Add to ORKGAdaptive Block FSAI (ABF) is an algebraic preconditioner for the efficient parallel solution of symmetric positive definite (SPD) linear systems. However, the iteration count to convergence tends to grow when the number of processors increases. Coupling a Domain Decomposition Schur complement approach with ABF can help improve the preconditioner performance and scalability, reducing at the same time the construction and communication computational burden. Numerical results show that the proposed algorithm proves particularly efficient in parallel geomechanical simulations
Parallel computers are potentially very attractive for the implementation of large size geomechanica...
The choice of the preconditioner is a key factor to accelerate the convergence of eigensolvers for l...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
Adaptive Block FSAI (ABF) is an algebraic preconditioner for the efficient parallel solution of symm...
Adaptive block factorized sparse approximate inverse (FSAI) (ABF) is a novel al- gebraic preconditio...
Adaptive Block FSAI (ABF) is a novel preconditioner which has proved efficient for the parallel solu...
Adaptive Block FSAI (ABF) is a novel and promising preconditioner for the efficient parallel solutio...
An adaptive algorithm is presented to generate automatically the nonzero pattern of the block factor...
Preconditioning is a key factor to accelerate the convergence of sparse eigensolvers. The present co...
A novel parallel preconditioner for symmetric positive definite matrices is developed coupling a gen...
2In this paper we propose a parallel preconditioner for the CG solver based on successive applicatio...
In this paper we propose and describe a parallel implementation of a block preconditioner for the so...
Factorized sparse approximate inverse (FSAI) preconditioners are robust algorithms for symmetric pos...
In this paper we propose a parallel implementation of the FSAI preconditioner to accelerate the PCG ...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
Parallel computers are potentially very attractive for the implementation of large size geomechanica...
The choice of the preconditioner is a key factor to accelerate the convergence of eigensolvers for l...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
Adaptive Block FSAI (ABF) is an algebraic preconditioner for the efficient parallel solution of symm...
Adaptive block factorized sparse approximate inverse (FSAI) (ABF) is a novel al- gebraic preconditio...
Adaptive Block FSAI (ABF) is a novel preconditioner which has proved efficient for the parallel solu...
Adaptive Block FSAI (ABF) is a novel and promising preconditioner for the efficient parallel solutio...
An adaptive algorithm is presented to generate automatically the nonzero pattern of the block factor...
Preconditioning is a key factor to accelerate the convergence of sparse eigensolvers. The present co...
A novel parallel preconditioner for symmetric positive definite matrices is developed coupling a gen...
2In this paper we propose a parallel preconditioner for the CG solver based on successive applicatio...
In this paper we propose and describe a parallel implementation of a block preconditioner for the so...
Factorized sparse approximate inverse (FSAI) preconditioners are robust algorithms for symmetric pos...
In this paper we propose a parallel implementation of the FSAI preconditioner to accelerate the PCG ...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...
Parallel computers are potentially very attractive for the implementation of large size geomechanica...
The choice of the preconditioner is a key factor to accelerate the convergence of eigensolvers for l...
The present paper describes a parallel preconditioned algorithm for the solution of partial eigenval...