Computing in memory (CIM) could be used to overcome the von Neumann bottleneck and to
provide sustainable improvements in computing throughput and energy efficiency …

Computing is a critical driving force in the development of human civilization. In recent years,
we have witnessed the emergence of intelligent computing, a new computing paradigm that …

The rapid growth of deep learning, spurred by its successes in various fields ranging from
face recognition [1] to game playing [2], has also triggered a growing interest in the design of …

Artificial intelligence (AI) and machine learning (ML) are revolutionizing many fields of study,
such as visual recognition, natural language processing, autonomous vehicles, and …

Brain-inspired computing is a growing and interdisciplinary area of research that
investigates how the computational principles of the biological brain can be translated into …

Conventional von Neumann architecture faces many challenges in dealing with data-
intensive artificial intelligence tasks efficiently due to huge amounts of data movement …

The growth of data and Internet of Things challenges traditional hardware, which encounters
efficiency and power issues owing to separate functional units for sensors, memory, and …

This article presents a compact, robust, and transposable SRAM in-memory computing
(IMC) macro to support feed forward (FF) and back propagation (BP) computation within a …

The rapid growth of CMOS logic circuits has surpassed the advancements in memory
access, leading to significant “memory wall” bottlenecks, particularly in artificial intelligence …

Currently, halide perovskites (HPs) are gaining traction in multiple applications, such as
photovoltaics and resistive switching (RS) devices. In RS devices, the high electrical …