{"title":"Enhancing the Nektar++ spectral/hp element framework for parallel-in-time simulations","authors":"Jacques Y. Xing , Chris D. Cantwell , David Moxey","doi":"10.1016/j.cpc.2025.109584","DOIUrl":null,"url":null,"abstract":"<div><div>We describe the efficient implementation of the Parareal algorithm in the <em>Nektar++</em> 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 <em>Nektar++</em> solvers.</div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"312 ","pages":"Article 109584"},"PeriodicalIF":7.2000,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Physics Communications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010465525000876","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper.
Computer Programs in Physics (CPiP)
These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged.
Computational Physics Papers (CP)
These are research papers in, but are not limited to, the following themes across computational physics and related disciplines.
mathematical and numerical methods and algorithms;
computational models including those associated with the design, control and analysis of experiments; and
algebraic computation.
Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.