Active Projects


  HPC4E – High Performance Computing for Energy : This is a EU-Brazil research Cooperation project. It aims to apply the new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources that are the present and the future of energy.


  Scientific Data Management – O termo “Big Data” refere-se ao volume exponencial de dados sendo produzidos nas ciências praticadas in-silico e em aplicações web como redes-sociais. Neste projeto, se esta interessado naqueles frutos do processo investigativo científico. Nesse contexto, o LNCC exerce um papel importante no cenário nacional, evidenciado por suas parcerias interinstitucionais, e considerado como centro de excelência em computação de alto desempenho e modelagem computacional. O volume de dados gerados por projetos nessas parcerias é da ordem de petabytes, e a gerência dos mesmos exige soluções desafiadoras, já que o ecossistema computacional atual não atendem aos requisitos de complexidade dessas aplicaçõesé incapaz de gerenciar eficientemente dados científicos tanto do ponto de vista de sua natureza quanto de seu volume. Como exemplo dessas parcerias em que o laboratório Data Extreme Lab (DEXL), coordenado por este proponente, participa podem ser citados os projetos: Dark Energy Survey, em parceria com o Observatório Nacional; o Hemolab, em parceria com colegas do LNCC; e PELD-Guanabara, em parceria com pesquisadores de instituições de pesquisa do Rio de Janeiro. Em continuação ao projeto de Gerência de Modelos Científicos, o presente projeto pretende focar em três pontos principais: a gerência de hipóteses científicas; a gerência de malhas de simulação e o processamento de grandes volumes de dados por workflows científicos.

  • Funding agency: CNPq

  • Period: 2013 to 2015

  • Total Funding: R$ 39.600,00


  •   Linea – The main objective of the project is to study the nature of the dark energy, a component recently discovered that represents 70% of the Universe content. The project will map a region close to the galactic South Pole covering 5000 square grades. The project will design and install in Chile a camera to capture images during 365 nights. A computational system will process and manage a huge volume of data and images produce by the camera, making them available to the general public. LNCC will collaborate on the design and development of the software layer to manage these data.

  • Funding agency: FINEP, MCT


  • Closed Projects


      Hoscar – This workshop is part of the collaborative project between the CNPq/Brazil - Inria/France which involves Brazilian and French researchers in the field of computational science and scientific computing. The general objective of the workshop is to setup a Brazil-France collaborative effort for taking full benefits of future high-performance massively parallel architectures in the framework of very large-scale datasets and numerical simulations. To this end, the workshop proposes multidisciplinary lectures ranging from exploiting the massively parallel architectures with high-performance programming languages, software components, and libraries, to devising numerical schemes and scalable solvers for systems of differential equations.

    • Funding agency: CNPQ - INRIA - International collaboration

    • Period: November 2012 to November 2015

    • Total funding: R$ 274.332,00


      Music – This is an international collaboration project between groups in Brazil and INRIA, in France. The aim of the project is to investigate data management and data processing techniques to support scientific data in the cloud. The project builds on a long lasting collaboration between the DEXL Lab, COPPE-UFRJ and the INRIA Zenith group.

  • Funding agency: FAPERJ - INRIA - International collaboration

  • Period: 2014 to 2016

  • Total funding: R$ 96.000.000,00

  • Coordinators: Fabio Porto (LNCC), Esther Pacitti (LIRMM-INRIA)


  •   EMC – Seismic data analysis

  • Funding agency: EMC reseach center

  • Period: 2014


  •   Olympic Laboratory – This project aims at supporting through scientific analysis the preparation of athletes of high standards during the preparation period. The Dexel Laboratory is responsible for using data models for representing complex systems, such as the metabolic pathways and try to correlate these kind of data with athletes results in championships. We intend to explore various tools, such as logical formalisms, Markov Models and different machine learning techniques.

  • Funding agency: FINEP

  • Period: January 2010 to December 2014

  • Total funding: R$ 13.000.000,00


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