To address the high computational complexity of sparse linear solvers caused by complex physical characteristics in practical applications,this paper presents a unified framework for feature-modified preconditioning algorithms.By refining the algebraic features affecting the efficiency from physical characteristics and combining multilevel feature analysis,we construct feature-modified components.The effectiveness of this framework is demonstrated through several typical feature-modified preconditioning algorithms and their application results.
关键词
稀疏线性代数方程组/特征修正/迭代方法/预条件算法/并行算法
Key words
sparse linear algebraic equations/feature-modified/iterative methods/preconditioning algorithms/parallel algorithms
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