Algorithmes à grain fin et schémas numériques pour des simulations exascales de plasmas turbulents

Abstract : Recent high performance computing architectures come with more and more cores on a greater number of computational nodes. Memory buses and communication networks are facing critical levels of use. Programming parallel codes for those architectures requires to put the emphasize on those matters while writing tailored algorithms. In this thesis, a plasma turbulence simulation code is analyzed and its parallelization is overhauled. The gyroaverage operator benefits from a new algorithm that is better suited with regard to its data distribution and that uses a computation -- communication overlapping scheme. Those optimizations lead to an improvement by reducing both execution times and memory footprint. We also study new designs for the code by developing a prototype based on task programming model and an asynchronous communication scheme. It allows us to reach a better load balancing and thus to achieve better execution times by minimizing communication overheads. A new reduced mesh is introduced, shrinking the overall mesh size while keeping the same numerical accuracy but at the expense of more complex operators. This prototype also uses a new data distribution and twists the mesh to adapt to the complex geometries of modern tokamak reactors. Performance of the different optimizations is studied and compared to that of the current code. A case scaling on a large number of cores is given.
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Nicolas Bouzat. Algorithmes à grain fin et schémas numériques pour des simulations exascales de plasmas turbulents. Calcul parallèle, distribué et partagé [cs.DC]. Université de Strasbourg, 2018. Français. ⟨NNT : 2018STRAD052⟩. ⟨tel-01975275v2⟩

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