by Ezequiel Glinsky Research Assistant, University of Buenos Aires, Argentina Supervisor: Prof. Gabriel A. Wainer SCE, Carleton University Thursday, November 15th, 2001 ESG Seminars Overhead analysis of Overhead analysis of Discrete Event models Discrete Event models execution execution
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by Ezequiel Glinsky Research Assistant, University of Buenos Aires, Argentina
Overhead analysis of Discrete Event models execution. by Ezequiel Glinsky Research Assistant, University of Buenos Aires, Argentina Supervisor: Prof. Gabriel A. Wainer SCE, Carleton University. ESG Seminars. Thursday, November 15th, 2001. Seminar topics will include. - PowerPoint PPT Presentation
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by Ezequiel GlinskyResearch Assistant, University of Buenos Aires, Argentina
Supervisor: Prof. Gabriel A. WainerSCE, Carleton University
Thursday, November 15th, 2001ESG Seminars
Overhead analysis of Overhead analysis of Discrete Event models executionDiscrete Event models execution
Seminar topics will include...Seminar topics will include...
Introduction to DEVS formalismPerformance analysis of different
DEVS toolsRT-DEVS extension to the formalismDevelopment of enhancements
(work-in-progress)
• DEVS = Discrete Event System Specification
• Provides sound formal M&S framework
• Supports full range of dynamic system representation capability
• Supports hierarchical, modular model development
Testing & Performance AnalysisTesting & Performance Analysis“Performance analysis of different DEVS environments”
We need a synthetic model generator to represent different possible model
configurations
Why do we need a Model Generator? Detect bottlenecks
Characterize tool’s overhead Test automatically and thoroughly
Appreciate current overhead and therefore consider the possibility of RT simulation execution
A model generator (contd.)A model generator (contd.)
Available parameters: Depth Width Dhrystone code in transition functions Model type
A model generator (contd.)A model generator (contd.)
Available parameters: Depth Width Dhrystone code in transition functions Model type
Number of levels of the modeling hierarchy.
A model generator (contd.)A model generator (contd.)
Available parameters: Depth Width Dhrystone code in transition functions Model type
Number of children belonging to each intermediate coupled component.
A model generator (contd.)A model generator (contd.)
Available parameters: Depth Width Dhrystone code in transition functions Model type
Allows us to execute time-consuming code inside both the internal and external transition functions.
A model generator (contd.)A model generator (contd.)
Available parameters: Depth Width Dhrystone code in transition functions Model type
Different types of models can be generated, with different behavior, coupling and interconnections.
A model generator (contd.)A model generator (contd.)
Sample model
ParametersDEPTH = 4WIDTH = 3Time in Internal Transition = 50 msTime in External Transition = 50 msModel Type = 1 (coupled component #1 and #2 are not shown)
Increasing complexity Increasing response times Nevertheless, percentages of overhead remains nearly stable
simulations can be carried out properly
Bottom line: After thorough testing, we can say the real-time simulator is able to execute simulations properly even under difficult conditions (high workload and mid to large-scale models)
Flattened SimulatorFlattened Simulator
Why do we need a flattened simulator?
To increase tool’s performance and simulate successfully even more
complex models with higher workload
(Work-in-progress)
Flattened SimulatorFlattened Simulator
Associated hierarchical simulator
Model hierarchy
Existing hierarchical simulator:
Intermediate coordinators associated to each coupled component
High number of messages exchanged along the simulation
This induces more overhead!
Flattened SimulatorFlattened Simulator
Proposed flattened simulator:
Must keep separation between model and actual simulator
Reduce number of intermediate coordinators
Simplify hierarchy and reduced message exchange along the simulation