Enhancing the Nektar++ spectral/hp element framework for parallel-in-time simulations

We describe the efficient implementation of the Parareal algorithm in the Nektar++ software, an open-source spectral/hp element framework for the solution of partial differential equations, which has been designed to achieve high-scalability on high-performance computing (HPC) clusters using distributed parallelism. Recently, time-parallel integration techniques are being recognized as a potential solution to further increase concurrency and computational speed-up beyond the limits of strong scaling obtained from a pure spatial domain decomposition. Amongst the various time-parallel approaches proposed in the literature, the Parareal algorithm is a non-intrusive and iterative approach, exploiting a fine and a coarse solvers to achieve time-parallelism, and can be applied to both linear and non-linear problems. We discuss the details of the implementation and discuss the specific techniques used to adapt the code to a time-parallel framework. We demonstrate the application of these methods to multiple linear and non-linear problems provided by the existing Nektar++ solvers.

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Publication Details

Journal
Computer Physics Communications
Published
2025-03-20
DOI
https://doi.org/10.1016/j.cpc.2025.109584
Primary Topic
Scientific Research and Discoveries
Type
article
Field-Weighted Citation Impact
0.00

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article

Enhancing the Nektar++ spectral/hp element framework for parallel-in-time simulations

Chris D. Cantwell, David Moxey, Jacques Y. Xing
Computer Physics Communications
Scientific Research and Discoveries
article

Enhancing the Nektar++ spectral/hp element framework for parallel-in-time simulations

Chris D. Cantwell, David Moxey, Jacques Y. Xing
article en

Abstract

We describe the efficient implementation of the Parareal algorithm in the Nektar++ software, an open-source spectral/hp element framework for the solution of partial differential equations, which has been designed to achieve high-scalability on high-performance computing (HPC) clusters using distributed parallelism. Recently, time-parallel integration techniques are being recognized as a potential solution to further increase concurrency and computational speed-up beyond the limits of strong scaling obtained from a pure spatial domain decomposition. Amongst the various time-parallel approaches proposed in the literature, the Parareal algorithm is a non-intrusive and iterative approach, exploiting a fine and a coarse solvers to achieve time-parallelism, and can be applied to both linear and non-linear problems. We discuss the details of the implementation and discuss the specific techniques used to adapt the code to a time-parallel framework. We demonstrate the application of these methods to multiple linear and non-linear problems provided by the existing Nektar++ solvers.

Computer Physics CommunicationsVol. 312
King's College London (GB), Imperial College London (GB)
UK Research and Innovation
Openalex Percentile: Top 95%
Scientific Research and Discoveries
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