Non-Volatile Storage Data Refresh Based on Programming Timing
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Solution Overview
Problem
Non-volatile storage devices face challenges in maintaining data integrity due to environmental factors like temperature variations, leading to erroneous data bits and the need for frequent refreshing, which can overstress the memory cells or hinder user access.
Innovation Solution
The method involves determining the need for data refresh in non-volatile storage devices based on the condition of the data and the timing of the last programming, identifying candidate blocks for refresh, and performing the refresh procedure on these blocks without necessarily detecting data integrity problems within them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is refreshed frequently to maintain data integrity, then data reliability is improved, but memory cell stress increases and user access is hindered
Solution Approach 1:
The system performs preliminary detection of data integrity issues by monitoring threshold voltage shifts and error patterns. When degradation is detected, refresh operations are triggered proactively before complete data loss occurs, rather than continuously refreshing all data regardless of actual need.
Solution Approach 2:
Instead of uniformly refreshing all memory blocks, the system identifies specific blocks or regions exhibiting data integrity issues and applies refresh operations only to those localized areas. This selective approach maintains data reliability where needed while minimizing unnecessary stress on healthy memory cells.
2Reliability
If data is refreshed frequently to maintain data integrity, then data reliability is improved, but user memory access is hindered
Solution Approach 1:
The system performs preliminary detection of data integrity issues by monitoring threshold voltage shifts and error patterns. When degradation is detected, refresh operations are triggered proactively before complete data loss occurs, rather than continuously refreshing all data regardless of actual need.
Solution Approach 2:
Instead of uniformly refreshing all memory blocks, the system identifies specific blocks or regions exhibiting data integrity issues and applies refresh operations only to those localized areas. This selective approach maintains data reliability where needed while minimizing unnecessary stress on healthy memory cells.
3Reliability
If error correction algorithms are applied to detect and correct corrupted data, then data reliability is improved, but processing time increases
Solution Approach 1:
The system performs preliminary detection of data integrity issues by monitoring threshold voltage shifts and error patterns. When degradation is detected, refresh operations are triggered proactively before complete data loss occurs, rather than continuously refreshing all data regardless of actual need.
Solution Approach 2:
For memory blocks showing signs of degradation, the system accelerates the refresh process by applying stronger programming pulses for longer durations, effectively skipping through the gradual degradation stages and directly restoring the data to its intended state, thereby reducing the time needed for correction.
Data Source
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AI summary
Techniques are disclosed to refresh data in a non-volatile storage device often enough to combat erroneous or corrupted data bits, but not so often as to interfere with memory access or to cause excessive stress on the memory cells. One embodiment includes determining to perform a refresh of data stored in a first group of non- volatile storage elements in a device based on a condition of data in the first group, determining that a second group of non-volatile storage elements in the device should undergo a refresh procedure based on when the second group of non-volatile storage elements were last programmed relative to when the first group of non- volatile storage elements were last programmed, and performing the refresh procedure on the second group of non-volatile storage element.