Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project

Patrick Valduriez; Marta Mattoso; Reza Akbarinia; Heraldo Borges; José Camata; Alvaro L G A Coutinho; Daniel Gaspar; Noel Lemus; Ji Liu; Hermano Lustosa; Florent Masseglia; Fabricio Nogueira da Silva; Vitor Silva; Renan Souza; Kary Ocaña; Eduardo Ogasawara; Daniel Oliveira; Esther Pacitti; Fábio Porto; Dennis Shasha

Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project

Acte de colloque

Open Access

Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project

Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José Camata, Alvaro L G A Coutinho, Daniel Gaspar, Noel Lemus, Ji Liu, Hermano Lustosa, …

Proceedings of the Latin America Data Science Workshop co-located with 44th International Conference on Very Large Data Bases (VLDB), Vol.2170

CEUR Workshop Proceedings

LADaS: Latin America Data Science Workshop (Rio de Janeiro, Brazil, 27/08/2018–27/08/2018)

2018

Résumé

Scientific data

Big data

Scalable Data-Intensive Computing

HPC

H.: Information Systems/H.2: DATABASE MANAGEMENT

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.

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Détails

Titre: Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project
Créateurs - sans rôle: Patrick Valduriez - Scientific Data Management
Marta Mattoso - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
Reza Akbarinia - Scientific Data Management
Heraldo Borges - Centro Federal de Educação Tecnológica Celso Suckow da Fonseca [Rio de Janeiro]
José Camata - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
Alvaro L G A Coutinho - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
Daniel Gaspar - Laboratório Nacional de Computação Científica
Noel Lemus - Laboratório Nacional de Computação Científica
Ji Liu - Scientific Data Management
Hermano Lustosa - Laboratório Nacional de Computação Científica
Florent Masseglia - Scientific Data Management
Fabricio Nogueira da Silva - Universidade Federal Fluminense
Vitor Silva - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
Renan Souza - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
Kary Ocaña - Laboratório Nacional de Computação Científica
Eduardo Ogasawara - Centro Federal de Educação Tecnológica Celso Suckow da Fonseca [Rio de Janeiro]
Daniel Oliveira - Universidade Federal Fluminense
Esther Pacitti - Scientific Data Management
Fábio Porto - Laboratório Nacional de Computação Científica
Dennis Shasha - Courant Institute of Mathematical Sciences
Détails de publication: Proceedings of the Latin America Data Science Workshop co-located with 44th International Conference on Very Large Data Bases (VLDB), Vol.2170
Colloque: LADaS: Latin America Data Science Workshop (Rio de Janeiro, Brazil, 27/08/2018–27/08/2018)
Publications en série: CEUR Workshop Proceedings
Identifiants: 99151075309311
Unité académique: Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier - LIRMM
Langue: English
Type de ressource: Conference proceeding
Champs locaux: lirmm-01867804