Eigenvalue spectrum estimation and photonic crystals
Eigenvalue spectrum estimation and photonic crystals
We have developed an algorithm for the estimation of eigenvalue spectra and have applied it to the determination of the density of states in a photonic crystal, which requires the repeated solution of a generalized eigenvalue problem. We demonstrate that the algorithm offers significant advantages in time, memory, and ease of parallelization over conventional subspace iteration algorithms. In particular it is possible to obtain more than two orders of magnitude speedup in time over subspace methods for modestly sized matrices. For larger matrices the savings are even greater, whilst retaining accurate resolution of features of the eigenspectrum
3-540-42495-4
578-586
Thomas, Ken S.
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Cox, Simon J.
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Beckett, Duan H.
86258cac-ad97-4a21-8de0-53216c0ee810
Hiett, Ben P.
55456bde-e9b3-446b-8ffa-2ceb3b79aa12
Generowicz, Jasek
20027c65-17e0-49b3-97d4-a7980db66970
Daniell, Geoffrey J.
82c59eea-5002-4889-8823-2c6e5b3288d3
August 2001
Thomas, Ken S.
b107015f-c7d9-42cc-b87b-207c49e5369a
Cox, Simon J.
0e62aaed-24ad-4a74-b996-f606e40e5c55
Beckett, Duan H.
86258cac-ad97-4a21-8de0-53216c0ee810
Hiett, Ben P.
55456bde-e9b3-446b-8ffa-2ceb3b79aa12
Generowicz, Jasek
20027c65-17e0-49b3-97d4-a7980db66970
Daniell, Geoffrey J.
82c59eea-5002-4889-8823-2c6e5b3288d3
Thomas, Ken S., Cox, Simon J., Beckett, Duan H., Hiett, Ben P., Generowicz, Jasek and Daniell, Geoffrey J.
(2001)
Eigenvalue spectrum estimation and photonic crystals.
In,
Euro-Par 2001: Parallel Processing: 7th International Euro-Par Conference.
(Lecture Notes in Computer Science, 2150)
7th International Euro-Par Conference: Euro-Par 2001 (28/08/01 - 31/08/01)
Berlin, Germany.
Springer, .
Record type:
Book Section
Abstract
We have developed an algorithm for the estimation of eigenvalue spectra and have applied it to the determination of the density of states in a photonic crystal, which requires the repeated solution of a generalized eigenvalue problem. We demonstrate that the algorithm offers significant advantages in time, memory, and ease of parallelization over conventional subspace iteration algorithms. In particular it is possible to obtain more than two orders of magnitude speedup in time over subspace methods for modestly sized matrices. For larger matrices the savings are even greater, whilst retaining accurate resolution of features of the eigenspectrum
More information
Published date: August 2001
Additional Information:
Series ISSN 0302-9743
Venue - Dates:
7th International Euro-Par Conference: Euro-Par 2001, Manchester, UK, Manchester, United Kingdom, 2001-08-28 - 2001-08-31
Organisations:
Electronic & Software Systems
Identifiers
Local EPrints ID: 256537
URI: http://eprints.soton.ac.uk/id/eprint/256537
ISBN: 3-540-42495-4
PURE UUID: 7bfb9d68-f82b-43cb-badc-946ed9fa0adc
Catalogue record
Date deposited: 30 Apr 2002
Last modified: 16 Mar 2024 00:38
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Contributors
Author:
Ken S. Thomas
Author:
Duan H. Beckett
Author:
Ben P. Hiett
Author:
Jasek Generowicz
Author:
Geoffrey J. Daniell
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