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000017996 084__ $$2WoS$$aMathematics, Applied
000017996 1001_ $$0P:(DE-HGF)0$$aAliaga, J.I.$$b0
000017996 245__ $$aSolving dense generalized eigenproblems on multi-threaded architectures
000017996 260__ $$aNew York, NY$$bElsevier$$c2012
000017996 300__ $$a11279 - 11289
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000017996 440_0 $$026083$$aApplied Mathematics and Computation$$v218$$y22
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000017996 520__ $$aWe compare two approaches to compute a fraction of the spectrum of dense symmetric definite generalized eigenproblems: one is based on the reduction to tridiagonal form, and the other on the Krylov-subspace iteration. Two large-scale applications, arising in molecular dynamics and material science, are employed to investigate the contributions of the application, architecture, and parallelism of the method to the performance of the solvers. The experimental results on a state-of-the-art 8-core platform, equipped with a graphics processing unit (GPU), reveal that in realistic applications, iterative Krylov-subspace methods can be a competitive approach also for the solution of dense problems. (C) 2012 Elsevier Inc. All rights reserved.
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000017996 65320 $$2Author$$aEigenvalues
000017996 65320 $$2Author$$aTridiagonal form
000017996 65320 $$2Author$$aKrylov-subspace iteration
000017996 65320 $$2Author$$aMulti-core architectures
000017996 65320 $$2Author$$aGraphics processors
000017996 7001_ $$0P:(DE-HGF)0$$aBientinesi, P.$$b1
000017996 7001_ $$0P:(DE-HGF)0$$aDavidovic, D.$$b2
000017996 7001_ $$0P:(DE-Juel1)144723$$aDi Napoli, E.$$b3$$uFZJ
000017996 7001_ $$0P:(DE-HGF)0$$aIgual, F.D.$$b4
000017996 7001_ $$0P:(DE-HGF)0$$aQuintana-Orti­, E.S.$$b5
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000017996 8567_ $$uhttp://dx.doi.org/10.1016/j.amc.2012.05.020
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