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Job-Scheduling of Distributed Simulation-Based Optimization with Support for Multi-Level Parallelism
Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-2315-0680
2015 (English)In: Proceedings of the 56th Conference on Simulation and Modelling (SIMS 56): October, 7-9, 2015, Linköping University, Sweden, Linköping: Linköping University Electronic Press, 2015, 187-197 p.Conference paper (Refereed)
Abstract [en]

In many organizations, the utilization of available computer power is very low. If it could be harnessed for parallel simulation and optimization, valuable time could be saved. A framework monitoring available computer resources and running distributed simulations is proposed. Users build their models locally, and then let a job scheduler determine how the simulation work should be divided among remote computers providing simulation services. Typical applications include sensitivity analysis, co-simulation and design optimization. The latter is used to demonstrate the framework. Optimizations can be parallelized either across the algorithm or across the model. An algorithm for finding the optimal distribution of the different levels of parallelism is proposed. An initial implementation of the framework, using the Hopsan simulation tool, is presented. Three parallel optimization algorithms have been used to verify the method and a thorough examination of their parallel speed-up is included.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. 187-197 p.
Series
Linköping Electronic Conference Proceedings, ISSN 1650-3686 (print), 1650-3740 (online) ; 119
Keyword [en]
Job-scheduling, parallelism, distributed simulation, optimization
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Fluid Mechanics and Acoustics
Identifiers
URN: urn:nbn:se:liu:diva-122752DOI: 10.3384/ecp15119187ISBN: 9789176859001OAI: oai:DiVA.org:liu-122752DiVA: diva2:872644
Conference
The 56th Conference on Simulation and Modelling (SIMS 56), “Modelling, Simulation and Optimization”, Linköping, Sweden, 7-9 October 2015
Available from: 2015-11-19 Created: 2015-11-19 Last updated: 2016-09-14Bibliographically approved
In thesis
1. Distributed System Simulation Methods: For Model-Based Product Development
Open this publication in new window or tab >>Distributed System Simulation Methods: For Model-Based Product Development
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Distributed system simulation can increase performance, re-usability and modularity in model-based product development. This thesis investigates four aspects of distributed simulation: multi-threaded simulations, simulation tool coupling, distributed equation solvers and parallel optimization algorithms.

Multi-threaded simulation makes it possible to split up the workload over several processing units. This reduces simulation time, which can save both time and money during the product development cycle. The transmission line element method (TLM) is used to decouple models to independent sub-models.

Different simulation tools are suitable for different problems. Tool coupling makes it possible to use the best suited tool for simulating each part of the whole product. Models from different tools can then be coupled into one aggregated simulation model. An emerging standard for tool coupling is the Functional Mock-up Interface (FMI). It is investigated how this can be used in conjunction with TLM.

Equation-based object-oriented languages (EOOs) are becoming increasing popular. A logical approach is to let the equation solvers maintain the same structure that was used in the modelling process. Methods for achieving this using TLM and FMI are implemented and evaluated.

In addition to parallel simulations, it is also possible to use parallel optimization algorithms. This introduces parallelism on several levels. For this reason, an algorithm for profile-based multi-level scheduling is proposed.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. 118 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1732
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:liu:diva-122754 (URN)10.3384/diss.diva-122754 (DOI)978-91-7685-875-2 (print) (ISBN)
Public defence
2015-12-18, ACAS, A-huset, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2015-11-19 Created: 2015-11-19 Last updated: 2015-12-02Bibliographically approved

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