Concepedia

A four-megabit compute-in-memory macro with eight-bit precision based on CMOS and resistive random-access memory for AI edge devices

Je-Min Hung, Cheng-Xin Xue, Hui-Yao Kao, Yen-Hsiang Huang, Fu-Chun Chang, Sheng-Po Huang, Ta-Wei Liu, Chuan-Jia Jhang, Chin-I Su, Win-San Khwa,

Nature Electronics · 2021 · 112 citations · 45 references

Concepts

ComputingComputer EngineeringComputer ScienceArtificial IntelligenceComputer ArchitectureEdge ComputingEdge ArchitectureEdge Artificial IntelligenceEdge DevicesMemory Subsystem DesignEdge Computing ArchitecturesEdge Computing HardwareEdge IntelligenceEdge-ai IntegrationPrecisionRandom Access Memory (Ram)Random-access MemoryResistive Random-access Memory

References

45

The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]

Li Deng · IEEE Signal Processing Magazine · 2012 · 4.6K citations

Computing, Computer Science, Artificial Intelligence +13

Memristive devices for computing

J. Joshua Yang, Dmitri B. Strukov, Duncan R. Stewart · Nature Nanotechnology · 2012 · 3.8K citations

Engineering, Computer Engineering, Electrical Engineering +11

Training and operation of an integrated neuromorphic network based on metal-oxide memristors

M. Prezioso, Farshad Merrikh‐Bayat, Brian D. Hoskins et al. · Nature · 2015 · 2.9K citations · Full text

Life Sciences, Electrical Engineering, Materials Science +12

In-memory computing with resistive switching devices

Daniele Ielmini, H.‐S. Philip Wong · Nature Electronics · 2018 · 2.2K citations · Full text

Engineering, Computer Engineering, Electrical Engineering +9

Fully hardware-implemented memristor convolutional neural network

Peng Yao, Huaqiang Wu, Bin Gao et al. · Nature · 2020 · 2.1K citations

Engineering, Computer Engineering, Electrical Engineering +12