With the progress of the manufacturing process, NAND flash memory has evolved from the single-level cell and multi-level cell into the triple-level cell (TLC). NAND flash memory has physical problems such as the characteristic of erase-before-write and the limitation of program/erase cycles. Moreover, TLC NAND flash memory has low reliability and short lifetime. Thus, we propose a dynamic Huffman coding method that can apply to the write operations of NAND flash memory. The proposed method exploits observations from a Huffman tree and machine learning from data patterns to dynamically select a suitable Huffman coding. According to the experimental results, the proposed method can improve the reliability of TLC NAND flash memory and also consider the compression performance for those applications that require the Huffman coding.

中文翻译：

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一种可靠的TLC NAND闪存的动态霍夫曼编码方法

随着制造工艺的进步，NAND闪存已经从单级单元和多级单元发展为三级单元（TLC）。NAND闪存具有写前擦除的特性和编程/擦除周期的限制等物理问题。此外，TLC NAND闪存可靠性低，寿命短。因此，我们提出了一种动态霍夫曼编码方法，可以应用于 NAND 闪存的写操作。所提出的方法利用霍夫曼树的观察结果和数据模式的机器学习来动态选择合适的霍夫曼编码。根据实验结果，该方法可以提高 TLC NAND 闪存的可靠性，同时考虑到那些需要 Huffman 编码的应用的压缩性能。