A case study of OpenCL-based parallel programming for low-power remote sensing applications

A. C. Angulo, R. Carrasco-Alvarez, Jaime Ortegón-Aguilar, J. V. Castillo, O. Marrufo, A. Atoche
{"title":"A case study of OpenCL-based parallel programming for low-power remote sensing applications","authors":"A. C. Angulo, R. Carrasco-Alvarez, Jaime Ortegón-Aguilar, J. V. Castillo, O. Marrufo, A. Atoche","doi":"10.1109/ICEEE.2015.7357959","DOIUrl":null,"url":null,"abstract":"With the advent of high-performance embedded computing (HPEC) systems, many digital processing algorithms are now implemented by special-purpose massively parallel processors. In this paper, a low-power ARM/GPU co-design architecture is addressed using OpenCL-based parallel programming for implementing complex reconstructive signal processing operations. Such operations are accelerated using data-parallel functions on the GPU and ARM processor, in a HW/SW co-design scheme via OpenCL API calls. Experimental results shows the achieved computational performance and the effectiveness of the OpenCL standard comparing the framework against traditional parallel embedded versions.","PeriodicalId":285783,"journal":{"name":"2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE.2015.7357959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

With the advent of high-performance embedded computing (HPEC) systems, many digital processing algorithms are now implemented by special-purpose massively parallel processors. In this paper, a low-power ARM/GPU co-design architecture is addressed using OpenCL-based parallel programming for implementing complex reconstructive signal processing operations. Such operations are accelerated using data-parallel functions on the GPU and ARM processor, in a HW/SW co-design scheme via OpenCL API calls. Experimental results shows the achieved computational performance and the effectiveness of the OpenCL standard comparing the framework against traditional parallel embedded versions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于opencl的低功耗遥感应用并行编程案例研究
随着高性能嵌入式计算(HPEC)系统的出现,许多数字处理算法现在都是由专用的大规模并行处理器实现的。本文采用基于opencl的并行编程实现了一种低功耗ARM/GPU协同设计架构,以实现复杂的重构信号处理操作。这些操作使用GPU和ARM处理器上的数据并行功能加速,在硬件/软件协同设计方案中通过OpenCL API调用。实验结果表明,与传统的并行嵌入式版本相比,该框架具有较高的计算性能和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Embedded system for real-time person detecting in infrared images/videos using super-resolution and Haar-like feature techniques A novel tire contact patch soft sensor via Neural Networks Technical feasibility of a 400 Gb/s unamplified WDM coherent transmission system for ethernet over 40 km of single-mode fiber Novel PCB fabrication process roughness free for high frequency applications. On the PD+Luenberger controller/observer for the trajectory tracking of Robot Manipulators
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1