A new metod (NI-DACG) for the partial eigensolution of large sparse symmetric FE eigenproblems is presented. NI-DACG relies on the optimization of Rayleigh quotients in successively deflated subspaces by a preconditioned conjugate gradient technique and uses a multiple grid type approach to asses an improved eigenvector estimate on nested FE grids on wich the solution to the continuous eigenproblem is sought. NI-DACG is implemented on the CRAY Y-MP supercomputer making use of vectorization and/or parallelization with two and four processors. Results relative to the calculation of the 50 smallest eigenpairs for two representative sample problems show a gain in CPU time that exceeds one order of magnitude with respect to the scalar implementa...
A parallel algorithm based on the S-dimensional minimization of the Rayleigh quotient is proposed to...
A preconditioned scheme, DACG, is proposed for compute in parallel the leftmost eigenpairs of the ge...
Techniques for the vectorization and parallelization of a sequential code for evaluating, one at a t...
A new metod (NI-DACG) for the partial eigensolution of large sparse symmetric FE eigenproblems is pr...
The evaluation of the leftmost eigenspectrum of large sparse symmetric matrices is of great interest...
A parallel algorithm for the calculation of the p leftmost eigenpairs of large, sparse F.E.M. matric...
We exploit an optimization method, called deflation-accelerated conjugate gradient (DACG), which seq...
n this paper we analyze the parallel efficiency of the approximate inverse preconditioners AINV and ...
A preconditioned scheme for solving sparse symmetric eigenproblems is proposed. The solution strateg...
We report about our analysis of an optimization method, called DACG (Deflation-Accelerated Conju...
Recently an efficient method for the solution of the partial symmetric eigenproblem (DACG, deflated-...
We exploit an optimization method, called DACG, which sequentially computes the smallest eigenpairs ...
Abstract A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is...
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...
A preconditioned scheme, DACG, is proposed for compute in parallel the leftmost eigenpairs of the ge...
Techniques for the vectorization and parallelization of a sequential code for evaluating, one at a t...
A new metod (NI-DACG) for the partial eigensolution of large sparse symmetric FE eigenproblems is pr...
The evaluation of the leftmost eigenspectrum of large sparse symmetric matrices is of great interest...
A parallel algorithm for the calculation of the p leftmost eigenpairs of large, sparse F.E.M. matric...
We exploit an optimization method, called deflation-accelerated conjugate gradient (DACG), which seq...
n this paper we analyze the parallel efficiency of the approximate inverse preconditioners AINV and ...
A preconditioned scheme for solving sparse symmetric eigenproblems is proposed. The solution strateg...
We report about our analysis of an optimization method, called DACG (Deflation-Accelerated Conju...
Recently an efficient method for the solution of the partial symmetric eigenproblem (DACG, deflated-...
We exploit an optimization method, called DACG, which sequentially computes the smallest eigenpairs ...
Abstract A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is...
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...
A preconditioned scheme, DACG, is proposed for compute in parallel the leftmost eigenpairs of the ge...
Techniques for the vectorization and parallelization of a sequential code for evaluating, one at a t...