Mandal Saptarshi, El-Amin Ammaarah, Alexander Kaitlyn, Rajendran Bipin, Jha Rashmi
Department of Electrical Engineering and Computer Science, University of Toledo, University of Toledo, OH 43606, USA.
Department of Electrical Engineering, Indian Institute of Technology, Bombay, India.
Sci Rep. 2014 Jun 18;4:5333. doi: 10.1038/srep05333.
This report discusses the electrical characteristics of two-terminal synaptic memory devices capable of demonstrating an analog change in conductance in response to the varying amplitude and pulse-width of the applied signal. The devices are based on Mn doped HfO₂ material. The mechanism behind reconfiguration was studied and a unified model is presented to explain the underlying device physics. The model was then utilized to show the application of these devices in speech recognition. A comparison between a 20 nm × 20 nm sized synaptic memory device with that of a state-of-the-art VLSI SRAM synapse showed ~10× reduction in area and >10(6) times reduction in the power consumption per learning cycle.
本报告讨论了双端突触存储器件的电学特性，该器件能够响应施加信号的幅度和脉宽变化而表现出模拟电导变化。这些器件基于掺锰的二氧化铪材料。研究了重构背后的机制，并提出了一个统一模型来解释潜在的器件物理原理。然后利用该模型展示了这些器件在语音识别中的应用。将一个20纳米×20纳米尺寸的突触存储器件与一个最先进的超大规模集成电路静态随机存取存储器突触进行比较，结果表明面积减少了约10倍，每个学习周期的功耗降低了10^6倍以上。
