A Neural Network Framework for Small Microcontrollers

Autores
Estrebou, César Armando; Fleming, Martín; Saavedra, Marcos David; Adra, Federico
Año de publicación
2021
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This paper presents a lightweight and compact library designed to perform convolutional neural network inference for microcontrollers with severe hardware limitations. A review of similar open source libraries is included and an experiment is developed to compare their performance on different microcontrollers. The proposed library shows at least a 9 times improvement over the implementation of Google Tensorflow Lite with respect to memory usage and inference time.
Workshop: WASI – Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Machine learning
Convolutional Neural Networks
Microcontrollers
Frameworks
TinyML
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/130315

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network_name_str SEDICI (UNLP)
spelling A Neural Network Framework for Small MicrocontrollersEstrebou, César ArmandoFleming, MartínSaavedra, Marcos DavidAdra, FedericoCiencias InformáticasMachine learningConvolutional Neural NetworksMicrocontrollersFrameworksTinyMLThis paper presents a lightweight and compact library designed to perform convolutional neural network inference for microcontrollers with severe hardware limitations. A review of similar open source libraries is included and an experiment is developed to compare their performance on different microcontrollers. The proposed library shows at least a 9 times improvement over the implementation of Google Tensorflow Lite with respect to memory usage and inference time.Workshop: WASI – Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática2021-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf51-60http://sedici.unlp.edu.ar/handle/10915/130315enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4info:eu-repo/semantics/reference/hdl/10915/129809info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:32:47Zoai:sedici.unlp.edu.ar:10915/130315Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:32:47.875SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A Neural Network Framework for Small Microcontrollers
title A Neural Network Framework for Small Microcontrollers
spellingShingle A Neural Network Framework for Small Microcontrollers
Estrebou, César Armando
Ciencias Informáticas
Machine learning
Convolutional Neural Networks
Microcontrollers
Frameworks
TinyML
title_short A Neural Network Framework for Small Microcontrollers
title_full A Neural Network Framework for Small Microcontrollers
title_fullStr A Neural Network Framework for Small Microcontrollers
title_full_unstemmed A Neural Network Framework for Small Microcontrollers
title_sort A Neural Network Framework for Small Microcontrollers
dc.creator.none.fl_str_mv Estrebou, César Armando
Fleming, Martín
Saavedra, Marcos David
Adra, Federico
author Estrebou, César Armando
author_facet Estrebou, César Armando
Fleming, Martín
Saavedra, Marcos David
Adra, Federico
author_role author
author2 Fleming, Martín
Saavedra, Marcos David
Adra, Federico
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Machine learning
Convolutional Neural Networks
Microcontrollers
Frameworks
TinyML
topic Ciencias Informáticas
Machine learning
Convolutional Neural Networks
Microcontrollers
Frameworks
TinyML
dc.description.none.fl_txt_mv This paper presents a lightweight and compact library designed to perform convolutional neural network inference for microcontrollers with severe hardware limitations. A review of similar open source libraries is included and an experiment is developed to compare their performance on different microcontrollers. The proposed library shows at least a 9 times improvement over the implementation of Google Tensorflow Lite with respect to memory usage and inference time.
Workshop: WASI – Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática
description This paper presents a lightweight and compact library designed to perform convolutional neural network inference for microcontrollers with severe hardware limitations. A review of similar open source libraries is included and an experiment is developed to compare their performance on different microcontrollers. The proposed library shows at least a 9 times improvement over the implementation of Google Tensorflow Lite with respect to memory usage and inference time.
publishDate 2021
dc.date.none.fl_str_mv 2021-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4
info:eu-repo/semantics/reference/hdl/10915/129809
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http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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51-60
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