We report on a parallel implementation of the Jacobi–Davidson (JD) to compute a few eigenpairs of a large real symmetric generalized matrix eigenvalue ...

The eigenvalue problem stems from the design of cavities of particle accelerators. It is obtained by the finite element discretization of the.

PDF | We report on a parallel implementation of the Jacobi–Davidson (JD) to compute a few eigenpairs of a large real symmetric generalized matrix.

The Jacobi-Davidson (JD) method is found to be a very effective solver provided that a good preconditioner is available for the correction equations that ...

In this paper, we consider a parallel eigensolver for computing a few of the smallest eigenvalues and corresponding eigenvectors of (1.2) as efficiently as ...

We report on a parallel implementation of the Jacobi–Davidson (JD) to compute a few eigenpairs of a large real symmetric generalized matrix eigenvalue ...

This paper describes the PRIMME software package for the solving large, sparse Hermitian and real symmetric eigenvalue problems. The difficulty and importan ...

We report on a parallel implementation of the Jacobi–Davidson algorithm to compute a few eigenvalues and corresponding eigenvectors of a large real ...

Towards a Parallel Multilevel Preconditioned Maxwell Eigensolver. Mendeley ... Applied parallel computing : state of the art in scientific computing.

Towards a Parallel Multilevel Preconditioned Maxwell Eigensolver. https://doi.org/10.1007/11558958_100 · Full text. Journal: Applied Parallel Computing.