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dc.contributor.author 구자현 -
dc.contributor.author 궁재하 -
dc.contributor.author 노석환 -
dc.date.accessioned 2025-07-30T12:10:10Z -
dc.date.available 2025-07-30T12:10:10Z -
dc.identifier.uri https://scholar.dgist.ac.kr/handle/20.500.11750/58824 -
dc.description.abstract A hardware accelerator includes a processing core including a plurality of multipliers configured to perform one-dimensional (1D) sub-word parallelization between symbols and mantissas of a first tensor and symbols and mantissas of a second tensor, a first processing device configured to operate in a two-dimensional (2D) mode of operation in which the first tensor and the second tensor are coupled to each other, and a second processing device configured to operate in a two-dimensional (2D) mode of operation in which the first tensor and the second tensor are coupled to each other. And a second processing device configured to operate in a three-dimensional (3D) operation mode in which the calculation results of the plurality of multipliers are accumulated in a channel direction, and then a result of accumulating the calculation results is output. -
dc.title 유연한 딥 러닝 가속기 -
dc.title.alternative HARDWARE ACCELERATOR FOR PERFORMING COMPUTATIONS OF DEEP NEURAL NETWORK AND ELECTRONIC DEVICE INCLUDING THE SAME -
dc.type Patent -
dc.publisher.country CC -
dc.identifier.patentApplicationNumber 202310077362.X -
dc.date.application 2023-01-19 -
dc.identifier.patentRegistrationNumber ZL202310077362.X -
dc.date.registration 2026-02-06 -
dc.contributor.assignee (재)대구경북과학기술원(100/0),(주)삼성전자(0/100) -
dc.type.iprs 특허 -
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궁재하
Kung, Jaeha궁재하

Department of Electrical Engineering and Computer Science

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