Evaluating Parallelization Strategies for Large-Scale Individual-based Infectious Disease Simulations

Ponge, Johannes; Horstkemper, Dennis; Hellingrath, Bernd; Bayer, Lukas; Bock, Wolfgang; Karch, André


Zusammenfassung

Individual-based models (IBMs) of infectious disease dynamics with full-country populations often suffer from high runtimes. While there are approaches to parallelize simulations, many prominent epidemic models exhibit single-core implementations, suggesting a lack of consensus among the research community on whether parallelization is desirable or achievable. Rising demands in model scope and complexity, however, imply that performance will continue to be a bottleneck. In this paper, we discuss the requirements and challenges of parallel IBMs in general and the German Epidemic Micro-Simulation System (GEMS) in particular. While the exploitation of unique model characteristics can yield significant performance improvement potential, parallelization strategies generally necessitate trade-offs in either hardware requirements, model fidelity, or implementation complexity. Therefore, the selection of parallelization strategies requires a comprehensive assessment. We present a point-based evaluation scheme to assess the potential of parallelization strategies as our main contribution and exemplify its application in the context of GEMS.

Schlüsselwörter
Epidemics; Runtime; Infectious diseases; Sociology; Hardware; Complexity theory; Statistics



Publikationstyp
Forschungsartikel in Online-Sammlung (Konferenz)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2023

Konferenz
Winter Simulation Conference 2023

Konferenzort
San Antonio, TX

Buchtitel
2023 Winter Simulation Conference (WSC)

Herausgeber
IEEE

Erste Seite
1088

Letzte Seite
1099

Verlag
Wiley-IEEE Computer Society Press

Ort
San Antonio, TX

ISSN
1558-4305

DOI