This paper presents an overview and perspective on processing technologies required for continued scaling of leading edge and emerging semiconductor devices. We introduce the main drivers and trends affecting future semiconductor device scaling and provide examples of emerging devices and architectures that may be implemented within the next 10-20 yr. We summarize multiple active areas of research to explain how future thin film deposition, etch, and patterning technologies can enable 3D (vertical) power, performance, area, and cost scaling. Emerging and new process technologies will be required to enable improved contacts, scaled and future devices and interconnects, monolithic 3D integration, and new computing architectures. These process technologies are explained and discussed with a focus on opportunities for continued improvement and innovation.

Perspective: New process technologies required for future devices and scaling

We consider adiabatic superconducting cells operating as an artificial neuron and synapse of a multilayer perceptron (MLP). Their compact circuits contain just one and two Josephson junctions, respectively. While the signal is represented as magnetic flux, the proposed cells are inherently nonlinear and close-to-linear magnetic flux transformers. The neuron is capable of providing the one-shot calculation of sigmoid and hyperbolic tangent activation functions most commonly used in MLP. The synapse features both positive and negative signal transfer coefficients in the range ∼ ( − 0.5 , 0.5 ). We briefly discuss implementation issues and further steps toward the multilayer adiabatic superconducting artificial neural network, which promises to be a compact and the most energy-efficient implementation of MLP.

/pdf/adiabatic-superconducting-artificial-neural-network-basic-56w3mhpz5p.pdf

Adiabatic superconducting artificial neural network: Basic cells

Superconducting logic offers the potential to perform computation at tremendous speeds and energy savings. However, a "semantic gap" lies between the level-driven logic that traditional hardware designs accept as a foundation and the pulse-driven logic that is naturally supported by the most compelling superconducting technologies. A pulse, unlike a level signal, will fire through a channel for only an instant. Arranging the network of superconducting components so that input pulses always arrive simultaneously to "logic gates'' to maintain the illusion of Boolean-only evaluation is a significant engineering hurdle. In this paper, we explore computing in a new and more native tongue for superconducting logic: time of arrival. Building on recent work in delay-based computations we show that superconducting logic can naturally compute directly over temporal relationships between pulse arrivals, that the computational relationships between those pulse arrivals can be formalized through a functional extension to a temporal predicate logic used in the verification community, and that the resulting architectures can operate asynchronously and describe real and useful computations. We verify our hypothesis through a combination of detailed analog circuit models, a formal analysis of our abstractions, and an evaluation in the context of several superconducting accelerators.

https://dl.acm.org/doi/pdf/10.1145/3373376.3378517

A Computational Temporal Logic for Superconducting Accelerators

Vortices in quantum condensates exist owing to a macroscopic phase coherence. Here we show, both experimentally and theoretically, that a quantum vortex with a well-defined core can exist in a rather thick normal metal, proximized with a superconductor. Using scanning tunneling spectroscopy we reveal a proximity vortex lattice at the surface of 50 nm—thick Cu-layer deposited on Nb. We demonstrate that these vortices have regular round cores in the centers of which the proximity minigap vanishes. The cores are found to be significantly larger than the Abrikosov vortex cores in Nb, which is related to the effective coherence length in the proximity region. We develop a theoretical approach that provides a fully self-consistent picture of the evolution of the vortex with the distance from Cu/Nb interface, the interface impedance, applied magnetic field, and temperature. Our work opens a way for the accurate tuning of the superconducting properties of quantum hybrids. Quantum condensates may penetrate from one material to another due to the proximity effect. Here, Stolyarov et al. report the spatial evolution of quantum vortices from a superconducting Nb layer to a 50 nanometer thick diffusive metallic Cu-film, which is quite thick away from the interface.

/pdf/expansion-of-a-superconducting-vortex-core-into-a-diffusive-4mrjkugjyo.pdf

Expansion of a superconducting vortex core into a diffusive metal

We consider adiabatic superconducting cells operating as an artificial neuron and synapse of a multilayer perceptron (MLP). Their compact circuits contain just one and two Josephson junctions, respectively. While the signal is represented as magnetic flux, the proposed cells are inherently nonlinear and close-to-linear magnetic flux transformers. The neuron is capable of providing a one-shot calculation of sigmoid and hyperbolic tangent activation functions most commonly used in MLP. The synapse features by both positive and negative signal transfer coefficients in the range ~ (-0.5,0.5). We briefly discuss implementation issues and further steps toward multilayer adiabatic superconducting artificial neural network which promises to be a compact and the most energy-efficient implementation of MLP.

/pdf/adiabatic-superconducting-artificial-neural-network-basic-4c59eag803.pdf

Adiabatic Superconducting Artificial Neural Network: Basic Cells.

The predictions of Moore's law are considered by experts to be valid until 2020 giving rise to "post-Moore's" technologies afterwards. Energy efficiency is one of the major challenges in high-performance computing that should be answered. Superconductor digital technology is a promising post-Moore's alternative for the development of supercomputers. In this paper, we consider operation principles of an energy-efficient superconductor logic and memory circuits with a short retrospective review of their evolution. We analyze their shortcomings in respect to computer circuits design. Possible ways of further research are outlined.

Alexander L Gudkov

Papers

Beyond Moore's technologies: operation principles of a superconductor alternative.