Seminar on Large Scale Vehicular Simulation

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Seminar by Tom Hewer on Dec. 9 2008

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Seminar on Large Scale Vehicular Simulation

  1. 1. LARGE SCALE VEHICULAR SIMULATION Challenges and Applications Thomas D. Hewer t.hewer@cs.ucl.ac.uk Centre for Computational Science, University College London and BT Research
  2. 2. INTRODUCTION Vehicular ad hoc networks are highly dynamic and therefore very different to static and personal networks The link times available are very short and are often only a few seconds long Simulation and computational modelling allows us to test and experiment the underlying technology.... ...all without breaking real cars!!
  3. 3. APPLICATIONS Content delivery through delay tolerant networks for media/web/location based services Intelligent transport systems (ITS) Collision avoidance and early-warning Adaptive vehicle routing
  4. 4. SIMULATION Go to video......
  5. 5. LARGE SCALE SYSTEMS Vehicular networks 7e+06 can become very 6e+06 diverse and 5e+06 widespread 4e+06 Time(s) Computational 3e+06 expense of 2e+06 performing 1e+06 simulations is very 0 0 2000 4000 6000 Number of Nodes 8000 10000 intensive
  6. 6. HPC SYSTEMS High performance computing systems fall into two main branches - Supercomputers and Distributed Computing Distributed computing resources are geographically sparse and connected through normal network connections - inter-process communication is time expensive Supercomputers are more tightly coupled, often with Gigabit connections, reducing the bottleneck of communication
  7. 7. DECOMPOSITION We must break up the simulation into smaller parts that can be run on separate processing units The way we decompose the simulation depends on the resource available and system requirements Discrete, event-driven simulations are complex to decompose as they must be synchronous
  8. 8. DECOMPOSITION Component decomposition offers advantages over domain and functional methods Primarily, with a global object available to each processor, local AND remote processing can be achieved with little communication We can also schedule the sharing of inter-process communication, which allows more efficient use of the HPC communications network
  9. 9. PARAMETER SEARCH Running serial simulations to explore a parameter set is time consuming Using HPC we can run a parameter set from a core simulation on many processors, exploring the space more quickly Aggregating the simulations size can improve the timeliness of a full run HPC allows us to consolidate output and perform mass processing
  10. 10. PARAMETER SEARCH
  11. 11. CONCLUSIONS Large scale vehicular network simulations requires huge computational resource HPC allows us to reduce the time taken to run simulation, leading to more timely results and analysis In urgent systems (collision avoidance) the ability to explore the parameter space faster enables more accurate decisions

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