The increasing energy consumption of data centers has highlighted the urgent need for ultra-low-power computing solutions. Single Flux Quantum (SFQ) circuits, which utilize superconducting Josephson junctions, offer promising advantages in terms of speed and energy efficiency; however, their power consumption has been limited by the need for noise suppression mechanisms. To address this, we propose the practical SFQ Brownian Logic Circuits (SBLCs), which exploit thermal noise for stochastic signal propagation, significantly reducing static power consumption. Especially, we address the three challenges: susceptibility to manufacturing variations, the absence of an actual CJoin gate implementation, which is essential for processing, and a lack of demonstrated practical advantages. This paper evaluates the robustness of SBLCs to manufacturing variations, proposes the first SFQ-based CJoin gate implementation, and demonstrates a Ripple Carry Adder (RCA) with a 3167x improvement in energy efficiency compared to traditional SFQ and CMOS circuits, confirming the superiority of SBLCs for future computing systems.

Computing technologies based on superconducting Josephson junctions, such as single-flux-quantum (SFQ) and half-flux-quantum (HFQ) circuits, are promising as next-generation computing platforms for their exceptional speed and low power consumption. Stochastic computing (SC), a non-deterministic computation approach known for its superior area efficiency, has attracted interest due to its compatibility with SFQ logic and its potential applications in hardware for machine learning. Existing multiplexer (MUX)-based SC adders using SFQ technology encounter challenges with accuracy, area efficiency, and power consumption. In this paper, we propose a low-power, compact, and correlation-insensitive SC adder that leverages the unique characteristics of the confluence buffer, a fundamental circuit element in SFQ and HFQ technologies. By adopting local two-phase clocking, our SC adders avoid computation inaccuracy due to correlation of input bit streams. Our evaluation results show that, compared with existing SFQ MUX-based SC adders, the proposed SFQ-based design achieves approximately 50% reductions in the number of Josephson junctions, implementation area, and power consumption. Furthermore, the proposed HFQ-based design reduces power consumption to approximately 1/3rd to 1/5th of SFQ-based designs for the same manufacturing technology.

Superconducting computing using single flux quantum (SFQ) technology has been recognized as a promising post-Moore's law era technology thanks to its extremely low power and high performance.Therefore, many researchers have proposed various SFQbased circuits (e.g., ALU, register file) and architectures (e.g., NPU, CPU) to exploit the potential.However, due to the absence of a reliable and high-frequency clocking scheme, general SFQ circuits cannot operate at high frequencies, making all architectural efforts for high-performance SFQ computing ineffective.In this paper, we propose SuperSFQ, a new design methodology for SFQ hardware that unlocks the high-frequency potential of SFQ technology by co-designing the clocking scheme, circuitry, and architecture.First, we propose SuperClocking, a new clocking scheme that enables high frequency in general SFQ hardware.Second, we implement an SFQ-based synchronizer to realize the reliable operation of SuperClocking.Finally, we provide two architectural design guidelines and corresponding solutions to ensure the functional correctness of SuperClocking in general SFQ devices.By applying our clocking scheme, synchronizer, and guidelines to the latest general-purpose SFQ CPU, SuperSFQ achieves up to 62.5 times higher frequency and improves single-thread and multithread performance by 17 and 62.5 times, respectively, compared to conventional designs, with only 34.4% Josephson junction overhead.In addition, to demonstrate the generality of SuperSFQ, we apply SuperSFQ to 48 different benchmark circuits, achieving 88.5 times higher frequency compared to conventional designs, on average.

This paper proposes a random walk circuit imple-mentation with single flux quantum devices, essential for Brownian circuits, to reduce processing energy consumption dramatically. SPICE-based simulation demonstrating its functional operation and random walks can be achieved via the Shapiro- Wilk test. Furthermore, we developed a Monte Carlo simulator for Brownian circuits, enabling functionality verification and computation step distribution analysis. Latency/energy evaluation using a half-adder as a case study revealed that proposed circuits could reduce energy consumption by 1/1260 and offer an opportunity for low-power computing systems.

Superconductor single-flux-quantum (SFQ) logic family has been recognized as a promising technology for cryogenic applications (e.g., quantum computing, astronomy, metrology) thanks to its ultra-fast and low-energy characteristics. Therefore, recent efforts in SFQ-based computing have focused on developing fast and low-power SFQ processors for cryogenic applications. However, there still has been little progress toward a convincing SFQ processor design due to the critical performance challenges originating from its extremely deep pipeline. In this paper, we propose a super-fast and low-power in-order SFQ processor by tackling the challenges from the deep pipeline. First, we develop a minimal-depth SFQ processor pipeline with novel architecture-level ideas. Next, we conduct in-depth performance analyses and identify three real performance bottlenecks in the deeply pipelined SFQ processors (i.e., stall/flush logic, RAW stall, fetch unit). Finally, we propose SuperCore, our super-fast SFQ-based processor architecture, with three SFQ-friendly solutions that effectively resolve the identified bottlenecks. With our solutions applied, SuperCore achieves 11 times speed-up over the SFQ processor baseline. In addition, SuperCore achieves six times speed-up and consumes up to 193 times less power compared to in-order CMOS processors running at 4K.

A 10+K qubit Quantum-Classical Interface (QCI) is essential to realize the quantum supremacy. However, it is extremely challenging to architect scalable QCIs due to the complex scalability trade-offs regarding operating temperatures, device and wire technologies, and microarchitecture designs. Therefore, architects need a modeling tool to evaluate various QCI design choices and lead to an optimal scalable QCI architecture.

Due to the high error rate of a qubit, detecting and correcting errors on it is essential for fault-tolerant quantum computing (FTQC). Surface code (SC) associated with its decoding algorithm is one of the most promising quantum error correction (QEC) methods because it has high fidelity and requires only nearest neighbor qubits connectivity. To realize FTQC, we need a decoder circuit capable of not only QEC in a 3-D lattice to deal with errors in measurement on ancillary qubits but also quantum operations on logically constructed qubits. Whereas several methods to perform logical operations on SC, such as lattice surgery (LS), are known, no practical decoders supporting them have been proposed yet.One of the most promising QC implementations today is made up of superconducting qubits that are located in a cryogenic environment. To reduce the hardware complexity of QC and latency of QEC, we are supposed to perform QEC in a cryogenic environment. Hence a power-efficient decoder is required due to the limited power budget inside a dilution refrigerator.In this paper, we propose an online-QEC algorithm that supports LS with a practical decoder circuit, as well as a new FTQC architecture. We design a key building block of the proposed architecture with a hybrid of SFQ- and Cryo-CMOS-based digital circuits and evaluate it with a SPICE-level simulation. Each logic element includes about 2400 Josephson junctions, and power consumption is estimated to be 2.07 μW when operating with a 2 GHz clock frequency. We evaluate the decoder performance by a quantum error simulator for an essential operation of LS with code distances up to 11, and it achieves a 0.6% accuracy threshold. In an LS-based architecture further supporting a magic-state distillation protocol, which is expected to run for near-term universal quantum computing, we evaluate the QEC performance and power consumption of the architecture and show that it is practical to be operated in 4-K temperature region of a dilution refrigerator.

10+K qubit quantum computer is essential to achieve a true sense of quantum supremacy. With the recent effort towards the large-scale quantum computer, architects have revealed various scalability issues including the constraints in a quantum control processor, which should be holistically analyzed to design a future scalable control processor. However, it has been impossible to identify and resolve the processor's scalability bottleneck due to the absence of a reliable tool to explore an extensive design space including microarchitecture, device technology, and operating temperature.

This paper presents the design of an ultra-high-speed, low-power arithmetic unit that supports variable bit-width operations with single flux quantum (SFQ) technology. Because of the high-speed nature of superconductor devices, we can achieve extremely high power-performance efficiency that cannot be achieved by state-of-the-art CMOS devices. To implement the complex function to support the variable bit-width feature, we introduce a novel circuit architecture to maintain the high-speed operation over 50GHz. Our prototype chip design successfully demonstrated 53.5GHz 1.59mW operations.

Due to the low error tolerance of a qubit, detecting and correcting errors on it is essential for fault-tolerant quantum computing. Surface code (SC) associated with its decoding algorithm is one of the most promising quantum error correction (QEC) methods. % One of the challenges of QEC is its high complexity and computational demand. QEC needs to be very power-efficient since the power budget is limited inside of a dilution refrigerator for superconducting qubits by which one of the most successful quantum computers (QCs) is built. In this paper, we propose an online-QEC algorithm and its hardware implementation with SFQ-based superconducting digital circuits. We design a key building block of the proposed hardware with an SFQ cell library and evaluate it by the SPICE-level simulation. Each logic element is composed of about 3000 Josephson junctions and power consumption is about 2.78 uW when operating with 2 GHz clock frequency which meets the required decoding speed. Our decoder is simulated on a quantum error simulator for code distances 5 to 13 and achieves a 1.0% accuracy threshold.

Superconductor single-flux-quantum (SFQ) logic family has been recognized as a highly promising solution for the post-Moore's era, thanks to its ultra-fast and low-power switching characteristics. Therefore, researchers have made a tremendous amount of effort in various aspects to promote the technology and automate its circuit design process (e.g., low-cost fabrication, design tool development). However, there has been no progress in designing a convincing SFQ-based architectural unit due to the architects' lack of understanding of the technology's potentials and limitations at the architecture level. In this paper, we present how to architect an SFQ-based architectural unit by providing design principles with an extreme-performance neural processing unit (NPU). To achieve the goal, we first implement an architecture-level simulator to model an SFQ-based NPU accurately. We validate this model using our die-level prototypes, design tools, and logic cell library. This simulator accurately measures the NPU's performance, power consumption, area, and cooling overheads. Next, driven by the modeling, we identify key architectural challenges for designing a performance-effective SFQ-based NPU (e.g., expensive on-chip data movements and buffering). Lastly, we present SuperNPU, our example SFQ-based NPU architecture, which effectively resolves the challenges. Our evaluation shows that the proposed design outperforms a conventional state-of-the-art NPU by 23 times. With free cooling provided as done in quantum computing, the performance per chip power increases up to 490 times. Our methodology can also be applied to other architecture designs with SFQ-friendly characteristics.