Differential Evolution Algorithm With Asymmetric Coding for Solving the Reliability Problem of 3D-TLC CT Flash-Memory Storage Systems

In recent years, NAND flash memory has been widely used in mobile devices, laptops, desktops, and data center storage systems due to its low-power consumption, high performance, high density, lightweight, shock resistance, and high-reliability natures. However, as the stacked layers and the storage density increase, flash memory also suffers from a higher raw bit error rate (RBER) and shorter lifetime. Observing that reliable cell states suffer from less data retention errors and program disturbance, we propose a differential evolution coding scheme to increase the probability of storing data in more reliable cell states, thereby reducing the RBER. We conducted the experiments over a development platform of SSD storage device with 3D-TLC charge trap (CT) NAND flash memory. The experimental results showed that the proposed differential evolution algorithm with asymmetric coding scheme could averagely reduce RBER by 48.88%, 65.45%, 52.61 %, 61.99 %, 80.19%, and 33.18% compared with baseline, asymmetric coding algorithm, asymmetric coding scheme with stripe-pattern elimination algorithm, UAC-nLC, word-line batch score modulation programming, and SCB schemes.

Automated summary

NAND flash memory is widely used in various devices due to its low-power consumption, high performance, and reliability. However, as the storage density increases, the error rate also rises. To address this issue, researchers propose a differential evolution coding scheme to store data in more reliable cell states and reduce the error rate.