Fabrication and Performance of Hybrid ReRAM-CMOS Circuit Elements for Dynamic Neural Networks

In neuromorphic applications, resistive memory solutions (implemented as Resistive Random Access Memory or ReRAM) have significant potential in emulating the desired two-terminal synaptic functionality of real synapses. One of the unique features for the demonstrated ReRAM devices includes conductance modulation, which allows for the implementation of the synaptic weight between neuronal elements. In this paper, we illustrate the multi-resistance level switching capabilities of our unique ReRAM-CMOS hybrid system, which is a demonstration vehicle for implementation of a memristive Dynamic Adaptive Neural Network Array, also known as mrDANNA. Discrete resistance levels have been achieved through application of varying gate voltage and discrete electric pulses in the order of nanoseconds.