“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 ...

A new technical paper titled “Embedding security into ferroelectric FET array via in situ memory operation” was published by researchers at Pennsylvania State University, University of Notre Dame, ...

Future of Memory and Storage Conference (FMS) – Kioxia Corporation, a subsidiary of Kioxia Holdings Corporation (TOKYO: 285A) and Sandisk C ...

A Nature paper describes an innovative analog in-memory computing (IMC) architecture tailored for the attention mechanism in large language models (LLMs). They want to drastically reduce latency and ...

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

TetraMem Inc., a Silicon Valley–based semiconductor company developing analog in-memory computing (IMC) solutions, today announced the successful tape-out, manufacturing, and initial silicon ...

The big problem that I am having is how to create the arrays (or arrays of pointers really) to dynamically assign memory at run time, to be able to collect the information from multiple selections ...

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.

The big picture: If successfully scaled to industrial production, these chips could extend Moore's Law into the atomic domain by enabling far greater component density without incurring unsustainable ...

For decades, compute architectures have relied on dynamic random-access memory (DRAM) as their main memory, providing temporary storage from which processing units retrieve data and program code. The ...