Hybrid spin-CMOS stochastic spiking neuron for high-speed emulation of in vivo neuron dynamics

Abstract

The spintronic stochastic spiking neuron (S3N) developed herein realises biologically mimetic stochastic spiking characteristics observed within in vivo cortical neurons, while operating several orders of magnitude more rapidly and exhibiting a favourable energy profile. This work leverages a novel probabilistic spintronic switching element device that provides thermally-driven and current-controlled tunable stochasticity in a compact, low-energy, and high-speed package. In order to close the loop, the authors utilise a second-order complementary metal-oxide-semiconductor (CMOS) synapse with variable weight control that accumulates incoming spikes into second-order transient current signals, which resemble the excitatory postsynaptic potentials found in biological neurons, and can be used to drive post-synaptic S3Ns. Simulation program with integrated circuit emphasis (SPICE) simulation results indicate that the equivalent of 1 s of in vivo neuronal spiking characteristics can be generated on the order of nanoseconds, enabling the feasibility of extremely rapid emulation of in vivo neuronal behaviours for future statistical models of cortical information processing. Their results also indicate that the S3N can generate spikes on the order of ten picoseconds while dissipating only 0.6-9.6 μW, depending on the spiking rate. Additionally, they demonstrate that an S3N can implement perceptron functionality, such as AND-gate- and OR-gate-based logic processing, and provide future extensions of the work to more advanced stochastic neuromorphic architectures.