Freddie D. Witherden

Orcid: 0000-0003-2343-412X

According to our database1, Freddie D. Witherden authored at least 43 papers between 2014 and 2024.

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Bibliography

2024
An efficient GPU-based h-adaptation framework via linear trees for the flux reconstruction method.
J. Comput. Phys., 2024

Cache blocking for flux reconstruction: Extension to Navier-Stokes equations and anti-aliasing.
Comput. Phys. Commun., 2024

Impact of Memory Bandwidth on the Performance of Accelerators.
Proceedings of the Practice and Experience in Advanced Research Computing 2024: Human Powered Computing, 2024

2023
Bounds preserving temporal integration methods for hyperbolic conservation laws.
Comput. Math. Appl., April, 2023

A positivity-preserving and conservative high-order flux reconstruction method for the polyatomic Boltzmann-BGK equation.
J. Comput. Phys., 2023

On the anti-aliasing properties of entropy filtering for under-resolved turbulent flows.
CoRR, 2023

Positivity-preserving entropy filtering for the ideal magnetohydrodynamics equations.
CoRR, 2023

Scaling Study of Flow Simulations on Composable Cyberinfrastructure.
Proceedings of the Practice and Experience in Advanced Research Computing, 2023

2022
Enabling four-dimensional conformal hybrid meshing with cubic pyramids.
Numer. Algorithms, 2022

Nonlinear p-Multigrid Preconditioner for Implicit Time Integration of Compressible Navier-Stokes Equations with p-Adaptive Flux Reconstruction.
J. Sci. Comput., 2022

Positivity-preserving entropy-based adaptive filtering for discontinuous spectral element methods.
J. Comput. Phys., 2022

Partially-averaged Navier-Stokes simulations of turbulence within a high-order flux reconstruction framework.
J. Comput. Phys., 2022

Hyperbolic diffusion in flux reconstruction: Optimisation through kernel fusion within tensor-product elements.
Comput. Phys. Commun., 2022

Cache blocking strategies applied to flux reconstruction.
Comput. Phys. Commun., 2022

Nonlinear p-multigrid preconditioner for implicit time integration of compressible Navier-Stokes equations.
CoRR, 2022

2021
On nodal point sets for flux reconstruction.
J. Comput. Appl. Math., 2021

Python at Petascale With PyFR or: How I Learned to Stop Worrying and Love the Snake.
Comput. Sci. Eng., 2021

Inline vector compression for computational physics.
Comput. Phys. Commun., 2021

Utilizing Time-Reversibility for Shock Capturing in Nonlinear Hyperbolic Conservation Laws.
CoRR, 2021

2020
ZEFR: A GPU-accelerated high-order solver for compressible viscous flows using the flux reconstruction method.
Comput. Phys. Commun., 2020

Foundations of space-time finite element methods: polytopes, interpolation, and integration.
CoRR, 2020

A Riemann Difference Scheme for Shock Capturing in Discontinuous Finite Element Methods.
CoRR, 2020

On Fourier analysis of polynomial multigrid for arbitrary multi-stage cycles.
CoRR, 2020

Fourier Spectrum Discrepancies in Deep Network Generated Images.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Experiences with OpenCL in PyFR: 2014-Present.
Proceedings of the IWOCL '20: International Workshop on OpenCL, 2020

2019
Locally adaptive pseudo-time stepping for high-order Flux Reconstruction.
J. Comput. Phys., 2019

Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning.
J. Comput. Phys., 2019

Parameter-Conditioned Sequential Generative Modeling of Fluid Flows.
CoRR, 2019

Fourier Spectrum Discrepancies in Deep Network Generated Images.
CoRR, 2019

Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
A parallel direct cut algorithm for high-order overset methods with application to a spinning golf ball.
J. Comput. Phys., 2018

A high-order cross-platform incompressible Navier-Stokes solver via artificial compressibility with application to a turbulent jet.
Comput. Phys. Commun., 2018

Deep Dynamical Modeling and Control of Unsteady Fluid Flows.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
A Direct Flux Reconstruction Scheme for Advection-Diffusion Problems on Triangular Grids.
J. Sci. Comput., 2017

On the utility of GPU accelerated high-order methods for unsteady flow simulations: A comparison with industry-standard tools.
J. Comput. Phys., 2017

2016
An Analysis of Solution Point Coordinates for Flux Reconstruction Schemes on Tetrahedral Elements.
J. Sci. Comput., 2016

GiMMiK - Generating bespoke matrix multiplication kernels for accelerators: Application to high-order Computational Fluid Dynamics.
Comput. Phys. Commun., 2016

Using the pyMIC Offload Module in PyFR.
CoRR, 2016

Towards green aviation with python at petascale.
Proceedings of the International Conference for High Performance Computing, 2016

2015
On the identification of symmetric quadrature rules for finite element methods.
Comput. Math. Appl., 2015

2014
An Analysis of Solution Point Coordinates for Flux Reconstruction Schemes on Triangular Elements.
J. Sci. Comput., 2014

PyFR: An open source framework for solving advection-diffusion type problems on streaming architectures using the flux reconstruction approach.
Comput. Phys. Commun., 2014

Heterogeneous Computing on Mixed Unstructured Grids with PyFR.
CoRR, 2014


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