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000185482 1001_ $$0P:(DE-HGF)0$$aBerljafa, Mario$$b0
000185482 245__ $$aAn optimized and scalable eigensolver for sequences of eigenvalue problems
000185482 260__ $$aChichester$$bWiley$$c2015
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000185482 520__ $$aIn many scientific applications, the solution of nonlinear differential equations are obtained through the setup and solution of a number of successive eigenproblems. These eigenproblems can be regarded as a sequence whenever the solution of one problem fosters the initialization of the next. In addition, in some eigenproblem sequences, there is a connection between the solutions of adjacent eigenproblems. Whenever it is possible to unravel the existence of such a connection, the eigenproblem sequence is said to be correlated. When facing with a sequence of correlated eigenproblems, the current strategy amounts to solving each eigenproblem in isolation. We propose an alternative approach that exploits such correlation through the use of an eigensolver based on subspace iteration and accelerated with Chebyshev polynomials (Chebyshev filtered subspace iteration (ChFSI)). The resulting eigensolver is optimized by minimizing the number of matrix–vector multiplications and parallelized using the Elemental library framework. Numerical results show that ChFSI achieves excellent scalability and is competitive with current dense linear algebra parallel eigensolvers.
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000185482 536__ $$0G:(DE-Juel1)SDLQM$$aSimulation and Data Laboratory Quantum Materials (SDLQM) (SDLQM)$$cSDLQM$$fSimulation and Data Laboratory Quantum Materials (SDLQM)$$x2
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000185482 7001_ $$0P:(DE-Juel1)131042$$aWortmann, Daniel$$b1$$ufzj
000185482 7001_ $$0P:(DE-Juel1)144723$$aDi Napoli, Edoardo$$b2$$ufzj
000185482 773__ $$0PERI:(DE-600)2052606-4$$a10.1002/cpe.3394$$gp. n/a - n/a$$n4$$p905–922$$tConcurrency and computation$$v27$$x1532-0626$$y2015
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