A parallel algorithm for computing the extremal eigenvalues of very large sparse matrices

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1541, Issue , 1998, Pages 332-336

  Manne, Fredrik ^a  

^a UNIVERSITY OF BERGEN   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

EIGENVALUES AND EIGENFUNCTIONS; PARALLEL ALGORITHMS; QUANTUM THEORY;

EIGENVALUES; EXTREMAL; GRAPH COLORINGS; MAIN MEMORY; ON THE FLIES; SPARSE MATRICES;

MATRIX ALGEBRA;

EID: 84947930854     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/bfb0095354     Document Type: Conference Paper

References (8)

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3. G. H. GOLUB and C. F. V. LOAN, Matrix Computations, North Oxford Academic, 2 ed., 1989.
4. R. B. LEHOUCQ, D. SORENSEN, and P. VU, ARPACK: An implementation of the implicitly re-started Arnoldi iteration that computes some of the eigenvaIues and eigenvectors of a large sparse matrix. Available from netlib@ornl.gov under the directory scalapack, 1996.
5. I. RØEGGEN. Private communications.
6. A. RUHE, SOR-methods for the eigenvalue problem with large sparse matrices, Math. Comp., 28 (1974), pp. 695-710.
7. H R Schwarz, The method of coordinate overrelaxation for (A-ʎB)x = O, Numer. Math., (1974), pp. 135-151.
8. I. SHAVITT, C. F. BENDER, A. PIPANO, and R. P. HOSTENY, The iterative calculation of several of the lowest or highest eigenvalues and corresponding eigenvectots of very large symmetric matrices, Journal of Computational Physics, (1973), pp. 90-108.