A Novel Hybrid FSAI-ILU Preconditioner for the Efficient Parallel Solution of Large Size Sparse Linear Systems

被引：0
|
作者：
Janna, C. [1 ]
Ferronato, M. [1 ]
Gambolati, G. [1 ]
机构：
[1] Univ Padua, DMMMSA, I-35100 Padua, Italy
来源：
PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY | 2010年 / 94卷
关键词：
parallel computing; iterative methods; preconditioning; ITERATIVE SOLUTION; PATTERNS; INVERSE; MATRIX;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
A novel parallel preconditioner combining a generalized Factored Sparse Approximate Inverse (FSAI) with a block Incomplete LU (ILU) decomposition is developed. The generalized Block FSAI (BFSAI) is derived by requiring the preconditioned matrix to resemble as much as possible a block diagonal matrix in the sense of the minimal Frobenius norm. A second preconditioning is then applied using an incomplete Block Jacobi strategy. The BFSAI-ILU preconditioner turns out to be a parallel hybrid of FSAI and ILU that proves superior to FSAI for any number of processors and is fully scalable for any given number of blocks.
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页数：10
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