DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Yoo, Hoi-Jun | - |
dc.contributor.advisor | 유회준 | - |
dc.contributor.author | Park, Gwangtae | - |
dc.date.accessioned | 2022-04-27T19:31:26Z | - |
dc.date.available | 2022-04-27T19:31:26Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=948704&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/296021 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2021.2,[iii, 22 p. :] | - |
dc.description.abstract | An energy-efficient capsule network processor is proposed for real-time 3D point cloud segmentation. The proposed processor adopts the heterogeneous core architecture pipelined in channel group level to achieve 35.4% latency reduction. Furthermore, the processor integrates a dynamic route skipping controller that predicts unimportant operations and skips them to reduce the external memory access by 39.1%. At last, the squash activation function unit exploits the look-up table (LUT) based computing with L2-norm approximation, which decreases capsule network inference time while only consuming around 1% area and power of the entire processor. The processor is simulated with the 65nm CMOS technology, showing 94.3mW power consumption and 1.15 TOPS/W energy-efficiency. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Capsule Network▼aDynamic Routing▼a3D Point Cloud Segmentation▼aApproximate Computing▼aLook-up Table▼aExternal Memory Access▼aEnergy-efficient Processor | - |
dc.subject | 캡슐 신경망▼a동적 라우팅▼a3차원 포인트 클라우드 세분화▼a근사 컴퓨팅▼a참조 테이블▼a외부 메모리 접근▼a고효율 프로세서 | - |
dc.title | Energy-efficient capsule network processor for real-time point cloud segmentation | - |
dc.title.alternative | 실시간 포인트 클라우드 세분화를 위한 고효율 캡슐 신경망 프로세서 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전기및전자공학부, | - |
dc.contributor.alternativeauthor | 박광태 | - |
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