Data-Age Memory Management with Validity-Rate Feedback
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Solution Overview
Problem
Existing memory sub-systems experience degraded performance due to inefficient media management operations that do not account for the amount of valid data, rate of change in valid data, and age of data, particularly in critical and demanding applications like mobile deployments.
Innovation Solution
Implement a data age and validity-based memory management system that compares the rate of change of valid translation unit counts to a bin transition rate to optimize media management operations such as garbage collection and wear leveling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional media management operations are performed without considering data age and validity dynamics, then device complexity is reduced, but memory sub-system performance degrades and write amplification increases
Solution Approach 1:
The patent applies parameter changes by monitoring multiple dynamic parameters (valid translation unit counts, data age, rate of change) and using these parameters to determine the timing and type of media management operations. The system changes operational parameters based on real-time data dynamics rather than using fixed schedules, thereby improving performance while managing complexity through intelligent adaptation.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring valid translation unit counts, calculating rates of change, and using this feedback information to dynamically adjust media management operations. This closed-loop approach allows the system to respond to actual data dynamics, improving performance while maintaining manageable complexity through data-driven decision making.
2Reliability
If media management operations are performed frequently to maintain performance, then reliability is improved, but write amplification increases and energy consumption rises
Solution Approach 1:
The patent applies dynamics by making media management operations adaptive rather than static. The system dynamically determines when to perform operations based on real-time monitoring of valid translation unit counts and their rates of change. This dynamic approach ensures operations are performed only when necessary to maintain reliability, thereby reducing unnecessary energy consumption while preserving system reliability.
Solution Approach 2:
The system performs preliminary monitoring and analysis of data dynamics before executing media management operations. By calculating rates of change and predicting future states, the system can proactively schedule operations at optimal moments, preventing performance degradation before it occurs while avoiding premature operations that would waste energy.
3Measurement precision
If data age and validity tracking is implemented, then media management precision is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the monitoring task into discrete, manageable components: tracking valid translation unit counts, calculating rates of change, and determining data age. This segmentation allows the system to achieve high measurement precision through multiple focused metrics rather than attempting to monitor all aspects simultaneously, thereby improving precision while keeping individual tracking components relatively simple.
Data Source
AI summary
A method includes determining respective valid translation unit counts of a block of non-volatile memory cells over a period of time, determining a rate of change of the respective valid translation unit counts of the block of non-volatile memory cells over the period of time, comparing the rate of change of the valid translation unit counts to a bin transition rate, and based on comparing the rate of change of the valid translation unit counts to the bin transition rate, performing a media management operation on the block of non-volatile memory cells.