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Solving the symmetric tridiagonal eigenvalue problem on the hypercube

Journal Article · · SIAM Journal on Scientific and Statistical Computing (Society for Industrial and Applied Mathematics); (USA)
DOI:https://doi.org/10.1137/0911013· OSTI ID:6502729
;  [1]
  1. Dept. of Computer Science, Yale Univ., New Haven, CT (US)
This paper describes implementations of Cuppen's method, bisection, and multisection for the computation of all eigenvalues and eigenvectors of a real symmetric tridiagonal matrix on a distributed-memory hypercube multiprocessor. Numerical results and timings for Intel's iPSC-1 are presented. Cuppen's method is found to be the numerically most accurate of three methods, while bisection with inverse iteration is observed experimentally to be the fastest method.
OSTI ID:
6502729
Journal Information:
SIAM Journal on Scientific and Statistical Computing (Society for Industrial and Applied Mathematics); (USA), Journal Name: SIAM Journal on Scientific and Statistical Computing (Society for Industrial and Applied Mathematics); (USA) Vol. 11:2; ISSN 0196-5204; ISSN SIJCD
Country of Publication:
United States
Language:
English