Advancing device-based computing by simplifying circuit complexity
- Authors
- Park, Taehyun; Kim, Minseo; Seo, Juhyung; Kim, Young-Joon; Trivedi, Amit Ranjan; Han, Joon-Kyu; Yoo, 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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