112 citations · 172 across the 13 of their papers we have counts for
7 papers · 1 filter
Unsupervised local learning based on voltage-dependent synaptic plasticity for resistive and ferroelectric synapses
Nikhil Garg, Ismael Balafrej, Joao Henrique Quintino Palhares +11
The deployment of AI on edge computing devices faces significant challenges related to energy consumption and functionality. These devices could greatly benefit from brain-inspired…
Analytical Modelling of the Transport in Analog Filamentary Conductive-Metal-Oxide/HfOx ReRAM Devices
Donato Francesco Falcone, Stephan Menzel, Tommaso Stecconi +4
The recent co-optimization of memristive technologies and programming algorithms enabled neural networks training with in-memory computing systems. In this context, novel analog fi…
Decoupling Electric Field and Temperature-Driven Atomistic Forming Mechanisms in TaOx/HfO2-Based ReRAMs using Reactive Molecular Dynamics Simulations
Simanta Lahkar, Valeria Bragaglia, Behnaz Bagheri +4
Resistive random access memories (ReRAMs) with a bilayer TaOx/HfO2 stack structure have shown unique multi-level resistive switching capabilities. However, the physical processes g…
Electroforming Kinetics in HfOx/Ti RRAM: Mechanisms Behind Compositional and Thermal Engineering
Manasa Kaniselvan, Kevin Portner, Donato Francesco Falcone +6
A critical issue affecting filamentary resistive random access memory (RRAM) cells is the requirement of high voltages during electroforming. Reducing the magnitude of these voltag…
Hardware Implementation of Ring Oscillator Networks Coupled by BEOL Integrated ReRAM for Associative Memory Tasks
Wooseok Choi, Thomas van Bodegraven, Jelle Verest +8
We demonstrate the first hardware implementation of an oscillatory neural network (ONN) utilizing resistive memory (ReRAM) for coupling elements. A ReRAM crossbar array chip, integ…
Edge Training and Inference with Analog ReRAM Technology for Hand Gesture Recognition
Victoria Clerico, Anirvan Dutta, Donato Francesco Falcone +8
Tactile hand gesture recognition is a crucial task for user control in the automotive sector, where Human-Machine Interactions (HMI) demand low latency and high energy efficiency.…
All-in-One Analog AI Hardware: On-Chip Training and Inference with Conductive-Metal-Oxide/HfOx ReRAM Devices
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi +9
Analog in-memory computing is an emerging paradigm designed to efficiently accelerate deep neural network workloads. Recent advancements have focused on either inference or trainin…