GALÆXI Scaling

Version 1.0
Kurz, Marius; Kempf, Daniel; Blind, Marcel P.; Kopper, Patrick; Offenhäuser, Philipp; Schwarz, Anna; Starr, Spencer; Keim, Jens; Beck, Andrea, 2024, "GALÆXI Scaling", https://doi.org/10.18419/darus-4140, DaRUS, V1, UNF:6:q8ZbcGhBxtm6VlmuTlqskA== [fileUNF]
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Description

Numerics Research Group

This Dataset contains the results of the scaling test cases of the GALÆXI Paper (Section 4).

The scaling behavior is evaluated using simulations with resolutions ranging from 16384 up to 8.6x109 degrees of freedom using up to 1024 GPUs on JUWELS booster. The provided results contain the raw data of the performance index PID for different loads investigated. The results of the different PIDs are further post-processed to present the strong scaling (speedup over number of devices) and weak scaling (parallel efficiency over number of devices). In case of the strong scaling, results are given with both enabled and disabled streams on the GPU.

Subject Computer and Information Science; Engineering; Physics
Keyword Discontinuous Galerkin, High-Performance Computing, GPUs, Accelerators, Turbulence, Compressible Flow
Related Publication Kempf, Daniel et al. “GALÆXI: Solving complex compressible flows with high-order discontinuous Galerkin methods on accelerator-based systems.” (2024). doi: 2404.12703
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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PID.tab
Tabular Data - 833 B
Published May 3, 2024
14 Downloads
7 Variables, 12 Observations UNF:6:QXwLovHaPVD25jHA5jxdGw==
Performance Index (PID) over the DOF per GPU for simulations with varying numbers of GPUs are given for GALÆXI.
Results
Preview "PID.tab"
strong_scaling_speedup_no_streams.tab
Tabular Data - 240 B
Published May 3, 2024
18 Downloads
3 Variables, 10 Observations UNF:6:HIUBZRfvw0IbbGgYJWACgQ==
Strong scaling investigation of GALÆXI not using streams. The speedup results are given.
Results
Preview "strong_scaling_speedup_no_streams.tab"
strong_scaling_speedup_using_streams.tab
Tabular Data - 320 B
Published May 3, 2024
16 Downloads
4 Variables, 10 Observations UNF:6:6Z0FQuw2pHeFtqb0DVCHMQ==
Strong scaling investigation of GALÆXI using streams. The speedup results are given.
Results
Preview "strong_scaling_speedup_using_streams.tab"
weak_scaling.tab
Tabular Data - 392 B
Published May 3, 2024
11 Downloads
6 Variables, 10 Observations UNF:6:6qnJebmmZ8WsOnwTWtTmNA==
Strong scaling investigation of GALÆXI. The Parallel efficiency results are given.
Results
Preview "weak_scaling.tab"
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