Title :
Ray-Tracing-Based Geospatial Optimization for Heterogeneous Architectures Enhancing Situational Awareness
Author :
Richie, David A. ; Ross, J. Andrew ; Park, S.J. ; Shires, Dale R.
Author_Institution :
Brown Deer Technol., Forest Hill, MD, USA
Abstract :
This paper presents the implementation of ray tracing-based algorithms for multi-objective geospatial optimization targeting various many-core processing technologies such as graphics processing units, x86 multi-cores, and ARM processors. High performance is achieved through highly parallel core algorithms, executed on multiple compute devices across a heterogeneous architecture using low-level OpenCL kernels. Algorithms for calculating line-of-sight ballistic threat, visual observability, ground plane extraction, and Markov chain Monte Carlo optimization provide an augmented geospatial intelligence and situational awareness in three-dimensional urban environments.
Keywords :
Markov processes; Monte Carlo methods; augmented reality; ballistics; geographic information systems; graphics processing units; multiprocessing systems; optimisation; parallel algorithms; parallel architectures; ray tracing; 3D urban environments; Markov chain Monte Carlo optimization; OpenCL kernels; augmented geospatial intelligence; ground plane extraction; heterogeneous architecture; high performance computing; line of sight ballistic threat calculation; manycore processing technology; parallel core algorithm; ray tracing-based multiobjective geospatial optimization; situational awareness; visual observability; Computer architecture; Graphics processing units; Kernel; Observability; Optimization; Ray tracing; Surveillance; GPGPU; geospatial optimization; heterogeneous systems; line-of-sight; parallel computing;
Conference_Titel :
Computational Science and Engineering (CSE), 2013 IEEE 16th International Conference on
Conference_Location :
Sydney, NSW
DOI :
10.1109/CSE.2013.22