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

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 …

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 …

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

We demonstrate nonvolatile and area-efficient ternary content-addressable memories
(TCAMs) featuring amorphous indium–gallium–zinc–oxide (a-IGZO) ferroelectric field-effect …

The rapidly increasing volume and complexity of data is demanding the relentless scaling of
computing power. With transistor feature size approaching physical limits, the benefits that …

Content Addressable Memory (CAM) is widely used for associative search tasks in
advanced machine learning models and data-intensive applications due to the highly …

Optical neural networks with Mach-Zender interferometers (MZIs) have demonstrated
advantages over their electronic counterparts in computing efficiency and power …

Ternary content addressable memory (TCAM), widely used in network routers and high-
associativity caches, is gaining popularity in machine learning and data-analytic …

CAMs are frequently employed for data-centric applications. They offer excellent parallelism.
Traditionally, they were implemented using the area-consuming SRAM. Recent …