Approximate computing has emerged as a new paradigm for high-performance and energy-
efficient design of circuits and systems. For the many approximate arithmetic circuits …

Neural networks (NNs) are effective machine learning models that require significant
hardware and energy consumption in their computing process. To implement NNs …

With the widespread use of mobile computing and internet of things, secured communication
and chip authentication have become extremely important. Hardware‐based security …

Hyperdimensional computing (HDC) is an emerging computing paradigm that imitates the
brain's structure to offer a powerful and efficient processing and learning model. In HDC, the …

Stochastic logic performs computation on data represented by random bit-streams. The
representation allows complex arithmetic to be performed with very simple logic, but it …

Abstract Convolutional Neural Networks (CNNs) achieve state-of-the-art performance in
many recognition problems. However, CNN models are computation-intensive and require …

Probabilistic computing is a paradigm in which data are not represented by stable bits, but
rather by the probability of a metastable bit to be in a particular state. The development of …

Memristive devices offer desirable voltage-regulated conductance switching and promise to
address zettabyte storage challenges in the big-data era. Generally, most of these reported …

When a computational task tolerates a relaxation of its specification or when an algorithm
tolerates the effects of noise in its execution, hardware, system software, and programming …

Arithmetic plays a major role in a computer? s performance and efficiency. Building new
computing platforms supported by the traditional binary arithmetic and silicon-based …