4.8 Review

Dynamical memristors for higher-complexity neuromorphic computing

Journal

NATURE REVIEWS MATERIALS
Volume 7, Issue 7, Pages 575-591

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41578-022-00434-z

Keywords

-

Funding

  1. Laboratory Directed Research and Development programme at Sandia National Laboratories
  2. U.S. Department of Energy's National Nuclear Security Administration [DE-NA0003525]
  3. National Key Research and Development Program of China [2017YFA0207600]
  4. National Natural Science Foundation of China [61925401, 92064004, 2019BD002, 2020BD010]
  5. PKU-Baidu Fund
  6. Fok Ying-Tong Education Foundation, Beijing Academy of Artificial Intelligence
  7. Tencent Foundation through the XPLORER PRIZE
  8. National Science Foundation [CCF-1900675, DMR-1810119]

Ask authors/readers for more resources

Research on electronic devices and materials is driven by the slowdown of transistor scaling and the growth of computing needs. Using devices like memristors to achieve complex dynamics enables new computing architectures with high energy efficiency and computing capacity.
Research on electronic devices and materials is currently driven by both the slowing down of transistor scaling and the exponential growth of computing needs, which make present digital computing increasingly capacity-limited and power-limited. A promising alternative approach consists in performing computing based on intrinsic device dynamics, such that each device functionally replaces elaborate digital circuits, leading to adaptive 'complex computing'. Memristors are a class of devices that naturally embody higher-order dynamics through their internal electrophysical processes. In this Review, we discuss how novel material properties enable complex dynamics and define different orders of complexity in memristor devices and systems. These native complex dynamics at the device level enable new computing architectures, such as brain-inspired neuromorphic systems, which offer both high energy efficiency and high computing capacity.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available