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POLYNOMIAL PRECONDITIONED ARNOLDI WITH STABILITY CONTROL
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DOI：10.1137/19M1302430.png)
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Abstract
En 中文
Polynomial preconditioning can improve the convergence of the Arnoldi method for computing eigenvalues. Such preconditioning significantly reduces the cost of orthogonalization; for difficult problems, it can also reduce the number of matrix-vector products. Parallel computations can particularly benefit from the reduction of communication-intensive operations. The GMRES algorithm provides a simple and effective way of generating the preconditioning polynomial. For some problems high degree polynomials are especially effective, but they can lead to stability problems that must be mitigated. A two-level double polynomial preconditioning strategy provides an effective way to generate high-degree preconditioners.
Keywords:
eigenvalues
polynomial preconditioning
Arnoldi
GMRES
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