Banked Conversion Table Compression for Faster Dictionary Retrieval
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Solution Overview
Problem
Existing data compression methods face delays due to sequential data retrieval from dictionaries, which can lead to transmission issues and complex hardware configurations, especially when the number of entry regions increases.
Innovation Solution
A data compressor is designed with a conversion table divided into bank regions, where each piece of data is mapped to a specific bank region using a hash function, allowing for reduced search times by narrowing the retrieval range and optimizing processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the retrieval process is implemented by hardware with parallel matching, then the retrieval time is shortened, but the circuit configuration becomes complicated when the number of entry regions increases
Solution Approach 1:
The conversion table is divided into multiple bank regions (e.g., 4 banks), where each bank contains a subset of entry regions. The determination unit identifies which bank contains the target entry, and the processing unit searches only within that specific bank. This segmentation reduces the number of entry regions that need to be searched in parallel, simplifying the hardware circuit configuration while maintaining fast retrieval performance.
2Device complexity
If the retrieval process is implemented by software with sequential searching, then the circuit configuration remains simple, but the retrieval process becomes a bottleneck causing delays
Solution Approach 1:
By dividing the conversion table into multiple banks, the system enables parallel search operations within each bank while keeping individual bank circuits simple. The determination unit quickly identifies the target bank, and the processing unit performs searches in parallel within that bank, significantly improving retrieval speed without requiring complex full-table parallel search hardware.
3Adaptability or versatility
If the number of entry regions in the conversion table increases to improve compression rates, then the compression capability is enhanced, but the retrieval time increases
Solution Approach 1:
The conversion table can accommodate a large total number of entry regions across multiple banks, providing extensive compression capability. However, the determination unit identifies the specific bank containing the target entry, and the search is limited to only the entries within that bank. This segmentation allows the system to maintain large conversion tables for high compression rates while keeping individual search operations fast by limiting the search scope to one bank at a time.
Data Source
AI summary
A technique to prevent a retrieving process of a conversion rule from taking a longer time is provided. Provided are a conversion table in which a predetermined number of entry regions capable of storing a mapping between first data and second data smaller in size than the first data are included, the predetermined number of entry regions are divided into a plurality of bank regions, and each of the plurality of bank regions includes entry regions smaller in number than the predetermined number, a determination unit configured to uniquely determine, among the plurality of bank regions, a bank region corresponding to the first data, and a processing unit configured to search entry regions of the determined bank region the predetermined number of times each or a smaller number of times than the predetermined number each, output, when the second data corresponding to the first data is stored, the second data, and when the second data corresponding to the first data is not stored, register the second data corresponding to the first data in an entry region in which another piece of second data is not stored and output the first data.