Add to ORKGWe investigate a method for efficiently solving a complex symmetric (non-Hermitian) generalized eigenvalue problem (EVP) Ax = λBx in parallel. An evaluation featuring up to 1024 CPU-cores evidences encour-aging runtime behavior.
In this paper, parallel extensions of a complete symmetric eigensolver, proposed by Yau and Lu in 19...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
We discuss a novel iterative approach for the computation of a number of eigenvalues and eigenvecto...
AbstractMethods for numerically solving generalized complex symmetric (non-Hermitian) eigenvalue pro...
Complex symmetric matrices often appear in quantum physics in the solution methods of partial differ...
This dissertation discusses parallel algorithms for the generalized eigenvalue problem Ax = λBx wher...
textThis thesis demonstrates an efficient parallel method of solving the generalized eigenvalue prob...
We present and discuss algorithms and library software for solving the generalized non-symmetric eig...
An efficient parallel algorithm, farmzeroinNR, for the eigenvalue problem of a symmetric tridiagonal...
This paper describes a new implementation of algorithms for solving large, dense symmetric eigen-pro...
A completely parallel algorithm for the symmetric eigenproblem AX = Lambda BX is outlined. The algor...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
The efficient use of the SUPRENUM computer calls for a careful choice of adequate algorithms and an ...
We discuss timing and performance modeling of a routine to find all the eigenvalues and eigenvectors...
AbstractSolving dense symmetric eigenvalue problems and computing singular value decompositions cont...
In this paper, parallel extensions of a complete symmetric eigensolver, proposed by Yau and Lu in 19...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
We discuss a novel iterative approach for the computation of a number of eigenvalues and eigenvecto...
AbstractMethods for numerically solving generalized complex symmetric (non-Hermitian) eigenvalue pro...
Complex symmetric matrices often appear in quantum physics in the solution methods of partial differ...
This dissertation discusses parallel algorithms for the generalized eigenvalue problem Ax = λBx wher...
textThis thesis demonstrates an efficient parallel method of solving the generalized eigenvalue prob...
We present and discuss algorithms and library software for solving the generalized non-symmetric eig...
An efficient parallel algorithm, farmzeroinNR, for the eigenvalue problem of a symmetric tridiagonal...
This paper describes a new implementation of algorithms for solving large, dense symmetric eigen-pro...
A completely parallel algorithm for the symmetric eigenproblem AX = Lambda BX is outlined. The algor...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
The efficient use of the SUPRENUM computer calls for a careful choice of adequate algorithms and an ...
We discuss timing and performance modeling of a routine to find all the eigenvalues and eigenvectors...
AbstractSolving dense symmetric eigenvalue problems and computing singular value decompositions cont...
In this paper, parallel extensions of a complete symmetric eigensolver, proposed by Yau and Lu in 19...
Obtaining the eigenvalues and eigenvectors of large matrices is a key problem in electronic structur...
We discuss a novel iterative approach for the computation of a number of eigenvalues and eigenvecto...