Computational Challenges for Modeling and Simulation

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Computational Challenges for Modeling and
Simulation

• Michael Macedonia
• Chief Technology Officer, US Army Program
  Executive Office for Simulation, Training and
  Instrumentation ( PEO STRI)

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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
Moores law are not enough to achieve capability
in this decade.
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Real-time Terrain Algorithms for Computer
Generated Forces

• 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

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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
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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
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Triangular Irregular Network
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Current Army Visibility Products
Source Doug Caldwell Topographic Engineering
Center
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TIREM Propagation Model
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A Familiar Curve
TRAC WSR LOS Study 1995
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A Pathological Example
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Real World Example Falling Performance of CCTT
CGF
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Why GPU/Streaming ?
Source Anselmo Lastra