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
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
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
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)
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
INCT - MACC – TSpecifically, this project proposes to implement a computational environment based on Grid technologies and high performance computing, for Medicine Assisted by Scientific Computing, offering the medical community, and researchers in general, services such as:
Modeling and simulation of the human cardiovascular system including the simulation of surgical procedures.
Modeling and simulation of medical procedures for craniofacial traumatism (including the process of the reconstruction of craniofacial prostheses).
Advanced processing of medical images, taking into account visualization and three-dimensional reconstruction of patterns with medical relevance, and its applications in the modeling and computational simulation of physiological systems and image based diagnosis.
Development of collaborative virtual environments for virtual and augmented reality, as well as for telemanipulation in the medicine for training and formation of human resources, and for surgical planning.
System for public health monitoring including remote monitoring and emergency medical attendance (acute myocardial infarction).
Support for multimedia traffic in medical videoconferences.
Cyberenvironments for high performance distributed computing for medical applications in the areas mentioned above.
Human resources formation in the areas mentioned above.
Funding agency: CNPQ - FAPERJ
Period: September 2009 to November 2015
Total funding: R$ 5.628.423,53
EMC – Seismic data analysis
Funding agency: EMC reseach center
YDB – Scientific hypotheses are tentative, testable explanations of phenomena. In the era of data-intensive science and big data, much of the scientific thinking is shifting to the data analysis phase of the research life cycle. The vision behind Y-DB meets this paradigm shift by abstracting the data-intensive scientific method as a well-defined application of uncertain and probabilistic databases.
LNCC Intranet – The project aims supporting the data and information needs of the LNCC both from an internal and external point of view. The Intranet is an information system that manages information about research results, graduate courses, students assistantship etc..
Funding agency: MCT-LNCC