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Metoda konjugovaných gradientů a Lanczosova metoda tvoří historický a metodologický základ tzv. metod krylovovských podprostorů pro numerickou aproximaci řešení lineárních rovnic a částečnou aproximaci spektra lineárních operátorů. Ačkoliv jsou v obecném povědomí spojovány především s numerickým řešením velmi rozsáhlých soustav lineárních algebraických rovnic a aproximací vlastních čísel velkých matic, je přirozené uvažovat jejich formulaci v kontextu operátorů na Hilbertových prostorech (konečné...
With the emergence of mixed precision hardware, mixed precision GMRES-based iterative refinement schemes for solving linear systems have recently been developed. However, in certain settings, GMRES may require too many iterations per refinement step, making it potentially more expensive than the alternative of recomputing the LU factors in a higher precision. In this work, we incorporate the idea of Krylov subspace recycling, a well-known technique for reusing information across sequential invocations,...
We prove nearly uniform convergence bounds for the BPX preconditioner based on smoothed aggregation under the assumption that the mesh is regular. The analysis is based on the fact that under the assumption of regular geometry, the coarse-space basis functions form a system of macroelements. This property tends to be satisfied by the smoothed aggregation bases formed for unstructured meshes.
An algorithm for using the preconditioned conjugate gradient method to solve a coarse level problem is presented.
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