Database-aided Workflows on HPC for Plasma Physics Simulation

The on-going work presented at ISGC25 Physics and Engineering track and in this article explores different technical approaches for management and analysis of data obtained from large physics simulations, with the goal of optimizing data-driven workflows across Cloud-Computing (IaaS) and HPC systems. The work is connected to research activities on database usage in the context of High Performance Computing conducted through the EXA4MIND Horizon Europe project. The case presented here, is a large-scale parameter study of plasma physics simulations carried out on supercomputing systems at LRZ (Garching b.M., DE). It uses the Particle-in-Cell [4] code PSC [7], using the FDTD [16] method for electric fields, to simulate the movement of ionized hydrogen plasma , i.e. protons and the corresponding electrons, in a small (nano- to micrometer scale) amount of matter (”mass limited target”, MLT) that is driven to very high energies by irradiation with ultra-intense femtosecond laser pulses. When evaluating the large amount (approx. 50 TB) of simulation output consisting mostly of particle trajectories, much work goes into postprocessing and re-assessing the data. This typically happens several times in a repeating process of varying parameters for processing, like time step selection, cut-off thresholds and plotting style adjustments. The goal is an integrated and comprehensive methodology to facilitate such a re-use of the data with an eye on FAIR research data management is our final objective.

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Publication Details

Published
2025-10-20
DOI
https://doi.org/10.22323/1.488.0024
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Database-aided Workflows on HPC for Plasma Physics Simulation

Stephan Hachinger, Jan Martinovič, Viktoria Pauw, Hachinger Stephan
Advanced Data Storage Technologies
article

Database-aided Workflows on HPC for Plasma Physics Simulation

Stephan Hachinger, Jan Martinovič, Viktoria Pauw, Hachinger Stephan
article en

Abstract

The on-going work presented at ISGC25 Physics and Engineering track and in this article explores different technical approaches for management and analysis of data obtained from large physics simulations, with the goal of optimizing data-driven workflows across Cloud-Computing (IaaS) and HPC systems. The work is connected to research activities on database usage in the context of High Performance Computing conducted through the EXA4MIND Horizon Europe project. The case presented here, is a large-scale parameter study of plasma physics simulations carried out on supercomputing systems at LRZ (Garching b.M., DE). It uses the Particle-in-Cell [4] code PSC [7], using the FDTD [16] method for electric fields, to simulate the movement of ionized hydrogen plasma , i.e. protons and the corresponding electrons, in a small (nano- to micrometer scale) amount of matter (”mass limited target”, MLT) that is driven to very high energies by irradiation with ultra-intense femtosecond laser pulses. When evaluating the large amount (approx. 50 TB) of simulation output consisting mostly of particle trajectories, much work goes into postprocessing and re-assessing the data. This typically happens several times in a repeating process of varying parameters for processing, like time step selection, cut-off thresholds and plotting style adjustments. The goal is an integrated and comprehensive methodology to facilitate such a re-use of the data with an eye on FAIR research data management is our final objective.

Friedrich-Schiller-Universität Jena, European Commission
Openalex Percentile: Top 65%
Advanced Data Storage Technologies
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