Low‐Rank SPIKE Framework for Solving Large Sparse Linear Systems With Applications

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New approximation method improves eigenvalue solver performance, optimizing large sparse linear systems effectively.

The approximation leads to improved performance in managing large sparse linear systems, enhancing overall computational efficiency.
This work details the use of a low-rank approximation to optimize structured off-diagonal blocks.
Implementation of distributed solvers demonstrates significant advancements in processing 3D finite element simulations.
Such advancements may enable faster calculations in complex engineering applications, particularly for eigenvalue problems.],

Spring et al. (2025) studied this question.

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