### Abstract

This paper discusses techniques for computing a few selected eigenvalue–eigenvector pairs of large and sparse symmetric matrices. A recently developed class of techniques to solve this type of problems is based on integrating the matrix resolvent operator along a complex contour that encloses the interval containing the eigenvalues of interest. This paper considers such contour integration techniques from a domain decomposition viewpoint and proposes two schemes. The first scheme can be seen as an extension of domain decomposition linear system solvers in the framework of contour integration methods for eigenvalue problems, such as FEAST. The second scheme focuses on integrating the resolvent operator primarily along the interface region defined by adjacent subdomains. A parallel implementation of the proposed schemes is described, and results on distributed computing environments are reported. These results show that domain decomposition approaches can lead to reduced run times and improved scalability.

Original language | English (US) |
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Article number | e2154 |

Journal | Numerical Linear Algebra with Applications |

Volume | 25 |

Issue number | 5 |

DOIs | |

State | Published - Oct 2018 |

### Keywords

- Cauchy integral formula
- FEAST
- domain decomposition
- parallel computing
- symmetric eigenvalue problem

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## Cite this

*Numerical Linear Algebra with Applications*,

*25*(5), [e2154]. https://doi.org/10.1002/nla.2154