基于现场可编程门阵列(fpga)的合成孔径雷达(SAR)算法加速研究

Youngsoo Kim, William Harding, C. Gloster, W. Alexander
{"title":"基于现场可编程门阵列(fpga)的合成孔径雷达(SAR)算法加速研究","authors":"Youngsoo Kim, William Harding, C. Gloster, W. Alexander","doi":"10.1145/2684746.2689125","DOIUrl":null,"url":null,"abstract":"Algorithms for radar signal processing, such as Synthetic Aperture Radar (SAR) are computationally intensive and require considerable execution time on a general purpose processor. Reconfigurable logic can be used to off-load the primary computational kernel onto a custom computing machine in order to reduce execution time by an order of magnitude as compared to kernel execution on a general purpose processor. Specifically, Field Programmable Gate Arrays (FPGAs) can be used to house hardware-based custom implementations of these kernels to speed up these applications. In this paper, we demonstrate a methodology for algorithm acceleration. We used SAR as a case study to illustrate the tremendous potential for algorithm acceleration offered by FPGAs. Initially, we profiled the SAR algorithm and implemented a homomorphic filter using a hardware implementation of the natural logarithm. Experimental results show an average speed-up of 188 when using the FPGA-based hardware accelerator as opposed to using a software implementation running on a typical general purpose processor.","PeriodicalId":388546,"journal":{"name":"Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Acceleration of Synthetic Aperture Radar (SAR) Algorithms using Field Programmable Gate Arrays (FPGAs) (Abstract Only)\",\"authors\":\"Youngsoo Kim, William Harding, C. Gloster, W. Alexander\",\"doi\":\"10.1145/2684746.2689125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Algorithms for radar signal processing, such as Synthetic Aperture Radar (SAR) are computationally intensive and require considerable execution time on a general purpose processor. Reconfigurable logic can be used to off-load the primary computational kernel onto a custom computing machine in order to reduce execution time by an order of magnitude as compared to kernel execution on a general purpose processor. Specifically, Field Programmable Gate Arrays (FPGAs) can be used to house hardware-based custom implementations of these kernels to speed up these applications. In this paper, we demonstrate a methodology for algorithm acceleration. We used SAR as a case study to illustrate the tremendous potential for algorithm acceleration offered by FPGAs. Initially, we profiled the SAR algorithm and implemented a homomorphic filter using a hardware implementation of the natural logarithm. Experimental results show an average speed-up of 188 when using the FPGA-based hardware accelerator as opposed to using a software implementation running on a typical general purpose processor.\",\"PeriodicalId\":388546,\"journal\":{\"name\":\"Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2684746.2689125\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2684746.2689125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

雷达信号处理算法,如合成孔径雷达(SAR)是计算密集型的,需要在通用处理器上执行相当长的时间。可重构逻辑可用于将主计算内核卸载到自定义计算机器上,以便与在通用处理器上执行内核相比,将执行时间减少一个数量级。具体来说,现场可编程门阵列(fpga)可用于容纳这些内核的基于硬件的自定义实现,以加速这些应用程序。在本文中,我们展示了一种算法加速的方法。我们使用SAR作为案例研究来说明fpga提供的算法加速的巨大潜力。首先,我们分析了SAR算法,并使用自然对数的硬件实现实现了一个同态滤波器。实验结果表明,当使用基于fpga的硬件加速器时,与使用运行在典型通用处理器上的软件实现相比,平均速度提高了188。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acceleration of Synthetic Aperture Radar (SAR) Algorithms using Field Programmable Gate Arrays (FPGAs) (Abstract Only)
Algorithms for radar signal processing, such as Synthetic Aperture Radar (SAR) are computationally intensive and require considerable execution time on a general purpose processor. Reconfigurable logic can be used to off-load the primary computational kernel onto a custom computing machine in order to reduce execution time by an order of magnitude as compared to kernel execution on a general purpose processor. Specifically, Field Programmable Gate Arrays (FPGAs) can be used to house hardware-based custom implementations of these kernels to speed up these applications. In this paper, we demonstrate a methodology for algorithm acceleration. We used SAR as a case study to illustrate the tremendous potential for algorithm acceleration offered by FPGAs. Initially, we profiled the SAR algorithm and implemented a homomorphic filter using a hardware implementation of the natural logarithm. Experimental results show an average speed-up of 188 when using the FPGA-based hardware accelerator as opposed to using a software implementation running on a typical general purpose processor.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信