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Exploiting bit sparsity in both activation and weight in neural networks accelerators.

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Title: Exploiting bit sparsity in both activation and weight in neural networks accelerators.
Authors: Jing, Naifeng1, Zhang, Zihan1, Sun, Yongshuai1, Liu, Pengyu1, Chen, Liyan1, Wang, Qin1, Jiang, Jianfei1, jiangjianfei@sjtu.edu.cn
Source: Integration: The VLSI Journal; Jan2023, Vol. 88, p400-409, 10p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 160331718
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.vlsi.2022.09.008
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      – Code: eng
        Text: English
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        PageCount: 10
        StartPage: 400
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      – TitleFull: Exploiting bit sparsity in both activation and weight in neural networks accelerators.
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            NameFull: Jing, Naifeng
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            NameFull: Zhang, Zihan
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            NameFull: Sun, Yongshuai
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            NameFull: Liu, Pengyu
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            NameFull: Chen, Liyan
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            NameFull: Wang, Qin
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            NameFull: Jiang, Jianfei
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            – D: 01
              M: 01
              Text: Jan2023
              Type: published
              Y: 2023
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              Value: 88
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