Read Disturb Evaluations of 3D NAND Flash for Highly Read-Intensive Edge-Computing Inference Device for Artificial Intelligence Applications

摘要

The coming era of artificial intelligence (AI) and the combination with internet of things (IoT) will require a large number of edge computing inference devices. We consider 3D NAND Flash has great potential to provide either near-memory or in-memory computing for low-cost high-performance inference device. One of the critical technology challenge of 3D NAND Flash for inference application is the read disturb, because in this application the NAND Flash needs to sustain continuous read over the entire product life time. In this work, we have studied how to optimize read disturb performance of single-gate vertical channel (SGVC) 3D NAND and demonstrated the possibility to meet > 10T (1E13) continuous read which may exceed 10-year usage without the need of data refresh.