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Journal Article 차세대 뉴로모픽 하드웨어 기술 동향
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Authors
문승언, 임종필, 김정훈, 이재우, 이미영, 이주현, 강승열, 황치선, 윤성민, 김대환, 민경식, 박배호
Issue Date
2018-12
Citation
전자통신동향분석, v.33, no.6, pp.58-68
ISSN
1225-6455
Publisher
한국전자통신연구원 (ETRI)
Language
Korean
Type
Journal Article
DOI
https://dx.doi.org/10.22648/ETRI.2018.J.330607
Abstract
A neuromorphic hardware that mimics biological perceptions and has a path toward human-level artificial intelligence (AI) was developed. In contrast with software-based AI using a conventional Von Neumann computer architecture, neuromorphic hardware-based AI has a power-efficient operation with simultaneous memorization and calculation, which is the operation method of the human brain. For an ideal neuromorphic device similar to the human brain, many technical huddles should be overcome; for example, new materials and structures for the synapses and neurons, an ultra-high density integration process, and neuromorphic modeling should be developed, and a better biological understanding of learning, memory, and cognition of the brain should be achieved. In this paper, studies attempting to overcome the limitations of next-generation neuromorphic hardware technologies are reviewed.
KSP Keywords
Computer Architecture, Efficient operation, Neuromorphic hardware, Next-generation, Operation method, Power-efficient, artificial intelligence, high density integration, human brain, new materials, ultra-high density
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
Type 4: