Ferroelectric materials, the charge equivalent of magnets, have been the subject of
continued research interest since their discovery more than 100 years ago. The …

In-memory computing (IMC) refers to non-von Neumann architectures where data are
processed in situ within the memory by taking advantage of physical laws. Among the …

Hyper-Dimensional computing (HDC) is a brain-inspired learning approach for efficient and
robust learning on today's embedded devices. HDC supports single-pass learning, where it …

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

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 …

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

The separation of computing units and memory in the computer architecture mandates
energy-intensive data transfers creating the von Neumann bottleneck. This bottleneck is …

The finding of the robust ferroelectricity in HfO 2-based thin films is fantastic from the view
point of both the fundamentals and the applications. In this review article, the current …

A fast and efficient search function across the database has been a core component for a
number of data-intensive tasks in machine learning, IoT applications, and inference …