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| 001 | 872963 | ||
| 005 | 20221109161717.0 | ||
| 024 | 7 | _ | |a arXiv:2001.04184 |2 arXiv |
| 024 | 7 | _ | |a 10.1137/20M1313933 |2 doi |
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| 037 | _ | _ | |a FZJ-2020-00420 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 510 |
| 100 | 1 | _ | |a Kollnig, Konrad |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Rational Spectral Filters with Optimal Convergence Rate |
| 260 | _ | _ | |a Philadelphia, Pa. |c 2021 |b SIAM |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a 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 nonlinear least-squares optimization of so-called rational filters, we introduce a systematic method to design these filters by minimizing the worst-case convergence rate 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. |
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| 588 | _ | _ | |a Dataset connected to arXivarXiv |
| 700 | 1 | _ | |a Bientinesi, Paolo |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Di Napoli, Edoardo |0 P:(DE-Juel1)144723 |b 2 |e Corresponding author |
| 773 | _ | _ | |a 10.1137/20M1313933 |g Vol. 43, no. 4, p. A2660 - A2684 |0 PERI:(DE-600)1468391-x |n 4 |p A2660–A2684 |t SIAM journal on scientific computing |v 43 |y 2021 |x 0196-5204 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/872963/files/2001.04184.pdf |y OpenAccess |
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