Add to ORKGIn LAPW-based methods a sequence of dense generalized eigenvalue problems appears. Traditionally these problems were solved using direct eigensolvers from standard libraries like ScaLAPACK. We developed a subspace iteration method pre-conditioned with Chebyshev polynomials of optimal degree (ChASE). This algorithm is consistently competitive with direct eigensolvers and greatly enhance performance and scalability. ChASE is included in the FLEUR software and improves its scaling behaviour for calculations of large physical systems on modern supercomputers
In many scientific applications the solution of non-linear differential equations are obtained throu...
As modern massively parallel clusters are getting larger with beefier compute nodes, traditional par...
Shift-invert and other methods for computing inner eigenvalues often require the solution of linear ...
As modern massively parallel clusters are getting larger with beefier compute nodes, traditional par...
In one of the most important methods in Density Functional Theory – the Full-Potential Linearized Au...
Research in several branches of chemistry and materials science relies on large ab initio numerical ...
We propose to step away from the black-box approach and allow the eigensolver to accept a...
Solving dense Hermitian eigenproblems arranged in a sequence with direct solvers fails to take advan...
Sequences of eigenvalue problems consistently appear in a large class of applications based on the i...
In many scientific applications, the solution of nonlinear differential equations are obtained throu...
In many scientific applications the solution of non-linear differential equations are obtained throu...
In Density Functional Theory simulations based on the LAPW method, each self-consistent field cycle ...
In many scientific applications the solution of non-linear differential equations are obtained throu...
In Density Functional Theory simulations based on the LAPW method, each self-consistent field cycle ...
Sequences of eigenvalue problems consistently appear in a large class of applications based on the i...
In many scientific applications the solution of non-linear differential equations are obtained throu...
As modern massively parallel clusters are getting larger with beefier compute nodes, traditional par...
Shift-invert and other methods for computing inner eigenvalues often require the solution of linear ...
As modern massively parallel clusters are getting larger with beefier compute nodes, traditional par...
In one of the most important methods in Density Functional Theory – the Full-Potential Linearized Au...
Research in several branches of chemistry and materials science relies on large ab initio numerical ...
We propose to step away from the black-box approach and allow the eigensolver to accept a...
Solving dense Hermitian eigenproblems arranged in a sequence with direct solvers fails to take advan...
Sequences of eigenvalue problems consistently appear in a large class of applications based on the i...
In many scientific applications, the solution of nonlinear differential equations are obtained throu...
In many scientific applications the solution of non-linear differential equations are obtained throu...
In Density Functional Theory simulations based on the LAPW method, each self-consistent field cycle ...
In many scientific applications the solution of non-linear differential equations are obtained throu...
In Density Functional Theory simulations based on the LAPW method, each self-consistent field cycle ...
Sequences of eigenvalue problems consistently appear in a large class of applications based on the i...
In many scientific applications the solution of non-linear differential equations are obtained throu...
As modern massively parallel clusters are getting larger with beefier compute nodes, traditional par...
Shift-invert and other methods for computing inner eigenvalues often require the solution of linear ...