Set-Associative Cache Compression for Real-Time Data Streams
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data compression methods prioritize compression gain over speed, which can be detrimental in time-critical applications like multimedia streaming and wireless data transfer, where rapid data delivery is essential.
Innovation Solution
The implementation of a cache mapping compression (CMC) model that utilizes pseudo cache memory as workspace to enhance compression speed, allowing for high-speed, lossless data compression and reconstruction, with features like low memory consumption, flexible block sizes, and deterministic data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If traditional data compression methods are used to improve compression gain, then compression ratio is improved, but processing speed deteriorates
Solution Approach 1:
The patent segments the data stream into fixed-size blocks and processes them independently through the compression algorithm. This segmentation allows the compression process to be divided into manageable units that can be processed in parallel, significantly improving processing speed while maintaining compression effectiveness through block-based dictionary matching and encoding operations.
Solution Approach 2:
The patent introduces a pseudo-cache memory structure as an intermediary workspace between the input data stream and the compressed output. This pseudo-cache stores recently processed data blocks and facilitates rapid comparison and matching operations, acting as a buffer that accelerates the compression process without sacrificing compression ratio by enabling efficient retrieval of matching patterns.
2Loss of substance
If complex compression algorithms are used to achieve higher compression ratios, then compression gain is improved, but device complexity increases
Solution Approach 1:
The patent employs a straightforward block-based compression algorithm that processes fixed-size data blocks through simple dictionary matching and encoding operations. Rather than using complex adaptive algorithms, the method uses a deterministic approach with fixed block sizes and simple comparison logic, reducing computational overhead and making the compression process suitable for resource-constrained embedded systems and hardware implementations.
Solution Approach 2:
The patent changes the fundamental parameters of the compression approach by using fixed block sizes and a pseudo-cache memory structure with specific metrics (K bits for address, N bits for block size, L bits for line number). These parameter changes simplify the algorithm by eliminating adaptive decision-making complexity while maintaining compression effectiveness through systematic block-based processing and deterministic encoding schemes.
3Loss of substance
If more memory is allocated for compression workspace to improve compression performance, then compression ratio is improved, but memory consumption increases
Solution Approach 1:
The patent uses a pseudo-cache memory structure that stores only the necessary recent data blocks required for compression matching, rather than allocating memory for entire data sets. The pseudo-cache is sized to hold K bits for address references, N bits for current block data, and L bits for line number tracking, providing just enough workspace to maintain compression effectiveness while minimizing memory usage through selective caching of relevant data portions.
Data Source
AI summary
A method is provided for compressing data from a stream of values using one or many distinct memory addresses as workspace, each memo address containing one or many values. The method works by reading two contiguous data values, of length K and N bits, from the stream, as a memory address reference (MAR) and a symbol, respectively. If the symbol does not match any of the values in the memory address pointed by MAR, the symbol replaces one of those values, and a MISS code, followed by the symbol, is appended to the compressed stream. Otherwise, a HIT code is added appended directly to the compressed stream, the code representing the location, of the matched value in the memory address. Advantageously, the workspace behaves analogous to a cache memory used in computer architecture, allowing it to be implemented using content addressable memory or associative arrays in hardware or software implementations, respectively.