1. GPU-Accelerated Route Planning for Computer Generated Forces
UNC-CH/PEOSTRI/RDECOM/SAIC
Our goals is to use the commodity GPUs for CGF computations (esp. the OneSAF). The goal is to map some of the OneSAF computations onto the GPUs.
Start point
Terrain Features
And Route Segments
Render Features
(Once)
Feature Buffer
(static)
Generated Route
Segments
Full
Feature set
Features
Lake
Cull segment set against
feature set (GPU)
Reduced segments
Features: lakes, rivers,
trees, buildings, etc.
Cull feature set against
segment set (GPU)
River
End point
Reduced features
and segments
Issues Concerning Route Planning for Computer Generated Forces (CGF)
High computational complexity
Widely applicable in simulation development
Can consume 50% of simulation time
Intersection calculations bottleneck route planning
Cull feature set against
Single segment (GPU)
Exact feature/segment
Tests (CPU)
Results
Current Status of Graphics Processing Units (GPUs)
Integral part of modern computers
Performance increases faster than Moore’s Law
Additional computational power to assist CPU
Optimizations
Culling is performed using the GPU’s occlusion query capability.
Each successive step reduces the number of segments and features that are tested in the subsequent steps
Final group tested by the CPU is minimized
Conservatively expand feature and segment sizes to avoid inaccuracy in calculations
input 1 3 2
Overview of GPU-Accelerated Route Planning
Ability to test multiple route segments in parallel
Queries all potential segments faster than individually testing on the CPU
More efficient search of the large planning space
System integrated with OneSAF
Demonstrated 30-50x speedup in feature analysis computation
Demonstrated 10x speed up of route planning in OneSAF on a single CPU-GPU machine
Three Phase GPU-Based Culling Procedure
The number of segments is reduced by culling them against the full feature set
The number of features is reduced by culling them against the reduced set of segments
The reduced feature set is culled against each individual segment in the reduced segment set
Participants
Dinesh Manocha (UNC-CH)
Troy Dere (RDECOM)
Ming C. Lin (UNC-CH)
Angel Rodriguez (RDECOM)
Russel Gayle (UNC-CH)
Marlo Verdesca (SAIC)
David Knott (UNC-CH)
LTC John Surdu (PEOSTRI)
Maria Bauer (RDECOM)
Jaeson Munro (SAIC)
Eric Root (SAIC)