Quantum computers, systems that process information leveraging quantum mechanical effects, will require faster and energy-efficient memory components, which will allow them to perform well on complex ...

As IC geometries shrink, the large, consolidated memory blocks within ICs are giving way to tens or even hundreds of smaller memory arrays distributed throughout each chip. These arrays serve as ...

Skyrocketing AI compute workloads and fixed power budgets are forcing chip and system architects to take a much harder look at compute in memory (CIM), which until recently was considered little more ...

Machine learning (ML), a subset of artificial intelligence (AI), has become integral to our lives. It allows us to learn and reason from data using techniques such as deep neural network algorithms.

A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling energy-efficient self-organizing maps without external arithmetic circuits. Memristors, ...

“In-memory computing is an attractive alternative for handling data-intensive tasks as it employs parallel processing without the need for data transfer. Nevertheless, it necessitates a high-density ...