As we approach the end of the silicon road map, alternative computing models that can solve at-scale problems in the data-centric world are becoming important. This is accompanied by the realization that binary abstraction and Boolean logic, which have been the foundations of modern computing revolution, fall short of the desired performance and power efficiency. In particular, hard computing problems relevant to pattern matching, image and signal processing, optimizations, and neuromorphic applications require alternative approaches. In this paper, we review recent advances in oscillatory dynamical system-based models of computing and their implementations. We show that simple configurations of oscillators connected using simple electrical circuits can result in interesting phase and frequency dynamics of such coupled oscillatory systems. Such networks can be controlled, programmed, and observed to solve computationally hard problems. Although our discussion in this paper is limited to insulator-to-metal transition devices and spin-torque oscillators, the general philosophy of such a computing paradigm of “let physics do the computing” can be translated to other mediums as well, including micromechanical and optical systems. We present an overview of the mathematical treatments necessary to understand the time evolution of these systems and highlight the recent experimental results in this area that suggest the potential of such computational models.

This paper will give a review of recent work on using networks of coupled oscillators for analog information processing. We will discuss the rationale of using coupled oscillators, and how they can be used to perform computational tasks, such as associative computing primitives, or how they can serve as hardware accelerators in vision processing pipelines. Further, we will study two specific physical implementations for such oscillator, namely relaxation oscillators based on metal-insulator phase transitions and magnetic spin-torque oscillators. We will also discuss the potential of such coupled-oscillator networks to solve computationally-hard optimization problems or even NP-hard problems.

In this paper, we demonstrate an optically inspired massively parallel non-Boolean operator which can emulate 3D wave dynamics on a 2D FPGA-based architecture. The algorithm is based on the Paraxial Helmholtz Equation: which describes the beam propagation through different media with different refractive indices. To solve this wave propagation equation numerically the FPGA-accelerated hardware have to operate with spatial varying templates. The FPGA-based implementation is very well parallelizable, consequently it is also be amenable to mega-core architectures.

Nanomagnet Logic (NML) accomplishes computation through magnetic dipole-dipole interactions. It has the potential for low-power dissipation, radiation hardness and non-volatility. NML circuits have been designed to process and move information via nearest neighbor, device-to-device coupling. However, the resultant layouts often fail to function correctly. This paper reveals an important cause of such failures showing that a robust NML layout must take into account not only nearest neighbor, but also the next nearest neighbor couplings. A new design method is then introduced to address this issue that leverages the minimum-energy states of an NML circuit to guide the layout process. Case studies show that the new method is efficient and effective in arriving at correct NML layouts.

We discuss the opportunities of performing associative processing based on the phase locking of coupled oscillators. The use of coupled oscillators, rather than Boolean logic, provides for implementations using emerging nano-technology such as magnetic spin torque oscillators and resonant body transistor oscillators, which each have the potential of lower energy operations and higher density scaling than traditional CMOS solutions.

Field-coupled nanomagnets can offer significant energy savings at iso-performance versus CMOS equivalents. Magnetic logic could be integrated with CMOS, operate in environments that CMOS cannot, and retain state without power. Clocking requirements lead to inherently pipelined circuits, and high throughput further improves application-level performance. However, bit conflicts -- that will occur in defect free, pipelined ensembles -- can make non-volatile logic volatile. Assuming a field-based clock, we present hardware designs to improve steady state non-volatility, and explain how design enhancements could increase clock energy. We then suggest materials-related design levers that could simultaneously deliver non-volatility and low clock energy.

The bistable ring physical(ly) unclonable function (BR-PUF) is a novel electrical intrinsic PUF design for physical cryptography. FPGA prototyping has provided a proof-of-concept, showing that the BR-PUF could be a promising candidate for strong PUFs. However, due to the limitations (device resources, placement and routing) of FPGA prototyping, the effectiveness of a practical ASIC implementation of the BR-PUF could not be validated. This paper characterizes the BR-PUF further through transistor-level simulations. Based on process variation, mismatch, and noise models provided or suggested by industry, these simulations are able to provide predictions on the figures-of-merit of ASIC implementations of the BR-PUF. This paper also suggests a more secure way of using the BR-PUF based on its supply voltage sensitivity.

We review some of our previous work on field-coupling in nano-scale cellular arrays. Electronic devices based on metallic and magnetic nanoscale dots and molecular structures have been suggested, however, no technologically viable architecture for nanoelectronic circuit integration has emerged so far. A natural architecture on the nanoscale appears to be near-neighbor cellular networking, and we explore promising alternative ways of integrating nanodevices by direct physical field coupling, i.e. either by Coulomb or by magnetic interactions. We review new architectures for such field-coupled nanocircuits.