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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Bibliographic Details
Published in:	IEEE journal of solid-state circuits Vol. 59; no. 8; pp. 2684 - 2693
Main Authors:	Lin, Chuan-Tung, Huang, Paul Xuanyuanliang, Oh, Jonghyun, Wang, Dewei, Seok, Mingoo
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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 Access:	Get full text
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