Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud

Livrables

Intermediate Status Report about Use Cases

Intermediate Status Report about use case integration and Devops methods

Available Technologies for accelerators and HPC

Assessment of available technologies for supporting accelerators and HPC, initial design and implementation plan (all tasks)

Final Report about Use Case integration

Final Report about use case integration

Consolidated reports from global DEEP meetings.
First prototype of the DEEP as a Service

First prototype implementation of the DEEP as a Service solution

Pilot testbed

Pilot testbed and integration architecture with EOSC large scale infrastructures

Final implementation of software platform for accessing accelerators and HPC
First Software Platform

First implementation of software platform for accessing accelerators and HPC

Implementation of Dissemination and Exploitation Report.
Design for the DEEP as a Service solution

Design document and work plan for the DEEP as a Service solution

Definition of the Architecture of the Hybrid Cloud

Definition of the architecture of the High Level Hybrid Cloud

Updated Dissemination and Exploitation Plan.
Initial plan for Use Cases

Initial Plan on the selection of use cases and the strategy for the devops pipelines.

High Level Hybrid Cloud solutions prototype

High Level Hybrid Cloud solutions prototype completed

Updated reports from global DEEP meetings.
Final Report on Dissemination and Exploitation.
Final report on EOSC integration and software management activities
Communication Measures: Plan and Implementation Status.
State-of-the-art on Machine Learning frameworks

State-of-the-art Deep Learning (DL), Neural Network (NN) and Machine Learning (ML) frameworks and libraries.

Final release of High Level Hybrid Cloud

Final release of High Level Hybrid Cloud solutions completed and deployed

Dissemination and Exploitation Plan.
Status of Software releases
Final implementation of the DEEP as a Service solution

Report on the final implementation of the DEEP as a Service solution.

Data Management considerations and initial plan

This deliverable will analyze the implications of existing Data Management Plans for the different datasets in the Case Studies, and how the derived data should be considered in the corresponding data life cycle.

Publications

A set of common software quality assurance baseline criteria for research projects

Auteurs: Orviz, Pablo; López García, Álvaro; Duma, Doina Cristina; Donvito, Giacinto; David, Mario; Gomes, Jorge
Publié dans: Numéro 1, 2018
Éditeur: N/A

An Information-centric Approach for Slice Monitoring from Edge Devices to Clouds

Auteurs: Binh Minh Nguyen, Huan Phan, Duong Quang Ha, Giang Nguyen
Publié dans: Procedia Computer Science, Numéro 130, 2018, Page(s) 326-335, ISSN 1877-0509
Éditeur: Elsevier
DOI: 10.1016/j.procs.2018.04.046

A heuristics approach to mine behavioural data logs in mobile malware detection system

Auteurs: Giang Nguyen, Binh Minh Nguyen, Dang Tran, Ladislav Hluchy
Publié dans: Data & Knowledge Engineering, Numéro 115, 2018, Page(s) 129-151, ISSN 0169-023X
Éditeur: Elsevier BV
DOI: 10.1016/j.datak.2018.03.002

A Multivariate Fuzzy Time Series Resource Forecast Model for Clouds using LSTM and Data Correlation Analysis

Auteurs: Nhuan Tran, Thang Nguyen, Binh Minh Nguyen, Giang Nguyen
Publié dans: Procedia Computer Science, Numéro 126, 2018, Page(s) 636-645, ISSN 1877-0509
Éditeur: Elsevier
DOI: 10.1016/j.procs.2018.07.298

Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey

Auteurs: Giang Nguyen, Stefan Dlugolinsky, Martin Bobák, Viet Tran, Álvaro López García, Ignacio Heredia, Peter Malík, Ladislav Hluchý
Publié dans: Artificial Intelligence Review, 2019, ISSN 0269-2821
Éditeur: Kluwer Academic Publishers
DOI: 10.1007/s10462-018-09679-z

Deep learning for weed identification based on seed images

Auteurs: Francisco Pando, Ignacio Heredia, Carlos Aedo Pérez, Mauricio Velayos Rodríguez, Lara Lloret Iglesias, Joel Calvo
Publié dans: Biodiversity Information Science and Standards, Numéro 2, 2018, Page(s) e25749, ISSN 2535-0897
Éditeur: Pensoft
DOI: 10.3897/biss.2.25749

Convolutional Neural Networks for Phytoplankton identification and classification

Auteurs: Lara Lloret, Ignacio Heredia, Fernando Aguilar, Elisabeth Debusschere, Klaas Deneudt, Francisco Hernandez
Publié dans: Biodiversity Information Science and Standards, Numéro 2, 2018, Page(s) e25762, ISSN 2535-0897
Éditeur: Pensoft
DOI: 10.3897/biss.2.25762

New Method for Constructing a Visibility Graph-Network in 3D Space and a New Hybrid System of Modeling

Auteurs: Matej Babič, Ladislav Hluchy, Peter Krammer, Branko Matovič, Ravi Kumar, Pavel Kovač
Publié dans: Computing and Informatics, Numéro 36/5, 2017, Page(s) 1107-1126, ISSN 1335-9150
Éditeur: Slovak Academic Press Ltd.
DOI: 10.4149/cai_2017_5_1107

Estimation of high frequency nutrient concentrations from water quality surrogates using machine learning methods

Auteurs: María Castrillo, Álvaro López García
Publié dans: Water Research, Numéro 172, 2020, Page(s) 115490, ISSN 0043-1354
Éditeur: Elsevier BV
DOI: 10.1016/j.watres.2020.115490

A workbench for species identification based on images and deep learning techniques

Auteurs: Ignacio Heredia, Lara Lloret, Jesús Marco, Francisco Pando
Publié dans: Proceedings of TDWG, Numéro 1, 2017, Page(s) e20569, ISSN 2535-0897
Éditeur: Pensoft
DOI: 10.3897/tdwgproceedings.1.20569

A Cloud-Based Framework for Machine Learning Workloads and Applications

Auteurs: Alvaro Lopez Garcia, Viet Tran, Andy S. Alic, Miguel Caballer, Isabel Campos Plasencia, Alessandro Costantini, Stefan Dlugolinsky, Doina Cristina Duma, Giacinto Donvito, Jorge Gomes, Ignacio Heredia Cacha, Jesus Marco De Lucas, Keiichi Ito, Valentin Y. Kozlov, Giang Nguyen, Pablo Orviz Fernandez, Zdenek Sustr, Pawel Wolniewicz, Marica Antonacci, Wolfgang Zu Castell, Mario David, Marcus Hardt, Lara
Publié dans: IEEE Access, Numéro 8, 2020, Page(s) 18681-18692, ISSN 2169-3536
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/ACCESS.2020.2964386

DEEPaaS API: a REST API for Machine Learning and Deep Learning models

Auteurs: Álvaro López García
Publié dans: Journal of Open Source Software, Numéro 4/42, 2019, Page(s) 1517, ISSN 2475-9066
Éditeur: NumFocus
DOI: 10.21105/joss.01517

DEEP-HybridDataCloud

Auteurs: Donvito, Giacinto; Gomes, Jorge; Ferrer, A. Juan; Kozlov, Valentin; López García, Álvaro; Matyska, Ludek; Meyer, Norbert; Moltó, Germán; Tran, Viet; Castell, Wolfgang zu
Publié dans: ISC High Performance Computing, 2018
Éditeur: ISC High Performance Computing

DEEP: Hybrid Approach for Deep Learning

Auteurs: Alic, Andy S.; Antonacci, Marica; Caballer, Miguel; Campos, Isabel; Costantini, Alessandro; David, Mario; Dlugolinsky, Stefan; Donvito, Giacinto; Duma, Cristina; Gomes, Jorge; Hardt, Marcus; Heredia, Ignacio; Hluchy, Ladislav; Ito, Keiichi; Kozlov, Valentin; Lloret, Lara; López García, Alvaro; Marco, Jesus; Matyska, Ludek; Moltó, Germán; Nguyen, Giang; Orviz, Pablo; Plociennik, Marcin; Šustr,
Publié dans: 2019
Éditeur: ISC

Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems

Auteurs: Cavallaro, Gabriele; Kozlov, Valentin; Götz, Markus; Riedel, Morris
Publié dans: Proc. of the 2019 conference on Big Data from Space (BiDS’2019), EUR 29660 EN, ISBN 978-92-76-00034-1, doi:10.2760/848593<br/>Conference on Big Data from Space (BiDS'19), Munich, Germany, 2019-02-19 - 2019-02-21, Numéro 19, 2019, ISBN 978-92-76-00034-1
Éditeur: Publications Office of the European Union
DOI: 10.2760/848593

Rootless Containers with Udocker

Auteurs: Gomes, Jorge; David, Mário; Martins, João Paulo; Pina, João; Campos, Isabel; López Garcia, Alvaro; Orviz, Pablo; Kozlov, Valentin
Publié dans: ISC High Performance (2019), Numéro 7, 2019
Éditeur: ISC

Benchmarking Deep Learning Infrastructures by Means of TensorFlow and Containers

Auteurs: Adrian Grupp, Valentin Kozlov, Isabel Campos, Mario David, Jorge Gomes, Álvaro López García
Publié dans: High Performance Computing - ISC High Performance 2019 International Workshops, Frankfurt, Germany, June 16-20, 2019, Revised Selected Papers, Numéro 11887, 2019, Page(s) 478-489, ISBN 978-3-030-34355-2
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-030-34356-9_36

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