Approximate SFQ-Based Computing Architecture Modeling With Device-Level Guidelines

Single-flux-quantum (SFQ) logic has emerged as a promising post-Moore technology thanks to its ultra-fast and low-energy operation. However, despite progress in various fields, its feasibility is questionable due to the prohibitive cooling cost. Proven conventional ideas, such as approximate computing, may help to resolve this challenge. However, introducing such ideas has been impossible due to the complex performance, power, and error trade-offs originating from the unique SFQ device characteristics. This work introduces approximate SFQ-based computing (AxSFQ) with an architecture modeling framework and essential design guidelines. Our optimized device-level AxSFQ showcases 30–100 times energy efficiency improvement, which motivates further circuit and architecture-level exploration.