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"34.2 A 16nm 96Kb Integer/Floating-Point ..."

Win-San Khwa et al. (2024)

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DOI: 10.1109/ISSCC49657.2024.10454447

access: closed

type: Conference or Workshop Paper

metadata version: 2024-03-19

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  - conf/isscc/KhwaWWSCKCHCCLLHTC24
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  - https://dblp.org/rec/conf/isscc/KhwaWWSCKCHCCLLHTC24
Win-San Khwa, Ping-Chun Wu, Jui-Jen Wu, Jian-Wei Su, Ho-Yu Chen, Zhao-En Ke, Ting-Chien Chiu, Jun-Ming Hsu, Chiao-Yen Cheng, Yu-Chen Chen, Chung-Chuan Lo, Ren-Shuo Liu, Chih-Cheng Hsieh, Kea-Tiong Tang, Meng-Fan Chang:
34.2 A 16nm 96Kb Integer/Floating-Point Dual-Mode-Gain-Cell-Computing-in-Memory Macro Achieving 73.3-163.3TOPS/W and 33.2-91.2TFLOPS/W for AI-Edge Devices. ISSCC 2024: 568-570

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