Evaluating graphical processing units for clutter model calculation in a simulation facility

B. Daniel, J. Meredith, J. Sumner, B. Vacaliuc, J. Ellenburg
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Abstract

Graphics processing units (GPUs) are being fused together with the traditional central processing units (CPUs) to form accelerated processing units (APUs). These hybrid computing machines provide a viable alternative to traditional processors for high-performance computing systems thanks to substantial computational performance and advanced programmability. A team at Oak Ridge National Laboratory experienced with radar clutter modeling and simulation, and with computation using a variety of processors, has explored the viability of GPUs for accelerating clutter simulation for the Joint Research Analysis and Assessment Center at the Missile and Space Intelligence Center. The results show substantial performance gains of approximately 20× relative to a CPU-only algorithm. We show a number of ways these accelerated clutter calculations provide real-time results starting from readily extended simulation models.
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评估仿真设备中杂波模型计算的图形处理单元
图形处理单元(gpu)正与传统的中央处理单元(cpu)融合,形成加速处理单元(apu)。由于具有可观的计算性能和先进的可编程性,这些混合计算机器为高性能计算系统提供了传统处理器的可行替代方案。橡树岭国家实验室的一个团队在雷达杂波建模和仿真方面经验丰富,并使用各种处理器进行计算,已经探索了gpu加速导弹和空间情报中心联合研究分析和评估中心杂波仿真的可行性。结果显示,相对于仅使用cpu的算法,性能提升了大约20倍。我们展示了这些加速杂波计算从易于扩展的仿真模型开始提供实时结果的许多方法。
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