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dc.contributor.authorPark, Jongkil-
dc.contributor.authorJeong, YeonJoo-
dc.contributor.authorKim, Jaewook-
dc.contributor.authorLee, Suyoun-
dc.contributor.authorKwak, Joon Young-
dc.contributor.authorPark, Jong-Keuk-
dc.contributor.authorKim, Inho-
dc.date.accessioned2024-09-19T00:00:28Z-
dc.date.available2024-09-19T00:00:28Z-
dc.date.created2024-09-14-
dc.date.issued2024-04-
dc.identifier.issn2834-9830-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/150606-
dc.description.abstractThis paper presents a large-scale digital neuromorphic processor for spiking neural network emulation. The processor is fabricated in a 28 nm CMOS and occupies a 9.00 mm(2) die area for 262,144 neurons. A time-embedded floating-point leaky integrate-and-fire neuron model is implemented to reduce the size of SRAM and the number of SRAM accesses. It achieves a high-density neuron integration (34.9 k neurons/mm(2)), which is 13 times higher than other state-of-the-art designs. Additionally, it achieves a high-dynamic range synapse (8-bit floating-point) and low energy consumption (28.26 pJ/synaptic operation).-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleHigh-Density Digital Neuromorphic Processor with High-Precision Neural and Synaptic Dynamics and Temporal Acceleration-
dc.typeConference-
dc.identifier.doi10.1109/AICAS59952.2024.10595869-
dc.description.journalClass1-
dc.identifier.bibliographicCitation6th International Conference on AI Circuits and Systems (AICAS), pp.322 - 326-
dc.citation.title6th International Conference on AI Circuits and Systems (AICAS)-
dc.citation.startPage322-
dc.citation.endPage326-
dc.citation.conferencePlaceUS-
dc.citation.conferencePlaceAbu Dhabi, U ARAB EMIRATES-
dc.citation.conferenceDate2024-04-22-
dc.relation.isPartOf2024 IEEE 6TH INTERNATIONAL CONFERENCE ON AI CIRCUITS AND SYSTEMS, AICAS 2024-
dc.identifier.wosid001280469200017-
dc.identifier.scopusid2-s2.0-85199873783-
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KIST Conference Paper > 2024
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