Read Level Edge Find Operations in Memory Sub-systems
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Solution Overview
Problem
Conventional memory sub-systems lack the capability to measure the read window budget (RWB) within the system product, failing to accurately characterize programming distributions and account for system-specific conditions such as use cases, workloads, and environment effects, which can lead to defects causing abnormal distributions.
Innovation Solution
The implementation of a read level edge find operation within the memory sub-system allows for in situ measurement of RWB by incrementally offsetting read level thresholds until they cross a target bit error rate (BER), interpolating between BER samples to compute accurate distribution edge locations, enabling accurate measurement of distribution widths and valley margins without relying on known program data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional memory sub-systems use traditional measurement methods, then the measurement process is simple, but the measurement precision of read window budget (RWB) is insufficient and cannot accurately characterize programming distributions
Solution Approach 1:
The patent performs preliminary actions by incrementally offsetting read level thresholds and measuring bit error rates at multiple offset values before the final RWB calculation. This preliminary sampling enables accurate interpolation to determine distribution edges at target BER, resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent replaces physical mechanical measurement systems with electrical signal-based BER sampling and computational interpolation methods. By substituting direct physical measurement with electrical threshold offsetting and mathematical interpolation, the system achieves high precision RWB measurement without requiring complex physical measurement apparatus
2Adaptability or versatility
If conventional methods are used, then the operation is straightforward, but the system cannot account for system-specific conditions such as use cases, workloads, and environment effects
Solution Approach 1:
The patent changes measurement parameters by incrementally offsetting read level thresholds and adjusting measurement conditions to account for different system environments, workloads, and temperature conditions. This enables the system to adapt to various operating conditions while characterizing programming distributions accurately
Solution Approach 2:
The patent implements feedback mechanisms by measuring BER at multiple offset values and using these measurements to interpolate and determine accurate distribution edge locations. The feedback from BER samples enables the system to adapt to system-specific conditions and accurately characterize distributions under varying environmental factors
3Reliability
If known program data is used for measurement, then the measurement process is simplified, but the measurement results do not reflect actual system product conditions
Solution Approach 1:
The patent enables the memory sub-system to perform self-measurement of RWB using its own internal resources and actual operating data. By eliminating the need for external known program data and using self-generated BER samples, the system achieves reliable measurements that reflect actual product conditions while maintaining ease of implementation through integrated measurement capabilities
Data Source
AI summary
A processing device performs operations including receiving a request to locate one or more distribution edges of one or more programming distributions of a memory cell, the request specifying a target error rate for the one or more programming distributions, measuring at least one error rate sample of a first programming distribution selected from the one or more programming distributions, and determining a location of a first distribution edge of the first programming distribution at the target error rate based on a comparison of the at least one error rate sample of the first programming distribution against the target error rate.