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Merge pull request #956 from Parallel-in-Time/bibtex-bibbot-954-912b556
pint.bib updates
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_bibliography/pint.bib

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@@ -6494,6 +6494,18 @@ @unpublished{DanieliEtAl2023
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year = {2023},
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}
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@article{DrewsEtAl2023,
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author = {Drews, Wiebke and Turek, Stefan and Lohmann, Christoph},
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doi = {10.17877/DE290R-23990},
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journal = {Ergebnisberichte des Instituts für Angewandte Mathematik;668},
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keywords = {convection-diffusion equations, variational multiscale methods, multigrid waveform relaxation, 610},
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language = {en},
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publisher = {TU Dortmund},
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title = {Numerical Analysis of a Time-Simultaneous Multigrid Solver for Stabilized Convection-Dominated Transport Problems in 1D},
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url = {https://eldorado.tu-dortmund.de/handle/2003/42157},
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year = {2023},
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}
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@unpublished{Erlangga2023,
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abstract = {This paper presents a parallel-in-time multilevel iterative method for solving differential algebraic equation, arising from a discretization of linear time-dependent partial differential equation. The core of the method is the multilevel Krylov method, introduced by Erlangga and Nabben~{\it [SIAM J. Sci. Comput., 30(2008), pp. 1572--1595]}. In the method, special time restriction and interpolation operators are proposed to coarsen the time grid and to map functions between fine and coarse time grids. The resulting Galerkin coarse-grid system can be interpreted as time integration of an equivalent differential algebraic equation associated with a larger time step and a modified $\theta$-scheme. A perturbed coarse time-grid matrix is used on the coarsest level to decouple the coarsest-level system, allowing full parallelization of the method. Within this framework, spatial coarsening can be included in a natural way, reducing further the size of the coarsest grid problem to solve. Numerical results are presented for the 1- and 2-dimensional heat equation using {\it simulated} parallel implementation, suggesting the potential computational speed-up of up to 9 relative to the single-processor implementation and the speed-up of about 3 compared to the sequential $\theta$-scheme.},
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author = {Yogi A. Erlangga},
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year = {2024},
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}
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@article{DrewsEtAl2024,
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author = {Drews, Wiebke and Turek, Stefan and Lohmann, Christoph},
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doi = {10.17877/DE290R-24129},
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journal = {Ergebnisberichte des Instituts für Angewandte Mathematik;670},
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keywords = {610},
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language = {en},
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publisher = {TU Dortmund},
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title = {Improving Convergence of Time-Simultaneous Multigrid Methods for Convection-Dominated Problems using VMS Stabilization Techniques},
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url = {https://eldorado.tu-dortmund.de/handle/2003/42293},
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year = {2024},
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}
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@article{DrewsEtAl2024b,
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author = {Drews, Wiebke and Turek, Stefan and Lohmann, Christoph},
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doi = {10.5772/acrt.37},
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issn = {2754-6292},
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journal = {AI, Computer Science and Robotics Technology},
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month = {July},
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publisher = {IntechOpen},
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title = {Numerical Analysis of a Time-Simultaneous Multigrid Solver for Stabilized Convection-Dominated Transport Problems in 1D},
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url = {http://dx.doi.org/10.5772/acrt.37},
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volume = {3},
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year = {2024},
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}
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@article{EndtmayerEtAl2024,
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author = {Endtmayer, B. and Langer, U. and Schafelner, A.},
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doi = {10.1016/j.camwa.2024.05.017},
@@ -7676,6 +7713,19 @@ @article{CaklovicEtAl2025
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year = {2025},
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}
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@inbook{DrewsEtAl2025,
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author = {Drews, Wiebke and Turek, Stefan and Lohmann, Christoph},
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booktitle = {Numerical Mathematics and Advanced Applications ENUMATH 2023, Volume 1},
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doi = {10.1007/978-3-031-86173-4_28},
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isbn = {9783031861734},
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issn = {2197-7100},
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pages = {278–286},
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publisher = {Springer Nature Switzerland},
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title = {Improving Convergence of Time-Simultaneous Multigrid Methods for Convection-Dominated Problems Using VMS Stabilization Techniques},
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url = {http://dx.doi.org/10.1007/978-3-031-86173-4_28},
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year = {2025},
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}
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@unpublished{DurastanteEtAl2025,
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abstract = {Implicit Runge--Kutta (IRK) methods are highly effective for solving stiff ordinary differential equations (ODEs) but can be computationally expensive for large-scale problems due to the need of solving coupled algebraic equations at each step. This study improves IRK efficiency by leveraging parallelism to decouple stage computations and reduce communication overhead, specifically we stably decouple a perturbed version of the stage system of equations and recover the exact solution by solving a Sylvester matrix equation with an explicitly known low-rank right-hand side. Two IRK families -- symmetric methods and collocation methods -- are analyzed, with extensions to nonlinear problems using a simplified Newton method. Implementation details, shared memory parallel code, and numerical examples, particularly for ODEs from spatially discretized PDEs, demonstrate the efficiency of the proposed IRK technique.},
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author = {Fabio Durastante and Mariarosa Mazza},

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