DORY: Automatic End-to-End Deployment of Real-World DNNs on Low-Cost IoT MCUs

The deployment of Deep Neural Networks (DNNs) on end-nodes at the extreme edge of the Internet-of-Things is a critical enabler to support pervasive Deep Learning-enhanced applications. Low-Cost MCU-based end-nodes have limited on-chip memory and often replace caches with scratchpads, to reduce area...

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Bibliographic Details
Published in:	IEEE transactions on computers Vol. 70; no. 8; pp. 1253 - 1268
Main Authors:	Burrello, Alessio, Garofalo, Angelo, Bruschi, Nazareno, Tagliavini, Giuseppe, Rossi, Davide, Conti, Francesco
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Acceleration Artificial neural networks C (programming language) Chips (memory devices) Computer architecture Deep neural networks DNN acceleration edge computing Internet of Things IoT Low cost Machine learning Memory management Micromechanical devices Nodes Open source software Software Source code Static random access memory System-on-chip Task analysis Tiling Topology
ISSN:	0018-9340, 1557-9956
Online Access:	Get full text
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