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Outputs (19)

Democratizing Uncertainty Quantification (2024)
Journal Article
Seelinger, L., Reinarz, A., Lykkegaard, M. B., Akers, R., Alghamdi, A. M., Aristoff, D., Bangerth, W., Bénézech, J., Diez, M., Frey, K., Jakeman, J. D., Jørgensen, J. S., Kim, K.-T., Kent, B. M., Martinelli, M., Parno, M., Pellegrini, R., Petra, N., Riis, N. A., Rosenfeld, K., …Scheichl, R. (2025). Democratizing Uncertainty Quantification. Journal of Computational Physics, 521(1), Article 113542. https://doi.org/10.1016/j.jcp.2024.113542

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling... Read More about Democratizing Uncertainty Quantification.

Doubt and Redundancy Kill Soft Errors---Towards Detection and Correction of Silent Data Corruption in Task-based Numerical Software (2021)
Presentation / Conference Contribution
Samfass, P., Weinzierl, T., Reinarz, A., & Bader, M. (2021, November). Doubt and Redundancy Kill Soft Errors---Towards Detection and Correction of Silent Data Corruption in Task-based Numerical Software. Presented at Supercomputing 21 - FTXS Workshop - 2021 IEEE/ACM 11th Workshop on Fault Tolerance for HPC at eXtreme Scale (FTXS), St Louis, MO

Resilient algorithms in high-performance computing are subject to rigorous non-functional constraints. Resiliency must not increase the runtime, memory footprint or I/O demands too significantly. We propose a task-based soft error detection scheme th... Read More about Doubt and Redundancy Kill Soft Errors---Towards Detection and Correction of Silent Data Corruption in Task-based Numerical Software.

High performance uncertainty quantification with parallelized multilevel Markov chain Monte Carlo (2021)
Presentation / Conference Contribution
Seelinger, L., Reinarz, A., Rannabauer, L., Bader, M., Bastian, P., & Scheichl, R. (2021, November). High performance uncertainty quantification with parallelized multilevel Markov chain Monte Carlo. Presented at SC21: International Conference for High Performance Computing, Networking, Storage and Analysis, St. Louis, MO

Numerical models of complex real-world phenomena often necessitate High Performance Computing (HPC). Uncertainties increase problem dimensionality further and pose even greater challenges. We present a parallelization strategy for multilevel Markov c... Read More about High performance uncertainty quantification with parallelized multilevel Markov chain Monte Carlo.

On GLM curl cleaning for a first order reduction of the CCZ4 formulation of the Einstein field equations (2020)
Journal Article
Dumbser, M., Fambri, F., Gaburro, E., & Reinarz, A. (2020). On GLM curl cleaning for a first order reduction of the CCZ4 formulation of the Einstein field equations. Journal of Computational Physics, 404, Article 109088. https://doi.org/10.1016/j.jcp.2019.109088

In this paper we propose an extension of the generalized Lagrangian multiplier method (GLM) of Munz et al. [52], [30], which was originally conceived for the numerical solution of the Maxwell and MHD equations with divergence-type involutions, to the... Read More about On GLM curl cleaning for a first order reduction of the CCZ4 formulation of the Einstein field equations.

ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems (2020)
Journal Article
Reinarz, A., Charrier, D. E., Bader, M., Bovard, L., Dumbser, M., Duru, K., Fambri, F., Gabriel, A.-A., Gallard, J.-M., Köppel, S., Krenz, L., Rannabauer, L., Rezzolla, L., Samfass, P., Tavelli, M., & Weinzierl, T. (2020). ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems. Computer Physics Communications, 254, Article 107251. https://doi.org/10.1016/j.cpc.2020.107251

ExaHyPE (“An Exascale Hyperbolic PDE Engine”) is a software engine for solving systems of first-order hyperbolic partial differential equations (PDEs). Hyperbolic PDEs are typically derived from the conservation laws of physics and are useful in a wi... Read More about ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems.