Strategies for Scaling and Pivoting for Sparse Symmetric Indefinite Problems

Strategies for Scaling and Pivoting for Sparse Symmetric Indefinite Problems
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DOI:
10.1137/04061043x
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发表时间:
2005-06
期刊:
SIAM J. Matrix Anal. Appl.
影响因子:
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通讯作者:
I. Duff;S. Pralet
I. Duff;S. Pralet
中科院分区:
其他
文献类型:
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作者:
I. Duff;S. Pralet

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我们考虑了对对称系统实现预排序和缩放的方法,并展示了将这种技术与多额码一起用于稀疏对称不定系统的效果。在提出了一种新的缩放方法之后,我们提出了一种使用近似对称加权匹配的方法,在排序和分析阶段之前预定义$1 \乘以1$和$2 \乘以2$轴。我们还提出了新的排序类,称为“(放松)约束排序”,它混合了结构和数值标准。
We consider ways of implementing preordering and scaling for symmetric systems and show the effect of using this technique with a multifrontal code for sparse symmetric indefinite systems. After having presented a new method for scaling, we propose a way of using an approximation to a symmetric weighted matching to predefine $1 \times 1$ and $2 \times 2$ pivots prior to the ordering and analysis phase. We also present new classes of orderings called "(relaxed) constrained orderings" that mix structural and numerical criteria.