Entry Natvig:1986:ECC from jcomputapplmath1980.bib

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BibTeX entry

@Article{Natvig:1986:ECC,
  author =       "J. Natvig and B. Nour-Omid and B. N. Parlett",
  title =        "Effect of the {CYBER 205} on the choice of method for
                 solving the eigenvalue problem {$ (A - \lambda M) x = 0
                 $}",
  journal =      j-J-COMPUT-APPL-MATH,
  volume =       "15",
  number =       "2",
  pages =        "137--159",
  month =        jun,
  year =         "1986",
  CODEN =        "JCAMDI",
  DOI =          "https://doi.org/10.1016/0377-0427(86)90023-3",
  ISSN =         "0377-0427 (print), 1879-1778 (electronic)",
  ISSN-L =       "0377-0427",
  bibdate =      "Sat Feb 25 11:59:56 MST 2017",
  bibsource =    "http://www.math.utah.edu/pub/bibnet/authors/p/parlett-beresford-n.bib;
                 http://www.math.utah.edu/pub/tex/bib/jcomputapplmath1980.bib",
  URL =          "http://www.sciencedirect.com/science/article/pii/0377042786900233",
  ZMnumber =     "0635.65032",
  abstract =     "For the eigenvalue problem {$ A x = \lambda M x $},
                 {$A$}, {$B$} large, sparse, symmetric matrices, two
                 methods, subspace iteration and Lanczos method, are
                 compared when running on typical examples from
                 structural dynamic analysis (order of {$A$}, {$B$} up
                 to 8000) on a Cyber 205. A fixed number of eigenpairs
                 is calculated. As on serial computers it turns out on
                 this vector computer that the Lanczos algorithm is
                 considerably faster. However, on problems with
                 substantial overhead in reading\slash writing, a block
                 Lanczos method is preferable.",
  acknowledgement = ack-nhfb,
  classmath =    "*65F15 Eigenvalues (numerical linear algebra) 65F50
                 Sparse matrices",
  fjournal =     "Journal of Computational and Applied Mathematics",
  journal-URL =  "http://www.sciencedirect.com/science/journal/03770427",
  keywords =     "comparison of methods; eigenvalue problem; Lanczos
                 method; large, sparse, symmetric matrices; subspace
                 iteration; vector computer; vectorization",
  reviewer =     "L. Elsner",
}

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