Semiconductor Engineering

Stacked Ferroelectric Memory Array Comprised Of Laterally Gated Ferroelectric Field-Effect Transistors

“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 ...
Nature

Highly-scaled and fully-integrated 3-dimensional ferroelectric transistor array for hardware implementation of neural networks

Hardware-based neural networks (NNs) can provide a significant breakthrough in artificial intelligence applications due to their ability to extract features from unstructured data and learn from them.
New Electronics

CEA-Leti demonstrates 22nm FeRAM breakthrough for edge AI applications

The development, presented at the VLSI Symposium in Honolulu, addresses long-standing challenges in achieving competitive ...
EDN

Would custom memory ease your SoC design?

A case study shows how custom memory design can adapt to functional, timing, or layout requirements of a particular SoC.
Nature

CMOS-compatible electrochemical synaptic transistor arrays for deep learning accelerators

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

FeFET Memory Encrypted Inside The Storage Array

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, ...
NextBigFuture

Analog in-memory Computing Attention Mechanism for Fast and Energy-efficient Large Language Models

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 ...
AFP

TetraMem Announces 22nm Multi-Level RRAM Analog In-Memory Computing SoC Milestone

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 ...
EDN

DRAM for energy- and area-efficient analog in-memory computing

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.
Nanowerk

Stacked memristor arrays compute Euclidean distance in memory to accelerate self-organizing maps

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

C - using malloc to dynamically assign memory for a array of strings

Hi,<BR><BR>I've been having some difficulty with a C assignment that I have (I'm starting to realize how much PHP and Java spoils me!). Its a simple cash register that asks for the type of purchase, ...