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)