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 reviews an analog circuit system of capacitively coupled relaxation oscillators whose time evolution can be used to solve the graph coloring problem. These oscillators consist of a series combination of an insulator-metal-transition (IMT) device and a resistance. Such circuits were also demonstrated experimentally using VO2(Vanadium Dioxide) as the phase transition material. The time evolution of circuit dynamics depend on eigenvectors of the adjacency matrix in the same way as is used by spectral algorithms for graph coloring. As such, a coupled network of such oscillators with piecewise linear dynamics have steady state phases which can be used to approximate the minimum vertex coloring of a graph.

In this paper we review recent work on computational paradigms involving coupled relaxation oscillators built using metal-insulator-transition (MIT) devices. Such oscillators made using MIT devices based on Vanadium-Dioxide thin films are very compact and can be realized in hardware. Networks of such oscillators have interesting phase and frequency dynamics which can be programmed to solve computationally hard problems.

There has been a significant interest in Spin Transfer Torque Magnetic Random Access Memory (STT-MRAM) as a candidate for emerging memory technology for last-level embedded caches in the recent years. High density (3-4x of SRAM), non-volatility, nano-second Read and Write speeds, and process and voltage compatibility with CMOS are the attractive properties of this technology. A few studies have expounded on the reliability in this technology but various fault manifestations have not been studied in detail in the past. This paper attempts to study the fault models in STT-MRAM under both parametric variations as well as electrical defects (opens and shorts). Sensitivity of Read, Write and Retention to material and lithographic process parameters has been studied. Also electrical defects viz. intra-cell and inter-cell opens and shorts have been considered and the corresponding fault models have been identified and classified.

Harnessing the computational capabilities of dynamical systems has attracted the attention of scientists and engineers form varied technical disciplines over decades. The time evolution of coupled, non-linear synchronous oscillatory systems has led to active research in understanding their dynamical properties and exploring their applications in brain-inspired, neuromorphic computational models. In this paper we present the realization of coupled and scalable relaxation-oscillators utilizing the metal-insulator-metal transition of vanadium-dioxide (VO2) thin films. We demonstrate the potential use of such a system in pattern recognition, as one possible computational model using such a system.