Multilevel interior penalty methods on GPUs

We present a matrix-free multigrid method for high-order Discontinuous Galerkin (DG) finite element methods with GPU acceleration. A performance analysis is conducted, comparing various data and compute layouts. Smoother implementations are optimized through localization and fast diagonalization tec...

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Bibliographic Details
Main Authors: Cui, Cu (Author) , Kanschat, Guido (Author)
Format: Article (Journal)
Language:English
Published: September 2025
In: ACM transactions on mathematical software
Year: 2025, Volume: 51, Issue: 3, Pages: 1-27
ISSN:1557-7295
DOI:10.1145/3765616
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1145/3765616
Verlag, kostenfrei, Volltext: https://dl.acm.org/doi/10.1145/3765616
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Author Notes:Cu Cui, Guido Kanschat
Description
Summary:We present a matrix-free multigrid method for high-order Discontinuous Galerkin (DG) finite element methods with GPU acceleration. A performance analysis is conducted, comparing various data and compute layouts. Smoother implementations are optimized through localization and fast diagonalization techniques. Leveraging conflict-free access patterns in shared memory, arithmetic throughput of up to 40% of the peak performance on NVIDIA A100 GPUs are achieved. Experimental results affirm the effectiveness of mixed-precision approaches and Message Passing Interface (MPI) parallelization in accelerating algorithms. Furthermore, an assessment of solver efficiency and robustness is provided across both two and three dimensions, with applications to Poisson problems.
Item Description:Gesehen am 26.01.2026
Physical Description:Online Resource
ISSN:1557-7295
DOI:10.1145/3765616