Neuromorphic computing using non-volatile memory
Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
for implementing massively-parallel and highly energy-efficient neuromorphic computing …
[HTML][HTML] Pathways to efficient neuromorphic computing with non-volatile memory technologies
Historically, memory technologies have been evaluated based on their storage density, cost,
and latencies. Beyond these metrics, the need to enable smarter and intelligent computing …
and latencies. Beyond these metrics, the need to enable smarter and intelligent computing …
Exploring neuromorphic computing based on spiking neural networks: Algorithms to hardware
Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …
attention lately due to its promise of reducing the computational energy, latency, as well as …
Recent advances in synaptic nonvolatile memory devices and compensating architectural and algorithmic methods toward fully integrated neuromorphic chips
Nonvolatile memory (NVM)‐based neuromorphic computing has been attracting
considerable attention from academia and the industry. Although it is not completely …
considerable attention from academia and the industry. Although it is not completely …
The viability of analog-based accelerators for neuromorphic computing: a survey
M Musisi-Nkambwe, S Afshari, H Barnaby… - Neuromorphic …, 2021 - iopscience.iop.org
Focus in deep neural network hardware research for reducing latencies of memory fetches
has steered in the direction of analog-based artificial neural networks (ANN). The promise of …
has steered in the direction of analog-based artificial neural networks (ANN). The promise of …
Toward on-chip acceleration of the backpropagation algorithm using nonvolatile memory
By performing computation at the location of data, non-Von Neumann (VN) computing
should provide power and speed benefits over conventional (eg, VN-based) approaches to …
should provide power and speed benefits over conventional (eg, VN-based) approaches to …
Emerging artificial synaptic devices for neuromorphic computing
In today's era of big‐data, a new computing paradigm beyond today's von‐Neumann
architecture is needed to process these large‐scale datasets efficiently. Inspired by the …
architecture is needed to process these large‐scale datasets efficiently. Inspired by the …
Challenges in materials and devices for resistive-switching-based neuromorphic computing
J Del Valle, JG Ramírez, MJ Rozenberg… - Journal of Applied …, 2018 - pubs.aip.org
This tutorial describes challenges and possible avenues for the implementation of the
components of a solid-state system, which emulates a biological brain. The tutorial is …
components of a solid-state system, which emulates a biological brain. The tutorial is …
Nonvolatile memory materials for neuromorphic intelligent machines
Recent progress in deep learning extends the capability of artificial intelligence to various
practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis …
practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis …
Neuro-inspired computing with emerging nonvolatile memorys
S Yu - Proceedings of the IEEE, 2018 - ieeexplore.ieee.org
This comprehensive review summarizes state of the art, challenges, and prospects of the
neuro-inspired computing with emerging nonvolatile memory devices. First, we discuss the …
neuro-inspired computing with emerging nonvolatile memory devices. First, we discuss the …