GPU-Accelerated High-Bandwidth Radar Centroiding

D. Brigada, Maximilian Merfeld, Kara Warner
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Abstract

Radar signal processing is a computationally inten-sive task, especially for high-bandwidth systems. Traditionally, such systems have relied on the interleaving of processing on multiple nodes of large compute clusters to achieve the necessary throughput. Development in general-purpose GPU computing has led to a massive increase in the computational power available to highly parallel tasks. Most parts of the radar signal processing pipeline are well suited for such a task. This paper describes an algorithm for centroiding, a key part of the search radar pipeline that has not yet been demonstrated on a GPU. With this centroiding algorithm, the entire high-data-rate portion of the processing pipeline can be run on the GPU, yielding a speedup factor of approximately 40. The primary benefit of this approach is a massive reduction in data copying from the GPU to the CPU-a factor of over 1200 in this case-alleviating the main barrier to G PU - based radar processing systems.
gpu加速高带宽雷达质心
雷达信号处理是一项计算密集型的任务,特别是对于高带宽系统。传统上,这类系统依赖于在大型计算集群的多个节点上交叉处理以实现必要的吞吐量。通用GPU计算的发展导致了高度并行任务的计算能力的大幅提高。雷达信号处理管道的大部分都很适合这样的任务。本文描述了一种中心化算法,这是搜索雷达流水线的关键部分,尚未在GPU上进行演示。使用这种中心化算法,处理管道的整个高数据速率部分可以在GPU上运行,产生大约40倍的加速因子。这种方法的主要好处是大量减少了从GPU到cpu的数据复制——在这种情况下超过1200倍,减轻了基于GPU的雷达处理系统的主要障碍。
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