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A Cloud-Based Framework for Machine Learning Workloads and Applications

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A Cloud-Based Framework for Machine Learning Workloads and Applications

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Lopez Garcia, A.; Marco De Lucas, J.; Antonacci, M.; Zu Castell, W.; David, M.; Hardt, M.; Lloret Iglesias, L.... (2020). A Cloud-Based Framework for Machine Learning Workloads and Applications. IEEE Access. 8:18681-18692. https://doi.org/10.1109/ACCESS.2020.2964386

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/156557

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Title: A Cloud-Based Framework for Machine Learning Workloads and Applications
Author: Lopez Garcia, Alvaro Marco De Lucas, Jesús Antonacci, Marica Zu Castell, Wolfgang David, Mario Hardt, Marcus Lloret Iglesias, Lara Moltó, Germán Plociennik, Marcin Tran, Viet Alic, Andrei Stefan Caballer Fernández, Miguel Campos Plasencia, Isabel Costantini, Alessandro Dlugolinsky, Stefan
UPV Unit: Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular
Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] In this paper we propose a distributed architecture to provide machine learning practitioners with a set of tools and cloud services that cover the whole machine learning development cycle: ranging from the models ...[+]
Subjects: Cloud computing , Computers and information processing , Deep learning , Distributed computing , Machine learning , Serverless architectures
Copyrigths: Reconocimiento (by)
Source:
IEEE Access. (eissn: 2169-3536 )
DOI: 10.1109/ACCESS.2020.2964386
Publisher:
Institute of Electrical and Electronics Engineers
Publisher version: https://doi.org/10.1109/ACCESS.2020.2964386
Project ID:
info:eu-repo/grantAgreement/EC/H2020/777435/EU/Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud/
Thanks:
This work was supported by the project DEEP-Hybrid-DataCloud ``Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud'' that has received funding from the European Union's Horizon 2020 ...[+]
Type: Artículo

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