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Proceedings Paper

Efficient eigenvalue computation on the Maspar
Author(s): Yan Huo; Robert Schreiber
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Paper Abstract

Many applications of the eigenvalue decomposition of dense matrices are well known. This work was prompted by research in the numerical simulation of disordered electronic systems, in which one of the most common approaches is to diagonalize random Hamiltonian matrices in order to study the eigenvalues and eigenfunctions of a single electron in the presence of a random potential. In this paper, we describe an effort to implement a matrix diagonalization routine for real symmetric dense matrices on massively parallel SIMD computers, the Maspar MP-1 and MP-2 systems. Results of numerical tests and timings are also presented.

Paper Details

Date Published: 1 November 1993
PDF: 10 pages
Proc. SPIE 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV, (1 November 1993); doi: 10.1117/12.160461
Show Author Affiliations
Yan Huo, Princeton Univ. (United States)
Robert Schreiber, NASA Ames Research Ctr. (United States)


Published in SPIE Proceedings Vol. 2027:
Advanced Signal Processing Algorithms, Architectures, and Implementations IV
Franklin T. Luk, Editor(s)

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