From the discovery of giant magnetoresistance (GMR) to tunnel magnetoresistance (TMR),
their subsequent application in large capacity hard disk drives (HDDs) greatly speeded up …

A computing scheme that can solve complex tasks is necessary as the big data field
proliferates. Probabilistic computing (p-computing) paves the way to efficiently handle …

The transistor celebrated its 75th birthday in 2022. The continued scaling of the transistor
defined by Moore's law continues, albeit at a slower pace. Meanwhile, computing demands …

The field of design and design automation of micro-/nano-circuits and systems has played a
pivotal role in advancing information technologies that are an inseparable part of all our …

Probabilistic (p-) computing is a physics-based approach to addressing computational
problems which are difficult to solve by conventional von Neumann computers. A key …

Probabilistic computing is a computing scheme that offers a more efficient approach than
conventional complementary metal-oxide–semiconductor (CMOS)-based logic in a variety of …

True random number generators (TRNGs) play a pivotal role in solving NP-hard problems,
neural network computing, and hardware accelerators for algorithms, such as the simulated …

Directed acyclic graphs or Bayesian networks that are popular in many AI-related sectors for
probabilistic inference and causal reasoning can be mapped to probabilistic circuits built out …

We present a magnetic tunnel junction (MTJ) based implementation of the spike time-
dependent (STDP) learning for pattern recognition applications. The proposed hybrid …

The recent trend in adapting ultra-energy-efficient (but error-prone) nanomagnetic devices to
non-Boolean computing and information processing (eg stochastic/probabilistic computing …