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Efficiency and scalability of fully-resolved fluid-particle simulations on heterogeneous CPU-GPU architectures

Year: 2023

Type: preprint

Abstract: This dataset contains performance results (*.out), corresponding job scripts (*.sh), an evaluation script (evaluate.py), a snapshot of the waLBerla framework (walberla.zip), and build information (build.sh, build.out) for the following paper: "Efficiency and scalability of fully-resolved fluid-particle simulations on heterogeneous CPU-GPU architectures". Run "python3 evaluate.py" to see the performance numbers from the paper on the terminal. The output of "python3 evaluate.py" can be found in "evaluate_output.txt".

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.7752953

Authors: Kemmler, Samuel, Rettinger, Christoph, Rüde, Ulrich, Cuéllar, Pablo, Köstler, Harald

Institutions: Friedrich-Alexander-Universität Erlangen-Nürnberg, Federal Institute For Materials Research and Testing

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6969179162

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