"SEMS: Scalable Embedding Memory System for Accelerating Embedding-Based DNNs."

Sejin Kim et al. (2022)

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DOI: 10.1109/LCA.2022.3227560

access: closed

type: Journal Article

metadata version: 2023-05-17

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Sejin Kim, Jungwoo Kim, Yongjoo Jang, Jaeha Kung, Sungjin Lee:
SEMS: Scalable Embedding Memory System for Accelerating Embedding-Based DNNs. IEEE Comput. Archit. Lett. 21(2): 157-160 (2022)

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