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Conference papers
Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project
Patrick Valduriez
1, 2
Marta Mattoso
3
Reza Akbarinia
1
Heraldo Borges
4
José Camata
3
Alvaro Coutinho
3
Daniel Gaspar
5
Noel Lemus
5
Ji Liu
1, 2
Hermano Lustosa
5
Florent Masseglia
1
Fabricio Nogueira da Silva
6
Vitor Silva
3
Renan Souza
3
Kary Ocaña
5
Eduardo Ogasawara
4
Daniel Oliveira
6
Esther Pacitti
1
Fábio Porto
5
Dennis Shasha
7
1
ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Patrick Valduriez 1, 2
Mail : Site :
Author Employer institution : Institut National de Recherche en Informatique et en Automatique IdHAL : patrick-valduriez ORCID : https://orcid.org/0000-0001-6506-7538
Marta Mattoso 3
Mail :
Author
Reza Akbarinia 1
Mail :
Author Employer institution : Institut National de Recherche en Informatique et en Automatique IdHAL : reza-akbarinia ORCID : https://orcid.org/0000-0002-7098-0361
Heraldo Borges 4
Author
José Camata 3
Mail :
Author
Alvaro L G A Coutinho 3
Author
Daniel Gaspar 5
Author
Noel Lemus 5
Author
Ji Liu 1, 2
Author
Hermano Lustosa 5
Mail :
Author
Florent Masseglia 1
Mail : Site :
Author Employer institution : Institut National de Recherche en Informatique et en Automatique IdHAL : florent-masseglia ORCID : https://orcid.org/0000-0002-1149-585X
Fabricio Nogueira da Silva 6
Author
Vitor Silva 3
Mail :
Author
Renan Souza 3
Author
Kary Ocaña 5
Author
Eduardo Ogasawara 4
Mail :
Author
Daniel Oliveira 6
Mail :
Author
Esther Pacitti 1
Mail : Site :
Author IdHAL : esther-pacitti ORCID : https://orcid.org/0000-0003-1370-9943
Fábio Porto 5
Mail :
Author
Dennis Shasha 7
Author
1
ZENITH - Scientific Data Management (France)
- LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (161 rue Ada - 34095 Montpellier - France)
- UM - Université de Montpellier : UMR5506 (163 rue Auguste Broussonnet - 34090 Montpellier - France)
- CNRS - Centre National de la Recherche Scientifique : UMR5506 (France)
- CRISAM - Inria Sophia Antipolis - Méditerranée (2004 route des Lucioles BP 93 06902 Sophia Antipolis - France)
- Inria - Institut National de Recherche en Informatique et en Automatique (Domaine de Voluceau Rocquencourt - BP 105 78153 Le Chesnay Cedex - France)
2
IBC - Institut de Biologie Computationnelle (95 rue de la Galéra, 34095 Montpellier - France)
- INRA - Institut National de la Recherche Agronomique (France)
- Inria - Institut National de Recherche en Informatique et en Automatique (Domaine de Voluceau Rocquencourt - BP 105 78153 Le Chesnay Cedex - France)
- UM - Université de Montpellier (163 rue Auguste Broussonnet - 34090 Montpellier - France)
- CNRS - Centre National de la Recherche Scientifique (France)
3
COPPE-UFRJ - COPPE - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia (Cidade Universitária Centro de Tecnologia, Bloco G, sala 101 Ilha do Fundão CEP: 21945-970 Caixa Postal: 68501 Rio de Janeiro - RJ - Brasil - Brazil)
- UFRJ - Universidade Federal do Rio de Janeiro (Av. Pedro Calmon, 550 - Cidade Universitária, Rio de Janeiro - RJ, 21941-901 - Brazil)
4
CEFET/RJ - Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (Rio de Janeiro) (Av. Maracanã, 229 - Maracanã, Rio de Janeiro - RJ, 20271-110
BRASIL - Brazil)
5
LNCC / MCT - Laboratorio Nacional de Computação Cientifica [Rio de Janeiro] (LNCC, Av. Getulio Vargas, 333, Quitandinha, 25651-075, Petropolis, RJ - Brazil)
6
UFF - Universidade Federal Fluminense [Rio de Janeiro] (Rua Miguel de Frias, 9 - Icaraí, Niterói - RJ, 24220-008 - Brazil)
7
CIMS - Courant Institute of Mathematical Sciences [New York] (251, Mercier Street, New York, NY 10012 - United States)
- NYU - New York University [New York] (70 Washington Square South, New York, NY 10012 - United States)
- NYU - NYU System (United States)
Abstract : Data-intensive science requires the integration of two fairly different paradigms: high-performance computing (HPC) and data-intensive scalable computing (DISC), as exemplified by frameworks such as Hadoop and Spark. In this context, the SciDISC project addresses the grand challenge of scientific data analysis using DISC, by developing architectures and methods to combine simulation and data analysis. SciDISC is an ongoing project between Inria, several research institutions in Rio de Janeiro and NYU. This paper introduces the motivations and objectives of the project, and reports on the first results achieved so far.
Document type :
Conference papers
Complete list of metadatas
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01867804
Contributor : Patrick Valduriez <>
Submitted on : Tuesday, September 4, 2018 - 4:09:22 PM
Last modification on : Monday, May 18, 2020 - 4:50:34 PM
Document(s) archivé(s) le : Wednesday, December 5, 2018 - 5:48:45 PM
Contributor : Patrick Valduriez <>
Submitted on : Tuesday, September 4, 2018 - 4:09:22 PM
Last modification on : Monday, May 18, 2020 - 4:50:34 PM
Document(s) archivé(s) le : Wednesday, December 5, 2018 - 5:48:45 PM
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ldas 2018 - scidisc.pdf
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- HAL Id : lirmm-01867804, version 1
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Citation
Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José Camata, et al.. Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project. LADaS: Latin America Data Science Workshop, Aug 2018, Rio de Janeiro, Brazil. ⟨lirmm-01867804⟩
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