Review of memristor devices in neuromorphic computing: materials sciences and device challenges

The memristor is considered as the one of the promising candidates for next generation computing systems. Novel computing architectures based on memristors have shown great potential in replacing or complementing conventional computing platforms based on the von Neumann architecture which faces chal...

Full description

Saved in:
Bibliographic Details
Published in:Journal of physics. D, Applied physics Applied physics, 2018-12, Vol.51 (50), p.503002
Main Authors: Li, Yibo, Wang, Zhongrui, Midya, Rivu, Xia, Qiangfei, Yang, J Joshua
Format: Article
Language:English
Subjects:
memristive devices
memristor
neuromorphic computing
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The memristor is considered as the one of the promising candidates for next generation computing systems. Novel computing architectures based on memristors have shown great potential in replacing or complementing conventional computing platforms based on the von Neumann architecture which faces challenges in the big-data era such as the memory wall. However, there are a number of technical challenges in implementing memristor based computing. In this review, we focus on the research performed on the memristor material stacks and their compatibility with CMOS processes, the electrical performance, and the integration. In addition, recent demonstrations of neuromorphic computing using memristors are surveyed.
ISSN:0022-3727
1361-6463
DOI:10.1088/1361-6463/aade3f