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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/96253

    Title: GPU acceleration of prediction-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: Graphics processing units;Computer programming;Data compression;MATLAB;Matrices
    Date: 2012-10
    Issue Date: 2014-03-06 17:08:33 (UTC+8)
    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.
    DOI: 10.1117/12.931311
    Appears in Collections:[Graduate Institute & Department of Information Management] Proceeding

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