PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine

References in zbMATH (referenced in 25 articles , 1 standard article )

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  1. Luporini, Fabio; Louboutin, Mathias; Lange, Michael; Kukreja, Navjot; Witte, Philipp; Hückelheim, Jan; Yount, Charles; Kelly, Paul H. J.; Herrmann, Felix J.; Gorman, Gerard J.: Architecture and performance of Devito, a system for automated stencil computation (2020)
  2. Moxey, David; Amici, Roman; Kirby, Mike: Efficient matrix-free high-order finite element evaluation for simplicial elements (2020)
  3. Navah, Farshad; de la Llave Plata, Marta; Couaillier, Vincent: A high-order multiscale approach to turbulence for compact nodal schemes (2020)
  4. Wang, Lai; Gobbert, Matthias K.; Yu, Meilin: A dynamically load-balanced parallel (p)-adaptive implicit high-order flux reconstruction method for under-resolved turbulence simulation (2020)
  5. Iyer, A. S.; Witherden, F. D.; Chernyshenko, S. I.; Vincent, P. E.: Identifying eigenmodes of averaged small-amplitude perturbations to turbulent channel flow (2019)
  6. Vermeire, B. C.; Loppi, N. A.; Vincent, P. E.: Optimal Runge-Kutta schemes for pseudo time-stepping with high-order unstructured methods (2019)
  7. Abide, Stéphane; Viazzo, Stéphane; Raspo, Isabelle; Randriamampianina, Anthony: Higher-order compact scheme for high-performance computing of stratified rotating flows (2018)
  8. Álvarez, X.; Gorobets, A.; Trias, F. X.; Borrell, R.; Oyarzun, G.: HPC(^2) -- a fully-portable, algebra-based framework for heterogeneous computing. Application to CFD (2018)
  9. Crabill, J.; Witherden, F. D.; Jameson, A.: A parallel direct cut algorithm for high-order overset methods with application to a spinning golf ball (2018)
  10. Gorobets, A.; Soukov, S.; Bogdanov, P.: Multilevel parallelization for simulating compressible turbulent flows on most kinds of hybrid supercomputers (2018)
  11. Hassanaly, Malik; Koo, Heeseok; Lietz, Christopher F.; Chong, Shao Teng; Raman, Venkat: A minimally-dissipative low-Mach number solver for complex reacting flows in openfoam (2018)
  12. Magee, Daniel J.; Niemeyer, Kyle E.: Accelerating solutions of one-dimensional unsteady PDEs with GPU-based swept time-space decomposition (2018)
  13. Ranocha, Hendrik: Generalised summation-by-parts operators and variable coefficients (2018)
  14. Sheshadri, Abhishek; Jameson, Antony: An analysis of stability of the flux reconstruction formulation on quadrilateral elements for the linear advection-diffusion equation (2018)
  15. Tsoutsanis, Panagiotis; Antoniadis, Antonis F.; Jenkins, Karl W.: Improvement of the computational performance of a parallel unstructured WENO finite volume CFD code for implicit large eddy simulation (2018)
  16. Romero, J.; Witherden, F. D.; Jameson, A.: A direct flux reconstruction scheme for advection-diffusion problems on triangular grids (2017)
  17. Vermeire, B. C.; Vincent, P. E.: On the behaviour of fully-discrete flux reconstruction schemes (2017)
  18. Chan, Jesse; Wang, Zheng; Modave, Axel; Remacle, Jean-Francois; Warburton, T.: GPU-accelerated discontinuous Galerkin methods on hybrid meshes (2016)
  19. Moxey, D.; Cantwell, C. D.; Kirby, R. M.; Sherwin, S. J.: Optimising the performance of the spectral/(hp) element method with collective linear algebra operations (2016)
  20. Vermeire, B. C.; Vincent, P. E.: On the properties of energy stable flux reconstruction schemes for implicit large eddy simulation (2016)

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