Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

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 …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Nanoscale ionic programmable resistors for analog deep learning are 1000 times smaller
than biological cells, but it is not yet clear how much faster they can be relative to neurons …

In-memory computing architectures based on memristive crossbar arrays could offer higher
computing efficiency than traditional hardware in deep learning applications. However, the …

Emerging memories have been developed as new physical infrastructures for hosting neural
networks owing to their low-power analog computing characteristics. However, accurately …

HfO 2-based resistive switching memory (RRAM) combines several outstanding properties,
such as high scalability, fast switching speed, low power, compatibility with complementary …

Neuromorphic devices and systems have attracted attention as next-generation computing
due to their high efficiency in processing complex data. So far, they have been demonstrated …

A neuromorphic system is composed of hardware-based artificial neurons and synaptic
devices, designed to improve the efficiency of neural computations inspired by energy …

In-memory computing (IMC) refers to non-von Neumann architectures where data are
processed in situ within the memory by taking advantage of physical laws. Among the …