Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (4): 25-29.doi: 10.11896/jsjkx.190500029

• Computer Architecture • Previous Articles     Next Articles

Extraction Algorithm of NDVI Based on GPU Multi-stream Parallel Model

ZUO Xian-yu1,2, ZHANG Zhe1,3, SU Yue-han1, LIU Yang1,2, GE Qiang1,2, TIAN Jun-feng1,2   

  1. 1 Institute of Data and Knowledge Engineering,College of Computer and Information Engineering,Henan University,Kaifeng,Henan 475004,China;
    2 Henan Key Laboratory of Big Data Analysis and Processing,Henan University,Kaifeng,Henan 475004,China;
    3 Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China
  • Received:2019-05-06 Online:2020-04-15 Published:2020-04-15
  • Contact: TIAN Jun-feng,born in 1980,Ph.D,lecturer.His main research interests include remote sensing image proces-sing and image encryption.
  • About author:ZUO Xian-yu,born in 1979,Ph.D,associate professor.His research interests include parallel computing and remote sensing image processing.
  • Supported by:
    This work was supported by the National Key Research and Development Program (2017YFD0301105),National Natural Science Foundation of China(U1704122,U1604145) and Key R&D and Promotion Projects of Henan Province (182102210242,182102110065,192102210096).

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Abstract: In general,the Normalized Differential Vegetation Index (NDVI) extraction algorithm optimized by GPU usually adopts GPU multi-thread parallel model,and there are problems such as data transmission between CPU and GPU and weak correlation calculations taking more time,which affect the further improvement of performance.Aiming at the above problems and the characteristics of NDVI,a NDVI extraction algorithm based on GPU multi-stream parallel model was proposed.Through the features of CUDA stream and Hyper-Q,the GPU multi-stream parallel model can overlap not only data transmission and kernel execution,but also kernel execution and kernel execution,and further improve parallelism and resources utilization of GPU.Firstly,the NDVI algorithm is optimized by the GPU multi-thread parallel model,and the optimized procedures are decomposed to find out the parts of the algorithm with data transmission or weak correlation calculation.Secondly,parts of data transmission and weak correlation calculation are reconstructed and optimized by GPU multi-stream parallel model to achieve overlapping between weak correlation calculation and weak correlation calculation,or weak correlation calculation and data transmission.Finally,expe-riments of NDVI algorithm that based on both GPU parallel models respectively were carried out,and the remote sensing image taken by the GF1 satellite were used as experimental data.The experimental results show that the proposed algorithm,when the image is larger than 12000x13400 pixels,achieves about 1.5 times acceleration compared with the traditional parallel NDVI algorithm based on the GPU multi-thread parallel model,and about 260 times acceleration compared with the NDVI sequential extraction algorithm,which has better performance and parallelism.

Key words: GPU parallel model, NDVI, Overlap, Parallel acceleration, Remote sensing information extraction

CLC Number: 

  • TP751
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