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Particle-In-Cell Simulation Using Asynchronous Tasking

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 12820)

Abstract

Recently, task-based programming models have emerged as a prominent alternative among shared-memory parallel programming paradigms. Inherently asynchronous, these models provide native support for dynamic load balancing and incorporate data flow concepts to selectively synchronize the tasks. However, tasking models are yet to be widely adopted by the HPC community and their effective advantages when applied to non-trivial, real-world HPC applications are still not well comprehended. In this paper, we study the parallelization of a production electromagnetic particle-in-cell (EM-PIC) code for kinetic plasma simulations exploring different strategies using asynchronous task-based models. Our fully asynchronous implementation not only significantly outperforms a conventional, synchronous approach but also achieves near perfect scaling for 48 cores.

Keywords

  • Manycore parallelism
  • Task-based programming
  • Asynchronous parallelism
  • Particle-in-cell
  • Kinetic plasma simulations

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Fig. 1.

(adapted from [30]).

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Notes

  1. 1.

    https://github.com/epeec/zpic-epeec.

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Acknowledgements

This work was partially supported by Fundação Ciência e Tecnologia (FCT) under grant UIDB /50021/2020 and by the EPEEC project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 801051.

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Guidotti, N. et al. (2021). Particle-In-Cell Simulation Using Asynchronous Tasking. In: Sousa, L., Roma, N., Tomás, P. (eds) Euro-Par 2021: Parallel Processing. Euro-Par 2021. Lecture Notes in Computer Science(), vol 12820. Springer, Cham. https://doi.org/10.1007/978-3-030-85665-6_30

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  • DOI: https://doi.org/10.1007/978-3-030-85665-6_30

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