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ASPLOS2026顶会

STRAW: Stress-Aware WL-Based Read Disturbance Management for High-Density NAND Flash Memory

Myoungjun Chun, Jaeyong Lee, Inhyuk Choi, Jisung Park, Myungsuk Kim, Jihong Kim

2026年份
3被引次数

摘要

While NAND flash memory has continuously increased its storage density over decades, this progress has exacerbated the read-disturbance problem. In this work, we identify two fundamental limitations of existing read-disturbance management techniques that trigger read reclaim (RR) at the block granularity: (i) they overlook the heterogeneous reliability impact of read disturbance across individual wordlines (WLs), leading to unnecessary RR in many cases; and (ii) they address read disturbance only after disturbance-induced errors have already accumulated, which forces substantial RR-induced copy overheads in read-disturbance-prone modern NAND flash memory. To address these limitations, we propose STRAW (STRess-Aware Wordline-based read-disturbance management), a new technique that minimizes RR overheads through two key ideas: (i) stress-aware WL-based read reclaim, which monitors the accumulated read-disturbance effect on each WL and reclaims only heavily disturbed WLs, and (ii) stress-reduced read, which mitigates disturbance on valid WLs during each read operation by scaling pass-through voltages based on WL validity. Our experimental results using a modern SSD emulator show that STRAW reduces RR-induced page-copy overhead by 88.6% on average compared with the state-of-the-art technique.

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