Artificial intelligence has become indispensable in modern life, but its energy consumption
has become a significant concern due to its huge storage and computational demands …

Intelligent computing paradigms have become increasingly important for the efficient
processing of massive amounts of data. However, using traditional electronic devices to …

The dynamical properties of skyrmions can be exploited to build devices with new
functionalities. Here, we first investigate a skyrmion-based ring-shaped device by means of …

Topological solitons are exciting candidates for the physical implementation of next-
generation computing systems. As these solitons are nanoscale and can be controlled with …

Many efforts have been made to improve the neuron integration efficiency on neuromorphic
chips, such as using emerging memory devices and shrinking CMOS technology nodes …

Data movement overheads caused by the recent explosion in big data applications have
made traditional von Neumann architecture fails to tackle big data workloads. Processing in …

Separate memory and processing units are utilized in conventional von Neumann
computational architectures. However, regarding the energy and the time, it is costly to …

The design of systems implementing low precision neural networks with emerging memories
such as resistive random access memory (RRAM) is a significant lead for reducing the …

Magnetic skyrmions are emerging as key elements of unconventional operations having
unique properties such as small size and low current manipulation. In particular, it is …

Spiking neural network (SNN) has emerged as one of the most powerful brain-inspired
computing paradigms in complex pattern recognition tasks that can be enabled by …