GALÆXI Validation: Taylor-Green Vortex

Version 1.1
Kurz, Marius; Kempf, Daniel; Blind, Marcel P.; Kopper, Patrick; Offenhäuser, Philipp; Schwarz, Anna; Starr, Spencer; Keim, Jens; Beck, Andrea, 2024, "GALÆXI Validation: Taylor-Green Vortex", https://doi.org/10.18419/DARUS-4139, DaRUS, V1, UNF:6:Q71FGjHTEHnKVAq/VkFpXA== [fileUNF]
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Description

Numerics Research Group

This Dataset contains the test case definition and reference data for the Taylor-Green Vortex (TGV) test case which builds the validation test case in the GALÆXI Paper (Section 5).

Incompressible TGV (Ma=0.1) according to (Link):
J. DeBonis, Solutions of the Taylor–Green vortex problem using high- resolution explicit finite difference methods, in: 51st AIAA Aerospace Sciences Meeting, 2013, p. 382

Compressible TGV (Ma=1.25) according to (Link):
J.-B. Chapelier, D. J. Lusher, W. Van Noordt, C. Wenzel, T. Gibis, P. Mossier, A. D. Beck, G. Lodato, C. Brehm, M. Ruggeri, C. Scalo, N. Sandham, Comparison of high-order numerical methodologies for the simulation of the supersonic taylor-green vortex flow, Physics of Fluids 2024; 36 (5): 055146.

Executable of FLEXI/GALÆXI can be built using the build.py script:

python3 build.py ./build-folder ./userblock.txt
Note: Please ensure that all necessary dependencies of GALÆXI/FLEXI are available (including CUDA) and a Python3 environment is installed on the system.
Subject Computer and Information Science; Engineering; Physics
Keyword Discontinuous Galerkin, High-Performance Computing, GPUs, Accelerators, Turbulence, Compressible Flow
Related Publication Kurz, M., Kempf, D., Blind, M., Kopper, P., Offenhäuser, P., Schwarz, A., Starr, S., Keim, J., & Beck, A. (2024). GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems. Computer Physics Communications, 109388.doi: 10.1016/j.cpc.2024.109388
Notes This work was funded by the European Union. This work has received funding from the European High Performance Computing Joint Undertaking (JU) and Sweden, Germany, Spain, Greece, and Denmark under grant agreement No 101093393. Moreover, this research presented was funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy EXC 2075 – 390740016, by the DFG Rebound – 420603919, and in the framework of the research unit FOR 2895. We acknowledge the support by the Stuttgart Center for Simulation Science (SimTech). The authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time through the John von Neumann Institute for Computing (NIC) on the GCS Supercomputer JUWELS at Jülich Supercomputing Centre (JSC) as well as the support and the computing time on “Hawk” and its “Hawk-AI” extension provided by the Supercomputing Centre Stuttgart (HLRS) through the project “hpcdg”. This work was completed in part at the Helmholtz GPU Hackathon, part of the Open Hackathons program. The authors would like to acknowledge OpenACC-Standard.org, JSC, HZDR, and HIDA for their support.
License/Data Use Agreement

CC BY 4.0

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build.py
build/Python Source Code - 5.4 KB
Published May 3, 2024
18 Downloads
MD5: c220e07653c938bb2c136b9e1c6450e1
Python Script for automatically cloning, patching and building the FLEXI/GALÆXI executable. Command: python3 ./build.py ./build-folder userblock.tmp
Build
FLEXI_CPU_TGV_compressible_userblock.txt
build/Plain Text - 12.5 KB
Published May 3, 2024
30 Downloads
MD5: 6fd0dcffd863d3130e0216e4148ebc34
Userblock file for automatically building FLEXI using the build.py script.
Build
Preview "build/FLEXI_CPU_TGV_compressible_userblock.txt"
FLEXI_CPU_TGV_incompressible_userblock.txt
build/Plain Text - 2.3 KB
Published May 3, 2024
35 Downloads
MD5: b926410a30ce724e5386e5eb84aa7781
Userblock file for automatically building FLEXI using the build.py script.
Build
Preview "build/FLEXI_CPU_TGV_incompressible_userblock.txt"
GALÆXI_GPU_TGV_compressibe_userblock.txt
build/Plain Text - 1.9 KB
Published May 3, 2024
31 Downloads
MD5: 208ac4569001a03bc23cffb1634b8993
Userblock file for automatically building GALÆXI using the build.py script.
Build
Preview "build/GALÆXI_GPU_TGV_compressibe_userblock.txt"
GALÆXI_GPU_TGV_incompressible_userblock.txt
build/Plain Text - 1.8 KB
Published May 3, 2024
38 Downloads
MD5: d79b0f923de0f0100a44818f334d6f76
Userblock file for automatically building GALÆXI using the build.py script.
Build
Preview "build/GALÆXI_GPU_TGV_incompressible_userblock.txt"
CART_HEX_PERIODIC_016_mesh.h5
TGV_compressible_Ma1p25/CPU/TGV_CPU_Ma1p25_16x16x16_N7/Hierarchical Data Format - 1.6 MB
Published May 3, 2024
12 Downloads
MD5: 27053f66f6fcbe05b9a7928fc0eca039
Mesh file for the simulation.
Setup
parameter_flexi.ini
TGV_compressible_Ma1p25/CPU/TGV_CPU_Ma1p25_16x16x16_N7/Unknown - 3.5 KB
Published May 3, 2024
17 Downloads
MD5: 1307a12ef25fe0791f04bc9243963549
Parameter file to execute the simulation with GALÆXI/FLEXI.
Setup
parameter_hopr.ini
TGV_compressible_Ma1p25/CPU/TGV_CPU_Ma1p25_16x16x16_N7/Unknown - 2.8 KB
Published May 3, 2024
13 Downloads
MD5: 2feedd4ee7758f3ea8803615979137c0
Parameter file to generate the mesh using HOPR (https://github.com/hopr-framework/hopr).
Setup
TGV_Re1600_TGVAnalysis.tab
TGV_compressible_Ma1p25/CPU/TGV_CPU_Ma1p25_16x16x16_N7/Tabular Data - 246.6 KB
Published May 3, 2024
31 Downloads
16 Variables, 633 Observations UNF:6:bJX0KqQ1NRLlYT6NuMz8Vg==
Results
Preview "TGV_compressible_Ma1p25/CPU/TGV_CPU_Ma1p25_16x16x16_N7/TGV_Re1600_TGVAnalysis.tab"
CART_HEX_PERIODIC_032_mesh.h5
TGV_compressible_Ma1p25/CPU/TGV_CPU_Ma1p25_32x32x32_N7/Hierarchical Data Format - 12.9 MB
Published May 3, 2024
16 Downloads
MD5: ba8378bde8dfc921f6008f0e25d816a1
Mesh file for the simulation.
Setup
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