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On the Parallel Technologies of Conjugate and Semi-conjugate Gradient Methods for Solving Very Large Sparse SLAEs

  • Valery P. Ilin
  • Dasha V. Knysh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4671)

Abstract

The parallel technologies of iterative solving the symmetric and nonsymmetric systems of linear algebraic equations (SLAEs) with very large sparse matrices by means of conjugate and semi-conjugate gradient iterative methods are described. The performance computing for various matrix formats (diagonal, compressed sparse row/column), at the different degrees of freedom of SLAEs, are analysed. The results of experimental measurements under OPENMP, MPI and hybrid systems are presented and discussed.

Keywords

Krylov Subspace Conjugate Gradient Algorithm Incomplete Factorization Parallel Technology Domain Decomposition Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Valery P. Ilin
    • 1
    • 2
  • Dasha V. Knysh
    • 1
    • 2
  1. 1.Head of Laboratory, Institute of Computational, Mathematics and Mathematical Geophysics, SBRAS, Novosibirsk, Lavrentiev ave.,6, (383) 330-60-62 
  2. 2.PhD student, Novosibirsk State University, Novosibirsk, Pirogova str, 2, 8-913-754-56-15 

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