Exploiting thread-level parallelism in the iterative solution of sparse linear systems
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Scholar |
Otros documentos de la autoría: Aliaga Estellés, José Ignacio; Bollhöfer, Matthias; Martín Huertas, Alberto F.; Quintana-Orti, Enrique S.
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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comunitat-uji-handle3:10234/8620
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Metadatos
Título
Exploiting thread-level parallelism in the iterative solution of sparse linear systemsAutoría
Fecha de publicación
2011Editor
ElsevierISSN
0167-8191Cita bibliográfica
Parallel Computing (March 2011) vol. 37, no. 3, p. 183-202Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0167819110001432Palabras clave / Materias
Resumen
We investigate the efficient iterative solution of large-scale sparse linear systems on shared-memory multiprocessors. Our parallel approach is based on a multilevel ILU preconditioner which preserves the mathematical ... [+]
We investigate the efficient iterative solution of large-scale sparse linear systems on shared-memory multiprocessors. Our parallel approach is based on a multilevel ILU preconditioner which preserves the mathematical semantics of the sequential method in ILUPACK. We exploit the parallelism exposed by the task tree corresponding to the nested dissection hierarchy (task parallelism), employ dynamic scheduling of tasks to processors to improve load balance, and formulate all stages of the parallel PCG method conformal with the computation of the preconditioner to increase data reuse. Results on a CC-NUMA platform with 16 processors reveal the parallel efficiency of this solution. [-]
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