An ultra-compact and low power neuron based on SOI platform

Analog and digital circuit designs have been proposed to mimic the biological neuron in CMOS compatible learning circuits for “brain” like computing. However, the adaptation of such conventional circuit based strategies requires many devices, large areas and hence power consumption. We propose a neuronal device based on the well-investigated impact-ionization based NPN selector on an SOI platform. The neuronal device has a small footprint (225·F²) and low active power (11.5nW/spike) and provides ~10,000x speed-up over biological timescales. In comparison to analog neuron, ultra-high density (>60x improvement) and low power operation (>5x improvement) are demonstrated.