An adiabatic regenerative capacitive artificial neuron

In recent years, RRAM technology has been actively developed as a means of reducing power dissipation and area in a host of circuits, most notably artificial neuron synapses. However, further reduction in energy consumption may be possible by transitioning to capacitive synapses and combining them with adiabatic technique. In this work, we present and analyse the function and power dissipation of an artificial neuron with capacitive synapses where the synaptic tree is fed by a regenerative clock. Whilst the weights are fixed in this case, developments into memcapacitor technology offer the promise of tuneability in the future. In our example, a 4-synapse design was used as a proof-of-concept baseline at various frequencies. Our simulation at 1MHz indicates a ≈ 91% reduction of energy when using Regenerative Capacitive Synapses vs. standard, non-regenerative ones, which translates into a ≈ 35% drop in overall artificial neuron energy dissipation. The higher the ratio of synapses/soma, the higher the power savings, which is important for building larger and more complex neurons in silico.