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Computational Challenges for Modeling and Simulation

Computational Challenges for Modeling and Simulation. Michael Macedonia Chief Technology Officer, US Army Program Executive Office for Simulation, Training and Instrumentation ( PEO STRI). Real-time Computational Challenges for Computer Generated Forces (CGF).

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Computational Challenges for Modeling and Simulation

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  1. Computational Challenges for Modeling and Simulation Michael Macedonia Chief Technology Officer, US Army Program Executive Office for Simulation, Training and Instrumentation ( PEO STRI)

  2. Real-time Computational Challenges for Computer Generated Forces (CGF) Need to provide interactive, real-time terrain reasoning for Computer Generated Forces given: • Extremely dense terrain databases (e.g. Baku, NYC, Baghdad) • Thousand of simulated entities (size of Army Unit of Action) • Simulation of long-range and novel sensors • Must fit on Future Combat System platforms (no Beowulf clusters allowed) Bottomline: Traditional CPU architecture and Moore’s law are not enough to achieve capability in this decade.

  3. Best algorithms are O(N2 ) where N = objects/entities in the CGF database (e.g., sensors, platforms, buildings, people) 40% to 80% of CGF CPU time is required for battalion-level scenarios spent in sensing functions: Collision detection Line of sight computation Real-time Terrain Algorithms for Computer Generated Forces

  4. Purpose of LOS Algorithms • Simulated LOS for Models and Simulations • Position Sensors to Maximum Visibility • Position Targets to Minimize Visibility • Basically, we need to answer the question: • Can a sensor at location A see a Target at • location B? Courtesy Danny Champion, TRAC

  5. Algorithm Considerations • Coordinate System (UTM or Lat/Long or Geocentric)? • Curved or Flat Earth or Radar LOS? • How is sensor/target elevations determined? • How are features (vegetation/urban) treated? • How is LOS blocked? (slope or calculated elevation) • Terrain Resolution and its effects on LOS • Lower Resolution – faster, less accurate • Higher Resolution – slower, more accurate • How should the algorithm be implemented? • Which algorithms work best with my hardware? • Precision, Precision, Precision Courtesy Danny Champion, TRAC

  6. Triangular Irregular Network

  7. Line-of-Sight Point-to-Point Masked Area Plot or Viewshed Point-to-Multipoint Current Army Visibility Products Source: Doug Caldwell Topographic Engineering Center

  8. TIREM Propagation Model

  9. A Familiar Curve TRAC WSR LOS Study 1995

  10. A Pathological Example

  11. Real World Example: Falling Performance of CCTT CGF

  12. Why GPU/Streaming ? Source: Anselmo Lastra

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