About this Research Topic
Conventional electronics leverage electron charge as the state variable for computation and is insufficient to achieve the computing requirements of increasingly data-intensive applications in the emerging areas of the Cognitive Internet-of-Things, Healthcare and Industry 4.0, and Smart Cities and Nations. In the quest to augment or even replace charge-based electronics, novel computing hardware based on material systems exhibiting physical phenomena such as magnetism, ferroelectric polarization, and oxygen-vacancy migration have been investigated. When coupled with computing paradigms that fully exploit the unique characteristics of the device technology, computing systems such as (but not limited to) those based on optoelectronic, spintronic, ferroelectronic, memelectronic, caloritronic, and valleytronic physics have the potential to overcome the limitations of charge-based electronics and meet the computing needs of applications that are increasingly data-intensive.
Emerging applications of artificial intelligence (AI) and the cognitive internet-of-things will serve as the main drivers for electronic technology advancements for the next decade and beyond. Research efforts in device technology, hardware architectures and software algorithms are intensifying to address the technological challenges in these areas and their synergies are being explored to achieve optimized solutions. Although a plethora of new device technologies, such as experimental observations of skyrmions and oxygen-migration in ferromagnetic material stacks, spin-valley coupled electronic behavior in 2D materials, and a new class of non-volatile electronic devices (memristor, memcapacitor, meminductor, and memtransistor, etc.) has been proposed and explored, exploration of their potential applications and implications is in its nascent stages. It is envisioned that device technology co-optimization (DTCO) will play an increasingly crucial role in enabling intelligent applications of emerging device technologies. The aim of this Research Topic is to cover global research efforts in exploring physical phenomena as well as their applications and implications in electronic device technologies, circuits, hardware architectures, and computation paradigms for computing machinery.
We invite papers covering research efforts across the hardware stack for enabling intelligent applications of emerging device technologies. Areas of interest include, but are not limited to:
• Physical modeling and simulation (technology computer-aided design, compact modeling, etc.)
• Device architectures, characterization, and optimization
• Memory devices, circuits, and hardware architectures
• Devices, circuits, and hardware architectures for Boolean computing
• Hardware architectures (including circuits) and computing paradigms that are enabled by emerging device technologies (e.g., Ising machines, neural network accelerators, in-memory computing, analog computing, stochastic computing, quantum computing, etc.)
• Mapping of algorithms and problems to hardware architectures based on emerging device technologies.
Keywords: Computation, Memories, Devices, Circuits, Architectures
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.