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

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


Abstract

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.

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



Publication type
Research article in digital collection (conference)

Peer reviewed
Yes

Publication status
Published

Year
2023

Conference
Winter Simulation Conference 2023

Venue
San Antonio, TX

Book title
2023 Winter Simulation Conference (WSC)

Editor
IEEE

Start page
1088

End page
1099

Publisher
Wiley-IEEE Computer Society Press

Place
San Antonio, TX

ISSN
1558-4305

DOI