• DocumentCode
    3181621
  • Title

    CUDA-Based Jacobi´s Iterative Method

  • Author

    Zhang, Zhihui ; Miao, Qinghai ; Wang, Ying

  • Author_Institution
    Coll. of Comput. & Commun. Eng., Grad. Univ. of Chinese Acad. of Sci. (GUCAS), Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    25-27 Dec. 2009
  • Firstpage
    259
  • Lastpage
    262
  • Abstract
    Solving linear equations is a common problem in the fields of science and engineering. Accelerating its solving process is of great significance. Modern GPUs are high performance many-core processors fit for large scale parallel computing. They provide us a novel way for accelerating the solving process. A GPU based parallel Jacobi´s iterative solver for dense linear equations is presented in this paper. First, we introduce the backgrounds for accelerating solving linear equations together with GPUs and the corresponding parallel platform CUDA on it. Then we implement Jacobi´s iterative method on CUDA. Finally, we compare the experimental results of CUDA programs on GPU with traditional programs on CPU. Experiments show that it obtains a speedup of approximately 59 times with single floating point at a low precision, 19 times with double at a high precision.
  • Keywords
    Jacobian matrices; coprocessors; iterative methods; linear algebra; parallel architectures; Jacobi iterative method; compute unified device architecture; dense linear equations; graphic processing unit; many-core processors; parallel computing; Acceleration; Computer architecture; Equations; Frequency; High performance computing; Iterative methods; Jacobian matrices; Large-scale systems; Parallel processing; Programming profession; CUDA; GPU; Jacobi´s iterative method; dense linear equations; precision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-0-7695-3930-0
  • Electronic_ISBN
    978-1-4244-5423-5
  • Type

    conf

  • DOI
    10.1109/IFCSTA.2009.68
  • Filename
    5385084