3D-TLC NAND闪存的出货前数据保留/读取干扰寿命预测和售后单元错误检测和校正神经网络

Masaki Abe, Toshiki Nakamura, K. Takeuchi
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引用次数: 3

摘要

提出了两种用于3D-TLC (Triple-Level Cell) NAND闪存的神经网络(NN)技术。1)预测出货前测试中芯片分拣的数据保留/读干扰寿命。2)发现并纠正售后的错误。首先,在出货前测试中,基于神经网络的寿命预测(NNLP)预测ECC解码失败率(EDFR)并估计数据保留/读取干扰寿命。基于预测寿命,NNLP对NAND闪存进行分类。其次,在售后市场,基于神经网络的错误检测(NNED)可以检测和纠正错误。NNED将误码率降低了81.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pre-shipment Data-retention/Read-disturb Lifetime Prediction & Aftermarket Cell Error Detection & Correction by Neural Network for 3D-TLC NAND Flash Memory
This paper proposes 2 neural network (NN) techniques for 3D-TLC (Triple-Level Cell) NAND flash memory. 1) Predict data-retention/read-disturb lifetime for chip sorting during preshipment test. 2) Detect and correct errors in aftermarket. First, in pre-shipment test, Neural Network-based Lifetime Prediction (NNLP) predicts ECC decoding fail rate (EDFR) and estimates data-retention/read-disturb lifetime. Based on predicted lifetime, NNLP sorts NAND flash. Second, in aftermarket, Neural Network-based Error Detection (NNED) detects and corrects errors. NNED decreases bit-error rate (BER) by 81.4%.
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