uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Fast event-based epidemiological simulations on national scales
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
2016 (English)In: The international journal of high performance computing applications, ISSN 1094-3420, E-ISSN 1741-2846, Vol. 30, 438-453 p.Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2016. Vol. 30, 438-453 p.
National Category
Computer Science Computational Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-264751DOI: 10.1177/1094342016635723ISI: 000387763100005OAI: oai:DiVA.org:uu-264751DiVA: diva2:861388
Projects
UPMARCeSSENCE
Available from: 2016-04-11 Created: 2015-10-16 Last updated: 2017-12-01Bibliographically approved
In thesis
1. Parallelism and efficiency in discrete-event simulation
Open this publication in new window or tab >>Parallelism and efficiency in discrete-event simulation
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Discrete-event models depict systems where a discrete state is repeatedly altered by instantaneous changes in time, the events of the model. Such models have gained popularity in fields such as Computational Systems Biology or Computational Epidemiology due to the high modeling flexibility and the possibility to easily combine stochastic and deterministic dynamics. However, the system size of modern discrete-event models is growing and/or they need to be simulated at long time periods. Thus, efficient simulation algorithms are required, as well as the possibility to harness the compute potential of modern multicore computers. Due to the sequential design of simulators, parallelization of discrete event simulations is not trivial. This thesis discusses event-based modeling and sensitivity analysis and also examines ways to increase the efficiency of discrete-event simulations and to scale models involving deterministic and stochastic spatial dynamics on a large number of processor cores.

Place, publisher, year, edition, pages
Uppsala University, 2015
Series
Information technology licentiate theses: Licentiate theses from the Department of Information Technology, ISSN 1404-5117 ; 2015-004
National Category
Computational Mathematics Computer Science
Research subject
Scientific Computing
Identifiers
urn:nbn:se:uu:diva-264756 (URN)
Supervisors
Projects
UPMARCeSSENCE
Available from: 2015-10-14 Created: 2015-10-16 Last updated: 2017-08-31Bibliographically approved
2. Parallelism in Event-Based Computations with Applications in Biology
Open this publication in new window or tab >>Parallelism in Event-Based Computations with Applications in Biology
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Event-based models find frequent usage in fields such as computational physics and biology as they may contain both continuous and discrete state variables and may incorporate both deterministic and stochastic state transitions. If the state transitions are stochastic, computer-generated random numbers are used to obtain the model solution. This type of event-based computations is also known as Monte-Carlo simulation.

In this thesis, I study different approaches to execute event-based computations on parallel computers. This ultimately allows users to retrieve their simulation results in a fraction of the original computation time. As system sizes grow continuously or models have to be simulated at longer time scales, this is a necessary approach for current computational tasks.

More specifically, I propose several ways to asynchronously simulate such models on parallel shared-memory computers, for example using parallel discrete-event simulation or task-based computing. The particular event-based models studied herein find applications in systems biology, computational epidemiology and computational neuroscience.

In the presented studies, the proposed methods allow for high efficiency of the parallel simulation, typically scaling well with the number of used computer cores. As the scaling typically depends on individual model properties, the studies also investigate which quantities have the greatest impact on the simulation performance.

Finally, the presented studies include other insights into event-based computations, such as methods how to estimate parameter sensitivity in stochastic models and how to simulate models that include both deterministic and stochastic state transitions.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. 48 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1586
Keyword
Event-based computations, Parallel algorithms, Discrete-event simulation, Monte-Carlo methods, Systems biology.
National Category
Other Computer and Information Science Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-332009 (URN)978-91-513-0125-9 (ISBN)
Public defence
2017-12-11, 2347, ITC, Lägerhyddsvägen 2, Uppsala, 10:15 (English)
Opponent
Supervisors
Projects
UPMARC
Available from: 2017-11-30 Created: 2017-10-22 Last updated: 2017-12-04

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Bauer, PavolEngblom, Stefan

Search in DiVA

By author/editor
Bauer, PavolEngblom, Stefan
By organisation
Division of Scientific ComputingComputational Science
In the same journal
The international journal of high performance computing applications
Computer ScienceComputational Mathematics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 631 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf