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 …

HfO 2-based FeFET is a remarkably promising candidate among emerging memory
technologies. Its manifold applications range from nonvolatile memory to neuromorphic …

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 …

Digital processing-in-memory (PIM) architectures are rapidly emerging to overcome the
memory-wall bottleneck by integrating logic within memory elements. Such architectures …

Digital processing-in-memory (PIM) architectures mitigate the memory wall problem by
facilitating parallel bitwise operations directly within memory. Recent works have …

Memristor-based crossbars, which can achieve 1-2 orders of magnitude energy efficiency
improvement over digital machines, have been introduced to accelerate the neural networks …

In this study, we proposed a novel multi-bit content addressable memory (MCAM) cell based
on one single double-gated ferroelectric-gate FET (DG-FeFET). Baseline DG-FeFET has …

Ferroelectric FETs (FeFETs) are promising emerging nonvolatile memory devices due to
their attractive features such as CMOS compatibility, non-volatility, multi-level cell (MLC) …

The throughput and energy efficiency of compute-centric architectures for memory intensive
Deep Neural Networks (DNN) applications are limited by memory bound issues like high …

The demand for high density storage devices are increasing with the surge in data intensive
applications. The exploration of multi-level cell (MLC) memories is pivotal due to the …