Ultra-Low Energy LIF Neuron Using Si NIPIN Diode for Spiking Neural Networks

• Published in: IEEE electron device letters 2018-12, Vol.39 (12), p.1832-1835
• Main Authors: Das, B., Schulze, J., Ganguly, U.
• Format: Article
• Language: English
• Subjects: Biological neural networks; Brain; Capacitors; CMOS; Energy; Energy consumption; Energy efficiency; impact ionization; LIF neuron; Memory devices; Neural networks; Neurons; Semiconductor devices; Si NIPIN diode; Silicon; Spiking; spiking neural network; Transistors
• ISSN: 0741-3106; 1558-0563
• DOI: 10.1109/LED.2018.2876684

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.