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Erschienen in:
2001 | OriginalPaper | Buchkapitel
Jacobi-Davidson Algorithm with Fast Matrix-Vector Multiplikation on Massively Parallel and Vector Supercomputers
verfasst von : M. Kinateder, G. Wellein, A. Basermann, H. Fehske
Erschienen in: High Performance Computing in Science and Engineering 2000
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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The exact diagonalization of very large sparse matrices is a numerical problem common to various fields in science and engineering. We present an advanced eigenvalue alorithm - the so-called Jacobi-Davidson algorithm - in combination with an efficient parallel matrix-vector multiplication. This implementation allows the calculation of several specified eigenvalues with high accuracy on modern supercomputers, such as CRAY T3E and NEC SX-4. Exemplarily the numerical technique is applied to analyze the ground state and spectral properties of the three-quarter filled Peierls-Hubbard Hamiltonian in relation to recent resonant Raman experiments on MX chain [-PtCl-] complexes.