Memory Integrity Scans Using Read-Disturb Risk Estimation
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Solution Overview
Problem
Data integrity in memory devices is compromised due to read disturb effects, leading to errors as memory density increases, necessitating an efficient method to manage data integrity scans.
Innovation Solution
Implementing a data integrity manager that uses risk factor estimation to determine the frequency of scans based on probabilistic determinations and read window budgets, adjusting thresholds and scan frequencies dynamically to mitigate read disturb effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data integrity scan frequency is increased to detect read disturb errors, then data reliability is improved, but system performance and throughput deteriorate due to increased scan overhead
Solution Approach 1:
The patent applies local quality by differentiating scan frequency based on memory region characteristics. High-density memory regions with greater read disturb susceptibility receive more frequent scans, while low-density regions receive less frequent scans. This selective approach maintains data reliability where needed while preserving system throughput by reducing unnecessary scans in lower-risk areas.
Solution Approach 2:
The patent implements dynamic scan frequency adjustment based on real-time risk factor estimation. The scan manager continuously monitors memory device characteristics, read disturb patterns, and error rates to dynamically modify scan frequencies. This dynamic approach optimizes the balance between reliability and productivity by adapting scan intensity to actual memory conditions rather than using fixed frequencies.
2Measurement precision
If comprehensive data integrity scans are performed frequently across all memory regions, then error detection capability is improved, but energy consumption increases due to repeated read operations
Solution Approach 1:
The patent reduces energy consumption by applying error detection resources selectively to high-risk memory regions rather than uniformly across all regions. The risk factor estimation identifies specific memory blocks or regions that require intensive scanning, while low-risk regions receive minimal or no scanning. This local quality approach maintains error detection capability where it is most needed while significantly reducing overall energy consumption from unnecessary scans.
Solution Approach 2:
The patent employs partial action by performing comprehensive scans only on high-risk memory regions identified through risk factor estimation, rather than scanning all memory regions with equal intensity. The scan manager adjusts scan depth and frequency based on estimated risk levels, applying excessive detection effort only where necessary to maintain reliability while conserving energy in lower-risk areas.
3Reliability
If scan frequency is uniformly increased across all memory devices, then overall data integrity is improved, but the complexity of scan management increases
Solution Approach 1:
The patent reduces scan management complexity by implementing self-service through automated risk factor estimation. The scan manager automatically evaluates memory device characteristics, read patterns, and error history to determine optimal scan frequencies for each region without requiring manual configuration or complex external management. This self-service approach maintains high data integrity through differentiated scanning while simplifying management by eliminating manual intervention.
Solution Approach 2:
The patent simplifies scan management through feedback mechanisms where the scan manager continuously monitors error rates, read disturb patterns, and memory device health metrics. This feedback information is used to automatically adjust scan frequencies and allocate scanning resources optimally. The closed-loop feedback system maintains data integrity while reducing management complexity by using real-time data to drive scan decisions rather than requiring static, manually-configured schedules.
Data Source
AI summary
Methods, systems, and apparatuses include determining a read counter for a portion of memory of a memory device satisfies a read threshold. A subportion identifier for a first subportion of the portion of memory is selected in response to the read counter satisfying the threshold. An increment/decrement value is retrieved using the subportion identifier. A second subportion of the portion of memory is determined using the subportion identifier and the increment/decrement value. A data validity scan is performed on the second subportion of memory.