A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications.

By Kuk-Hwan Kim, Siddharth Gaba, D. Wheeler, J. Cruz-Albrecht, T. Hussain, Narayan Srinivasa, Wei Dang Lu. Nano letters (Print), 2012

886 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/96531e1936fd37e3690d47a67f4fd44ee41ad4b9

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In Cellular and Molecular Neuroscience

In Electrical and Electronic Engineering

Citations in the corpus

Finding a roadmap to achieve large neuromorphic hardware systems (2013, background): “Recently, a team from U. of Michigan announced the ﬁrst functioning memristor two-dimensional (30 × 30) array built on a CMOS chip in 2012 (Kim et al., 2012), claiming applications in neuromorphic engineering, the same group has published innovative devices for digital (Jo and Lu, 2009) and analog…”
Face classification using electronic synapses (2017, methodology): “Besides, they are compatible with CMOS fabrication process 30–32 and can be scaled down 33 remarkably to reach density as high as 10 11 synapses per cm 2 .”
Large-Scale Optical Neural Networks based on Photoelectric Multiplication (2018, background): “Analog crossbar arrays based on CMOS gates [18] or memristors [19, 20] promise better performance, but as analog electronic devices, they suffer from calibration issues and limited accuracy [21].”
Memory and Information Processing in Neuromorphic Systems (2015, background): “In particular, there have been many recent publications describing the use of new materials and nano-technologies for building nano-scale devices that can emulate some of the properties observed in biological synapses [15], [16], [17], [18], [19], [20].”
The future of electronics based on memristive systems (2018, background): “…not be able to provide the required bandwidth between the memristor layer and the CMOS circuitry, and monolithic integration of memristor arrays directly on top of CMOS circuitry with very-high-density local interconnects is necessary and has indeed been shown experimentally to be feasible 52,53 .”
ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars (2016, background): “Memristor crossbars have been recently proposed for analog dot product computations [32], [51].”
An artificial nociceptor based on a diffusive memristor (2018, background): “…represent information, memristor has been demonstrated for a wide variety of applications ranging from non-volatile memory 16 – 32 , bio-system emulators 33 – 36 , analog 37,38,39 and neuromorphic computing 40 – 46 , recon ﬁ gurable radio-frequency systems 47,48 to security applications 49 – 54 .”
Neuro-Inspired Computing With Emerging Nonvolatile Memorys (2018, background): “[95] demonstrated onetime programming weights into 40 × 40 Ag: a-Si crossbar array.”