A Twin-8T SRAM Computation-in-Memory Unit-Macro for Multibit CNN-Based AI Edge Processors

Computation-in-memory (CIM) is a promising candidate to improve the energy efficiency of multiply-and-accumulate (MAC) operations of artificial intelligence (AI) chips. This work presents an static random access memory (SRAM) CIM unit-macro using: 1) compact-rule compatible twin-8T (T8T) cells for w...

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Veröffentlicht in:	IEEE journal of solid-state circuits Jg. 55; H. 1; S. 189 - 202
Hauptverfasser:	Si, Xin, Chen, Jia-Jing, Tu, Yung-Ning, Huang, Wei-Hsing, Wang, Jing-Hong, Chiu, Yen-Cheng, Wei, Wei-Chen, Wu, Ssu-Yen, Sun, Xiaoyu, Liu, Rui, Yu, Shimeng, Liu, Ren-Shuo, Hsieh, Chih-Cheng, Tang, Kea-Tiong, Li, Qiang, Chang, Meng-Fan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial intelligence Artificial intelligence (AI) Common Information Model (computing) computation-in-memory (CIM) convolutional neural network (CNN) Energy efficiency Kernel Mapping Power demand Power efficiency Program processors Random access memory SRAM cells Static random access memory Twin 8T (T8T)
ISSN:	0018-9200, 1558-173X
Online-Zugang:	Volltext
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