.png){kind=icon}
返回
IMF: AN INCOMPLETE MULTIFRONTAL LU-FACTORIZATION FOR ELEMENT-STRUCTURED SPARSE LINEAR SYSTEMS
.png){kind=icon}
OA
AI
DOI：10.1137/100818996.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We propose an incomplete multifrontal LU-factorization (IMF) preconditioner that extends supernodal multifrontal methods to incomplete factorizations. It can be used as a preconditioner in a Krylov-subspace method to solve large-scale sparse linear systems with an element structure, e. g., those arising from a finite element discretization of a partial differential equation. The fact that the element matrices are dense is exploited to increase the computational performance and the robustness of the factorization through efficient partial pivoting. IMF is compared with the multilevel ARMS2, the level of fill-in ILU, and the threshold-based ILUTP preconditioners. Our experiments indicate that IMF is competitive with ARMS2 on saddle-point problems arising in the solution of the steady-state Navier-Stokes equation. Experiments with element-structured matrices arising from structural engineering applications, found in the University of Florida Sparse Matrix Collection, illustrate the robustness of IMF. Finally, the computational performance of IMF clearly surpasses that of the related ARMS2 preconditioner.
Keyword:
incomplete factorization
supernodal multifrontal method
multilevel preconditioner
block LU-factorization
finite element method
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.6
论文数:
5.1K
被引数:
1.8W
机构
引用论文
.png){kind=icon}
分享收藏Effect of Exercise Training on the Mental and Physical Well-Being of Caregivers for Persons Living With Chronic Illnesses: A Systematic Review and Meta-Analysis运动训练对慢性病患者照顾者身心健康的影响: 系统综述和荟萃分析
PREAI
分享收藏
查看更多内容