iMCU: A 28-nm Digital In-Memory Computing-Based Microcontroller Unit for TinyML

Tiny machine learning (TinyML) envisions executing a deep neural network (DNN)-based inference on an edge device for improving battery life, latency, security, and privacy. Toward this vision, recent microcontroller units (MCUs) integrate in-memory computing (IMC) hardware to leverage its high energ...

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Veröffentlicht in:	IEEE journal of solid-state circuits Jg. 59; H. 8; S. 2684 - 2693
Hauptverfasser:	Lin, Chuan-Tung, Huang, Paul Xuanyuanliang, Oh, Jonghyun, Wang, Dewei, Seok, Mingoo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Computation Computer architecture Data models Deep learning Density Energy efficiency Hardware hardware/software co-design In-memory computing in-memory computing (IMC) Machine learning microcontroller units (MCUs) Microcontrollers Multiplication neural network accelerators Random access memory Software Software development State-of-the-art reviews Static random access memory tiny machine learning (TinyML)
ISSN:	0018-9200, 1558-173X
Online-Zugang:	Volltext
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