NekRS, a GPU-Accelerated Spectral Element Navier-Stokes Solver
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Abstract (arXiv)
The development of NekRS, a GPU-oriented thermal-fluids simulation code based on the spectral element method (SEM) is described. For performance portability, the code is based on the open concurrent compute abstraction and leverages scalable developments in the SEM code Nek5000 and in libParanumal, which is a library of high-performance kernels for high-order discretizations and PDE-based miniapps. Critical performance sections of the Navier-Stokes time advancement are addressed. Performance results on several platforms are presented, including scaling to 27,648 V100s on OLCF Summit, for calculations of up to 60B gridpoints.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Apr 2021.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 1; 2026: 4.
8 papers.
- 2024Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networkscited by 11
- 2026Curvature-Aware Optimization for High-Accuracy Physics-Informed Neural Networkscited by 11
- 2023Distributed Neural Representation for Reactive in situ Visualizationcited by 8
- 2025Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstructioncited by 8
- 2026Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensemblescited by 4
- 2024Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modelingcited by 2
- 2026Super-resolution of turbulent reacting flows on complex meshes using graph neural networkscited by 2
- 2026Fixed-Budget Gaussian Volume Encoding with Structure-Aware Allocationcited by 1
- 2026Fixed-Budget Gaussian Volume Encoding with Structure-Aware Allocation14 Aug 2026
- 2026Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles18 Apr 2026
- 2026Curvature-Aware Optimization for High-Accuracy Physics-Informed Neural Networks6 Apr 2026
- 2026Super-resolution of turbulent reacting flows on complex meshes using graph neural networks1 Mar 2026
- 2025Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstruction10 Sep 2025
- 2024Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling2 Oct 2024
- 2024Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks12 Sep 2024
- 2023Distributed Neural Representation for Reactive in situ Visualization28 Mar 2023