Associate Teams

Current projects

HPDaSC (High performance Data Science) gathers four research teams of the state of Rio de Janeiro (LNCC, COPPE/UFRJ, UFF and CEFET), and Inria ZENITH Team.  The project has begun in 2020 and is headed by Patrick Valduriez (Inria) for the French part, and by Fabio Porto (LNCC) for the Brazilian part. Following the lessons learned in the SciDISC (2016-2019) associated team, this project addresses the grand challenge of High Performance Data Science (HPDaSc), by developing architectures and methods to combine simulation, ML and data analytics for applications in life science and agronomy, and geoscience (oil & gas).

Previous projects

SciDISC (Scientific data analysis using Data-Intensive Scalable Computing) is an Associate Team between Inria Zenith and 4 teams in the state of Rio de Janeiro (LNCC, COPPE/UFRJ, UFF and CEFET). It was headed by Marta Mattoso (COPPE/UFRJ) and Patrick Valduriez (Inria-Zenith). The project began in 2016 and ended in 2019. In this project, we studied architectures (post-processing, in situ and in transit) and methods to combine simulation and scientific data analysis using Data-Intensive Scalable Computing (DISC).

HOMAR (High performance Multiscale Algorithms for wave pRopagation problems) was created by NACHOS and LNCC (Laboratório Nacional de Computação Científica, Brazil). It started in 2015 and ended in 2017. This project deals with the study of time dependent wave propagation problems presenting multiscale features (in space and time). The general goal is the design, analysis and implementation of a family of innovative high-performance numerical methods particularly well suited to the simulation of such multiscale wave propagation problems. The present collaborative project focused on two particular application contexts: the interaction of light (i.e. optical wave) with nanometer scale structure (i.e. nanophotonics) and, the interaction of seismic wave propagation with geological media for quantitative and non-destructive evaluation of imperfect interfaces.

MUSIC (MUltiSite Cloud (MUSIC) data management) is an Associate Team between ZENITH Inria Team Project and 4 teams in the state of Rio de Janeiro (LNCC, COPPE/UFRJ, UFF and CEFET). It was headed by Esther Pacitti (Inria-Zenith) and Fabio Porto (LNCC). The project started in 2014 and ended in 2016 and was funded by Inria and FAPERJ. The main objective of this research and scientific collaboration was to study the use of different distributed and parallel architectures for managing and analyzing scientific data, including support for heterogeneous data; distributed scientific workflows, and complex big data analysis. In particular, they studied the use of a multisite cloud architecture that can be used to host a variety of scientific applications that benefit from computing, storage, and networking resources that span multiple data centers.

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