In this manuscript, recent progress in the area of resistive random access memory (RRAM)
technology which is considered one of the most standout emerging memory technologies …

Content-addressable memory (CAM) and associative memory (AM) are types of storage
structures that allow searching by content as opposed to searching by address. Such …

Deep neural networks are efficient at learning from large sets of labelled data, but struggle to
adapt to previously unseen data. In pursuit of generalized artificial intelligence, one …

A content-addressable memory compares an input search word against all rows of stored
words in an array in a highly parallel manner. While supplying a very powerful functionality …

We report a monolithically integrated 3-D metal-oxide memristor crossbar circuit suitable for
analog, and in particular, neuromorphic computing applications. The demonstrated crossbar …

A dynamic Verilog-A resistive random access memory (RRAM) compact model, including
cycle-to-cycle variation, is developed for circuit/system explorations. The model not only …

Tree-based machine learning techniques, such as Decision Trees and Random Forests, are
top performers in several domains as they do well with limited training datasets and offer …

Ferroelectric field effect transistors (FeFETs) are being actively investigated with the
potential for in-memory computing (IMC) over other nonvolatile memories (NVMs). Content …

Nonvolatile memory (NVM)-based computing-in-memory (nvCIM) is a promising candidate
for artificial intelligence (AI) edge devices to overcome the latency and energy consumption …

Modern computing machines are increasingly characterized by large scale parallelism in
hardware (such as GPGPUs) and advent of large scale and innovative memory blocks …