.png){kind=icon}
Return
DISTRIBUTED SCHUR COMPLEMENT TECHNIQUES FOR GENERAL SPARSE LINEAR SYSTEMS
.png){kind=icon}
PRE
AI
DOI：10.1137/S1064827597328996.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper presents a few preconditioning techniques for solving general sparse linear systems on distributed memory environments. These techniques utilize the Schur complement system for deriving the preconditioning matrix in a number of ways. Two of these preconditioners consist of an approximate solution process for the global system, which exploits approximate LU factorizations for diagonal blocks of the Schur complement. Another preconditioner uses a sparse approximate-inverse technique to obtain certain local approximations of the Schur complement. Comparisons are reported for systems of varying difficulty.
Keywords:
parallel preconditioning
distributed sparse linear systems
Schur complement techniques
domain decomposition
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.6
Papers:
5.1K
Citations:
1.8W
Organization
Cited Papers
ShareSavePhotosynthesis studies on European evergreen and deciduous oaks grown under Central European climate conditions: II. Photoinhibitory and light-independent violaxanthin deepoxidation and downregulation of photosystem II in evergreen, winter-acclimated European Quercus taxa.png)
Trees
TreesIF0
PREAI
ShareSave no more
no more