC and TE, and struggle with the complexity of lossless compression methods like AFBC.
Innovation Solution
A data processing method that classifies each raw datum in a data packet based on preset data types and applies different lossless compression modes specific to each data type, ensuring data integrity and reducing bandwidth and storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression technologies (ASTC, TE) are used to compress mixed data on the bus, then bandwidth and storage space are reduced, but data integrity cannot be guaranteed
Solution Approach 1:
The patent segments the mixed data on the bus into different data types (e.g., texture data, vertex data, index data) and applies specific compression modes to each type. This segmentation allows lossless compression to be applied to data types requiring integrity while enabling lossy compression for data types where some quality degradation is acceptable, thus resolving the contradiction between bandwidth reduction and data integrity.
Solution Approach 2:
The patent implements local quality by applying different compression strategies to different portions of the data based on their specific requirements. Critical data portions (like vertex data and index data) receive lossless compression to ensure integrity, while less critical portions (like some texture data) can use lossy compression to maximize bandwidth efficiency. This localized approach resolves the universal contradiction faced by prior art.
2Reliability
If AFBC compression technology is used to ensure data integrity, then data compression is achieved, but the implementation complexity increases significantly
Solution Approach 1:
The patent changes the parameter of compression approach from a single uniform method (AFBC) to multiple data-type-specific methods. By identifying and categorizing different data types in the mixed data stream, the system applies appropriate compression parameters and algorithms to each type, reducing the overall implementation complexity while maintaining data integrity where required.
Solution Approach 2:
The patent segments the data processing task by identifying different data types within the mixed data stream and applying targeted compression strategies to each segment. This avoids the need to implement complex universal compression algorithms like AFBC for all data types, thereby reducing implementation complexity while preserving data integrity for critical data types through lossless compression.
3Ease of manufacture
If uniform compression mode is applied to all raw data in the data packet, then implementation is simplified, but compression efficiency and data integrity are compromised
Solution Approach 1:
The patent applies local quality by determining the data type of each raw datum and applying the most appropriate compression mode locally to each data type. This targeted approach improves compression efficiency by using optimal algorithms for each data type while maintaining implementation simplicity through automated data type identification and mode selection, resolving the contradiction between simplicity and efficiency.
Data Source
AI summary
A data processing method, device and apparatus, and a storage medium are disclosed. The data processing method includes obtaining a data packet including multiple raw data; determining a target data type corresponding to each raw datum in the data packet; determining a target data processing mode corresponding to each raw datum based on a data processing requirement for the data packet and the target data type corresponding to each raw datum in the data packet, the data processing requirement including at least one or more of data compression, data storage and data decoding; and performing data processing on each raw datum based on the target data processing mode corresponding to each raw datum. The method can ensure the integrity of compression of mixed data, reduce the bandwidth and storage space occupied by the transmission of the compressed data packet, and can be implemented in a relatively simple way.