Abstract

An energy efficient neuron is essential for spiking neural network (SNN) to operate at low energy to mimic the human brain functionalities in hardware. Several CMOS-based Si transistors, memory devices, spintronic devices have been used as a neuron for SNN. However, the main concern is the energy efficiency for these neurons. In this letter, we experimentally demonstrate a Si-based CMOS compatible asymmetric NIPIN diode as a LIF neuron. First, we demonstrate the LIF neuron characteristics by comparing the spike-frequency (f) versus voltage curve with that of a simple LIF neuron model. This neuron shows a classical ReLU behavior, which is attractive for typical software neuron models. Then, we show an ultra-low energy consumption of $\sim \text {2}\times \text {10}^{-\text {17}} {J}$ per spike at 10-nm node of this neuron, as NIPIN diode is highly scalable ( $\text {4}{F}^{\text {2}}$ ) due to its capacitorless structure. This is the lowest reported energy/spike for any LIF neuron for SNN application. Thus, the NIPIN is suitable for ultra-low energy LIF neuron application for energy efficient SNN.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call