The Future of Memristors: Materials Engineering and Neural Networks
Hebei University · National University of Singapore
Abstract
Abstract From Deep Blue to AlphaGo, artificial intelligence and machine learning are booming, and neural networks have become the hot research direction. However, due to the size limit of complementary metal–oxide–semiconductor (CMOS) transistors, von Neumann‐based computing systems are facing multiple challenges (such as memory walls). As the number of transistors required by the neural network increases, the development of neural networks based on the von Neumann computer is limited by volume and energy consumption. As the fourth basic circuit element, memristor shines in the field of neuromorphic computing. The new computer architecture based on memristor is widely considered as a substitute for the von…
Citation impact
- FWCI
- 20.91
- Percentile
- 100%
- References
- 339
Authors
3Topics & keywords
- Memristor
- Neuromorphic engineering
- Von Neumann architecture
- Artificial neural network
- Computer science
- Artificial intelligence
- Transistor
- CMOS