JOURNAL OF LIGHT INDUSTRY

CN 41-1437/TS  ISSN 2096-1553

Volume 34 Issue 2
March 2019
Article Contents
LIU Huihui, WEN Mengsha, QIAN Shenyi, et al. Research on parallelization of Clean algorithm in ARL[J]. Journal of Light Industry, 2019, 34(2): 88-94. doi: 10.3969/j.issn.2096-1553.2019.02.012
Citation: LIU Huihui, WEN Mengsha, QIAN Shenyi, et al. Research on parallelization of Clean algorithm in ARL[J]. Journal of Light Industry, 2019, 34(2): 88-94. doi: 10.3969/j.issn.2096-1553.2019.02.012 shu

Research on parallelization of Clean algorithm in ARL

  • Received Date: 2018-12-13
  • The deconvolution algorithm in the ARL of the SKA algorithm reference library is inefficient and cannot meet the needs of real-time processing of massive data. The parallelized Clean algorithm in the cooperative working mode of CPU and GPU was proposed. The steps of parallel computing in Clean algorithm were executed in parallel on GPU using multi-threads, and the steps in the Clean algorithm that couldn't be parallelized were executed serially on the CPU. The results showed that the running time of parallel Clean algorithm under CPU and GPU cooperative mode was significantly shorter than that under CPU. When the image size reached 4096×4096, the parallel Clean algorithm GPU cooperative mode could be speeded up by 10 times, which showed that the parallel Clean algorithm could significantly improve the efficiency of operation when dealing with massive data.
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