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Conference object . 2026
License: CC BY NC ND
Data sources: Datacite
ZENODO
Conference object . 2026
License: CC BY NC ND
Data sources: Datacite
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Cross-platform Programming Model for GPU Implementation of OpenFOAM Using ISO C++

Authors: Kumar, Mayank; Castagna, Jony; Janssens, Mattijs; Tan, Raynold; Berrisford, Liam; Liu, Wendi; Tabor, Gavin; +1 Authors

Cross-platform Programming Model for GPU Implementation of OpenFOAM Using ISO C++

Abstract

In this work, we present our port of OpenFOAM to GPUs using the C++ standard parallel execution model (stdpar) introduced in ISO C++17. With a minimally intrusive strategy—primarily replacing serial loops with stdpar constructs—we offload the full computational workload of typical CFD simulations to multicore and manycore architectures. This approach is vendor‑agnostic, maintains a single unified codebase, and can be integrated easily into the main OpenFOAM release. We demonstrate performance using the icoFoam and simpleFoam solvers across four test cases: the 3D lid‑driven cavity, 3D conical diffuser, HPC motorbike, and drivAer automotive geometry. Experiments were conducted on a range of NVIDIA and AMD systems, including CPU‑only, hybrid CPU–GPU, and unified‑memory CPU–GPU configurations. Measured speedups relative to a fully populated 32‑core CPU socket range from 0.4× to 7.7×, depending on boundary‑condition complexity, turbulence modelling, and solver type. Details of the porting methodology and performance results are provided.

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Keywords

ARCHER2, Celebration of Science, OpenFOAM, Standard Parallelism C++, eCSE, CFD

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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