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6/25/2015 1 MRM Computational Challenges for Modeling and Simulation Michael Macedonia Chief Technology Officer, US Army Program Executive Office for Simulation,

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Presentation on theme: "6/25/2015 1 MRM Computational Challenges for Modeling and Simulation Michael Macedonia Chief Technology Officer, US Army Program Executive Office for Simulation,"— Presentation transcript:

1 6/25/2015 1 MRM Computational Challenges for Modeling and Simulation Michael Macedonia Chief Technology Officer, US Army Program Executive Office for Simulation, Training and Instrumentation ( PEO STRI)

2 6/25/2015 2 MRM 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 6/25/2015 3 MRM Real-time Terrain Algorithms for Computer Generated Forces Best algorithms are O(N 2 ) 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

4 6/25/2015 4 MRM 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 6/25/2015 5 MRM 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 Algorithm Considerations Courtesy Danny Champion, TRAC

6 6/25/2015 6 MRM Triangular Irregular Network

7 6/25/2015 7 MRM Current Army Visibility Products Line-of-Sight Point-to-Point Masked Area Plot or Viewshed Point-to-Multipoint Source: Doug Caldwell Topographic Engineering Center

8 6/25/2015 8 MRM TIREM Propagation Model

9 6/25/2015 9 MRM A Familiar Curve TRAC WSR LOS Study 1995

10 6/25/2015 10 MRM A Pathological Example

11 6/25/2015 11 MRM Real World Example: Falling Performance of CCTT CGF

12 6/25/2015 12 MRM Why GPU/Streaming ? Source: Anselmo Lastra


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