Parallel finite element density functional computations exploiting grid refinement and subspace recycling
In this communication computational methods that facilitate finite element analysis of density functional computations are developed. They are: (i) h¿adaptive grid refinement techniques that reduce the total number of degrees of freedom in the real space grid while improving on the approximate resol...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/35132 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/35132 |
| Access Level: | acceso abierto |
| Palabra clave: | Density functional theory Finite element discretization Grid refinement Large-scale eigenvalue problem Message-passing parallelization CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL |
| Sumario: | In this communication computational methods that facilitate finite element analysis of density functional computations are developed. They are: (i) h¿adaptive grid refinement techniques that reduce the total number of degrees of freedom in the real space grid while improving on the approximate resolution of the wanted solution; and (ii) subspace recycling of the approximate solution in self-consistent cycles with the aim of improving the performance of the generalized eigenproblem solver. These techniques are shown to give a convincing speed-up in the computation process by alleviating the overhead normally associated with computing systems with many degrees-of-freedom. |
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