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Advancing device-based computing by simplifying circuit complexity

Authors
Park, TaehyunKim, MinseoSeo, JuhyungKim, Young-JoonTrivedi, Amit RanjanHan, Joon-KyuYoo, Hocheon
Issue Date
Apr-2025
Publisher
Cell Press
Keywords
circuit compaction; device-based computing; DTI-2: Explore; neuromorphic computing; stochastic computing; transistor counts
Citation
Device, v.3, no.4
Indexed
SCOPUS
ESCI
Journal Title
Device
Volume
3
Number
4
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/207336
DOI
10.1016/j.device.2025.100720
ISSN
2666-9986
2666-9986
Abstract
With Moore's law approaching its scaling limits, the quest for higher integration density in computing devices has become increasingly challenging. Device-based computer architecture can achieve circuit compaction by creating devices with a simpler circuit tailored for specific purposes. However, paradoxically, many of these devices require a greater number of transistors or other electronic components than conventional von Neumann systems. This review highlights recent advances in device-based computing. We seek to demonstrate how device-based computing can be used to implement von Neumann architectures more efficiently through Boolean logic and also to realize next-generation non-von Neumann systems, with a focus on improving integration density and energy efficiency.
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