Adaptive Proactive Failure Analysis for Non-Volatile Memory
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Solution Overview
Problem
Existing memory systems, particularly storage-class memories, face challenges in proactive failure analysis due to varying endurance levels, thermal issues, and differing electrical and reliability characteristics compared to DRAM-based systems, making it difficult to effectively monitor and manage the health and predictive failure thresholds of non-volatile memory devices.
Innovation Solution
An information handling system that includes a processor, non-volatile memories, and a failure analysis module capable of setting and adapting predictive failure thresholds based on functional and health status parameters of each non-volatile memory, utilizing health registers and ECC checks to monitor and alert on potential failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If adaptive proactive failure analysis is implemented for non-volatile memories, then reliability is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary failure analysis by monitoring health status parameters and adapting predictive failure thresholds before actual failures occur. The failure analysis module continuously evaluates memory health and adjusts thresholds proactively, enabling early detection and prevention of failures rather than reacting after failures happen.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring memory health status parameters and using this information to adapt predictive failure thresholds. The failure analysis module receives feedback from health registers and ECC checks, then adjusts thresholds dynamically based on observed memory behavior and degradation patterns.
2Measurement precision
If predictive failure thresholds are adapted based on health status parameters, then measurement precision is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The failure analysis module acts as an intermediary between raw health status parameters from memory devices and the predictive failure threshold adjustments. It processes and interprets health register data and ECC check results, translating these intermediate measurements into meaningful threshold adaptations without requiring direct complex measurements of failure modes.
Solution Approach 2:
The system replaces direct physical measurement of memory degradation with electrical and logical measurements through health registers and ECC checks. Instead of mechanically probing memory cell degradation, the system uses electrical read operations and error correction code analysis to infer health status and predict failures.
Data Source
AI summary
In accordance with embodiments of the present disclosure, an information handling system may include a processor, a memory communicatively coupled to the processor and comprising a plurality of non-volatile memories, and a failure analysis module comprising a program of instructions, the failure analysis module configured to, when read and executed by the processor, set a predictive failure threshold for each of the plurality of non-volatile memories based at least on functional parameters of such non-volatile memory, and adapt the predictive failure threshold for each of the plurality of non-volatile memories based at least on health status parameters of such non-volatile memory.