Parallel Neural Coding for High-Ratio, High-Speed Data Compression
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Solution Overview
Problem
Existing data compression and decompression systems face challenges in achieving both high compression ratios and high processing speeds, particularly in the context of IoT data, which often involves large volumes of multidimensional data.
Innovation Solution
A parallel processing approach using a neural network-based model divides data into predetermined units for parallel coding processes, employing a compressor and decompressor configuration with components like encoder filters, FM tilers, quantizers, and entropy encoders/decoders on parallel processing devices to enhance speed and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If an advanced model such as a neural network is used for data compression, then compression ratio is improved, but processing speed deteriorates
Solution Approach 1:
The patent divides the data compression and decompression process into multiple independent coding units that can be processed in parallel. Each coding unit processes a specific portion of the input data independently, allowing simultaneous execution across multiple processing cores. This segmentation maintains the advanced neural network model's compression effectiveness while enabling parallel processing to overcome the speed limitation.
2Productivity
If data is processed in parallel using multiple cores, then processing speed is improved, but device complexity increases
Solution Approach 1:
The patent segments the computational workload into distinct coding units that can be distributed across multiple processing cores. Each core handles independent coding units with identical processing logic, which simplifies the overall system architecture compared to complex distributed algorithms. The segmentation enables linear scaling of processing speed with the number of cores while maintaining manageable complexity at each processing node.
Data Source
AI summary
Both of a high compression ratio and a high processing speed are achievable. In a data compression and decompression system that includes a parallel processing device performing a plurality of processes in parallel, the parallel processing device divides original data into a plurality of data by a predetermined unit. The parallel processing device performs coding processes on the plurality of data in parallel using a predetermined model to create a plurality of coded data. The parallel processing device creates compressed data of the original data from the plurality of coded data.