R&D: CeSR+Assisted LDPC, Holistic Strategy to Improve MLC NAND Flash Reliability
Compared with NRC strategy, CeSR can reduce RBER of hot and cold data by up to 20/30% and 85/13%, respectively.
This is a Press Release edited by StorageNewsletter.com on May 14, 2020 at 2:35 pmIEEE Access has published an article written by Hongwei Qin, Yutong Zhao, Dan Feng, Jingning Liu, and Wei Tong, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
Architecture of CeSR + Assisted LDPC
Abstract: “NAND flash suffers from program interference and retention errors, which negatively affect its reliability. Existing schemes preprocess raw data before writing them to reduce Raw Bit Error Rate (RBER) and leverage ECCs (such as LDPC codes) to reduce Uncorrectable Bit Error Rate (UBER). Prior arts failed to take into account the counteractions between the program interference and retention errors.Thus, they may lead to sub-optimal error avoidance. Besides, after the preprocessing procedure, data randomness may be affected. Since NAND flash shows numerical-correlated error characteristics, there’s a potential to provide such information to LDPC codes to further improve performance. In this article, we propose a holistic strategy consisting of two coupled procedures to enhance flash reliability. First, we use our previously proposed CeSR strategy to reduce RBER. Second, we improve the existing LDPC codes and name it Assisted LDPC strategy to reduce UBER. The Assisted LDPC is deeply coupled with CeSR. It leverages the data pattern after CeSR to improve the decoding success rate and accelerate the decoding procedure. The evaluation shows that compared with the state-of-the-art NRC strategy, CeSR can reduce the RBER of hot and cold data by up to 20.30% and 85.13%, respectively. Besides, compared with the traditional LDPC, the Assisted LDPC decoding strategy can increase the decoding success rate by up to 97% for cold data and reduce the average decoding iteration number of MSB pages for hot and cold data by up to 31.6% and 73.9%, respectively.“