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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/80754

    Title: Accelerating Volkov's Hybrid Implementation of Cholesky Factorization on a Fermi GPU
    Authors: Wei, Shih-chieh;Huang, Bormin
    Contributors: 淡江大學資訊管理學系
    Keywords: parallel computing;Cholesky factorization;general purpose graphics processing unit
    Date: 2012-12
    Issue Date: 2013-03-04 16:32:16 (UTC+8)
    Publisher: Singapore: Nanyang Tenhnological University
    Abstract: In linear algebra, Cholesky factorization is useful in solving a system of equations with a symmetric positive definite coefficient matrix. Cholesky factorization is roughly twice as fast relative to LU factorization which applies to general matrices. In recent years, with advances in technology, a Fermi GPU card can accommodate hundreds of cores compared to the small number of 8 or 16 cores on CPU. Therefore a trend is seen to use the graphics card as a general purpose graphics processing unit (GPGPU) for parallel computation. In this work, Volkov's hybrid implementation of Cholesky factorization is evaluated on the new Fermi GPU with others and then some improvement strategies were proposed. After experiments, compared to the CPU version using Intel Math Kernel Library (MKL), our proposed GPU improvement strategy can achieve a speedup of 3.85x on Cholesky factorization of a square matrix of dimension 10,000.
    Relation: Proceeding of 2012 IEEE 18th International Conference on Parallel and Distributed Systems, pp.896-900
    DOI: 10.1109/ICPADS.2012.147
    Appears in Collections:[Graduate Institute & Department of Information Management] Chapter

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