Misc,

Replication Data for: Load-Balancing for Scalable Simulations with Large Particle Numbers

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Dataset, (2021)Related to: Hirschmann, S.: Load-Balancing for Scalable Simulations with Large Particle Numbers. PhD thesis. University of Stuttgart, 2021, submitted.
DOI: 10.18419/darus-1851

Abstract

This dataset contains input data, scripts, etc. for replicating the numerical experiments in Steffen Hirschmann's dissertation. The data is prefixed with folders indicating the specific experiment as is the processing metadata. The experiments are: 00_periodicity_experiment: Experiment in Chapter 5.1. Agglomerate moves over boundary and we inspect how well different partitioning methods perform. 01_homogeneous_scaling: Experiment in Chapter 8.1. Weak scaling of ESPResSo with and without our additions of a homogeneous fluid. 02_droplet_formation: Experiment in Chapter 8.1. Comparison of the behavior of a non-homogeneous particle distribution with and without load-balancing. 03_coupled_lbm_md: Experiment in Chapter 8.2. Weak scaling evaluation of our joint Lattice-Boltzmann (LBM) Molecular Dynamics (MD) partitioning. 04_lb_adaptions: Experiments in Chapter 8.3. Simulation of a spinodal decomposition with different load-balancing methods and different variants. 05_heterogeneity: Script for evaluating the heterogeneity measure defined in Chapter 7.1. 06_soot_particle_agglomeration: Script to simulate the soot particle agglomeration scenario. Methodology described in Chapter 4, simulation described in Chapter 8.4. The indications to chapters reference the publication described in "Related Publication".

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