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Parallelization of the discrete gradient method of non-smooth optimization and its applications
conference contribution
posted on 2003-01-01, 00:00 authored by Gleb BeliakovGleb Beliakov, J Monsalve Tobon, A BagirovWe investigate parallelization and performance of the discrete gradient method of nonsmooth optimization. This derivative free method is shown to be an effective optimization tool, able to skip many shallow local minima of nonconvex nondifferentiable objective functions. Although this is a sequential iterative method, we were able to parallelize critical steps of the algorithm, and this lead to a significant improvement in performance on multiprocessor computer clusters. We applied this method to a difficult polyatomic clusters problem in computational chemistry, and found this method to outperform other algorithms.
History
Title of proceedings
Computational science - ICCS 2003 : international conference, Melbourne, Australia and St. Petersburg, Russia, June 2-4, 2003 : proceedingsEvent
ICCS 2003 (Conference) (2003 : Melbourne, Vic., and Saint Petersburg, Russia)Pagination
592 - 601Publisher
SpringerLocation
Melbourne, Australia and St. Petersburg, RussiaPlace of publication
Berlin, GermanyPublisher DOI
Start date
2003-06-02End date
2003-06-04ISSN
0302-9743eISSN
1611-3349ISBN-13
9783540401964ISBN-10
3540401962Language
engNotes
The original publication can be found at www.springerlink.comPublication classification
E1 Full written paper - refereedCopyright notice
2003, Springer-Verlag Berlin HeidelbergEditor/Contributor(s)
P Sloot, D Abramson, A Bogdanov, Y Gorbachev, J Dongarra, A ZomayaUsage metrics
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