STARC: Crafting Low-Power Mixed-Signal Neuromorphic Processors by Bridging SNN Frameworks and Analog Designs

Developing low-power neuromorphic processors capable of inferring outcomes from SNN Frameworks presents significant challenges, largely due to the gap between frameworks and analog circuit-based SNNs. This paper analyzes the root of this gap as stemming from over/underflow issues and proposes mixed-signal neurons as a solution, further developing a neural core composed of these neurons. In the development of the neural core, we incorporate a design methodology for application-specific neural core optimization. We advance to develop a neural engine as an independent IP, ultimately introducing the snnTorch Architecture (STARC), an integrated mixed-signal neuromorphic processor architecture. The STARC processor, developed as a prototype, demonstrates operational correctness and exceptional low-power performance.