Content addressable memory (CAM) is widely used in associative search tasks due to its
parallel pattern matching capability. As more complex and data‐intensive tasks emerge, it is …

In this paper, we present a temperature and variability-aware Verilog-A-based compact
model for simulating Ferroelectric FET. The model captures the rich physics of ferroelectric …

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 …

Ferroelectric FET (FeFET) is a singularly attractive emerging technology with a rich feature
set. Boasting high versatility, it has already been implemented in a host of applications, like …

While Graph Neural Networks (GNNs) have demonstrated remarkable achievements in
knowledge graph reasoning, their computational efficiency on conventional computing …

The Ferroelectric Field-Effect Transistor (FeFET) is an emerging Non-Volatile Memory (NVM)
technology enabling novel data-centric architectures that go far beyond von Neumann …

Neuromorphic and in-memory computing architectures using emerging nonvolatile
memories (e-NVMs) have emerged as promising solutions for area-and energy-efficient …

Hyperdimensional computing (HDC) is an emerging learning paradigm that has gained a lot
of attention due to its ability to train with fewer data, lightweight implementation, and …

Physics-based simulations using technology computer aided design (TCAD) offer high
accuracy while suffering from exceedingly slow computations and significant license costs …

The discovery of ferroelectricity in doped HfO2 has led to its widespread use in various
applications, including embedded non-volatile memories and deep learning acceleration …