Massively parallel simulations of spread of infectious diseases over realistic social networks

Abhinav Bhatele, Jae Seung Yeom, Nikhil Jain, Chris J. Kuhlman, Yarden Livnat, Keith R. Bisset, Laxmikant V. Kale, Madhav V. Marathe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Controlling the spread of infectious diseases in large populations is animportant societal challenge. Mathematically, the problem is best captured as acertain class of reaction-diffusion processes (referred to as contagionprocesses) over appropriate synthesized interaction networks. Agent-basedmodels have been successfully used in the recent past to study such contagionprocesses. We describe EpiSimdemics, a highly scalable, parallel code writtenin Charm++ that uses agent-based modeling to simulate disease spreads overlarge, realistic, co-evolving interaction networks. We present a new parallelimplementation of EpiSimdemics that achieves unprecedented strong and weakscaling on different architectures-Blue Waters, Cori and Mira. EpiSimdemicsachieves five times greater speedup than the second fastest parallel code inthis field. This unprecedented scaling is an important step to support the longterm vision of real-Time epidemic science. Finally, we demonstrate the capabilities of EpiSimdemics by simulating thespread of influenza over a realistic synthetic social contact network spanningthe continental United States (~280 million nodes and 5.8 billion social contacts).

Original languageEnglish (US)
Title of host publicationProceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages689-694
Number of pages6
ISBN (Electronic)9781509066100
DOIs
StatePublished - Jul 10 2017
Event17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017 - Madrid, Spain
Duration: May 14 2017May 17 2017

Publication series

NameProceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017

Other

Other17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017
CountrySpain
CityMadrid
Period5/14/175/17/17

Keywords

  • Agent-based modeling
  • Discrete-event simulation
  • Epidemiology
  • Performance
  • scaling

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

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  • Cite this

    Bhatele, A., Yeom, J. S., Jain, N., Kuhlman, C. J., Livnat, Y., Bisset, K. R., Kale, L. V., & Marathe, M. V. (2017). Massively parallel simulations of spread of infectious diseases over realistic social networks. In Proceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017 (pp. 689-694). [7973759] (Proceedings - 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCGRID.2017.141