Page Type-Aware Data Migration Technique for Read Disturb Management of NAND Flash Memory

Read disturb is a phenomenon in which the cells of all unselected wordlines (WLs) within a block are soft programed while reading a selected WL, which causes errors. To solve the problem of read disturb, read reclaim (RR) operations, which migrate deteriorated block data to a new free block, are executed when the read count of the deteriorated block exceeds a preset threshold. RR requires additional operations, such as error correction, reprogramming, block erasure, and occupying I/O. So as the number of RR operations increases, the performance and reliability of the memory degrade. We observe that read disturb affects pages within a block differently according to page types. With this perspective, we propose Page Type-aware Data Migration technique (PTDM) technique, which migrates pages within blocks according to the vulnerability to read disturb. Shifting RR from the conventional block level to the page level improves the efficiency of the memory by reducing data migration. Also, we propose distributing read-hot data into several blocks during migration to reduce read disturb impact. Our experimental results show that the proposed method can reduce the amount of RR data migration and the overall erasure counts by 39.53% and 21.69%, respectively.

Automated summary

Read disturb is a phenomenon where unselected wordlines in a block are affected while reading a selected wordline, causing errors. To address this, read reclaim operations migrate deteriorated block data to a new free block when a preset threshold is exceeded. However, these operations result in decreased performance and reliability. To mitigate this, we propose a Page Type-aware Data Migration technique (PTDM) that migrates pages within blocks based on their vulnerability to read disturb. Shifting from block-level to page-level read reclaim improves memory efficiency, and distributing read-hot data across multiple blocks reduces read disturb impact. Experimental results show a significant reduction in RR data migration and overall erasure counts using our proposed method.