A survey on superconducting computing technology: circuits, architectures and design tools

Huang, Junying; Fu, Rongliang; Ye, Xiaochun; Fan, Dongrui

doi:10.1007/s42514-022-00089-w

Cited by 8 publications

(3 citation statements)

References 110 publications

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“…Growth within these fields has also been driven by the need to decrease power consumption and thermal effects of very large scale integration (VLSI) circuits [16]. More recently, with the end of Moore's Law, there has been growth in beyond-CMOS technologies that offer low power and high speed such as, single flux quantum technologies, adiabatic quantum flux parametron technologies [17], [18], and spintronics [15]. There has also been growth in the research for automating the design verification process in such SCE technologies [19], [18] and automating circuit sizing optimization in AMSC [20].…”

Section: Historical Perspectivementioning

confidence: 99%

“…More recently, with the end of Moore's Law, there has been growth in beyond-CMOS technologies that offer low power and high speed such as, single flux quantum technologies, adiabatic quantum flux parametron technologies [17], [18], and spintronics [15]. There has also been growth in the research for automating the design verification process in such SCE technologies [19], [18] and automating circuit sizing optimization in AMSC [20]. Another growing research area is the exploration of neuromorphic computing, which is defined as an approach to computing where the structure and function of the computer are inspired by emulation of the human brain [21].…”

Section: Historical Perspectivementioning

confidence: 99%

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Three Decades of Low Power: From Watts to Wisdom

Munir,

Modi,

Cooper

et al. 2024

IEEE Access

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Low power technologies have been critical to the advancement of many fields of research including computer architecture, analog, digital, and mixed signal circuit design, semiconductor technologies, wireless technologies, networks-on-chip, distributed computing, Internet-of-Things, and machine learning on mobile devices. Many of the research advancements in each of these low power fields seem independent of the other fields, but are actually inter-related through the flow of ideas between fields of research. Many ideas used in research seem novel within one field, but in actuality they are often borrowed from other fields showing the interdisciplinary nature of research with ideas transferring from applied physics and chemistry to areas in semiconductor technologies and computer engineering. In this paper, we first examine a few significant research ideas in the area of low power technologies and then explore the interdisciplinary nature, growth, and impact of low power technologies through a network science based analysis of research publications over the past 30 years.INDEX TERMS Graph convolutional networks, graph machine learning, Internet-of-Things, low power technologies, network science, semiconductor technologies, wireless technologies.

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Section: Historical Perspectivementioning

confidence: 99%

Section: Historical Perspectivementioning

confidence: 99%

Three Decades of Low Power: From Watts to Wisdom

Munir,

Modi,

Cooper

et al. 2024

IEEE Access

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“…Superconducting single-flux-quantum (SFQ) circuits have remarkable features, such as a clock frequency of several hundred gigahertz and low power consumption [1][2][3]. However, the technology for the large-scale application of SFQ circuits is not yet established [4][5][6] because of their low integration density and low-voltage output signals, and it is difficult to create computing systems or memories with only SFQ and other superconducting technologies. * Author to whom any correspondence should be addressed.…”

Section: Introductionmentioning

confidence: 99%

Ginzburg–Landau simulations of three-terminal operation of a superconducting nanowire cryotron

Yasukawa,

Nishio,

Mawatari

2024

Supercond. Sci. Technol.

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Superconducting nanowire cryotrons (nTrons) are expected to be used as interfaces for super-high-performance hybrid devices in which superconductor and semiconductor circuits are combined. However, nTrons are still under development, and diverse analyses of these devices are needed. Accordingly, we have developed a numerical technique to simulate the three-terminal operation of an nTron by using the finite element method to solve the time-dependent Ginzburg–Landau (TDGL) equation and the heat-diffusion equation. Simulations using this technique offer understanding of the dynamics of the order parameter, the thermal behavior, and the characteristics of three-terminal operation, and the TDGL model reproduces qualitatively the results of nTron experiments conducted at the Massachusetts Institute of Technology. In addition, we investigated how some geometric and physical parameters (the design elements) affect the operation characteristics. The TDGL model has far fewer free parameters compared with the lumped-element electrothermal model commonly used for simulating superconducting devices. Furthermore, the TDGL model provides time-dependent visual information about the superconducting state and the normal state, thereby offering insights into the relationship between nTron geometry and three-terminal operation. These simulation results offer a route to nTron optimization and the development of nTron applications.

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