Multi-Plane Memory Programming for Accurate Defective Block Retirement
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Solution Overview
Problem
Existing memory sub-systems face issues during multi-plane programming operations due to defective blocks causing incorrect data programming and erroneous retirement of good blocks, leading to increased latency and complexity.
Innovation Solution
A memory sub-system controller manages defective blocks by performing verification checks, maintaining bad block and incident data structures, and conducting data integrity checks to identify and correct erroneous block retirements, thereby reducing the retirement of good blocks and improving performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If defective blocks are managed during multi-plane programming operations, then data integrity is improved, but device complexity increases
Solution Approach 1:
The patent performs verification checks on blocks before completing programming operations, and maintains incident counters that track suspicious blocks across multiple program cycles. This preliminary detection and tracking approach identifies defective blocks early, preventing incorrect data programming while managing complexity through structured data structures rather than complex control logic.
2Measurement precision
If verification checks are performed on all blocks, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent applies verification checks selectively rather than uniformly to all blocks. Incident counters are maintained only for blocks that exhibit suspicious behavior, and verification resources are concentrated on these targeted blocks across multiple program cycles. This local focus maintains high verification accuracy for problematic blocks while minimizing time loss on blocks that are likely to be fine.
3Reliability
If incident counters are maintained for all blocks, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments the block population into different categories based on their verification history. Incident counters are maintained in a structured data structure that organizes blocks by their suspicious behavior patterns, allowing efficient tracking and management. This segmentation approach improves reliability by systematically identifying defective blocks while managing complexity through organized data structures rather than unmanaged complexity.
Data Source
AI summary
Systems and methods are disclosed including a memory device and a processing device operatively coupled to the memory device. The processing device can perform operations comprising performing a set of write operations on a first block in a first plane of the memory device and on a second block in a second plane of the memory device, performing a program verification check on the first block, and responsive to determining that the first block fails the program verification check, retiring the first block and the second block.