High-fidelity Real-time Antiship Cruise Missile Modeling on the GPU

被引:0
|
作者
Scannell, Christopher [1 ]
Decker, Jonathan [1 ]
Collins, Joseph [1 ]
Smith, William [2 ]
机构
[1] Naval Res Lab, Washington, DC 20375 USA
[2] ITT Informat Syst, Mclean, VA USA
关键词
GPU; OpenCL; antiship; cruise; missile;
D O I
10.3233/978-1-61499-041-3-175
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The United States Navy is actively researching techniques for creating high-fidelity, real-time simulations of antiship cruise missiles (ASCM) in order to develop improved defensive countermeasures for Navy ships. One active area of investigation is the combined use of OpenMP and MPI to reach real-time constraints on stand-alone cluster computers with high-speed interconnect fabrics. The separate nodes of this high performance computing (HPC) platform calculate the successive responses of a single cruise missile to successive reflections of the RF transmitter radar returns from the target ship in a pipeline fashion using MPI. Numerically intensive portions of the calculation of the missile-ship system behavior for an individual RF pulse can be calculated in parallel on the individual nodes of the HPC platform using OpenMP. The speed at which these portions can be calculated determines the length of the pipeline and thus the total number of computing nodes required. This approach incurs some approximations into the simulation that are proportional to the length of the pipeline because there is a feedback from the ship-radar response back to the missile guidance. While this use of OpenMP has proven effective, it is limited by the number of cores available at each node. This code, however, presents opportunities for parallelism well beyond the available computational resources at each node. Additionally, the ratio of computation to data transfer for this portion of the simulation is very high. These two factors have led us to investigate executing the most compute-intensive portion, the calculation of the RF responses of the individual ship scatterers, on Graphics Processing Units (GPUs).
引用
收藏
页码:175 / 182
页数:8
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