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 …

Memristors are now becoming a prominent candidate to serve as the building blocks of non-
von Neumann in-memory computing architectures. By mapping analog numerical matrices …

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 …

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 …

Modern analog computing, by gaining momentum from nonvolatile resistive memory
devices, deals with matrix computations. In-memory analog computing has been …

The increasing demand for data-intensive computing applications, such as artificial
intelligence (AI) and more specifically machine learning (ML), raises the need for novel …

Matrix-vector multiplication (MVM) is the core operation of many important algorithms.
Crosspoint resistive memory array enables naturally calculating MVM in one operation, thus …

Analog matrix computing (AMC) with resistive memory implies naturally massive parallelism
and in-memory processing, thus representing a promising solution for accelerating data …

In-memory computing (IMC) has emerged as one of the most promising candidates for
distributed computing frameworks such as edge computing, owing to its unrivalled energy …

Matrix operations are widely used in practical engineering, but the traditional processing
methods rely on the loop iterations and neural network algorithm on the software, requiring a …