Hyperdimensional computing (HDC) is a brain-inspired computational framework that relies
on long hypervectors (HVs) for learning. In HDC, computational operations consist of simple …

In this paper, we review the recent trends in parallel search and artificial intelligence (AI)
applications using emerging non-volatile ternary content addressable memory (TCAM) …

Pattern searches, a key operation in many data analytic applications, often deal with data
represented by multiple states per dimension. However, hash tables, a common software …

In a number of machine learning models, an input query is searched across the trained class
vectors to find the closest feature class vector in cosine similarity metric. However …

Artificial intelligence has made remarkable advancements in recent years, leading to the
development of algorithms and models capable of handling ever-increasing amounts of …

Indium gallium zinc oxide (IGZO)-based ferroelectric thin-film transistors (FeTFTs) are being
vigorously investigated for being deployed in computing-in-memory (CIM) applications …

Over the past decades, emerging, data-driven machine learning (ML) paradigms have
increased in popularity, and revolutionized many application domains. To date, a substantial …

This letter reports multi-level-cell (MLC) operation of ferroelectric FETs (FeFET) arranged in
AND-connected memory arrays with a bit-error rate (BER) of 4% when writing a random data …

This is the first work to present a reliable application for highly scaled (down to merely 3nm),
multi-bit Ferroelectric FET (FeFET) technology. FeFET is one of the up-and-coming …

The data explosion of Internet of Things (IoT) and machine learning tasks raises a great
demand on highly efficient computing hardware and paradigms. Brain-inspired …