Probabilistic Data Integrity Scan Interval Management
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Solution Overview
Problem
Memory subsystems face challenges in maintaining data integrity due to read disturb errors, which occur when read operations on one memory row affect neighboring rows, leading to errors and reduced reliability, especially as memory density increases. Existing solutions that track read disturb using counters can result in host latency and resource inefficiency.
Innovation Solution
Implementing a probabilistic data integrity scheme that restricts the interval between data integrity scans to minimize resource consumption and avoid close proximity scans, thereby mitigating read disturb errors by tracking read operations and performing scans only when necessary, ensuring consistent and efficient data retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data integrity scans are performed frequently to detect read disturb errors, then data reliability is improved, but resource consumption and host latency increase
Solution Approach 1:
The patent implements dynamic scan interval adjustment where the time between data integrity scans is not fixed but adapts based on observed error rates and memory conditions. When error rates are low, scan intervals are extended to reduce resource consumption; when error rates increase, intervals are shortened to maintain reliability. This dynamic approach resolves the contradiction by making scan frequency flexible rather than static.
Solution Approach 2:
The system changes the parameter of scan interval duration based on operational conditions and observed memory behavior. By monitoring error rates and adjusting the scan interval parameter accordingly, the system optimizes the balance between detecting read disturb errors (reliability) and minimizing the performance impact of scans (resource consumption).
2Reliability
If data integrity scans are performed frequently to ensure data integrity, then error detection capability is improved, but host latency increases
Solution Approach 1:
The scan interval is made dynamic, adjusting based on observed memory error patterns. When the memory shows stable behavior with low error rates, the system extends scan intervals, thereby reducing host latency. When error patterns indicate potential read disturb issues, the system shortens intervals to maintain error detection capability. This dynamic adaptation resolves the time-latency contradiction.
Solution Approach 2:
The patent implements periodic data integrity scans with variable periods. Rather than continuous scanning or fixed-interval scanning, the system performs scans at optimized periodic intervals that adapt to memory conditions. This periodic approach with adjustable timing maintains error detection while minimizing disruption to host operations and reducing latency.
3Speed
If scan intervals are shortened to reduce host latency, then responsiveness is improved, but resource consumption increases
Solution Approach 1:
The system dynamically adjusts scan interval length based on memory conditions and observed error rates. When memory is stable, intervals are extended to conserve resources; when responsiveness is needed or errors are detected, intervals are shortened. This dynamic behavior resolves the contradiction between speed (responsiveness) and resource consumption by adapting to actual conditions rather than using a fixed interval.
Solution Approach 2:
The scan interval parameter is changed based on operational needs and observed memory behavior. The system monitors memory conditions and adjusts the interval parameter to optimize the trade-off between responsiveness (shorter intervals) and resource consumption (longer intervals). This parameter adaptation resolves the technical contradiction.
4Productivity
If probabilistic data integrity scheme is implemented to reduce resource consumption, then efficiency is improved, but scan interval optimization is needed
Solution Approach 1:
The patent implements a self-adjusting scan interval mechanism where the system automatically monitors its own memory error patterns and adjusts scan intervals without external intervention. The memory subsystem serves itself by detecting read disturb errors, analyzing error rates, and autonomously optimizing scan timing. This self-service approach maintains efficiency while managing the complexity of interval optimization internally without requiring complex external control.
Solution Approach 2:
The system implements feedback loops where scan results and observed error rates feed back into the scan interval determination logic. This feedback mechanism allows the system to learn from past performance and automatically optimize scan intervals, improving efficiency while managing complexity through adaptive control rather than rigid predetermined schedules.
Data Source
AI summary
Exemplary methods, apparatuses, and systems include receiving read operations. The read operations are divided into a current set of a sequence of read operations and one or more other sets of sequences of read operations. An aggressor read operation is selected from the current set. A position in the sequence of read operations in the current set is determined such that the position that is preceded by at least a minimum number of read operations following a previous data integrity scan in a previous set of read operations. A data integrity scan is performed on a victim of the aggressor read operation at the determined position in the sequence of the current set of read operations.