Zone Memory Parity Layout for Block Failure Protection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional memory sub-systems face high overprovisioning and resource inefficiency due to the need for multiple SLC cache blocks per QLC block, which reduces competitiveness and increases resource usage during block programming in zone-based memory systems.
Innovation Solution
Implementing a block failure protection method that uses a RAIN technique for error correction, where non-parity zones are matched and parity is generated across these zones, stored in parity zones, and used for data recovery, reducing the number of SLC blocks required per non-cache block.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple SLC cache blocks are used per QLC block for block failure protection, then data reliability is improved, but device complexity and overprovisioning increase
Solution Approach 1:
The memory device is segmented into multiple zones (host-write zones and parity zones) that can be independently managed. This segmentation allows the system to distribute data and parity across different zones, enabling block failure protection without requiring multiple SLC cache blocks per QLC block, thus reducing overprovisioning while maintaining reliability
Solution Approach 2:
A zone binning algorithm acts as an intermediary mechanism that matches host-write zones with corresponding parity zones based on zone characteristics. This intermediary layer enables intelligent pairing of zones for parity generation, allowing the system to achieve block failure protection through cross-zone redundancy rather than through traditional multiple SLC cache blocks per QLC block
2Reliability
If multiple SLC cache blocks are used per QLC block for block failure protection, then data reliability is improved, but resource efficiency deteriorates
Solution Approach 1:
Parity zones serve multiple functions: they store parity data for block failure protection, act as additional storage capacity, and can be dynamically matched with different host-write zones based on zone characteristics. This multi-functionality allows the same parity infrastructure to provide both reliability and additional storage resources, improving overall resource efficiency compared to dedicating separate SLC cache blocks solely for protection
Solution Approach 2:
The system dynamically changes zone parameters (such as zone matching criteria and parity generation parameters) based on workload characteristics and zone status. The zone binning algorithm adjusts which zones are paired together based on parameters like zone capacity, wear level, and performance characteristics, enabling optimal resource utilization while maintaining block failure protection
Data Source
AI summary
Various embodiments provide block failure protection for a memory sub-system that supports zones, such a memory sub-system that uses a RAIN (redundant array of independent NAND-type flash memory devices) technique for data error-correction. For some embodiments, non-parity zones of a memory sub-system that are filling up at a similar rate are matched together, a parity is generated for stored data from across the matching zones, and the generated parity is stored in a parity zone of the memory device.


