2D Materials-based Neuromorphic Computing Electronic Device

Abstract

Nowadays, with the rapid information explosion connected to all devices, there is a huge demand for effectively processing big data. In particular, conventional von Neumann computing system with physically separated processing and memory units face significant problems in dealing with massive unstructured data such as sound, images, and video because of a von Neumann bottleneck. As a key feature of parallel operations, neuromorphic computing systems can analyze massive unstructured data in a time and energy efficient manner. However, critical issues related to reliability and variability of nonlinearity and asymmetric weight update, have been great challenges in the implementation of artificial synaptic device in practical neuromorphic hardware system. Also, hardware systems enabling artificial neural networks in-situ personal data are essential for adaptive wearable neuromorphic edge computing.