Beyond-CMOS Non-Boolean Logic Benchmarking: Insights and Future Directions
Emerging technologies are facing significant challenges to compete with CMOS with respect to Boolean logic. There is an increasing need for using non-traditional circuits to realize the full potential of beyond-CMOS devices. This paper presents a uniform benchmarking methodology for non-Boolean computation based on the cellular neural network (CNN) for a variety of beyond-CMOS device technologies, including charge-based and spintronic devices. Three types of CNN implementations are investigated benchmarked for a given input noise and recall accuracy target using analog, digital, and spintronic circuits. Results demonstrate that spintronic devices are promising candidates to implement CNNs, where up to 3× EDP improvement is predicted in domain wall devices compared to its conventional CMOS counterpart. This shows that alternative non-Boolean computing platforms are crucial for developing future emerging technologies.