Title :
Bio-inspired ultra lower-power neuromorphic computing engine for embedded systems
Author :
Beiye Liu ; Miao Hu ; Hai Li ; Yiran Chen ; Chun Xue
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Pittsburgh, Pittsburgh, PA, USA
fDate :
Sept. 29 2013-Oct. 4 2013
Abstract :
Neuromorphic computing, which is inspired by the working mechanism of human brain, recently emerges as a hot research area to combat the contradiction between the limited functions of computing systems and the ever increasing variety of applications. In this work, we will introduce our research on a bio-inspired neuromorphic embedded computing engine named Centaur, which aims to achieve an ultra-high power efficiency beyond One-TeraFlops-Per-Watt by adopting the bio-inspired computation model and the advanced memristor technology. The success of Centaur design may promote the embedded system power efficiency three orders of magnitude from the current level while the small footprint and real-time re-configurability of the design allow an easy integration into MPSoCs, enabling many emerging mobile and embedded applications.
Keywords :
embedded systems; neural nets; resistors; Centaur; advanced memristor technology; bio-inspired computation model; bio-inspired ultra lower-power neuromorphic computing engine; design reconfigurability; embedded applications; embedded system power efficiency; embedded systems; human brain; mobile applications; ultra-high power efficiency; Computational efficiency; Embedded systems; Engines; Hardware; Memristors; Neuromorphics; Training; embedded systems; memristor; neuromorphic;
Conference_Titel :
Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2013 International Conference on
Conference_Location :
Montreal, QC
DOI :
10.1109/CODES-ISSS.2013.6659010