Bio-inspired computing with resistive memories - Models, architectures and applications

Abstract

The traditional Von Neumann architecture has constrained the potential for applying massively parallel architecture to embedded high performance computing where we must optimize the size, weight and power of the system. Inspired by highly parallel biological systems, such as the human brain, the neuromorphic architecture offers a promising novel computing paradigm for compact and energy efficient platforms. The discovery of memristor devices provided the element we need with unprecedented efficiency in realizing such a computing architecture. There are still many challenges left to meet our goal of a fully functional bio-inspired computer. Here we will discuss our research in memristor crossbar based architecture, adaptation of this architecture for cogent confabulation models, and potential applications of the bio-inspired computer. © 2014 IEEE.

DOI
10.1109/ISCAS.2014.6865265
Year