Title :
Storage and Solving of Large Sparse Matrix Linear Equations
Author :
Liu, Chao ; Ye, Junmin ; Ma, Yining
Author_Institution :
Comput. Sci. Dept., Central China Normal Univ., Wuhan, China
Abstract :
Solving of large sparse matrix linear equations is always the research focus of scientific and engineering calculation field. With the sparsity and symmetry characteristics of coefficient matrix, Compressed Sparse Row (CSR) is adopted in the storage of large sparse matrix linear equations. Under the condition of CSR, Symmetrica Successive Over Relaxations-Preconditioned Conjugate Gradient method (SSOR-PCG) is employed in the solution of large sparse matrix linear equations.
Keywords :
conjugate gradient methods; finite element analysis; sparse matrices; CSR; SSOR-PCG; coefficient matrix sparsity characteristics; coefficient matrix symmetry characteristics; compressed sparse row; large sparse matrix linear equations; scientific and engineering calculation field; symmetrica successive over relaxations-preconditioned conjugate gradient method; Computational modeling; Equations; Finite element methods; Gradient methods; Mathematical model; Sparse matrices; Symmetric matrices; CSR; Finite element calculation; SSOR-PCG; Sparse matrix;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
DOI :
10.1109/ICCIS.2012.293
