Most of the energy an AI chip burns never goes toward actual computation. It goes toward moving data: shuttling model weights ...

“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 ...

The internet, social media, and digital technologies have completely transformed the way we establish commercial, personal and professional relationships. At its core, this society relies on the ...

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, ...

SanDisk on Wednesday introduced an interesting new memory that could wed the capacity of 3D NAND and the extreme bandwidth enabled by high bandwidth memory (HBM). SanDisk's high-bandwidth flash (HBF) ...

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 ...

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.

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 ...

Content Addressable Memory (CAM) architectures provide a powerful approach to high-speed data searches by comparing search data against an entire memory in parallel, rather than relying on sequential ...