Dynamic Valley Margin Control for Memory Endurance
Solution Overview
Problem
Conventional memory sub-systems face challenges in independently adjusting valley margins between programming distributions, which affects retention loss and error rates, as these margins cannot be dynamically controlled across logical page types.
Innovation Solution
The implementation of a method that performs continuous read level calibration (cRLC) and dynamic program targeting (DPT) operations to independently adjust valley margins by scaling difference error counts and calibrating program-verify targets, allowing for dynamic control of valley widths between programming distributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional memory sub-systems use fixed programming distributions, then manufacturing is simpler, but valley margins cannot be independently adjusted leading to higher error rates and retention loss
Solution Approach 1:
The patent implements dynamic programming distributions where PV targets are adjusted based on measured valley margins. The system transitions from fixed programming distributions to dynamic ones that adapt to actual memory cell characteristics, enabling independent adjustment of valley margins for different logical page types to reduce error rates and retention loss.
Solution Approach 2:
The system performs iterative measurements of valley margins between adjacent programming distributions and uses this feedback to adjust PV targets. The controller measures valley margins, compares them against target values, and modifies subsequent programming operations accordingly, creating a closed-loop control system that optimizes programming distributions for minimal error rates.
2Duration of action of stationary object
If valley margins are independently adjusted for different logical page types, then retention loss is reduced, but the programming operation becomes more complex
Solution Approach 1:
The patent segments the programming operation into distinct phases: initial programming, measurement phase, and adjustment phase. By dividing the programming process and treating different logical page types separately with dedicated PV targets, the system can independently optimize valley margins for each segment without overwhelming complexity, thereby improving retention time.
Solution Approach 2:
The system changes programming parameters dynamically by adjusting PV targets based on measured valley margins. Different logical page types receive different PV target adjustments, allowing independent optimization of retention characteristics for each page type while managing complexity through parameter-based control rather than structural changes.
3Duration of action of moving object
If multiple PV targets are adjusted to balance bit error rates, then endurance is improved, but manufacturing precision requirements increase
Solution Approach 1:
The memory sub-system performs self-calibration by measuring its own valley margins and automatically adjusting PV targets without external intervention. This self-service approach reduces the need for high-precision manufacturing by allowing the system to compensate for manufacturing variations through automated measurement and adjustment, thereby improving endurance while reducing manufacturing precision requirements.
Solution Approach 2:
The system uses feedback from valley margin measurements to automatically adjust PV targets, creating a self-correcting mechanism that compensates for manufacturing variations. This feedback loop enables the system to achieve balanced bit error rates and improved endurance without requiring extremely precise initial manufacturing, as the system adapts to actual conditions during operation.
Data Source
AI summary
A system includes a memory device and a processing device, operatively coupled with the memory device, to perform operations including determining first values of a metric that is indicative of a margin for a valley that is located between programming distributions of a memory cell of the memory device. The operations further include determining second values of the metric based on the first values, and adjusting valley margins of the memory cell in accordance with the second values of the metric.