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In VisualSim, the simulation flow can be explained as follows: the simulator translates the graphical depiction of the system into a form suitable for simulation execution and executes simulation of the system model, using user specified model parameters for simulation iteration.
The performance of an optimistic parallel discrete event simulator (PDES) in terms of the total simulation execution time of an experiment depends on a large set of variables.
Furthermore, experiment shows the better results obtained after the simulation execution for intelligent predictive algorithm.
High-performance computing technologies have therefore been extensively used to enable parallel simulation execution.
It will be a great challenge in designing and controlling simulation execution.
For some time now (at least since 7.3 if not earlier) parallel simulation execution can involve any combination of mutithreaded, distributed model, and bulletin board style parallelization.
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For 3MRA, comparison of stand-alone PC versus SuperMUSE simulation executions showed a parallel computing overhead of only 0.57 seconds/simulation, a relative cost increase of 0.7% over average model runtime.
Secondly we observe that the simulation execution-time rapidly increases as we increase μ beyond its optimum value unlike in the case of geometric model where it tends to stagnate after some value of μ.
Figure 5 shows the timelines for these simulation executions.
Points in the figures correspond to measurements obtained from different simulation executions.
During simulation executions, there is a randomly selected vehicle node to broadcast traffic warning messages with inaccurate content every 20 seconds.
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