Brain-inspired computing employs devices and architectures that emulate biological functions for more adaptive and energy-efficient systems. Oscillatory neural networks (ONNs) are an alternative approach in emulating biological functions of the human brain and are suitable for solving large and complex associative problems. In this work, we investigate the dynamics of coupled oscillators to implement such ONNs. By harnessing the complex dynamics of coupled oscillatory systems, we forge a novel computation model--information is encoded in the phase of oscillations. Coupled interconnected oscillators can exhibit various behaviors due to the strength of the coupling. In this article, we present a novel method based on subharmonic injection locking (SHIL) for controlling the oscillatory states of coupled oscillators that allow them to lock in frequency with distinct phase differences. Circuit-level simulation results indicate SHIL effectiveness and its applicability to large-scale oscillatory networks for pattern recognition.

Ising machines have received growing interest as efficient and hardware-friendly solvers for combinatorial optimization problems (COPs). They search for the absolute or approximate ground states of the Ising model with a proper annealing process. In contrast to Ising machines built with superconductive or optical circuits, complementary metal–oxide–semiconductor (CMOS) Ising machines offer inexpensive fabrication, high scalability, and easy integration with mainstream semiconductor chips. As low-energy and CMOS-compatible emerging technologies, spintronics and phase-transition devices offer functionalities that can enhance the scalability and sampling performance of Ising machines. In this article, we survey various approaches in the process flow for solving COPs using CMOS, hybrid CMOSspintronic, and phase-transition devices. First, the methods for formulating COPs as Ising problems and embedding Ising formulations to the topology of the Ising machine are reviewed. Then, Ising machines are classified by their underlying operational principles and reviewed from a perspective of hardware implementation. CMOS solutions are advantageous with denser connectivity, whereas hybrid CMOS-spintronic and phase-transition device-based solutions show great potential in energy efficiency and high performance. Finally, the challenges and prospects are discussed for the Ising formulation, embedding process, and implementation of Ising machines.

Nano-oscillators based on phase-transition materials are being explored for the implementation of different non-conventional computing paradigms. In particular, vanadium dioxide (VO₂) devices are used to design autonomous non-linear oscillators from which oscillatory neural networks (ONNs) can be developed. In this work, we propose a new architecture for ONNs in which sub-harmonic injection locking (SHIL) is exploited to ensure that the phase information encoded in each neuron can only take two values. In this sense, the implementation of ONNs from neurons that inherently encode information with two-phase values has advantages in terms of robustness and tolerance to variability present in VO₂ devices. Unlike conventional interconnection schemes, in which the sign of the weights is coded in the value of the resistances, in our proposal the negative (positive) weights are coded using static inverting (non-inverting) logic at the output of the oscillator. The operation of the proposed architecture is shown for pattern recognition applications.

Tunnel transistors are one of the most attractive steep subthreshold slope devices currently being investigated as a means of overcoming the power density and energy inefficiency limitations of CMOS technology. In this paper, the evaluation and the comparison of the performance of distinct fan-in logic gates, using a set of widely accepted power-speed metrics, are addressed for five projected tunnel transistor (TFET) technologies and four mosfet and FinFET transistors. The impact of logic depth, switching activity, and minimum supply voltage has been also included in our analysis. Provided results suggest that benefits in terms of a certain metric, in which a higher weight is placed on power or delay, are strongly determined by the selected device. Particularly, the suitability of two of the explored TFET technologies to improve CMOS performance for different metrics is pointed out. A circuit level benchmark is evaluated to validate our analysis.

Devices combining transistors and phase transition materials are being investigated to obtain steep switching and a boost in the ION/IOFF ratio and, thus, to solve power and energy limitations of CMOS technologies. This paper analyzes the operation of circuits built with these devices. In particular, we use a recently projected device called hyper-FET to simulate different circuits, and to analyze the impact of the degraded dc output voltage levels of hyper-FET logic gates on their circuit operation. Experiments have been carried out to evaluate power of these circuits and to compare with counterpart circuits using FinFETs. The estimated power advantages from device level analysis are also compared with the results of circuit level measurements.We show that these estimation scan reduce, cancel, or even lead to power penalties in low switching and/or low-frequency circuits. We also discuss relationships with some device level parameters showing that circuit level considerations should be taken into account for device design.

In this paper, five projected tunnel FET (TFET) technologies are evaluated and compared with MOSFET and FinFET transistors for high-performance low-power objectives. The scope of this benchmarking exercise is broader than that of previous studies in that it seeks solutions to different identified limitations. The power and the energy of the technologies are evaluated and compared assuming given operating frequency targets. The results clearly show how the power/energy advantages of TFET devices are heavily dependent on required operating frequency, switching activity, and logic depth, suggesting that architectural aspects should be taken into account in benchmarking experiments. Two of the TFET technologies analyzed prove to be very promising for different operating frequency ranges and, therefore, for different application areas.