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Current Research Projects

  • ANR SaSHiMi 2019-2022
  • ANR Dedales 2014-2018: it aims at developing high performance software for the simulation of two phase flow in porous media. The project will specifically target parallel computers where each node is itself composed of a large number of processing cores, such as are found in new generation many-core architectures.
  • ANR Solhar 2013-2017: This project aims at studying and designing algorithms and parallel programming models for implementing direct methods for the solution of sparse linear systems on emerging computers equipped with accelerators.
  • FastLA 2011-2017 (Equipe Associée Inria) : In this joint project between Inria HiePACS, Lawrence Berkeley National Laboratory (LBNL) and Stanford we propose to study, design and implement hierarchical parallel scalable numerical techniques to address two challenging numerical kernels involved in many intensive simulation codes: namely, N-body interaction calculations and the solution of large sparse linear systems. Those two kernels share common hierarchical features and algorithmic challenges as well as numerical tools such as low-rank matrix approximations expressed through H-matrix calculations.
  • MORSE 2011-2017 (Equipe Associée Inria) : The goal of Matrices Over Runtime Systems at Exascale (MORSE) project is to design dense and sparse linear algebra methods that achieve the fastest possible time to an accurate solution on large-scale multicore systems with GPU accelerators, using all the processing power that future high end systems can make available. To develop software that will perform well on petascale and exascale systems with thousands of nodes and millions of cores, several daunting challenges have to be overcome, both by the numerical linear algebra and the runtime system communities.