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Scalable and Efficient Algorithms for Unstructured Mesh Computations

Abstract : The growing need for numerical simulations results in larger and more complex computing centers and more HPC softwares. Actual HPC system architectures have an increasing requirement for energy efficiency and performance. Recent advances in hardware design result in an increasing number of nodes and an increasing number of cores per node. However, some resources do not scale at the same rate. The increasing number of cores and parallel units implies a lower memory per core, higher requirement for concurrency, higher coherency traffic, and higher cost for coherency protocol. Most of the applications and runtimes currently in use struggle to scale with the present trend. In the context of finite element methods, exposing massive parallelism on unstructured mesh computations with efficient load balancing and minimal synchronizations is challenging. To make efficient use of these architectures, several parallelization strategies have to be combined together to exploit the multiple levels of parallelism. This P.h.D. thesis proposes several contributions aimed at overpassing this limitation by addressing irregular codes and data structures in an efficient way. We developed a hybrid parallelization approach combining the distributed, shared, and vectorial forms of parallelism in a fine grain taskbased approach applied to irregular structures. Our approach has been ported to several industrial applications developed by Dassault Aviation and has led to important speedups using standard multicores and the Intel Xeon Phi manycore.
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  • HAL Id : tel-01701925, version 1

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Loïc Thebault. Scalable and Efficient Algorithms for Unstructured Mesh Computations. Distributed, Parallel, and Cluster Computing [cs.DC]. Université Paris-Saclay, 2016. English. ⟨NNT : 2016SACLV088⟩. ⟨tel-01701925⟩

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