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Extensibility and Composability of a Multi-Stencil Domain Specific Framework

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Abstract

As the computation power of modern high performance architectures increases, their heterogeneity and complexity also become more important. One of the big challenges of exascale is to reach programming models that give access to high performance computing (HPC) to many scientists and not only to a few HPC specialists. One relevant solution to ease parallel programming for scientists is domain specific language (DSL). However, one problem to avoid with DSLs is to mutualize existing codes and libraries instead of implementing each solution from scratch. For example, this phenomenon occurs for stencil-based numerical simulations, for which a large number of languages has been proposed without code reuse between them. The Multi-Stencil Framework (MSF) presented in this paper combines a new DSL to component-based programming models to enhance code reuse and separation of concerns in the specific case of stencils. MSF can easily choose one parallelization technique or another, one optimization or another, as well as one back-end implementation or another. It is shown that MSF can reach same performances than a non component-based MPI implementation over 16,384 cores. Finally, the performance model of the framework for hybrid parallelization is validated by evaluations.

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Notes

  1. https://www.top500.org/list/2017/11/.

  2. https://gcc.gnu.org/projects/gomp/.

  3. http://www.univ-orleans.fr/mapmo/soft/FullSWOF/.

  4. L2C has been recently extended with the possibility of static linking.

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Acknowledgements

This work has partially been supported by the PIA ELCI project of the French FSN. This work was granted access to the HPC resources of TGCC under the allocations t2015067470, x2016067617 and AP010610191 made by GENCI.

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Correspondence to Hélène Coullon.

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Coullon, H., Bigot, J. & Perez, C. Extensibility and Composability of a Multi-Stencil Domain Specific Framework. Int J Parallel Prog 47, 1046–1085 (2019). https://doi.org/10.1007/s10766-017-0539-5

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