Exploiting the capabilities of modern GPUs for dense matrix computations
Impacto
Scholar |
Otros documentos de la autoría: Barrachina Mir, Sergio; Castillo Catalán, María Isabel; Igual, Francisco D.; Mayo, Rafael; Quintana-Orti, Enrique S.; Quintana-Ortí, Gregorio
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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http://dx.doi.org/10.1002/cpe.1472 |
Metadatos
Título
Exploiting the capabilities of modern GPUs for dense matrix computationsAutoría
Fecha de publicación
2009Editor
John Wiley & SonsISSN
1532-0626; 1532-0634Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://onlinelibrary.wiley.com/doi/10.1002/cpe.1472/fullPalabras clave / Materias
Resumen
We present several algorithms to compute the solution of a linear system of equations on a graphics processor (GPU), as well as general techniques to improve their performance, such as padding and hybrid GPU-CPU ... [+]
We present several algorithms to compute the solution of a linear system of equations on a graphics processor (GPU), as well as general techniques to improve their performance, such as padding and hybrid GPU-CPU computation. We compare single and double precision performance of a modern GPU with unified architecture, and show how iterative refinement with mixed precision can be used to regain full accuracy in the solution of linear systems, exploiting the potential of the processor for single precision arithmetic. Experimental results on a GTX280 using CUBLAS 2.0, the implementation of BLAS for NVIDIA® GPUs with unified architecture, illustrate the performance of the different algorithms and techniques proposed. [-]
Publicado en
Concurrency and Computation: Practice and Experience, 21, 18, p. 2457–2477Derechos de acceso
Copyright © 2009 John Wiley & Sons, Ltd.
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info:eu-repo/semantics/restrictedAccess
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