优化了基于可扩展Myrinet/现场可编程阵列节点的自动目标识别算法

Y.H. Cho
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引用次数: 12

摘要

合成孔径雷达(SAR)图像中的自动目标识别(ATR)通常需要每秒数十亿次操作。本文描述了Myricom开发的一个紧凑的可扩展系统,用于高性能实现桑迪亚国家实验室开发的基于模板的SAR ATR算法。Myricom系统被映射到由Myricom连接的多个并发现场可编程阵列(FPGA)计算节点上。这些FPGA节点通过利用FPGA中ATR算法的独特特性,实现了高效率。本文的贡献在于描述了基于可扩展FPGA节点的ATR系统的体系结构设计。
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Optimized automatic target recognition algorithm on scalable Myrinet/field programmable array nodes
Automatic target recognition (ATR) in synthetic aperture radar (SAR) imagery often requires billions of operations per second. This paper describes a compact scalable system developed at Myricom for high-performance implementation of the template-based SAR ATR algorithms developed by Sandia National Laboratories. The Myricom system is mapped on the multiple concurrent field programmable array (FPGA) computing nodes connected by Myrinet. These FPGA nodes achieve high efficiency, through the exploitation of the unique characteristics of the ATR algorithm in FPGA. The contributions of this paper are the descriptions of the architectural designs for the ATR system on the scalable FPGA nodes.
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