Publications

Google Scholar Citations

Selected Publications

2024

  1. T. Dzanic, K. Mittal, D. Kim, J. Yang, S. Petrides, B. Keith, R. Anderson, DynAMO: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws, Journal of Computational Physics, 506, 112924, 2024
  2. K. Mittal, V. Dobrev, P. Knupp, T. Kolev, F. Ledoux, C. Roche, V. Tomov, Mixed-Order Meshes through rp-adaptivity for Surface Fitting to Implicit Geometries, Proceedings of the 2024 SIAM International Meshing Roundtable (IMR). 2024.
  3. T. Stitt, K. Belcher, A. Campos, T. Kolev, P. Mocz, R. Rieben, A. Skinner, V. Tomov, A. Vargas, K. Weiss, Performance portable GPU acceleration of a high-order finite element multiphysics application, Journal of Fluids Engineering, 146(4):041102, 2024.
  4. V. Dobrev, P. Knupp, T. Kolev, K. Mittal, R. Rieben, M. Stees, V. Tomov, Asymptotic Analysis of Compound Volume+ Shape Metrics for Mesh Optimization, Proceedings of the 2024 SIAM International Meshing Roundtable (IMR). 2024.
  5. W. Pazner, Tz. Kolev, P. Vassilevski, Matrix-free high-performance saddle-point solvers for high-order problems in H(div), SIAM Journal on Scientific Computing, 2024. Also available as arXiv:2304.12387.
  6. G. Fu, S. Osher, W. Pazner, and W. Li. Generalized optimal transport and mean field control problems for reaction-diffusion systems with high-order finite element computation, Journal of Computational Physics, 2024. Also available as arXiv:2306.06287.
  7. J. Andrej, N. Atallah, J.-P. Bäcker, J. Camier, D. Copeland, V. Dobrev, Y. Dudouit, T. Duswald, B. Keith, D. Kim, Tz. Kolev, B. Lazarov, K. Mittal, W. Pazner, S. Petrides, S. Shiraiwa, M. Stowell, V. Tomov. High-performance finite elements with MFEM, accepted for publication in the International Journal of High Performance Computing Applications, 2024. Also available as arXiv:2402.15940.
  8. A. Gillette, B. Keith, S. Petrides, Learning robust marking policies for adaptive mesh refinement, SIAM Journal on Scientific Computing, 2024. Also available as arXiv:2207.06339.
  9. T. Duswald, B. Keith, B. Lazarov, S. Petrides, B. Wohlmuth, Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization(in-review). Also available as arXiv:2403.03658

2023

  1. J. Vedral, Dissipative WENO stabilization of high-order discontinuous Galerkin methods for hyperbolic problems, in review.
  2. D. Kuzmin, H. Hajduk, Property-Preserving Numerical Schemes for Conservation Laws, World Scientific, 2023
  3. D. Kuzmin, J. Vedral, Dissipation-based WENO stabilization of high-order finite element methods for scalar conservation laws, Journal of Computational Physics, 487, 112153, 2023
  4. B. Keith, T.M. Surowiec, Proximal Galerkin: A structure-preserving finite element method for pointwise bound constraints, 2023.
  5. R. Bollapragada, C. Karamanli, B. Keith, B. Lazarov, S. Petrides, J. Wang, An Adaptive Sampling Augmented Lagrangian Method for Stochastic Optimization with Deterministic Constraints, Computers & Mathematics with Applications, 2023. Also available as arXiv:2305.01018.
  6. J. Yang, K. Mittal, T. Dzanic, S. Petrides, B. Keith, B. Petersen, D. Faissol, R. Anderson, Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement, Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023.
  7. J. Yang, T. Dzanic, B. Petersen, J. Kudo, K. Mittal, V. Tomov, J.S. Camier, T. Zhao, H. Zha, T. Kolev, R. Anderson, Reinforcement learning for adaptive mesh refinement, Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023.
  8. W. Pazner, Tz. Kolev, and J. Camier, End-to-end GPU acceleration of low-order-refined preconditioning for high-order finite element discretizations, The International Journal of High Performance Computing Applications, 2023. Also available as arXiv:2210.12253.
  9. W. Pazner, Tz. Kolev, and C. Dohrmann, Low-order preconditioning for the high-order finite element de Rham complex, SIAM Journal on Scientific Computing, 2023. Also available as arXiv:2203.02465.
  10. J. Barrera, Tz. Kolev, K. Mittal, and V. Tomov, High-Order Mesh Morphing for Boundary and Interface Fitting to Implicit Geometries, Computer-Aided Design, 158, 103499, 2023. Also available as arXiv:2208.05062.
  11. J. Camier, V. Dobrev, P. Knupp, Tz. Kolev, K. Mittal, R. Rieben, and V. Tomov, Accelerating high-order mesh optimization using finite element partial assembly on GPUs, Journal of Computational Physics, 474, 111808, 2023. Also available as arXiv:2205.12721.
  12. F. Gómez-Lozada, C. Andrés del Valle, J. D. Jiménez-Paz, B. S. Lazarov and J. Galvis, Modelling and simulation of brinicle formation, Royal Society Open Science, 10, 10, 230268, 2023.

2022

  1. D. Kuzmin, J.-P. Bäcker, An unfitted finite element method using level set functions for extrapolation into deformable diffuse interfaces, Journal of Computational Physics, 461, 111218, 2022
  2. A. Vargas, T. Stitt, K. Weiss, V. Tomov, J. Camier, Tz. Kolev, and R. Rieben, Matrix-free approaches for GPU acceleration of a high-order finite element hydrodynamics application using MFEM, Umpire, and RAJA, The International Journal of High Performance Computing Applications, 36(4):492-509, 2022. Also available as arXiv:2112.07075.
  3. J. Nikl, M. Kuchařík, and S. Weber, High-Order Curvilinear Finite Element Magneto-Hydrodynamics I: A Conservative Lagrangian Scheme, Journal of Computational Physics, 464, 111158, 2022. Also available as arXiv:2110.11669.
  4. T. L. Horvath and S. Rhebergen, A conforming sliding mesh technique for an embedded-hybridized discontinuous Galerkin discretization for fluid-rigid body interaction, in review, 2022.
  5. N. Yavich, N. Koshev, M. Malovichko, A. Razorenova and M. Fedorov, Conservative Finite Element Modeling of EEG and MEG on Unstructured Grids, IEEE Transactions on Medical Imaging, 41(3):647-656, 2022.
  6. Q. Tang, L. Chacon, Tz. Kolev, J. N. Shadid and X.-Z. Tang, An adaptive scalable fully implicit algorithm based on stabilized finite element for reduced visco-resistive MHD, Journal of Computational Physics, (454) 110967, 2022. Also available as arXiv:2106.00260.
  7. J. A. Turner, J. Belak, N. Barton, M. Bement, N. Carlson, R. Carson, S. DeWitt, J.-L. Fattebert, N. Hodge, Z. Jibben, W. King, L. Levine, C. Newman, A. Plotkowski, B. Radhakrishnan, S. T. Reeve, M. Rolchigo, A. Sabau, S. Slattery, and B. Stump. ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure. The International Journal of High Performance Computing Applications, 36(1):13-39, 2022.
  8. Tz. Kolev and W. Pazner, Conservative and accurate solution transfer between high-order and low-order refined finite element spaces, SIAM Journal on Scientific Computing, 44(1), A1-A27, 2022. Also available as arXiv:2103.05283.

2021

  1. A. Abdelfattah, V. Barra, N. Beams, R. Bleile, J. Brown, J. Camier, R. Carson, N. Chalmers, V. Dobrev, Y. Dudouit, P. Fischer, A. Karakus, S. Kerkemeier, Tz. Kolev, Y. Lan, E. Merzari, M. Min, M. Phillips, T. Rathnayake, R. Rieben, T. Stitt, A. Tomboulides, S. Tomov, V. Tomov, A. Vargas, T. Warburton, K. Weiss, GPU Algorithms for Efficient Exascale Discretizations, Parallel Computing, 108, 102841, 2021.
  2. W. Pazner and Tz. Kolev, Uniform subspace correction preconditioners for discontinuous Galerkin methods with hp-refinement, Communications on Applied Mathematics and Computation, 2021. Also available as arXiv:2009.01287.
  3. Tz. Kolev, P. Fischer, J. Brown, V. Dobrev, J. Dongarra, M. Min, M. Shephard, S. Tomov, T. Warburton, A. Abdelfattah, V. Barra, N. Beams, J.-S. Camier, N. Chalmers, Y. Dudouit, W. Pazner, C. Smith, K. Swirydowicz, J. Thompson and V. Tomov, Efficient Exascale Discretizations: High Order Finite Element Methods, The International Journal on High Performance Computing Applications, 35(6), 527-552, 2021.
  4. V. Dobrev, P. Knupp, Tz. Kolev, K. Mittal, and V. Tomov, hr-adaptivity for nonconforming high-order meshes with the target matrix optimization paradigm, Engineering with Computers, 2021. Also available as arXiv:2010.02166.
  5. W. Pazner, Sparse invariant domain preserving discontinuous Galerkin methods with subcell convex limiting, Computer Methods in Applied Mechanics and Engineering, 382, 113876,2021. Also available as arXiv:2004.08503.
  6. J. Yang, T. Dzanic, B. Petersen, J. Kudo, K. Mittal, V. Tomov, J.-S. Camier, T. Zhao, H. Zha, Tz. Kolev, R. Anderson, D. Faissol, Reinforcement Learning for Adaptive Mesh Refinement, in review, 2021.
  7. D. Kalchev, P. Vassilevski, and U. Villa, Parallel Element-based Algebraic Multigrid for H(curl) and H(div) Problems Using the ParELAG Library, in review, 2021.
  8. N. Whitman, T. Palmer, P. Greaney, S. Hosseini, D. Burkes, and D. Senor, Gray Phonon Transport Prediction of Thermal Conductivity in Lithium Aluminate with Higher-Order Finite Elements on Meshes with Curved Surfaces, Journal of Computational and Theoretical Transport, 2021.
  9. H. Hajduk, Monolithic convex limiting in discontinuous Galerkin discretizations of hyperbolic conservation laws, Computers & Mathematics with Applications, (87) 120-138, 2021. Also available as arXiv:2007.01212.
  10. J. Nikl, I. Göthel, M. Kuchařík, S. Weber, and M. Bussmann, Implicit reduced Vlasov-Fokker-Planck-Maxwell model based on high-order mixed elements, Journal of Computational Physics, (434) 110214, 2021.
  11. D. Kalchev, P. Vassilevski, and U. Villa, On ParELAG's Parallel Element-based Algebraic Multigrid and its MFEM Miniapps for H(curl) and H(div) Problems: a report including lowest and next to the lowest order numerical results, LLNL Tech. Report, LLNL-TR-824455, 2021.
  12. J. Brown, A. Abdelfattah, V. Barra, N. Beams, J. Camier, V. Dobrev, Y. Dudouit, L. Ghaffari, Tz. Kolev, D. Medina, W. Pazner, T. Ratnayaka, J. Thompson and S. Tomov, libCEED: Fast algebra for high-order element-based discretizations, The Journal of Open Source Software, 2021.
  13. P. Knupp, Tz. Kolev, K. Mittal, V. Tomov, Adaptive Surface Fitting and Tangential Relaxation for High-Order Mesh Optimization. International Meshing Roundtable, 2021.

2020

  1. N. Beams, A. Abdelfattah, S. Tomov, J. Dongarra, T. Kolev, and Y. Dudouit, High-Order Finite Element Method using Standard and Device-Level Batch GEMM on GPUs, IEEE/ACM 11th ScalA Workshop, 53-60, 2020.
  2. A. Barker and Tz. Kolev, Matrix-free preconditioning for high-order H(curl) discretizations, Numerical Linear Algebra with Applications, 28(2) e2348, 2020.
  3. D. Kuzmin and M. Quezada de Luna, Entropy conservation property and entropy stabilization of high-order continuous Galerkin approximations to scalar conservation laws, Computers & Fluids, (213) 104742, 2020.
  4. A. Sandu, V. Tomov, L. Cervena, and Tz. Kolev, Conservative High-Order Time Integration for Lagrangian Hydrodynamics, SIAM Journal on Scientific Computing, 43(1), A221-A241, 2020.
  5. B. S. Southworth, M. Holec, and T. Haut. Diffusion synthetic acceleration for heterogeneous domains, compatible with voids, Nuclear Science and Engineering, 195(2), 119-136, 2020.
  6. T. Haut, B. Southworth, P. Maginot, V. Tomov, Diffusion Synthetic Acceleration Preconditioning for Discontinuous Galerkin Discretizations of SN Transport on High-Order Curved Meshes, SIAM Journal on Scientific Computing, 42(5), B1271-B1301, 2020.
  7. R. Anderson, J. Andrej, A. Barker, J. Bramwell, J.-S. Camier, J. Cerveny V. Dobrev, Y. Dudouit, A. Fisher, Tz. Kolev, W. Pazner, M. Stowell, V. Tomov, I. Akkerman, J. Dahm, D. Medina, and S. Zampini, MFEM: A Modular Finite Element Library, Computers & Mathematics with Applications, (81) 42-74, 2020. Also available as arXiv:1911.09220.
  8. R. Li and C. Zhang, Efficient Parallel Implementations of Sparse Triangular Solves for GPU Architectures, Proceedings of the 2020 SIAM Conference on Parallel Processing for Scientific Computing, 2020.
  9. W. Pazner, Efficient low-order refined preconditioners for high-order matrix-free continuous and discontinuous Galerkin methods, SIAM Journal on Scientific Computing, 42(5), pp. A3055-A3083, 2020.
  10. B. Yee, S. Olivier, T. Haut, M. Holec, V. Tomov, P. Maginot, A Quadratic Programming Flux Correction Method for High-Order DG Discretizations of SN Transport, Journal of Computational Physics, (419) 109696, 2020.
  11. T. L. Horvath and S. Rhebergen, An exactly mass conserving space-time embedded-hybridized discontinuous Galerkin method for the Navier-Stokes equations on moving domains, Journal of Computational Physics, (417) 109577, 2020.
  12. S. Rhebergen and G. N. Wells, An embedded-hybridized discontinuous Galerkin finite element method for the Stokes equations, Computer Methods in Applied Mechanics and Engineering, (358) 112619, 2020.
  13. P. Bello-Maldonado, Tz. Kolev, R. Rieben, and V. Tomov, A Matrix-Free Hyperviscosity Formulation for High-Order ALE Hydrodynamics, Computers & Fluids, (205) 104577, 2020.
  14. V. Dobrev, P. Knupp, Tz. Kolev, K. Mittal, R. Rieben, and V. Tomov, Simulation-Driven Optimization of High-Order Meshes in ALE Hydrodynamics, Computers & Fluids, (208) 104602, 2020.
  15. H. Hajduk, D. Kuzmin, Tz. Kolev, V. Tomov, I. Tomas, and J. Shadid, Matrix-free subcell residual distribution for Bernstein finite elements: Monolithic limiting, Computers & Fluids, (200) 104451, 2020.
  16. M. Franco, J.-S. Camier, J. Andrej, and W. Pazner, High-order matrix-free incompressible flow solvers with GPU acceleration and low-order refined preconditioners, Computers & Fluids, (203) 104541, 2020.
  17. S. Friedhoff and B. S. Southworth,On "Optimal" h-independent convergence of Parareal and multigrid-reduction-in-time using Runge-Kutta time integration, Numerical Linear Algebra with Applications, e2301, 2020.
  18. B. S. Southworth, A. A. Sivas, and S. Rhebergen, On fixed-point, Krylov, and 2x2 block preconditioners for nonsymmetric problems, SIAM Journal on Matrix Analysis and Applications, 41(2), pp. 871-900, 2020.
  19. P. Fischer, M. Min, T. Rathnayake, S. Dutta, Tz. Kolev, V. Dobrev, J.S. Camier, M. Kronbichler, T. Warburton, K. Swirydowicz, and J. Brown, Scalability of High-Performance PDE Solvers, The International Journal on High Performance Computing Applications, 34(5), pp. 562-586, 2020.
  20. G. Sosa Jones, J. J. Lee, and S. Rhebergen, A space-time hybridizable discontinuous Galerkin method for linear free-surface waves, Journal of Scientific Computing, (85) 61, 2020. Also available as arXiv:1910.07315
  21. Z. Peng, Q. Tang and X.-Z. Tang. An adaptive discontinuous Petrov-Galerkin method for the Grad-Shafranov equation, SIAM Journal on Scientific Computing, 42(5):B1227-B1249, 2020.

2019

  1. H. Hajduk, D. Kuzmin, Tz. Kolev, and R. Abgrall, Matrix-free subcell residual distribution for Bernstein finite elements: Low-order schemes and FCT, Comp. Meth. Appl. Mech. Eng., (359) 112658, 2019.
  2. K. Suzuki, M. Fujisawa, and M. Mikawa, Simulation Controlling Method for Generating Desired Water Caustics, 2019 International Conference on Cyberworlds (CW), Kyoto, Japan, pp. 163-170, 2019.
  3. D. White, Y. Choit, and J. Kudo, A dual mesh method with adaptivity for stress constrained topology optimization, Structural and Multidisciplinary Optimization, 61, pp. 749-762, 2019.
  4. S. Watts, W. Arrighi, J. Kudo, D. A. Tortorelli, and D. A. White, Simple, accurate surrogate models of the elastic response of three-dimensional open truss micro-architectures with applications to multiscale topology design, Structural and Multidisciplinary Optimization, 60, pp. 1887-1920, 2019.
  5. V. Dobrev, P. Knupp, Tz. Kolev, and V. Tomov, Towards Simulation-Driven Optimization of High-Order Meshes by the Target-Matrix Optimization Paradigm, 27th International Meshing Roundtable, Oct 1-8, 2018, Albuquerque, Lecture Notes in Computational Science and Engineering, 127, pp. 285-302, 2019.
  6. J. Cerveny, V. Dobrev, and Tz. Kolev, Non-Conforming Mesh Refinement For High-Order Finite Elements, SIAM Journal on Scientific Computing, 41(4):C367-C392, 2019.
  7. D. White, W. Arrighi, J. Kudo, and S. Watts, Multiscale topology optimization using neural network surrogate models, Comp. Meth. Appl. Mech. Eng., 346, pp. 1118-1135, 2019.
  8. V. A. Dobrev, T. V. Kolev, C. S. Lee, V. Z. Tomov, and P. S. Vassilevski, Algebraic Hybridization and Static Condensation with Application to Scalable H(div) Preconditioning, SIAM Journal on Scientific Computing, 41(3):B425-B447, 2019.
  9. D. White, and A. Voronin, A computational study of symmetry and well-posedness of structural topology optimization, Structural and Multidisciplinary Optimization, 59(3), pp. 759-766, 2019.
  10. T. Haut, P. Maginot, V. Tomov, B. Southworth, T. Brunner and T. Bailey, An Efficient Sweep-Based Solver for the SN Equations on High-Order Meshes, Nuclear Science and Engineering, 193(7):746-759, 2019.
  11. V. Dobrev, P. Knupp, Tz. Kolev, K. Mittal, and V. Tomov, The Target-Matrix Optimization Paradigm For High-Order Meshes, SIAM Journal on Scientific Computing, 41(1):B50-B68, 2019.
  12. K. L. A. Kirk, T. L. Horvath, A. Cesmelioglu, and S. Rhebergen, Analysis of a space-time hybridizable discontinuous Galerkin method for the advection-diffusion problem on time-dependent domains, SIAM Journal on Numerical Analysis, 57(4), pp. 1677-1696, 2019.
  13. T. L. Horvath and S. Rhebergen, A locally conservative and energy-stable finite element method for the Navier-Stokes problem on time-dependent domains, International Journal for Numerical Methods in Fluids, 89(12):519-532, 2019.
  14. R. Li, Y. Xi, L. Erlandson, and Y. Saad, The Eigenvalues Slicing Library (EVSL): Algorithms, Implementation, and Software, SIAM Journal on Scientific Computing, 41(4), pp. C393-C415, 2019.

2018

  1. H. Auten, The High Value of Open Source Software, Science & Technology Review, January/February 2018, pp. 5-11, 2018.
  2. R. W. Anderson, V. A. Dobrev, Tz. V. Kolev, R. N. Rieben, and V. Z. Tomov, High-Order Multi-Material ALE Hydrodynamics, SIAM Journal on Scientific Computing, 40(1), pp. B32-B58, 2018.
  3. A. T. Barker, V. Dobrev, J. Gopalakrishnan, and Tz. Kolev, A scalable preconditioner for a primal discontinuous Petrov-Galerkin method, SIAM Journal on Scientific Computing, 40(2), pp. A1187-A1203, 2018.
  4. V. Dobrev, T. Kolev, D. Kuzmin, R. Rieben, and V. Tomov, Sequential limiting in continuous and discontinuous Galerkin methods for the Euler equations, Journal of Computational Physics, 356, pp. 372-390, 2018.
  5. M. Reberol and B. Lévy, Computing the Distance between Two Finite Element Solutions Defined on Different 3D Meshes on a GPU, SIAM Journal on Scientific Computing, 40(1), pp. C131-C155, 2018.
  6. A. Mazuyer, P. Cupillard, R. Giot, M. Conin, Y. Leroy, and P. Thore, Stress estimation in reservoirs using an integrated inverse method, Computers & Geosciences, 114, pp. 30-40, 2018.
  7. J. Gopalakrishnan, M. NeumĂĽller, and P. Vassilevski, The auxiliary space preconditioner for the de Rham complex, SIAM Journal on Numerical Analysis, 56(6), pp. 3196-3218, 2018.
  8. D. A. White, M. Stowell, and D. A. Tortorelli, Topological optimization of structures using Fourier representations, Structural and Multidisciplinary Optimization, pp. 1-16, 2018.
  9. S. Rhebergen and G. N. Wells, Preconditioning of a hybridized discontinuous Galerkin finite element method for the Stokes equations, Journal of Scientific Computing, 77(3), pp. 1936-1501, 2018.
  10. T. S. Haut, P. G. Maginot, V. Z. Tomov, T. A. Brunner, and T. S. Bailey, An Efficient Sweep-based Solver for the $S_N$ Equations on High-Order Meshes, American Nuclear Society 2018 Annual Meeting, June 14-21, Philadelphia, PA, 2018.
  11. A. Sánchez-Villar and M. Merino, Advances in Wave-Plasma Modelling in ECR Thrusters, 2018 Space Propulsion Conference, May 14-18, Seville, Spain, 2018.

2017

  1. S. Osborn, P. S. Vassilevski, and U. Villa, A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields, SIAM Journal on Scientific Computing, 39(5), pp. S543-S562, 2017.
  2. R. D. Falgout, T. A. Manteuffel, B. O'Neill, and J. B. Schroder, Multigrid Reduction In Time For Nonlinear Parabolic Problems: A Case Study, SIAM Journal on Scientific Computing, 39(5), pp. S298-S322, 2017.
  3. T. A. Manteuffel, L. N. Olson, J. B. Schroder, and B. S. Southworth, A Root-Node Based Algebraic Multigrid Method, SIAM Journal on Scientific Computing, 39(5), pp. S723-S756, 2017.
  4. A. T. Barker, C. S. Lee, and P. S. Vassilevski, Spectral Upscaling for Graph Laplacian Problems with Application to Reservoir Simulation, SIAM Journal on Scientific Computing, 39(5), pp. S323-S346, 2017.
  5. V. A. Dobrev, Tz. Kolev, N. A. Peterson, and J. B. Schroder, Two-level Convergence Theory For Multigrid Reduction In Time (MGRIT), SIAM Journal on Scientific Computing, 39(5), pp. S501-S527, 2017.
  6. R. E. Bank, P. S. Vassilevski, and L. T. Zikatanov, Arbitrary Dimension Convection-Diffusion Schemes For Space-Time Discretizations, Journal of Computational and Applied Mathematics, 310, pp. 19-31, 2017.
  7. S. Osborn, P. Zulian, T. Benson, U. Villa, R. Krause, and P. S. Vassilevski, Scalable hierarchical PDE sampler for generating spatially correlated random fields using non-matching meshes, Numerical Linear Algebra with Applications, 25, pp. e2146, 2017.
  8. J. H. Adler, I. Lashuk, and S. P. MacLachlan, Composite-grid multigrid for diffusion on the sphere, Numerical Linear Algebra with Applications, 25(1), pp. e2115, 2017.
  9. S. Zampini, P. S. Vassilevski, V. Dobrev, and T. Kolev, Balancing Domain Decomposition by Constraints Algorithms for Curl-conforming Spaces of Arbitrary Order, Domain Decomposition Methods in Science and Engineering XXIV, 2017.
  10. M. Larsen, J. Ahrens, U. Ayachit, E. Brugger, H. Childs, B. Geveci, and C. Harrison, The ALPINE In Situ Infrastructure: Ascending from the Ashes of Strawman, ISAV 2017: In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization, 2017.
  11. J. Wright and S. Shiraiwa, Antenna to Core: A New Approach to RF Modelling, 22 Topical Conference on Radio-Frequency Power in Plasmas, 2017.
  12. S. Shiraiwa, J. C. Wright, P. T. Bonoli, Tz. Kolev, and M. Stowell, RF wave simulation for cold edge plasmas using the MFEM library, 22 Topical Conference on Radio-Frequency Power in Plasmas, 2017.
  13. C. Hofer, U. Langer, M. Neumüller, and I. Toulopoulos, Time-Multipatch Discontinuous Galerkin Space-Time Isogeometric Analysis of Parabolic Evolution Problems, RICAM-Report 2017-26, 2017.
  14. J. Billings, A. McCaskey, G. Vallee, and G. Watson, Will humans even write code in 2040 and what would that mean for extreme heterogeneity in computing?, arXiv:1712.00676, 2017.
  15. M. L. C. Christensen, U. Villa, A. Engsig-Karup, and P. S. Vassilevski, Numerical Multilevel Upscaling For Incompressible Flow in Reservoir Simulation: An Element-Based Algebraic Multigrid (AMGe) Approach, SIAM Journal on Scientific Computing, 39(1), pp. B102-B137, 2017.
  16. R. Anderson, V. Dobrev, Tz. Kolev, D. Kuzmin, M. Q. de Luna, R. Rieben, and V. Tomov, High-order local maximum principle preserving (MPP) discontinuous Galerkin finite element method for the transport equation, Journal of Computational Physics, 334, pp. 102-124, 2017.
  17. R. Li and Y. Saad, Low-Rank Correction Methods for Algebraic Domain Decomposition Preconditioners, SIAM Journal on Matrix Analysis and Applications, 38(3), pp. 807-828, 2017.

2016

  1. D. Z. Kalchev, C. S. Lee, U. Villa, Y. Efendiev, and P. S. Vassilevski, Upscaling of Mixed Finite Element Discretization Problems by the Spectral AMGe Method, SIAM Journal on Scientific Computing, 38(5), pp. A2912-A2933, 2016.
  2. V. A. Dobrev, Tz. V. Kolev, R. N. Rieben, and V. Z. Tomov, Multi-material closure model for high-order finite element Lagrangian hydrodynamics, International Journal for Numerical Methods in Fluids, 82(10), pp. 689-706, 2016.
  3. J. Guermond, B. Popov, and V. Tomov, Entropy-viscosity method for the single material Euler equations in Lagrangian frame, Computer Methods in Applied Mechanics and Engineering, 300, pp. 402-426, 2016.
  4. M. Holec, J. Limpouch, R. Liska, and S. Weber, High-order discontinuous Galerkin nonlocal transport and energy equations scheme for radiation hydrodynamics, International Journal for Numerical Methods in Fluids, 83(10), pp. 779-797, 2016.
  5. Tz. V. Kolev, J. Xu, and Y. Zhu, Multilevel Preconditioners for Reaction-Diffusion Problems with Discontinuous Coefficients, Journal of Scientific Computing, 67(1), pp. 324-350, 2016.
  6. M. Reberol and B. Lévy, Low-order continuous finite element spaces on hybrid non-conforming hexahedral-tetrahedral meshes, CoRR, abs/1605.02626, 2016.
  7. O. Marques, A. Druinsky, X. S. Li, A. T. Barker, P. Vassilevski, and D. Kalchev, Tuning the Coarse Space Construction in a Spectral AMG Solver, Procedia Computer Science, 80, pp. 212-221, International Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA, 2016.
  8. J. S. Yeom, J. J. Thiagarajan, A. Bhatele, G. Bronevetsky, and T. Kolev, Data-Driven Performance Modeling of Linear Solvers for Sparse Matrices, 2016 7th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), 2016.

2015 and earlier

  1. D. Osei-Kuffuor, R. Li, and Y. Saad, Matrix Reordering Using Multilevel Graph Coarsening for ILU Preconditioning, SIAM Journal on Scientific Computing, 37(1), pp. A391-A419, 2015.
  2. R. Anderson, V. Dobrev, Tz. Kolev, and R. Rieben, Monotonicity in high-order curvilinear finite element ALE remap, Int. J. Numer. Meth. Fluids, 77(5), pp. 249-273, 2014.
  3. V. Dobrev, Tz. Kolev, and R. Rieben, High-order curvilinear finite element methods for elastic-plastic Lagrangian dynamics, J. Comp. Phys., (257B), pp. 1062-1080, 2014.
  4. P. Vassilevski and U. Villa, A mixed formulation for the Brinkman problem, SIAM Journal on Numerical Analysis, 52-1, pp. 258-281, 2014.
  5. J. H. Adler and P. S. Vassilevski, Error Analysis for Constrained First-Order System Least-Squares Finite-Element Methods, SIAM Journal on Scientific Computing, 36(3), pp. A1071-A1088, 2014.
  6. A. Aposporidis, P. S. Vassilevski, and A. Veneziani, Multigrid preconditioning of the non-regularized augmented Bingham fluid problem, ETNA. Electronic Transactions on Numerical Analysis, 41, 2014.
  7. P. S. Vassilevski and U. M. Yang, Reducing communication in algebraic multigrid using additive variants, Numerical Linear Algebra with Applications, 21(2), pp. 275-296, 2014.
  8. T. Dong, V. Dobrev, T. Kolev, R. Rieben, S. Tomov, and J. Dongarra, A Step towards Energy Efficient Computing: Redesigning a Hydrodynamic Application on CPU-GPU, 2014 IEEE 28th International Parallel and Distributed Processing Symposium, May 2014.
  9. P. Vassilevski and U. Villa, A block-diagonal algebraic multigrid preconditioner for the Brinkman problem, SIAM Journal on Scientific Computing, 35-5, pp. S3-S17, 2013.
  10. V. Dobrev, T. Ellis, Tz. Kolev, and R. Rieben, High-order curvilinear finite elements for axisymmetric Lagrangian hydrodynamics, Computers & Fluids, pp. 58-69, 2013.
  11. D. Kalchev, C. Ketelsen, and P. S. Vassilevski, Two-level adaptive algebraic multigrid for sequence of problems with slowly varying random coefficients, SIAM Journal on Scientific Computing, 35(6), pp. B1215-B1234, 2013.
  12. P. D'Ambra and P. S. Vassilevski, Adaptive AMG with coarsening based on compatible weighted matching, Computing and Visualization in Science, 16(2), pp. 59-76, 2013.
  13. T. A. Brunner, T. V. Kolev, T. S. Bailey, and A. T. Till, Preserving Spherical Symmetry in Axisymmetric Coordinates for Diffusion, International Conference on Mathematics and Computational Methods Applied to Nuclear Science & Engineering, 2013.
  14. Tz. Kolev and P. Vassilevski, Parallel auxiliary space AMG solver for H(div) problems, SIAM Journal on Scientific Computing, 34, pp. A3079-A3098, 2012.
  15. V. Dobrev, Tz. Kolev, and R. Rieben, High-order curvilinear finite element methods for Lagrangian hydrodynamics, SIAM Journal on Scientific Computing, 34, pp. B606-B641, 2012.
  16. I. Lashuk and P. Vassilevski, Element agglomeration coarse Raviart-Thomas spaces with improved approximation properties, Numerical Linear Algebra with Applications, 19, pp. 414-426, 2012.
  17. D. Kalchev, Adaptive algebraic multigrid for finite element elliptic equations with random coefficients, LLNL Tech. Report, LLNL-TR-553254, 2012.
  18. A. Aposporidis, P. Vassilevski, and A. Veneziani, A geometric nonlinear AMLI preconditioner for the Bingham fluid flow in mixed variables, LLNL Tech. Report, LLNL-JRNL-600372, 2012.
  19. P. Knupp, Introducing the target-matrix paradigm for mesh optimization by node movement, Engineering with Computers, 28(4), pp. 419-429, 2012.
  20. T. A. Brunner, Mulard: A Multigroup Thermal Radiation Diffusion Mini-Application, DOE Exascale Research Conference, Portland, Oregon, 2012.
  21. A. Baker, R. Falgout, T. Kolev, and U. Yang, Multigrid smoothers for ultra-parallel computing, SIAM Journal on Scientific Computing, 33(5), pp. 2864-2887, 2011.
  22. V. Dobrev, T. Ellis, Tz. Kolev, and R. Rieben, Curvilinear finite elements for Lagrangian hydrodynamics, Int. J. Numer. Meth. Fluids, 65, pp. 1295-1310, 2011.
  23. V. Dobrev, J.-L. Guermond, and B. Popov, Surface reconstruction and image enhancement via L1-minimization, SIAM Journal on Scientific Computing, 32 (3), pp. 1591-1616, 2010.
  24. J. Brannick and R. Falgout, Compatible relaxation and coarsening in algebraic multigrid, SIAM Journal on Scientific Computing, 32, pp. 1393-1416, 2010.
  25. A. Baker, Tz. Kolev, and U. M. Yang, Improving algebraic multigrid interpolation operators for linear elasticity problems, Numerical Linear Algebra with Applications, 17, pp. 495-517, 2010.
  26. U. M. Yang, On long-range interpolation operators for aggressive coarsening, Numerical Linear Algebra with Applications, 17, pp. 453-472, 2010.
  27. Tz. Kolev and P. Vassilevski, Parallel auxiliary space AMG for H(curl) problems, Journal of Computational Mathematics, 27, pp. 604-623, 2009.
  28. Tz. V. Kolev and R. N. Rieben, A tensor artificial viscosity using a finite element approach, Journal of Computational Physics, 228(22), pp. 8336 - 8366, 2009.
  29. A. Baker, E. Jessup, and Tz. Kolev, A simple strategy for varying the restart parameter in GMRES(m), J. Comp. Appl. Math., 230, pp. 751-761, 2009.
  30. Tz. Kolev, J. Pasciak, and P. Vassilevski, H(curl) auxiliary mesh preconditioning, Numerical Linear Algebra with Applications, 15, pp. 455-471, 2008.
  31. H. De Sterck, R. Falgout, J. Nolting, and U. M. Yang, Distance-two interpolation for parallel algebraic multigrid, Numerical Linear Algebra with Applications, 15, pp. 115-139, 2008.
  32. V. Dobrev, R. Lazarov, and L. Zikatanov, Preconditioning of symmetric interior penalty discontinuous Galerkin FEM for second order elliptic problems, in Domain Decomposition Methods in Science and Engineering XVII, Lecture Notes in Computational Science and Engineering, vol. 60, U. Langer et al. eds, Springer-Verlag, Berlin, Heidelberg, pp. 33-44, 2008.
  33. D. Alber and L. Olson, Parallel coarse grid selection, Numerical Linear Algebra with Applications, 14, pp. 611-643, 2007.
  34. V. Dobrev, R. Lazarov, P. Vassilevski, and L. Zikatanov, Two-level preconditioning of discontinuous Galerkin approximations of second-order elliptic equations, Numerical Linear Algebra with Applications, 13 (9), pp. 753-770, 2006.
  35. Tz. Kolev and P. Vassilevski, AMG by element agglomeration and constrained energy minimization interpolation, Numerical Linear Algebra with Applications, 13, pp. 771-788, 2006.
  36. J. Bramble, Tz. Kolev, and J. Pasciak, A least-squares approximation method for the time-harmonic Maxwell equations, Journal of Numerical Mathematics, 13(4), pp. 237-263, 2005.
  37. P. Vassilevski, Sparse matrix element topology with application to AMG(e) and preconditioning, Numerical Linear Algebra with Applications, 9, pp. 429-444, 2002.