Title :
Bio-inspired computing with resistive memories — models, architectures and applications
Author :
Qing Wu ; Beiye Liu ; Yiran Chen ; Hai Li ; Qiuwen Chen ; Qinru Qiu
Author_Institution :
Inf. Directorate, Air Force Res. Lab., Rome, NY, USA
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.
Keywords :
biocomputers; biocomputing; memristors; Von Neumann architecture; bio-inspired computer; bio-inspired computing; cogent confabulation models; embedded high performance computing; highly parallel biological systems; massively parallel architecture; memristor crossbar based architecture; memristor devices; neuromorphic architecture; Arrays; Biological system modeling; Computational modeling; Hardware; Memristors; Neuromorphics; architecture; bio-inspired; confabulation; memristor; neuromorphic;
Conference_Titel :
Circuits and Systems (ISCAS), 2014 IEEE International Symposium on
Conference_Location :
Melbourne VIC
Print_ISBN :
978-1-4799-3431-7
DOI :
10.1109/ISCAS.2014.6865265