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PyDTNN: A user-friendly and extensible framework for distributed deep learning
dc.contributor.author | Barrachina Mir, Sergio | |
dc.contributor.author | Castelló, Adrián | |
dc.contributor.author | Catalán Carbó, Mar | |
dc.contributor.author | Dolz, Manuel F. | |
dc.contributor.author | Mestre Miravet, Jose Ignacio | |
dc.date.accessioned | 2021-05-11T08:30:43Z | |
dc.date.available | 2021-05-11T08:30:43Z | |
dc.date.issued | 2021-02-22 | |
dc.identifier.citation | Barrachina, S., Castelló, A., Catalán, M. et al. PyDTNN: A user-friendly and extensible framework for distributed deep learning. J Supercomput (2021). https://doi.org/10.1007/s11227-021-03673-z | ca_CA |
dc.identifier.issn | 0920-8542 | |
dc.identifier.issn | 1573-0484 | |
dc.identifier.uri | http://hdl.handle.net/10234/193089 | |
dc.description.abstract | We introduce a framework for training deep neural networks on clusters of computers with the following appealing properties: (1) It is developed in Python, exposing an amiable interface that provides an accessible entry point for the newcomer; (2) it is extensible, offering a customizable tool for the more advanced user in deep learning; (3) it covers the main functionality appearing in convolutional neural networks; and (4) it delivers reasonable inter-node parallel performance exploiting data parallelism by leveraging MPI via MPI4Py for communication and NumPy for the efficient execution of (multithreaded) numerical kernels. | ca_CA |
dc.format.extent | 15 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Springer | ca_CA |
dc.rights | © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | * |
dc.subject | deep neural networks | ca_CA |
dc.subject | distributed parallel training | ca_CA |
dc.subject | Python | ca_CA |
dc.title | PyDTNN: A user-friendly and extensible framework for distributed deep learning | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1007/s11227-021-03673-z | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://www.springer.com/journal/11227 | ca_CA |
dc.type.version | info:eu-repo/semantics/acceptedVersion | ca_CA |
project.funder.name | Ministerio de Ciencia, Innovación y Universidades (Spain) | ca_CA |
project.funder.name | Generalitat Valenciana | ca_CA |
oaire.awardNumber | TIN2017-82972-R | ca_CA |
oaire.awardNumber | CDEIGENT/2018/014 | ca_CA |
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