Memory-centric neuromorphic computing for unstructured data processing

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The unstructured data such as visual information, natural language, and human behaviors opens up a wide array of opportunities in the field of artificial intelligence (AI). The memory-centric neuromorphic computing (MNC) has been proposed for the efficient processing of unstructured data, bypassing the von Neumann bottleneck of current computing architecture. The development of MNC would provide massively parallel processing of unstructured data, realizing the cognitive AI in edge and wearable systems. In this review, recent advances in memory-centric neuromorphic devices are discussed in terms of emerging nonvolatile memories, volatile switches, synaptic plasticity, neuronal models, and memristive neural network.
Publisher
TSINGHUA UNIV PRESS
Issue Date
2021-09
Language
English
Article Type
Review
Citation

NANO RESEARCH, v.14, no.9, pp.3126 - 3142

ISSN
1998-0124
DOI
10.1007/s12274-021-3452-6
URI
http://hdl.handle.net/10203/287224
Appears in Collection
MS-Journal Papers(저널논문)
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