Current Associate Teams with LNCC
DECoHPC (Data movement, Energy COnsumption and performance in High-Performance Computing), as follow-up of HPCProSol (Next-generation HPC PROblems and SOLutions) is an Associate Team coordinated by Carla Osthoff from LNCC and Francieli Zanon-Boito from Inria TADAAM team. In the context of the convergence of HPC and big data, the project starting in 2021 will propose monitoring and profiling techniques for applications, and the design of new coordination mechanisms to arbitrate resources in HPC environments. Researchers from UFF, UGRDS and CEFET Rio are also involved in this project.
SusAIN (Towards a Sustainable Artificial Intelligence) has started in 2021 and gathers Mariza Ferro and Bruno Schulze from LNCC, Inria project- team SPIRALS with Romain Rouvoy as PI and Nayat Sanchez-Pi and Luis Marti from Inria Chile. The project will address the challenge of reducing the power consumption of artificial intelligence algorithms deployed in the context of high performance computing
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.
