TY - GEN
T1 - The relationship between the features of sparse matrix and the matrix solving status
AU - Han, Dianwei
AU - Xu, Shuting
AU - Zhang, Jun
PY - 2008
Y1 - 2008
N2 - Solving very large sparse linear systems are often encountered in many scientific and engineering applications. Generally there are two classes of methods available to solve the sparse linear systems. The first class is the direct solution methods, represented by the Gauss elimination method. The second class is the iterative solution methods, of which the preconditioned Krylov subspace methods are considered to be the most effective ones currently available in this field. The sparsity structure and the numerical value distribution which are considered as features of the sparse matrices may have important effect on the iterative solution of linear systems. We first extract the matrix features, and then preconditioned iterative methods are used to the linear system. Our experiments show that a few features that may affect, positively or negatively, the solving status of a sparse matrix with the level-based preconditioners.
AB - Solving very large sparse linear systems are often encountered in many scientific and engineering applications. Generally there are two classes of methods available to solve the sparse linear systems. The first class is the direct solution methods, represented by the Gauss elimination method. The second class is the iterative solution methods, of which the preconditioned Krylov subspace methods are considered to be the most effective ones currently available in this field. The sparsity structure and the numerical value distribution which are considered as features of the sparse matrices may have important effect on the iterative solution of linear systems. We first extract the matrix features, and then preconditioned iterative methods are used to the linear system. Our experiments show that a few features that may affect, positively or negatively, the solving status of a sparse matrix with the level-based preconditioners.
KW - ACM proceedings
KW - Features of matrices
KW - Iterative methods
KW - Preconditioner
UR - http://www.scopus.com/inward/record.url?scp=70449876064&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70449876064&partnerID=8YFLogxK
U2 - 10.1145/1593105.1593236
DO - 10.1145/1593105.1593236
M3 - Conference contribution
AN - SCOPUS:70449876064
SN - 9781605581057
T3 - Proceedings of the 46th Annual Southeast Regional Conference on XX, ACM-SE 46
SP - 501
EP - 506
BT - Proceedings of the 46th Annual Southeast Regional Conference on XX, ACM-SE 46
T2 - 46th Annual Southeast Regional Conference on XX, ACM-SE 46
Y2 - 28 March 2009 through 29 March 2009
ER -