Name
Abstract | ||
|---|---|---|
Discrete event simulation (DES) performance is a crucial factor when applying large scale simulation models. It limits the ability to produce high quality simulation results within given time bounds, and thus limits the ability for iterative model evaluation. In a holistic hierarchical modeling approach, models are built from basic building blocks, which define the model granularity. Hence, the resulting model granularity is not optimal with respect to the execution semantic, and thus has a limiting impact on simulation performance (granularity gap). The Purpose of this article is to propose an automated model reduction approach to close the granularity gap. The key idea is to merge basic model entities in order to lower model granularity and improve simulation performance. The article discusses requirements and limitations of model reduction in DES and presents the architecture of a research prototype. |
Year | Venue | Keywords |
|---|---|---|
2013 | SIMUTools | large scale simulation model,iterative model evaluation,basic model entity,model reduction,automated model reduction approach,resulting model granularity,model granularity,lower model granularity,discrete event simulation performance,granularity gap,simulation performance,performance |
Field | DocType | Citations |
Hierarchical modeling,Architecture,Iterative and incremental development,Computer science,Real-time computing,Simulation modeling,Granularity,Merge (version control),Limiting,Discrete event simulation | Conference | 0 |
PageRank | References | Authors |
0.34 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Pacholik | 1 | 4 | 2.54 |
| Wolfgang Fengler | 2 | 11 | 9.42 |
| Tommy Baumann | 3 | 23 | 7.81 |
| Michael Rath | 4 | 1 | 0.69 |