Memristive crossbar arrays for storage and computing applications
The emergence of memristors with potential applications in data storage and artificial
intelligence has attracted wide attentions. Memristors are assembled in crossbar arrays with …
intelligence has attracted wide attentions. Memristors are assembled in crossbar arrays with …
A review of germanium-antimony-telluride phase change materials for non-volatile memories and optical modulators
Chalcogenide phase change materials based on germanium-antimony-tellurides (GST-
PCMs) have shown outstanding properties in non-volatile memory (NVM) technologies due …
PCMs) have shown outstanding properties in non-volatile memory (NVM) technologies due …
Accurate deep neural network inference using computational phase-change memory
In-memory computing using resistive memory devices is a promising non-von Neumann
approach for making energy-efficient deep learning inference hardware. However, due to …
approach for making energy-efficient deep learning inference hardware. However, due to …
Neuromorphic computing with multi-memristive synapses
Neuromorphic computing has emerged as a promising avenue towards building the next
generation of intelligent computing systems. It has been proposed that memristive devices …
generation of intelligent computing systems. It has been proposed that memristive devices …
Li-ion synaptic transistor for low power analog computing
Nonvolatile redox transistors (NVRTs) based upon Li-ion battery materials are demonstrated
as memory elements for neuromorphic computer architectures with multi-level analog …
as memory elements for neuromorphic computer architectures with multi-level analog …
In-memory hyperdimensional computing
Hyperdimensional computing is an emerging computational framework that takes inspiration
from attributes of neuronal circuits including hyperdimensionality, fully distributed …
from attributes of neuronal circuits including hyperdimensionality, fully distributed …
ECRAM materials, devices, circuits and architectures: A perspective
Non‐von‐Neumann computing using neuromorphic systems based on two‐terminal
resistive nonvolatile memory elements has emerged as a promising approach, but its full …
resistive nonvolatile memory elements has emerged as a promising approach, but its full …
Recent progress in phase-change memory technology
GW Burr, MJ Brightsky, A Sebastian… - IEEE Journal on …, 2016 - ieeexplore.ieee.org
We survey progress in the PCM field over the past five years, ranging from large-scale PCM
demonstrations to materials improvements for high–temperature retention and faster …
demonstrations to materials improvements for high–temperature retention and faster …
Deep learning incorporating biologically inspired neural dynamics and in-memory computing
Spiking neural networks (SNNs) incorporating biologically plausible neurons hold great
promise because of their unique temporal dynamics and energy efficiency. However, SNNs …
promise because of their unique temporal dynamics and energy efficiency. However, SNNs …
A phase-change memory model for neuromorphic computing
Phase-change memory (PCM) is an emerging non-volatile memory technology that is based
on the reversible and rapid phase transition between the amorphous and crystalline phases …
on the reversible and rapid phase transition between the amorphous and crystalline phases …