upalpha-Soma: Single Flux Quantum Threshold Cell for Spiking Neural Network Implementations

• Published in: IEEE transactions on applied superconductivity Vol. 33; no. 5; pp. 1 - 5
• Main Authors: Karamuftuoglu, Mustafa Altay, Pedram, Massoud
• Format: Journal Article
• Language: English
• Published: IEEE 01.08.2023
• Subjects: Alpha cell; Behavioral sciences; Bidirectional control; Clocks; excitatory pulse; inhibitory pulse; Libraries; Logic gates; Pins; single flux quantum; Soma; spiking neuronsuperconductor electronics
• ISSN: 1051-8223; 1558-2515
• DOI: 10.1109/TASC.2023.3264703

The main challenge for the hardware implementation of spiking neural networks is the design of a reliable neuron. Soma, which is the nucleus of the neuron, is a key part of such a design. More precisely, the soma design must accurately capture the excitatory/inhibitory interactions, intrinsic charge dynamics, refractory period, spike encoding, neuronal action potential, and output spike firing processes in order to mimic the corresponding biological processes. This work presents the design of an artificial soma cell with excitatory and inhibitory inputs, called <inline-formula><tex-math notation="LaTeX">\upalpha</tex-math></inline-formula>-Soma. The key idea is to design and employ a new interconnect cell, named <inline-formula><tex-math notation="LaTeX">\upalpha</tex-math></inline-formula>-cell, and integrate this cell within the proposed soma cell design. The design implementation utilizes the Rapid Single Flux Quantum (RSFQ) logic circuit technology. We demonstrate the correct functionality, high performance, and energy efficiency of the proposed <inline-formula><tex-math notation="LaTeX">\upalpha</tex-math></inline-formula>-Soma cell with detailed circuit simulations under different spiking conditions.