A Microscaling Multi-Mode Gain-Cell Computing-in-Memory Macro for Advanced AI Edge Device

The microscaling (MX) format is an emerging data representation that quantizes high-bitwidth floating-point (FP) values into low-bitwidth FP-like values with a shared-scale (SS) exponent. When implemented with computing-in-memory (CIM), MX allows an attractive tradeoff between accuracy and hardware...

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Veröffentlicht in:	IEEE journal of solid-state circuits S. 1 - 14
Hauptverfasser:	Tien, Jen-Chun, Wu, Ping-Chun, Khwa, Win-San, Sanjay Lele, Ashwin, Su, Jian-Wei, Cheng, Chiao-Yen, Hsu, Jun-Ming, Chen, Yu-Chen, Hsieh, Le-Jung, Bai, Jyun-Cheng, Kao, Yu-Sheng, Lou, Tsung-Han, Wu, Jui-Jen, Lo, Chung-Chuan, Liu, Ren-Shuo, Hsieh, Chih-Cheng, Tang, Kea-Tiong, Chang, Meng-Fan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2025
Schlagworte:	Accuracy Adders Artificial intelligence (AI) Artificial neural networks Common Information Model (computing) Common Information Model (electricity) Computer architecture computing-in-memory (CIM) Data transfer Energy consumption gain cell (GC) Hardware In-memory computing microscaling (MX) multiply-and-accumulate (MAC)
ISSN:	0018-9200, 1558-173X
Online-Zugang:	Volltext
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