This tutorial introduces the basics of emerging nonvolatile memory (NVM) technologies
including spin-transfer-torque magnetic random access memory (STTMRAM), phase …

There has been a surge of interest in Non-Volatile Memory (NVM) in recent years. With
many advantages, such as density and power consumption, NVM is carving out a place in …

Convolution neural networks (CNNs) are the heart of deep learning applications. Recent
works PRIME [1] and ISAAC [2] demonstrated the promise of using resistive random access …

Processing-in-memory (PIM) is a promising solution to address the" memory wall"
challenges for future computer systems. Prior proposed PIM architectures put additional …

The scalability of DRAM faces challenges from increasing power consumption and the
difficulty of building high aspect ratio capacitors. Consequently, emerging memory …

A simple method of trajectory generation of robot manipulators is presented. It is based on
an optimal control problem formulation. The jerk, the third derivative of position, of the …

Although ReRAM-based convolutional neural network (CNN) accelerators have been widely
studied, state-of-the-art solutions suffer from either incapability of training (eg, ISSAC [1]) or …

In this work, a built-in selector synaptic memristor is proposed to minimize sneak current in
synapse array. The Ti/TiO 2/HfO 2/Si device exhibits nonlinear and high rectifying current …

As its core computation, a self-attention mechanism gauges pairwise correlations across the
entire input sequence. Despite favorable performance, calculating pairwise correlations is …

A 3 CNFETs and 2 memristors-based half-select disturbance free 3T2R resistive RAM
(RRAM) cell is proposed in this paper. While the two memristors act as the nonvolatile …