Classified Multi-Path Storage for Noise and Redundancy Reduction
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Solution Overview
Problem
Existing storage systems fail to effectively address noise and data redundancy in data processing, leading to increased processing time and reduced efficiency, particularly in applications like machine learning and artificial intelligence.
Innovation Solution
Implementing a storage system with dual data paths, one path without data compression for uncompressed data and another with data compression using a processor to preprocess data, addressing noise and redundancy before storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored without preprocessing, then storage speed is improved, but data quality deteriorates due to noise and redundancy
Solution Approach 1:
The patent applies preliminary action by preprocessing data (removing noise and redundancy) before storage. The system includes a preprocessing unit that cleans data before it enters the storage unit, ensuring high data quality is achieved in advance rather than requiring post-processing later.
2Manufacturing precision
If data preprocessing is performed, then data quality is improved, but processing time increases
Solution Approach 1:
The patent performs data preprocessing in advance before storage operations, so that when data is retrieved, it is already clean and ready for use. This eliminates the need for repeated processing during read operations, reducing overall processing time despite the initial preprocessing step.
3Productivity
If multiple data paths are implemented, then data processing efficiency is improved, but device complexity increases
Solution Approach 1:
The patent segments the storage system into distinct functional units: a preprocessing unit and a storage unit with multiple data paths. Each unit has a specific function, allowing parallel processing of data through multiple paths while maintaining manageable complexity through clear functional separation.
Solution Approach 2:
The storage unit is designed with multi-functionality, serving both as a preprocessing stage and a storage stage with multiple data paths. This universal design allows the same hardware structure to handle different data processing tasks, improving efficiency without proportionally increasing complexity.
Data Source
AI summary
In some implementations, a storage system may receive, via a system controller of the storage system, a write command and data associated with the write command. The storage system may classify, via the system controller, the data. The storage system may associate, via the system controller, the data with a queue based on classifying the data. The storage system may retrieve, via a processor of the storage system, the data associated with the queue. The storage system may compress, via the processor, the data to form compressed data for storage in a memory device of the storage system based on the write command.


