A fast band–Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processors
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Otros documentos de la autoría: Aliaga Estellés, José Ignacio; Alonso-Jordá, Pedro; Badía, José; Chacón, Pablo; Davidovic, Davor; López Blanco, José R.; Quintana-Orti, Enrique S.
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http://dx.doi.org/10.1016/j.jcp.2016.01.007 |
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Título
A fast band–Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processorsAutoría
Fecha de publicación
2016-03-15Editor
ElsevierCita bibliográfica
ALIAGA ESTELLÉS, José Ignacio; ALONSO JORDÁ, Pedro; BADÍA CONTELLES, José Manuel; CHACÓN, Pablo; DAVIDOVIC, Davor; LÓPEZ BLANCO, José R.; QUINTANA ORTÍ, Enrique S. A fast band–Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processors. Journal of Computational Physics (2016), v. 309, pp. 314-323Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0021999116000085Palabras clave / Materias
Resumen
We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator ... [+]
We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel.
The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousands degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures. [-]
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Journal of Computational Physics (2016), v. 309Derechos de acceso
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info:eu-repo/semantics/restrictedAccess
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