Volatile and nonvolatile memristive devices for neuromorphic computing
Ion migration as well as electron transfer and coupling in resistive switching materials
endow memristors with a physically tunable conductance to resemble synapses, neurons …
endow memristors with a physically tunable conductance to resemble synapses, neurons …
Challenges and trends of SRAM-based computing-in-memory for AI edge devices
CJ Jhang, CX Xue, JM Hung… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
When applied to artificial intelligence edge devices, the conventionally von Neumann
computing architecture imposes numerous challenges (eg, improving the energy efficiency) …
computing architecture imposes numerous challenges (eg, improving the energy efficiency) …
Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing
EJ Fuller, ST Keene, A Melianas, Z Wang, S Agarwal… - Science, 2019 - science.org
Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional
computing through parallel programming and readout of artificial neural network weights in …
computing through parallel programming and readout of artificial neural network weights in …
Memristor‐based analog computation and neural network classification with a dot product engine
Using memristor crossbar arrays to accelerate computations is a promising approach to
efficiently implement algorithms in deep neural networks. Early demonstrations, however …
efficiently implement algorithms in deep neural networks. Early demonstrations, however …
A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing
Y Van De Burgt, E Lubberman, EJ Fuller, ST Keene… - Nature materials, 2017 - nature.com
The brain is capable of massively parallel information processing while consuming only∼ 1–
100 fJ per synaptic event,. Inspired by the efficiency of the brain, CMOS-based neural …
100 fJ per synaptic event,. Inspired by the efficiency of the brain, CMOS-based neural …
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 …
Probabilistic neural computing with stochastic devices
S Misra, LC Bland, SG Cardwell… - Advanced …, 2023 - Wiley Online Library
The brain has effectively proven a powerful inspiration for the development of computing
architectures in which processing is tightly integrated with memory, communication is event …
architectures in which processing is tightly integrated with memory, communication is event …
Sparse coding with memristor networks
PM Sheridan, F Cai, C Du, W Ma, Z Zhang… - Nature …, 2017 - nature.com
Sparse representation of information provides a powerful means to perform feature
extraction on high-dimensional data and is of broad interest for applications in signal …
extraction on high-dimensional data and is of broad interest for applications in signal …
Photonic multiply-accumulate operations for neural networks
MA Nahmias, TF De Lima, AN Tait… - IEEE Journal of …, 2019 - ieeexplore.ieee.org
It has long been known that photonic communication can alleviate the data movement
bottlenecks that plague conventional microelectronic processors. More recently, there has …
bottlenecks that plague conventional microelectronic processors. More recently, there has …
[HTML][HTML] Analog architectures for neural network acceleration based on non-volatile memory
TP **ao, CH Bennett, B Feinberg, S Agarwal… - Applied Physics …, 2020 - pubs.aip.org
Analog hardware accelerators, which perform computation within a dense memory array,
have the potential to overcome the major bottlenecks faced by digital hardware for data …
have the potential to overcome the major bottlenecks faced by digital hardware for data …