Reconfigurable Buffer Search Engine for Data Compression
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Solution Overview
Problem
Existing data compression methods, whether hardware-based or software-based, face inefficiencies in resource utilization and performance, particularly when dealing with large datasets, with hardware-based methods being inflexible and software-based methods consuming excessive CPU and memory resources.
Innovation Solution
An electronic device with a compression unit, search engine, and compression controller that dynamically adjusts the structure of a buffer-based search engine to optimize data compression by varying the sizes of buffers and connections based on data characteristics, using a compression controller to determine the optimal structure for efficient data matching and compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If hardware-based data compression uses dedicated hardware components, then energy consumption is reduced, but flexibility is lost due to reliance on specific algorithms implemented in hardware
Solution Approach 1:
The patent implements a dynamically reconfigurable search engine where buffer sizes and connections can be adjusted based on data characteristics. The compression controller determines the optimal structure by analyzing data patterns and configuring the search engine accordingly, allowing the system to adapt between different compression scenarios while maintaining hardware efficiency.
Solution Approach 2:
The system changes physical parameters of the hardware components, specifically the size of first and second buffers and their connections, to optimize compression performance for different data types. This allows the same hardware to efficiently handle various compression tasks by adjusting its configuration rather than requiring multiple fixed algorithms.
2Adaptability or versatility
If software-based data compression uses software algorithms, then flexibility is improved, but CPU and memory usage increase and performance decreases for large datasets
Solution Approach 1:
The patent replaces software-based compression algorithms with a hardware-based search engine that performs data matching and compression operations. This substitution moves the computational workload from CPU to dedicated hardware circuits, significantly improving performance for large datasets while maintaining flexibility through reconfigurable buffer structures.
3Loss of information
If compression algorithms perform a search to identify patterns in data, then compression effectiveness is improved, but system resources are excessively consumed
Solution Approach 1:
The patent applies local quality by configuring different buffer sizes for different data characteristics. Instead of using a uniform search approach, the compression controller analyzes data patterns and allocates buffer resources locally optimized for each data type, reducing overall resource consumption while maintaining high compression effectiveness.
Data Source
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AI summary
An electronic device for compressing data includes a compression unit, a search engine, and a compression controller. The search engine includes a first buffer, a second buffer, and a plurality of comparators configured to perform matching between data stored in the first buffer and data stored in the second buffer. The compression controller is configured to determine a structure of the search engine, adjust a connection between the first buffer and the second buffer based on the determined structure and cause the compression unit to perform compression on target data using the search engine.