Memory Subsystem Data Relocation via Power-On-Time Scaling
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Solution Overview
Problem
Conventional memory sub-systems frequently relocate data based on power-on events, leading to excessive Program/Erase (P/E) cycles, which shorten the memory component's lifespan and waste resources, as they do not accurately account for data storage duration.
Innovation Solution
A memory sub-system that estimates data occupancy time using a power-on-time (POT) value and applies a scaling factor to determine when data relocation is necessary, thereby reducing the frequency of P/E cycles and extending the memory's lifespan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data relocation is performed frequently based on power-on events, then data integrity is improved, but the number of P/E cycles increases and memory lifespan decreases
Solution Approach 1:
The patent changes the parameter basis for data relocation from simple power-on event counting to a time-based parameter (POT value representing actual operational hours). This allows the system to relocate data based on actual usage duration rather than frequency of power events, reducing unnecessary relocations and extending memory lifespan while maintaining data integrity.
2Reliability
If data relocation is performed daily, then data integrity is improved, but processing resources are wasted
Solution Approach 1:
The patent implements periodic data relocation based on time intervals (e.g., every 720 hours or 30 days) rather than daily periodic action. This reduced frequency of periodic operations conserves processing resources and energy while still ensuring data integrity through regular, but less frequent, relocation operations.
3Device complexity
If data relocation is performed based on power-on events, then data occupancy time tracking is simplified, but accuracy of relocation timing is reduced
Solution Approach 1:
The patent introduces a POT (Power-On-Time) value as an intermediary mechanism that accurately tracks actual operational time. This intermediary provides precise measurement of data occupancy time without significantly increasing system complexity, as it can be implemented through standard timer/counters that accumulate operational hours.
Data Source
AI summary
A total estimated occupancy value of a first data on a first data block of a plurality of data blocks is determined. To determine the total estimated occupancy value of the first data block, a total block power-on-time (POT) value of the first data block is determined. Then, a scaling factor is applied to the total block POT value to determine the total estimated occupancy value of the first data block. Whether the total estimated occupancy value of the first data block satisfies a threshold criterion is determined. Responsive to determining that the total estimated occupancy value of the first data block satisfies the threshold criterion, data stored at the first data block is relocated to a second data block of the plurality of data blocks.


