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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/80744


    Title: GPU acceleration of predictiion-based lower triangular transform for lossless compression
    Authors: Wei, Shih-chieh;Huang, Bormin
    Contributors: 淡江大學資訊管理學系
    Keywords: Computer programming;Data compression;Graphics processing units;MATLAB;Matrices
    Date: 2012-10-16
    Issue Date: 2013-03-04 13:49:47 (UTC+8)
    Publisher: Bellingham, Washington: Society of Photo-Optical Instrumentation Engineers (SPIE)
    Abstract: The prediction-based lower triangular transform (PLT) features the same de-correlation and coding gain properties as the Karhunen-Loeve transform (KLT), but with a lower design and implementational cost. Unlike KLT, PLT has the perfect reconstruction property which allows its direct use for lossless compression. Our previous work has shown that PLT is good for lossless compression of ultraspectral sounder data with several thousands of channels. As the computation involves many operations on large matrices, this work will exploit the parallel compute power of graphics processing unit (GPU) to speed up the PLT encoding scheme. The CUDA (Compute Unified Device Architecture) platform by NVidia will be used for comparison with a single threaded CPU core. The experimental result reveals that our GPU implementation of the PLT encoding scheme shows a speedup of 95x compared to its original Matlab implementation on CPU. Thus it is promising to apply the GPU-based PLT encoding scheme for ultraspectral sounder data compression.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
    Relation: Proceedings of SPIE 8514 (Satellite Data Compression, Communications, and Processing VIII), 851404
    DOI: 10.1117/12.931311
    Appears in Collections:[資訊管理學系暨研究所] 專書之單篇

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