Mtj-based hardware synapse implementation for binary and ternary deep neural networks

Abstract

A stochastic synapse for use in a neural network, comprising: first and second magnetic tunnel junction (MTJ) devices, each MTJ device having a fixed layer port and a free layer port; a first and second control circuit, each connected respectively to the free layer port of the first and second MTJ devices, wherein the fixed layer ports of the first and second MTJ devices are connected to each other; wherein the first and second control circuits are configured to perform a gated XNOR operation between synapse and activation values; and wherein an output of the gated XNOR is represented by the output current through both of the first and second MTJ devices.