Parallelization of Aggregated FMUs using Static Scheduling
This thesis implements and evaluates static scheduling for aggregated FMUs. An aggregate FMU is several coupled FMUs placed in a single FMU. The implementation creates task graphs from the internal dependencies and connections between the coupled FMUs. These task graphs are then scheduled using two...
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Linköpings universitet, Programvara och system
2018
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ndltd-UPSALLA1-oai-DiVA.org-liu-1522722018-10-26T06:15:35ZParallelization of Aggregated FMUs using Static SchedulingengHammar, MattiasLinköpings universitet, Programvara och system2018FMIFMUCo-simulationparallelizationComputer EngineeringDatorteknikThis thesis implements and evaluates static scheduling for aggregated FMUs. An aggregate FMU is several coupled FMUs placed in a single FMU. The implementation creates task graphs from the internal dependencies and connections between the coupled FMUs. These task graphs are then scheduled using two different list scheduling heuristics, MCP and HLFET. The resulting schedules are then executed in parallel by using OpenMP in the runtime. The implementation is evaluated by looking at the utilization of the schedule, the execution time of the scheduling and the speedup of the simulation. These measurements are taken on three different test models. With model exchange FMUs only a really small speedup is observed. With co-simulation models the speedup varies a lot depending on the model, the highest achieved speedup was 2.8 running on four cores. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152272application/pdfinfo:eu-repo/semantics/openAccess |
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English |
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Others
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FMI FMU Co-simulation parallelization Computer Engineering Datorteknik |
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FMI FMU Co-simulation parallelization Computer Engineering Datorteknik Hammar, Mattias Parallelization of Aggregated FMUs using Static Scheduling |
description |
This thesis implements and evaluates static scheduling for aggregated FMUs. An aggregate FMU is several coupled FMUs placed in a single FMU. The implementation creates task graphs from the internal dependencies and connections between the coupled FMUs. These task graphs are then scheduled using two different list scheduling heuristics, MCP and HLFET. The resulting schedules are then executed in parallel by using OpenMP in the runtime. The implementation is evaluated by looking at the utilization of the schedule, the execution time of the scheduling and the speedup of the simulation. These measurements are taken on three different test models. With model exchange FMUs only a really small speedup is observed. With co-simulation models the speedup varies a lot depending on the model, the highest achieved speedup was 2.8 running on four cores. |
author |
Hammar, Mattias |
author_facet |
Hammar, Mattias |
author_sort |
Hammar, Mattias |
title |
Parallelization of Aggregated FMUs using Static Scheduling |
title_short |
Parallelization of Aggregated FMUs using Static Scheduling |
title_full |
Parallelization of Aggregated FMUs using Static Scheduling |
title_fullStr |
Parallelization of Aggregated FMUs using Static Scheduling |
title_full_unstemmed |
Parallelization of Aggregated FMUs using Static Scheduling |
title_sort |
parallelization of aggregated fmus using static scheduling |
publisher |
Linköpings universitet, Programvara och system |
publishDate |
2018 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152272 |
work_keys_str_mv |
AT hammarmattias parallelizationofaggregatedfmususingstaticscheduling |
_version_ |
1718787327210291200 |