Data Analysis and Prediction for NAND Flash Decoding Status

Abstract

This paper investigates the feasibility of predicting the NAND flash decoding status by machine learning algorithms. The memory system can handle the future decoding failure in advance according to the prediction results so that to relieve the penalties. Several data preprocessing techniques to improve the accuracy are addressed. A thorough analysis flow is given and the experimental results show significant improvements. Incorporating with proper memory error handling schemes, a 34% improvement in throughput can be achieved.