Endurance prediction and error Reduction in NAND flash using machine learning

@article{Fitzgerald2017EndurancePA,
  title={Endurance prediction and error Reduction in NAND flash using machine learning},
  author={Barry Fitzgerald and Damien Hogan and Conor Ryan and Joe Sullivan},
  journal={2017 17th Non-Volatile Memory Technology Symposium (NVMTS)},
  year={2017},
  pages={1-8}
}
NAND flash is rapidly becoming the media of choice for data storage, due in part to its speed and low power consumption. However, flash wears out through repeated program-erase (P-E) cycling, causing the raw bit error rate (RBER) to increase. Error correction codes (ECCs) are used to detect and correct errors in a sector of data called a codeword. An uncorrectable error occurs when the number of bit errors in a codeword exceeds a certain level, meaning the data cannot be recovered. This… CONTINUE READING