GPGPU Accelerated Fast Convolution Back-Projection for Radar Image Reconstruction

IF 5.2 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Bin Zhou (周 斌), Yingning Peng (彭应宁), Chunmao Yeh (叶春茂), Jun Tang (汤 俊)
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引用次数: 2

Abstract

This paper describes a parallel fast convolution back-projection algorithm design for radar image reconstruction. State-of-the-art general purpose graphic processing units (GPGPU) were utilized to accelerate the processing. The implementation achieves much better performance than conventional processing systems, with a speedup of more than 890 times on NVIDIA Tesla C1060 supercomputing cards compared to an Intel P4 2.4 GHz CPU. 256×256 pixel images could be reconstructed within 6.3 s, which makes real-time imaging possible. Six platforms were tested and compared. The results show that the GPGPU super-computing system has great potential for radar image processing.

GPGPU加速的快速卷积反投影雷达图像重建
本文描述了一种用于雷达图像重建的并行快速卷积反投影算法设计。利用最先进的通用图形处理单元(GPGPU)来加速处理。该实现比传统处理系统实现了更好的性能,与英特尔P4 2.4 GHz CPU相比,NVIDIA特斯拉C1060超级计算卡的速度提高了890倍以上。256×256像素的图像可以在6.3s内重建,这使得实时成像成为可能。对六个平台进行了测试和比较。结果表明,GPGPU超级计算系统在雷达图像处理方面具有巨大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
12.10
自引率
0.00%
发文量
2340
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