SUSHI: Ultra-High-Speed and Ultra-Low-Power Neuromorphic Chip Using Superconducting Single-Flux-Quantum Circuits

The rapid single-flux-quantum (RSFQ) superconducting technology is highly promising due to its ultra-high-speed computation with ultra-low-power consumption, making it an ideal solution for the post-Moore era. In superconducting technology, information is encoded and processed based on pulses that resemble the neuronal pulses present in biological neural systems. This has led to a growing research focus on implementing neuromorphic processing using superconducting technology. However, current research on superconducting neuromorphic processing does not fully leverage the advantages of superconducting circuits due to incomplete neuromorphic design and approach. Although they have demonstrated the benefits of using superconducting technology for neuromorphic hardware, their designs are mostly incomplete, with only a few components validated, or based solely on simulation. This paper presents SUSHI (Superconducting neUromorphic proceSsing cHIp) to fully leverage the potential of superconducting neuromorphic processing. Based on three guiding principles and our architectural and methodological designs, we address existing challenges and enables the design of verifiable and fabricable superconducting neuromorphic chips. We fabricate and verify a chip of SUSHI using superconducting circuit technology. Successfully obtaining the correct inference results of a complete neural network on the chip, this is the first instance of neural networks being completely executed on a superconducting chip to the best of our knowledge. Our evaluation shows that using approximately 105 Josephson junctions, SUSHI achieves a peak neuromorphic processing performance of 1,355 giga-synaptic operations per second (GSOPS) and a power efficiency of 32,366 GSOPS per Watt (GSOPS/W). This power efficiency outperforms the state-of-the-art neuromorphic chips TrueNorth and Tianjic by 81 and 50 times, respectively.