Publications

Published Papers

  1. Aygun A., Maulik R., Karakus A. (2023). Physics-Informed Neural Networks for Mesh Deformation Problems with Exact Boundary Enforcement. Engineering Applications of Artificial Intelligence, 125, 106660.
  2. Fischer, P., Kerkemeier, S., Min, M., Lan, Y. H., Phillips, M., Rathnayake, T., …, Karakus A., … & Warburton, T. (2022). NekRS, a GPU-Accelerated Spectral Element Navier-Stokes Solver. Parallel Computing.
  3. Aygun, A., & Karakus, A. (2022). Physics Informed Neural Networks for Two Dimensional Incompressible Thermal Convection Problems. Isı Bilimi ve Tekniği Dergisi, 42(2), 221-232.
  4. Karakus, A., Chalmers, N., & Warburton, T. (2022). A local discontinuous Galerkin level set reinitialization with subcell stabilization on unstructured meshes. Computers & Mathematics with Applications, 123, 160-170.
  5. Karakus, A. (2022). An accelerated nodal discontinuous Galerkin method for thermal convection on unstructured meshes: formulation and validation. Isı Bilimi ve Tekniği Dergisi, 42(1), 91-100.
  6. Abdelfattah, A., Barra, V., Beams, N., Bleile, R., Brown, J., Camier, J. S.,…, Karakus A., … & Weiss, K. (2021). GPU algorithms for efficient exascale discretizations. Parallel Computing, 108, 102841.
  7. Kolev, T., Fischer, P., Min, M., Dongarra, J., Brown, J., Dobrev, V., …, Karakus A., … & Tomov, V. (2021). Efficient exascale discretizations: High-order finite element methods. The International Journal of High Performance Computing Applications, 35(6), 527-552.
  8. Karakus, A., Chalmers, N., Hesthaven, J. S., & Warburton, T. (2019). Discontinuous Galerkin discretizations of the Boltzmann–BGK equations for nearly incompressible flows: Semi-analytic time stepping and absorbing boundary layers. Journal of Computational Physics, 390, 175-202.
  9. Karakus, A., Chalmers, N., Świrydowicz, K., & Warburton, T. (2019). A GPU accelerated discontinuous Galerkin incompressible flow solver. Journal of Computational Physics, 390, 380-404.
  10. Świrydowicz, K., Chalmers, N., Karakus, A., & Warburton, T. (2019). Acceleration of tensor-product operations for high-order finite element methods. The International Journal of High Performance Computing Applications, 33(4), 735-757.
  11. Karakus, A., Warburton, T., Aksel, M. H., & Sert, C. (2018). An adaptive fully discontinuous Galerkin level set method for incompressible multiphase flows. International Journal of Numerical Methods for Heat & Fluid Flow.
  12. Karakus, A., Warburton, T., Aksel, M. H., & Sert, C. (2016). A GPU accelerated level set reinitialization for an adaptive discontinuous Galerkin method. Computers & Mathematics with Applications, 72(3), 755-767.
  13. Karakus, A., Warburton, T., Aksel, M. H., & Sert, C. (2016). A GPU-accelerated adaptive discontinuous Galerkin method for level set equation. International Journal of Computational Fluid Dynamics, 30(1), 56-68.

Technical Reports

  1. Kolev, T., Fischer, P., Abdelfattah, A., Ananthan, S., Barra, V., Beams, N., Karakus A., … & Weiss, K. (2020). CEED-MS34: Improve performance and capabilities of CEED-enabled ECP applications on Summit/Sierra. Exascale Computing Project Milestone Report (No. LLNL-TR-808458). Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States).
  2. Kolev, T., Fischer, P., Abdelfattah, A., Ananthan, S., Barra, V., Beams, N., Karakus A., … & Weiss, K. (2020). ECP Milestone Report Improve performance and capabilities of CEED-enabled ECP applications on Summit/Sierra WBS 2.2. 6.06, Milestone CEED-MS34.
  3. Tomov, S., Abdelfattah, A., Barra, V., Beams, N., Brown, J., Camier, J. S., Karakus A., … & Warburton, T. (2019). ECP Milestone Report Performance tuning of CEED software and 1st and 2nd wave apps WBS 2.2. 6.06, Milestone CEED-MS32.
  4. Min, M., Camier, J. S., Fischer, P., Karakus, A., Kerkemeier, S., Kolev, T., … & Warburton, T. (2018). ECP Milestone Report Engage second wave ECP/CEED applications WBS 2.2. 6.06, Milestone CEED-MS23

Submitted Papers

  • Aygun A., Karakus A. (2024). Physics-Informed Neural Networks for Weakly Compressible Flows Using Galerkin-Boltzmann Formulation. arXiv:2409.05892