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• W2999690835 abstract "In recent years, contour-based eigensolvers have emerged as a standard approach for the solution of large and sparse eigenvalue problems. Building upon recent performance improvements through non-linear least square optimization of so-called rational filters, we introduce a systematic method to design these filters by minimizing the worst-case convergence ratio and eliminate the parametric dependence on weight functions. Further, we provide an efficient way to deal with the box-constraints which play a central role for the use of iterative linear solvers in contour-based eigensolvers. Indeed, these parameter-free filters consistently minimize the number of iterations and the number of FLOPs to reach convergence in the eigensolver. As a byproduct, our rational filters allow for a simple solution to load balancing when the solution of an interior eigenproblem is approached by the slicing of the sought after spectral interval." @default.
• W2999690835 created "2020-01-23" @default.
• W2999690835 creator A5048393932 @default.
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• W2999690835 date "2020-01-13" @default.
• W2999690835 modified "2023-09-27" @default.
• W2999690835 title "Rational spectral filters with optimal convergence rate." @default.
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• W2999690835 hasPublicationYear "2020" @default.
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