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Akademický článek

Non-Invasive, Memory Access-Triggered Near-Data Processing for DNN Training Acceleration on GPUs

Autor: Hyungkyu Ham, Hyunuk Cho, Minjae Kim, Jueon Park, Jeongmin Hong, Hyojin Sung, Eunhyeok Park, Euicheol Lim, Gwangsun Kim

Publikováno v: IEEE Access, Vol 12, Pp 142651-142667 (2024)

Currently, GPUs face significant challenges due to limited off-chip bandwidth (BW) and memory capacity during DNN training. To address these bottlenecks, we propose a memory access-triggered near-data processing matNDP architecture that offloads memo

Externí odkaz: https://doaj.org/article/5e0733ab887241b48181918dc53d2a04

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Akademický článek

Helical Artifact Reduction Method Using Image Segmentation With CNN Denoising Technique

Autor: Seungwon Choi, Byeongjoon Kim, Chulkyu Park, Jueon Park, Yousuk Kim, Sungil Choi, Jongduk Baek

Publikováno v: IEEE Access, Vol 11, Pp 49261-49272 (2023)

Helical computed tomography (CT) scans are often performed to obtain three-dimensional images of an object that is longer than the detector. However, the existing quasi-exact and exact reconstruction methods, such as re-binning and Katsevich algorith

Externí odkaz: https://doaj.org/article/4bd94d6e522e4dc098c694ee879bc3bc

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