Memory Sector Failure Prediction via Iterative Check Patterns
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Solution Overview
Problem
Current systems face challenges in accurately predicting and managing sector failures in Low-Density Parity Check (LDPC) codec iterative systems, leading to inefficient power usage and potential data loss due to unexpected sector failures.
Innovation Solution
A method and system that perform satisfaction checks on memory sectors, analyze the number and location of unsatisfied checks across multiple iterations to identify periodic patterns, and proactively remove sectors prone to failure, thereby optimizing power management and preventing data loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satisfaction checks are performed on memory sectors and unsatisfied checks are tracked across multiple iterations, then prediction accuracy of failing sectors is improved, but system complexity increases
Solution Approach 1:
The system performs satisfaction checks on memory sectors during normal operation and tracks unsatisfied checks across multiple iterations before failure occurs. By conducting these checks in advance and monitoring patterns over time, the system identifies failing sectors proactively rather than reactively, improving prediction accuracy while managing complexity through structured monitoring protocols.
Solution Approach 2:
The system continuously monitors the number and location of unsatisfied checks across global iterations and uses this feedback to detect periodic patterns that indicate impending sector failure. This feedback mechanism allows the system to adapt its monitoring based on observed patterns, improving prediction accuracy while controlling complexity through pattern-based detection algorithms.
2Reliability
If sectors identified as prone to failure are removed from memory, then system reliability is improved, but productivity decreases due to reduced storage capacity
Solution Approach 1:
The system identifies and removes only those sectors that show clear periodic patterns of unsatisfied checks indicating certain failure, rather than removing sectors based on single instances or random selection. This preliminary identification based on pattern analysis ensures that only truly failing sectors are removed, maximizing reliability improvement while minimizing the impact on overall storage capacity.
Solution Approach 2:
The system applies different monitoring and management strategies to different sectors based on their individual performance characteristics. Sectors with periodic patterns of unsatisfied checks are identified and removed, while sectors maintaining satisfactory performance continue to be used. This localized approach ensures that reliability improvements are achieved without unnecessarily reducing overall storage capacity.
3Reliability
If power is allocated to sectors identified as prone to failure, then data recovery capability is improved, but energy consumption increases
Solution Approach 1:
The system performs satisfaction checks and tracks unsatisfied checks patterns in advance to identify failing sectors before they actually fail. By detecting the periodic patterns of unsatisfied checks, the system can proactively remove these sectors from service, preventing data loss and eliminating the need for continuous power allocation to sectors that are already failing, thus reducing energy consumption while maintaining data recovery capability through proactive identification.
Data Source
AI summary
A method and system is disclosed for identification and removal of a memory sector prone to failure. The method performs satisfaction checks on the memory sector and monitors and stores returned Unsatisfied Checks (USC) for analysis by a pattern recognition algorithm. Once a first global iteration is pattern matched with a second global iteration from the sector, the method determines the period of the repetitive pattern. The method then identifies, as the sector prone to failure, the sector having the defined pattern and period. Once identified, the method uses a power management scheme to remove the sector prone to failure from further use by the memory system and displays to a user the details of the action taken.