Error Generation for 3D NAND Flash Memory
Weihua Liu, Fei Wua, Songmiao Meng, Xiang Chen and Changsheng Xie
Wuhan National Laboratory for Optoelectronics, Key Laboratory of Information Storage System, Engineering Research Center of Data Storage Systems and Technology, Ministry of Education of China
awufei@hust.edu.cn
ABSTRACT
Three-dimension (3D) NAND flash memory is the preferred storage component of solid-state drive (SSD) for its high ratio of capacity and cost. Optimizing the reliability of modern SSD needs to test and collect a large amount of realworld error data from 3D NAND flash memory. However, the test costs have surged dozens of times as its capacity increases. It's imperative to reduce the costs of testing denser and highcapacity flash memory. To facilitate it, in this paper, we aim to enable reproducing error data efficiently for 3D NAND flash memory. We use a conditional generative adversarial network (cGAN) to learn the error distribution with multiple interferences and generate diverse error data comparable to the real-world. Evaluation results demonstrate it is feasible and efficient for error generation with cGAN.
Keywords: Test, Generation, 3D NAND flash memory, Reliability.
