Parallel compressive sampling matching pursuit algorithm for compressed sensing signal reconstruction with OpenCL

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• 作者：Fang Huang^a ; ^b ; ^cAuthor Vitae ; Jian Tao^cAuthor Vitae ; Yang Xiang^dAuthor Vitae ; Peng Liu^fAuthor Vitae ; Lei Dong^aAuthor Vitae ; Lizhe Wang ; ^e ; ^f ; ^{lizhe.wang@gmail.com} ; ^{Lizhe.Wang@computer.org}Author Vitae
• 关键词：Compressive sensing ; CoSaMP ; Heterogeneous computing ; Many-core computing ; OpenCL
• 刊名：Journal of Systems Architecture
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：72
• 期：Complete
• 页码：51-60
• 全文大小：1296 K
• 卷排序：72

文摘

Using the newly computing technology to solve the computing intensive problem in Geo-sciences area. Using OpenCL, the developed parallel algorithm has the capability that can run on different heterogeneous computing platforms, either the NVIDA or AMD GPU-based platform; Using CUDA to develop is not has such crossing-platform capability. In Geo-sciences area, according to our knowledge, there is almost no research that using heterogeneous computing technology to solve the such problem. This work should be helpful to the researchers in this field.