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信息与电子科学

基于CUDA的阈值迭代算法并行实现

  • 耿旻明 ,
  • 蒋成龙 ,
  • 张冰尘
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  • 1. 中国科学院电子学研究所微波成像技术重点实验室, 北京 100190;
    2. 中国科学院大学, 北京 100190

收稿日期: 2012-06-15

  修回日期: 2013-01-21

  网络出版日期: 2013-09-15

基金资助

国家973计划项目(2010CB731905)资助 

Parallel implementation of iterative shrinkage-thresholding algorithm via CUDA

  • GENG Min-Ming ,
  • JIANG Cheng-Long ,
  • ZHANG Bing-Chen
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  • 1. National Key Laboratory of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
    2. University of Chinese Academy of Sciences, Beijing 100190, China

Received date: 2012-06-15

  Revised date: 2013-01-21

  Online published: 2013-09-15

摘要

利用CUDA编程在GPU平台设计并行实现阈值的迭代算法,并应用于稀疏微波成像. 仿真实验结果表明,在正确重建信号的前提下,相对于常规的CPU串行计算,采用GPU并行处理能加快运算,提高成像速度.

本文引用格式

耿旻明 , 蒋成龙 , 张冰尘 . 基于CUDA的阈值迭代算法并行实现[J]. 中国科学院大学学报, 2013 , 30(5) : 676 -681 . DOI: 10.7523/j.issn.2095-6134.2013.05.016

Abstract

We design and implement iterative shrinkage-thresholding algorithm (ISTA) on GPU via CUDA programming, and apply it in sparse microwave imaging. The simulation results show that, compared to CPU-based implementation, GPU-based implementation reconstructs correct signals at a faster computation speed.

参考文献

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