Storage and Solving of Large Sparse Matrix Linear Equations

Storage and Solving of Large Sparse Matrix Linear Equations

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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Chao Liu, Junmin Ye, Yining Ma
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Computational modeling
CSR
Equations
Finite element calculation
Finite element methods
Gradient methods
Mathematical model
Sparse matrices
Sparse matrix
SSOR-PCG
Symmetric matrices
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Beschreibung
Zusammenfassung: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.
DOI:10.1109/ICCIS.2012.293