Add to ORKGWe report about our analysis of an optimization method, called DACG (Deflation-Accelerated Conjugate Gradient
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
A parallel algorithm based on the S-dimensional minimization of the Rayleigh quotient is proposed to...
We exploit an optimization method, called deflation-accelerated conjugate gradient (DACG), which seq...
A new metod (NI-DACG) for the partial eigensolution of large sparse symmetric FE eigenproblems is pr...
Recently an efficient method for the solution of the partial symmetric eigenproblem (DACG, deflated-...
A preconditioned scheme for solving sparse symmetric eigenproblems is proposed. The solution strateg...
A preconditioned scheme, DACG, is proposed for compute in parallel the leftmost eigenpairs of the ge...
n this paper we analyze the parallel efficiency of the approximate inverse preconditioners AINV and ...
An improvement in accelerated conjugate gradient iterations is presented for the evaluation of sever...
Abstract A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is...
The evaluation of the leftmost eigenspectrum of large sparse symmetric matrices is of great interest...
We exploit an optimization method, called DACG, which sequentially computes the smallest eigenpairs ...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
A parallel algorithm based on the S-dimensional minimization of the Rayleigh quotient is proposed to...
We exploit an optimization method, called deflation-accelerated conjugate gradient (DACG), which seq...
A new metod (NI-DACG) for the partial eigensolution of large sparse symmetric FE eigenproblems is pr...
Recently an efficient method for the solution of the partial symmetric eigenproblem (DACG, deflated-...
A preconditioned scheme for solving sparse symmetric eigenproblems is proposed. The solution strateg...
A preconditioned scheme, DACG, is proposed for compute in parallel the leftmost eigenpairs of the ge...
n this paper we analyze the parallel efficiency of the approximate inverse preconditioners AINV and ...
An improvement in accelerated conjugate gradient iterations is presented for the evaluation of sever...
Abstract A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is...
The evaluation of the leftmost eigenspectrum of large sparse symmetric matrices is of great interest...
We exploit an optimization method, called DACG, which sequentially computes the smallest eigenpairs ...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
A parallel algorithm based on the S-dimensional minimization of the Rayleigh quotient is proposed to...