Dynamic PV Targets Across Memory Distributions for Wear Compensation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional memory sub-systems fail to dynamically adjust program verify (PV) targets of initial and last programming distributions, leading to reduced endurance due to fixed guard bands that limit available margin for calibration, thereby affecting reliability and longevity.
Innovation Solution
A program targeting (PT) operation that adjusts PV targets based on a set of rules, utilizing continuous read level calibration (cRLC) to balance bit error rates (BER) and equalize valley margins across logical page types, allowing for dynamic compensation of wear and improving endurance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed guard bands are used for initial and last programming distributions, then reliability is maintained, but endurance is reduced due to limited available margin for calibration
Solution Approach 1:
The patent applies dynamics by transitioning from fixed PV targets to dynamically adjustable PV targets. The system continuously monitors valley margins and BER metrics, then adjusts PV targets for initial and last programming distributions in real-time to optimize the balance between reliability and endurance throughout the memory device's operational lifetime.
Solution Approach 2:
The patent implements parameter changes by modifying PV target values based on measured valley margins and BER performance. The system changes physical parameters (PV targets) in response to operational conditions, allowing the memory device to adapt its programming characteristics to maintain reliability while extending endurance through optimized margin utilization.
2Ease of manufacture
If PV targets of initial and last programming distributions are kept fixed, then manufacturing simplicity is maintained, but calibration margin is limited reducing longevity
Solution Approach 1:
The patent applies preliminary action by establishing initial PV targets during manufacturing with built-in adjustability. The system pre-configures the capability for PV target adjustment and includes the necessary control logic and monitoring mechanisms, enabling future dynamic optimization without complicating the core manufacturing process.
Solution Approach 2:
The patent implements self-service through automated PV target adjustment based on real-time monitoring of valley margins and BER metrics. The memory device autonomously adjusts its own PV targets without external intervention, using embedded control logic to optimize performance and extend longevity while maintaining manufacturing simplicity.
3Duration of action of moving object
If dynamic adjustment of PV targets is implemented, then endurance is improved through optimized margin usage, but device complexity increases
Solution Approach 1:
The patent applies feedback by continuously monitoring valley margins and BER metrics, then using this information to adjust PV targets. The system implements closed-loop control where performance metrics feed back into the adjustment mechanism, enabling intelligent optimization of endurance while managing device complexity through purposeful, data-driven adjustments.
Solution Approach 2:
The patent implements self-service through automated PV target adjustment based on real-time monitoring of valley margins and BER metrics. The memory device autonomously adjusts its own PV targets without external intervention, using embedded control logic to optimize performance and extend longevity while managing device complexity.
4Ease of operation
If fixed guard bands are used, then ease of operation is maintained, but available margin for calibration is reduced affecting reliability
Solution Approach 1:
The patent applies dynamics by transitioning from static guard bands to dynamic PV target adjustment. The system automatically adapts PV targets based on measured valley margins and BER performance, maintaining ease of operation through automation while improving reliability by optimizing margin utilization in real-time throughout the device's operational life.
Data Source
AI summary
A processing device determines a plurality of computing error metrics that are indicative of operational characteristics between programming distributions within the memory device. The processing device performs a program targeting operation on a memory cell of the memory device to calibrate one or more program verify (PV) targets associated with the programming distributions. Performing the program targeting operation comprises the processing device selecting a rule from a predefined set of rules based on the plurality of computing error metrics, wherein the predefined set of rules corresponds to an adjusting of a PV target of a last programming distribution. In addition, the processing device adjusts, based on the selected rule, the one or more PV targets of a plurality of PV targets associated with the programming distributions, wherein the one or more PV targets correspond to one or more respective voltage values for programming memory cells of the memory device.