Name
Title | ||
|---|---|---|
A high performance framework for modeling and simulation of large-scale complex systems |
Abstract | ||
|---|---|---|
Due to the quick advances in the scale of problem domain of complex systems under investigation, the complexity of multi-input component models used to construct logical processes (LP) has significantly increased. High-performance computing technologies have therefore been extensively used to enable parallel simulation execution. However, the traditional multi-process parallel method (MPM) executes LPs in parallel on multi-core platforms, which ignores the intrinsic parallel capabilities of multi-input component models. In this study, a vectorized component model (VCM) framework has been proposed. The design aims to better utilize the parallelism of multi-input component models. A two-level composite parallel method (CPM) has then been constructed within the framework, which can sustain complex system simulation applications consisting of multi-input component models. CPM first employs MPM to dispatch LPs onto a multi-core computing platform. It then maps VCMs to the multiple-core platform for parallel execution. Experimental results indicate that (1) the proposed VCM framework can better utilize the parallelism of multi-input component models, and (2) CPM can significantly improve the performance comparing to the traditional MPM. The results also show that CPM can effectively cope with the size and complexity of complex simulation applications with multi-input component models. We presented a CCM framework for modeling complex systems.We developed a vectorized extension of CCM framework.We proposed a two-level composite parallel execution method. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.future.2014.11.018 | Future Generation Computer Systems |
Keywords | DocType | Volume |
Complex systems,Modeling and simulation,Parallel computing,Composite parallel method,Discrete event simulation | Journal | 51 |
Issue | ISSN | Citations |
C | 0167-739X | 6 |
PageRank | References | Authors |
0.53 | 37 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng Zhu | 1 | 11 | 6.83 |
| Yiping Yao | 2 | 120 | 31.11 |
| Wenjie Tang | 3 | 46 | 11.91 |
| Dan Chen | 4 | 1096 | 59.02 |