Objectives
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This PhD thesis aims at developing innovative randomized algorithms and software for sparse matrix computations, either for direct or iterative methods. The resulting software will be applied to large-size simulations addressed by ParSys and its Paris-Saclay partners in the area of high-performance computing (LIMSI, EDF, Centrale Paris). Moreover, for sake of visibility of the results, the software developed during this thesis would be part of a reference public domain library for fast HPC solvers.
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