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212 Publications


2023 | Conference Paper | LibreCat-ID: 46188
Faj, Jennifer, et al. “Scalable Multi-FPGA Design of a Discontinuous Galerkin Shallow-Water Model on Unstructured Meshes.” Proceedings of the Platform for Advanced Scientific Computing Conference (PASC), ACM, 2023, doi:10.1145/3592979.3593407.
LibreCat | Files available | DOI | Download (ext.)
 

2022 | Conference Paper | LibreCat-ID: 46193 | OA
Karp, Martin, et al. “A High-Fidelity Flow Solver for Unstructured Meshes on Field-Programmable Gate Arrays: Design, Evaluation, and Future Challenges.” International Conference on High Performance Computing in Asia-Pacific Region, ACM, 2022, doi:10.1145/3492805.3492808.
LibreCat | DOI | Download (ext.)
 

2022 | Preprint | LibreCat-ID: 36879 | OA
Churavy, Valentin, et al. Bridging HPC Communities through the Julia Programming Language. 2022.
LibreCat | Download (ext.)
 

2022 | Preprint | LibreCat-ID: 32404
Kühne, Thomas, et al. “CP2K on the Road to Exascale.” ArXiv:2205.14741, 2022.
LibreCat | Download (ext.) | arXiv
 

2022 | Preprint | LibreCat-ID: 32177
Borghini, Nicolas, et al. “Early Time Behavior of Spatial and Momentum Anisotropies in Kinetic  Theory across Different Knudsen Numbers.” ArXiv:2201.13294, 2022.
LibreCat | arXiv
 

2022 | Preprint | LibreCat-ID: 32178
Bachmann, Benedikt, et al. “Even Anisotropic-Flow Harmonics Are from Venus, Odd Ones Are from Mars.” ArXiv:2203.13306, 2022.
LibreCat | arXiv
 

2022 | Preprint | LibreCat-ID: 33493
Gavini, Vikram, et al. “Roadmap on Electronic Structure Codes in the Exascale Era.” ArXiv:2209.12747, 2022.
LibreCat | arXiv
 

2022 | Preprint | LibreCat-ID: 46275
Gavini, Vikram, et al. “Roadmap on Electronic Structure Codes in the Exascale Era.” ArXiv:2209.12747, 2022.
LibreCat | arXiv
 

2021 | Conference Paper | LibreCat-ID: 46194
Kenter, Tobias, et al. “Algorithm-Hardware Co-Design of a Discontinuous Galerkin Shallow-Water Model for a Dataflow Architecture on FPGA.” Proceedings of the Platform for Advanced Scientific Computing Conference (PASC), ACM, 2021, doi:10.1145/3468267.3470617.
LibreCat | Files available | DOI | Download (ext.)
 

2021 | Conference Paper | LibreCat-ID: 20886
Nickchen, Tobias, et al. “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts.” Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021, pp. 1994–2002.
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