ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic

Detalles Bibliográficos
Autores: Niknia, Farzad|||0000-0002-4062-3638, Wang, Ziheng|||0000-0001-9668-7318, Liu, Shanshan|||0000-0001-6226-2880, Reviriego Vasallo, Pedro|||0000-0003-2540-5234, Louri, Ahmed|||0000-0003-4262-6688, Lombardi, Fabrizio|||0000-0003-3152-3245
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad Politécnica de Madrid
Repositorio:Archivo Digital UPM
OAI Identifier:oai:oa.upm.es:80698
Acceso en línea:https://oa.upm.es/80698/
Access Level:acceso abierto
Palabra clave:Neurons
Training
Hardware
Backpropagation
Artificial neural networks
Vectors
Nanoscale devices
Artificial neural network (ANN)
multilayer perceptron (MLP)
floating-point
ASIC design
inference
training
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oai_identifier_str oai:oa.upm.es:80698
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network_name_str España
repository_id_str
spelling ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point ArithmeticNiknia, Farzad|||0000-0002-4062-3638Wang, Ziheng|||0000-0001-9668-7318Liu, Shanshan|||0000-0001-6226-2880Reviriego Vasallo, Pedro|||0000-0003-2540-5234Louri, Ahmed|||0000-0003-4262-6688Lombardi, Fabrizio|||0000-0003-3152-3245NeuronsTrainingHardwareBackpropagationArtificial neural networksVectorsNanoscale devicesArtificial neural network (ANN)multilayer perceptron (MLP)floating-pointASIC designinferencetraining20242024-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articlehttps://oa.upm.es/80698/reponame:Archivo Digital UPMinstname:Universidad Politécnica de MadridInglésenopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:oa.upm.es:806982026-06-21T12:45:07Z
dc.title.none.fl_str_mv ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
title ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
spellingShingle ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
Niknia, Farzad|||0000-0002-4062-3638
Neurons
Training
Hardware
Backpropagation
Artificial neural networks
Vectors
Nanoscale devices
Artificial neural network (ANN)
multilayer perceptron (MLP)
floating-point
ASIC design
inference
training
title_short ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
title_full ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
title_fullStr ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
title_full_unstemmed ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
title_sort ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic
dc.creator.none.fl_str_mv Niknia, Farzad|||0000-0002-4062-3638
Wang, Ziheng|||0000-0001-9668-7318
Liu, Shanshan|||0000-0001-6226-2880
Reviriego Vasallo, Pedro|||0000-0003-2540-5234
Louri, Ahmed|||0000-0003-4262-6688
Lombardi, Fabrizio|||0000-0003-3152-3245
author Niknia, Farzad|||0000-0002-4062-3638
author_facet Niknia, Farzad|||0000-0002-4062-3638
Wang, Ziheng|||0000-0001-9668-7318
Liu, Shanshan|||0000-0001-6226-2880
Reviriego Vasallo, Pedro|||0000-0003-2540-5234
Louri, Ahmed|||0000-0003-4262-6688
Lombardi, Fabrizio|||0000-0003-3152-3245
author_role author
author2 Wang, Ziheng|||0000-0001-9668-7318
Liu, Shanshan|||0000-0001-6226-2880
Reviriego Vasallo, Pedro|||0000-0003-2540-5234
Louri, Ahmed|||0000-0003-4262-6688
Lombardi, Fabrizio|||0000-0003-3152-3245
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Neurons
Training
Hardware
Backpropagation
Artificial neural networks
Vectors
Nanoscale devices
Artificial neural network (ANN)
multilayer perceptron (MLP)
floating-point
ASIC design
inference
training
topic Neurons
Training
Hardware
Backpropagation
Artificial neural networks
Vectors
Nanoscale devices
Artificial neural network (ANN)
multilayer perceptron (MLP)
floating-point
ASIC design
inference
training
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://oa.upm.es/80698/
url https://oa.upm.es/80698/
dc.language.none.fl_str_mv Inglés
en
language_invalid_str_mv Inglés
en
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Archivo Digital UPM
instname:Universidad Politécnica de Madrid
instname_str Universidad Politécnica de Madrid
reponame_str Archivo Digital UPM
collection Archivo Digital UPM
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869418128794976256
score 15.300724

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