Flash Memory Wear Leveling via Hot-Cold Data Classification
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Solution Overview
Problem
Existing wear leveling techniques in flash memory devices are insufficient in reducing data movements, which limits the extension of the lifespan of flash memory.
Innovation Solution
A method and memory device that utilize a predictive model to classify incoming data as hot or cold, and then write the data to blocks based on their erase counts, with hot data written to blocks with the lowest erase count and cold data written to blocks with the highest erase count.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If existing wear leveling techniques are used to distribute write operations evenly, then the lifespan of flash memory is extended, but the number of data movements is not sufficiently reduced
Solution Approach 1:
The system performs preliminary classification of incoming data as hot or cold data before writing to blocks. This advance classification allows the wear leveling system to pre-determine the optimal block destination based on data characteristics, avoiding future data movement operations and reducing the total number of data movements while extending flash memory lifespan
Solution Approach 2:
The system applies different wear leveling strategies to different types of data. Hot data is written to blocks with lowest erase count while cold data is written to blocks with highest erase count. This localized differentiation based on data characteristics optimizes the wear distribution and minimizes data movements for each data type
2Reliability
If static wear leveling is used to redistribute all blocks periodically, then wear is evenly distributed, but the complexity of data management increases
Solution Approach 1:
Instead of applying uniform wear leveling to all blocks, the system classifies data into hot and cold categories and applies different wear leveling strategies to each category. This localized approach maintains wear distribution uniformity while simplifying data management by avoiding the need to periodically redistribute all blocks
Solution Approach 2:
The system automatically determines the appropriate block destination for each data type based on current block erase counts and data characteristics. This self-service mechanism eliminates the need for complex periodic redistribution operations while maintaining reliable wear distribution
Data Source
AI summary
The application provides a method and a memory device for performing wear leveling in a memory device. The method includes: receiving data to be written transmitted by a host in the memory device; predicting the data to be written as a first type of data or a second type of data; referencing an erase count table in an erase count table buffer of the memory device; and when the data to be written is predicted as the first type of data, writing the data to be written into the block with a highest erase count among these blocks, and when the data to be written is predicted as the second type of data, writing the data to be written into the block with a lowest erase count among these blocks.