Passive Memristor Crossbars with Etch-Down Fabrication and Fine-Tuning Characteristics

(Presenting April 8, 2019) Memristors and their arrays with tunable conductance states are promising building blocks for the hardware-implementation of artificial neural network with analog computation. In this work,  we report a CMOS-compatible fabrication technique for passive memristor crossbar array with etch-down and its analog computing application. Switching and fine-tuning characteristics of memristor devices are presented across a 64×64 crossbar array. In addition, vector-matrix multiplication (VMM) is demonstrated with the forward inference of single-layer neural network for MNIST images recognition and its accuracy is analyzed depending on programming precision.