Precondicionador multigrid algébrico para métodos iterativos não estacionários na solução de sistemas lineares de grande porte
Ano de defesa: | 2021 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal do Espírito Santo
BR Mestrado em Informática Centro Tecnológico UFES Programa de Pós-Graduação em Informática |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://repositorio.ufes.br/handle/10/15478 |
Resumo: | The objective of this work is to evaluate the computational performance of Algebraic Multigrid (AMG) as a preconditioner for methods based on Krylov subspaces. An alternative coarsening strategy known as Double Pairwise Aggregation (DPA) has been implemented which applies a graph matching algorithm twice at each level of the hierarchy in order to produce the coarsening operators. In this context, matrices of different origins were used to compare the different AMG coarsening strategies with each other and with preconditioners derived from the incomplete LU factorization (ILU) and the Gauss-Seidel factorization applied to the Generalized Minimum Residual Method (GMRES). Additional computational experiments were performed with stencil matrices and with matrices originating from problems governed by Euler equations discretized by the Finite Element method, where a row and column reordering algorithm was also taken into account. Finally, the strengths and weaknesses of each method and coarsening algorithms are highlighted in each context, with emphasis on the advantages obtained with the implementation of DPA. |