Memristive devices, which combine a resistor with memory functions such that voltage
pulses can change their resistance (and hence their memory state) in a nonvolatile manner …

In-memory computing (IMC) has emerged as a new computing paradigm able to alleviate or
suppress the memory bottleneck, which is the major concern for energy efficiency and …

With the demand for low‐power‐operating artificial intelligence systems, bio‐inspired
memristor devices exhibit potential in terms of high‐density memory functions and the …

Memristor-integrated passive crossbar arrays (CAs) could potentially accelerate neural
network (NN) computations, but studies on these devices are limited to software-based …

Photonic in-memory computing exhibits promising potential to address the inherent
limitations of traditional von Neumann architecture. In this study, we demonstrate a tantalum …

Tree-based machine learning techniques, such as Decision Trees and Random Forests, are
top performers in several domains as they do well with limited training datasets and offer …

The recent advancements in multivalued logic gates represent a rapid paradigm shift in
semiconductor technology toward a new era of hyper Moore's law. Particularly, the …

Content addressable memory (CAM) is widely used for data-centric computing for its
massive parallelism and pattern matching capability. Though the CAM density has been …

As a leading candidate for further memory and computing applications, memristors are
being developed in an important direction of transient electronics. Herein, wafer‐scale acidic …

With the rapid growth of computer science and big data, the traditional von Neumann
architecture suffers the aggravating data communication costs due to the separated structure …