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A fast spectral divide‐and‐conquer method for banded matrices

Published:2021-03-08 Issue:4 Volume:28 Page:
ISSN:1070-5325
Container-title:Numerical Linear Algebra with Applications
language:en
Short-container-title:Numer Linear Algebra Appl

Author:

Šušnjara Ana¹^ORCID,Kressner Daniel¹^ORCID

Affiliation:

1. MATH‐ANCHP École Polytechnique Fédérale de Lausanne Lausanne Switzerland

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

Wiley

Subject

Applied Mathematics,Algebra and Number Theory

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nla.2365

Reference33 articles.

1. Stable and Efficient Spectral Divide and Conquer Algorithms for the Symmetric Eigenvalue Decomposition and the SVD

2. A framework for symmetric band reduction

3. Parallel solution of partial symmetric eigenvalue problems from electronic structure calculations

4. Condensed forms for the symmetric eigenvalue problem on multi-threaded architectures

5. HaidarA LtaiefH DongarraJ. Parallel reduction to condensed forms for symmetric eigenvalue problems using aggregated fine‐grained and memory‐aware kernels. Proceedings of the 2011 International Conference for High Performance Computing Networking Storage and Analysis. New York NY: ACM;2011. p. 8:1–8:11.

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1. Optimizing a Super-Fast Eigensolver for Hierarchically Semiseparable Matrices;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12

2. Computing the k-th Eigenvalue of Symmetric H2-Matrices;Proceedings of the 52nd International Conference on Parallel Processing;2023-08-07

3. SuperDC: Superfast Divide-And-Conquer Eigenvalue Decomposition With Improved Stability for Rank-Structured Matrices;SIAM Journal on Scientific Computing;2022-09-22

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