The factorization method presented in this paper takes advantage of the special structures and properties of saddle point matrices. A variant of Gaussian elimination equivalent to the Cholesky's factorization is suggested and implemented for factorizing the saddle point matrices block-wise with small blocks of order 1 and 2. The Gaussian elimination applied to these small blocks on block level also induces a block 3 x 3 structured factorization of which the blocks have special properties. We compare the new block factorization with the Schilders' factorization in terms of the sparsity of their factors and computational efficiency. The factorization can be used as a direct method, and also anticipate for preconditioning techniques
International audience—The applicability of many signal processing and data analysis techniques is l...
AbstractEfficient numerical solution of large elliptic systems is often facilitated with an approxim...
Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have...
The factorization method presented in this paper takes advantage of the special structures and prope...
We present unique and existing micro-block and induced macro-block Crout-based factorizations for ma...
Mastronardi and Van Dooren [SIAM J. Matrix Anal. Appl., 34 (2013), pp. 173--196] recently introduced...
\u3cp\u3eThis paper focuses on efficiently solving large sparse symmetric indefinite systems of line...
International audienceThe block Lanczos algorithm proposed by Peter Montgomery is an efficient means...
AbstractThis paper introduces several strategies to deal with pivot blocks in multi-level block inco...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
AbstractA new sparse approximate triangular factorization technique for solving large sparse linear ...
International audience—The applicability of many signal processing and data analysis techniques is l...
AbstractEfficient numerical solution of large elliptic systems is often facilitated with an approxim...
Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have...
The factorization method presented in this paper takes advantage of the special structures and prope...
We present unique and existing micro-block and induced macro-block Crout-based factorizations for ma...
Mastronardi and Van Dooren [SIAM J. Matrix Anal. Appl., 34 (2013), pp. 173--196] recently introduced...
\u3cp\u3eThis paper focuses on efficiently solving large sparse symmetric indefinite systems of line...
International audienceThe block Lanczos algorithm proposed by Peter Montgomery is an efficient means...
AbstractThis paper introduces several strategies to deal with pivot blocks in multi-level block inco...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
This paper focuses on efficiently solving large sparse symmetric indefinite systems of linear equati...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
AbstractA new sparse approximate triangular factorization technique for solving large sparse linear ...
International audience—The applicability of many signal processing and data analysis techniques is l...
AbstractEfficient numerical solution of large elliptic systems is often facilitated with an approxim...
Factorization based preconditioning algorithms, most notably incomplete LU (ILU) factorization, have...