Mirage: A framework for data-driven collaborative high-resolution simulation

Byung H. Park; Melissa R. Allen; Devin White; Eric Weber; John T. Murphy; Michael J. North; Pam Sydelko

doi:10.1007/978-3-319-22786-3_35

Mirage: A framework for data-driven collaborative high-resolution simulation

Byung H. Park, Melissa R. Allen, Devin White, Eric Weber, John T. Murphy, Michael J. North, Pam Sydelko

Performance Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Information about how human populations shift in response to various stimuli is limited because no single model is capable of addressing these stimuli simultaneously, and integration of the best existing models has been challenging because of the vast disparity among constituent model purposes, architectures, scales, and execution environments. To demonstrate a potential model coupling for approaching this problem, three major model components are integrated into a fully coupled system that executes a worldwide infection-infected routine where a human population requires a food source for sustenance and an infected population can spread an infection when it is in contact with the remaining healthy population. To enable high-resolution data-driven model federation and an ability to capture dynamics and behaviors of billions of humans, a high-performance computing agent-based framework has been created and is demonstrated in this chapter.

Original language	English
Title of host publication	Advances in Geocomputation - Geocomputation 2015—The 13th International Conference
Editors	Daniel A. Griffith, Yongwan Chun, Denis J. Dean
Publisher	Springer Heidelberg
Pages	395-403
Number of pages	9
ISBN (Print)	9783319227856
DOIs	https://doi.org/10.1007/978-3-319-22786-3_35
State	Published - 2017
Event	13th International Conference on Advances in Geocomputation, Geocomputation 2015 - Dallas, United States Duration: May 20 2015 → May 23 2015

Publication series

Name	Advances in Geographic Information Science
Volume	0
ISSN (Print)	1867-2434
ISSN (Electronic)	1867-2442

Conference

Conference	13th International Conference on Advances in Geocomputation, Geocomputation 2015
Country/Territory	United States
City	Dallas
Period	05/20/15 → 05/23/15

Funding

This manuscript has been authored in part by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the US Department of Energy. This manuscript also has been authored in part by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a US Department of Energy Office of Science Laboratory, is operated under contract number DE-AC02-06CH11357. The United States Government retains, and the publisher, by accepting the article for publication, acknowledges that the United States Government retains, a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The work used the Oak Ridge Leadership Computing Facility.

Funders	Funder number
US Department of Energy Office of Science Laboratory	DE-AC02-06CH11357
U.S. Department of Energy

Keywords

Agent-based
High-performance computing
Model coupling

Access to Document

10.1007/978-3-319-22786-3_35

Cite this

Park, B. H., Allen, M. R., White, D., Weber, E., Murphy, J. T., North, M. J., & Sydelko, P. (2017). Mirage: A framework for data-driven collaborative high-resolution simulation. In D. A. Griffith, Y. Chun, & D. J. Dean (Eds.), Advances in Geocomputation - Geocomputation 2015—The 13th International Conference (pp. 395-403). (Advances in Geographic Information Science; Vol. 0). Springer Heidelberg. https://doi.org/10.1007/978-3-319-22786-3_35

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Park, BH , Allen, MR, White, D, Weber, E, Murphy, JT, North, MJ & Sydelko, P 2017, Mirage: A framework for data-driven collaborative high-resolution simulation. in DA Griffith, Y Chun & DJ Dean (eds), Advances in Geocomputation - Geocomputation 2015—The 13th International Conference. Advances in Geographic Information Science, vol. 0, Springer Heidelberg, pp. 395-403, 13th International Conference on Advances in Geocomputation, Geocomputation 2015, Dallas, United States, 05/20/15. https://doi.org/10.1007/978-3-319-22786-3_35

Mirage: A framework for data-driven collaborative high-resolution simulation. / Park, Byung H.; Allen, Melissa R.; White, Devin et al.
Advances in Geocomputation - Geocomputation 2015—The 13th International Conference. ed. / Daniel A. Griffith; Yongwan Chun; Denis J. Dean. Springer Heidelberg, 2017. p. 395-403 (Advances in Geographic Information Science; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Park BH , Allen MR, White D, Weber E, Murphy JT, North MJ et al. Mirage: A framework for data-driven collaborative high-resolution simulation. In Griffith DA, Chun Y, Dean DJ, editors, Advances in Geocomputation - Geocomputation 2015—The 13th International Conference. Springer Heidelberg. 2017. p. 395-403. (Advances in Geographic Information Science). doi: 10.1007/978-3-319-22786-3_35

Mirage: A framework for data-driven collaborative high-resolution simulation

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