Multi-scale Coupling for Predictive Injector Simulations. - Mathis Bode; Marco Davidovic; Heinz Pitsch (JHPCS, 2016)

Extreme-Scale In Situ Visualization of Turbulent Flows on IBM Blue Gene/Q JUQUEEN. - Jens Henrik Göbbert; Mathis Bode; Brian J. N. Wylie (ISC Workshops, 2016)

Towards Prediction of Turbulent Flows at High Reynolds Numbers Using High Performance Computing Data and Deep Learning. - Mathis Bode; Michael Gauding; Jens Henrik Göbbert; Baohao Liao; Jenia Jitsev; Heinz Pitsch (ISC Workshops, 2018)

On the self-similarity of line segments in decaying homogeneous isotropic turbulence. - Michael Gauding; Lipo Wang; Jens Henrik Göbbert; Mathis Bode; Luminita Danaila; Emilien Varea (CoRR, 2018)

A discrete mathematics approach for large scale improvement in classification training time. - Sumedh Yadav; Mathis Bode (IEEE BigData, 2019)

Deep Learning at Scale for Subgrid Modeling in Turbulent Flows: Regression and Reconstruction. - Mathis Bode; Michael Gauding; Konstantin Kleinheinz; Heinz Pitsch (ISC Workshops, 2019)

Deep learning at scale for subgrid modeling in turbulent flows. - Mathis Bode; Michael Gauding; Konstantin Kleinheinz; Heinz Pitsch (CoRR, 2019)

Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows. - Mathis Bode; Michael Gauding; Zeyu Lian; Dominik Denker; Marco Davidovic; Konstantin Kleinheinz; Jenia Jitsev; Heinz Pitsch (CoRR, 2019)

A graphical heuristic for reduction and partitioning of large datasets for scalable supervised training. - Sumedh Yadav; Mathis Bode (J. Big Data, 2019)

Using Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Reconstruct Mixture Fraction Statistics of Turbulent Jet Flows. - Michael Gauding; Mathis Bode (ISC Workshops, 2021)

Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. - Agastya P. Bhati; Shunzhou Wan; Dario Alfè; Austin R. Clyde; Mathis Bode; Li Tan; Mikhail Titov; André Merzky; Matteo Turilli; Shantenu Jha; Roger R. Highfield; Walter Rocchia; et al. (CoRR, 2021)

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data. - Mathis Bode; Michael Gauding; Dominik Goeb; Tobias Falkenstein; Heinz Pitsch (CoRR, 2022)

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean Premixed Gas Turbine Combustors. - Mathis Bode (CoRR, 2022)

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Non-Premixed Combustion on Non-Uniform Meshes and Demonstration of an Accelerated Simulation Workflow. - Mathis Bode (CoRR, 2022)

A three-dimensional cell-based volume-of-fluid method for conservative simulations of primary atomization. - Fabian Fröde; Temistocle Grenga; Vincent Le Chenadec; Mathis Bode; Heinz Pitsch (J. Comput. Phys., 2022)

AI Super-Resolution Subfilter Modeling for Multi-Physics Flows. - Mathis Bode (PASC, 2023)

Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI. - Victor A. Mateevitsi; Mathis Bode; Nicola J. Ferrier; Paul F. Fischer; Jens Henrik Göbbert; Joseph A. Insley; Yu-Hsiang Lan; Misun Min; Michael E. Papka; Saumil Patel; Silvio Rizzi 001; Jonathan Windgassen (SC Workshops, 2023)

Hybrid scheme for complex flows on staggered grids and application to multiphase flows. - Mathis Bode; Abhishek Deshmukh; Tobias Falkenstein; Seongwon Kang; Heinz Pitsch (J. Comput. Phys., 2023)

Software and Analysis for paper: Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI. - Victor A. Mateevitsi; Mathis Bode; Nicola J. Ferrier; Paul F. Fischer; Jens Henrik Göbbert; Joseph A. Insley; Yu-Hsiang Lan; Misun Min; Michael E. Papka; Saumil Patel; Silvio Rizzi 001; Jonathan Windgassen (Zenodo, 2023)

Visuals on the House: Optimizing HPC Workflows with No-Cost CPU Visualization. - Victor A. Mateevitsi; Andres Sewell; Mathis Bode; Paul F. Fischer; Jens Henrik Göbbert; Joseph A. Insley; Ioannis Kavroulakis; Damaskinos Konioris; Yu-Hsiang Lan; Misun Min; Dimitrios Papageorgiou; Michael E. Papka; et al. (LDAV, 2024)

Application-Driven Exascale: The JUPITER Benchmark Suite. - Andreas Herten; Sebastian Achilles; Damian Alvarez; Jayesh Badwaik; Eric Behle; Mathis Bode; Thomas Breuer; Daniel Caviedes-Voullième; Mehdi Cherti; Adel Dabah; Salem El Sayed; Wolfgang Frings; et al. (SC, 2024)

nekCRF: A next generation high-order reactive low Mach flow solver for direct numerical simulations. - Stefan Kerkemeier; Christos E. Frouzakis; Ananias Tomboulides; Paul F. Fischer; Mathis Bode (CoRR, 2024)

JuMonC: A RESTful tool for enabling monitoring and control of simulations at scale. - Christian Witzler; Filipe Souza Mendes Guimarães; Daniel Mira; Hartwig Anzt; Jens Henrik Göbbert; Wolfgang Frings; Mathis Bode (Future Gener. Comput. Syst., 2025)

Deciphering boundary layer dynamics in high-Rayleigh-number convection using 3360 GPUs and a high-scaling in-situ workflow. - Mathis Bode; Damian Alvarez; Paul F. Fischer; Christos E. Frouzakis; Jens Henrik Göbbert; Joseph A. Insley; Yu-Hsiang Lan; Victor A. Mateevitsi; Misun Min; Michael E. Papka; Silvio Rizzi 001; Roshan J. Samuel; et al. (CoRR, 2025)

Scaled Block Vecchia Approximation for High-Dimensional Gaussian Process Emulation on GPUs. - Qilong Pan 001; Sameh Abdulah; Mustafa Abduljabbar; Hatem Ltaief; Andreas Herten; Mathis Bode; Matthew T. Pratola; Arindam Fadikar; Marc G. Genton; David E. Keyes; Ying Sun 002 (CoRR, 2025)