Add to ORKGIt is well known that the solution of sparse linear systems, generally expressed in th
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
The sparse matrix solver is a critical component in circuit simulators. Some researches have develop...
AbstractNormalized factorization procedures for the solution of large sparse linear finite element s...
Krylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an efficient appr...
The concept of supernodes, originally developed to accelerate direct solution methods for linear sys...
AbstractKrylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an effici...
We investigate performance characteristics for the LU factorization of large matrices with various ...
Abstract. We investigate several ways to improve the performance of sparse LU factorization with par...
AbstractAn algorithm is presented for the general solution of a set of linear equations Ax=b. The me...
We investigate performance characteristics for the LU factorization of large matrices with various s...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
In Part I of this this paper, we proposed a new parallel bidirectional algorithm, based on Cholesky...
This paper describes implementations of eight algorithms of Newton and quasi-Newton type for solving...
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Ci...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
The sparse matrix solver is a critical component in circuit simulators. Some researches have develop...
AbstractNormalized factorization procedures for the solution of large sparse linear finite element s...
Krylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an efficient appr...
The concept of supernodes, originally developed to accelerate direct solution methods for linear sys...
AbstractKrylov methods preconditioned by Factorized Sparse Approximate Inverses (FSAI) are an effici...
We investigate performance characteristics for the LU factorization of large matrices with various ...
Abstract. We investigate several ways to improve the performance of sparse LU factorization with par...
AbstractAn algorithm is presented for the general solution of a set of linear equations Ax=b. The me...
We investigate performance characteristics for the LU factorization of large matrices with various s...
International audienceIn the context of solving sparse linear systems, an ordering process partition...
In Part I of this this paper, we proposed a new parallel bidirectional algorithm, based on Cholesky...
This paper describes implementations of eight algorithms of Newton and quasi-Newton type for solving...
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Ci...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
Abstract. Sparse matrix factorization is a critical step for the circuit simulation problem, since i...
The sparse matrix solver is a critical component in circuit simulators. Some researches have develop...