Fast block QR update in digital signal processing
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Scholar |
Altres documents de l'autoria: Alventosa, Fran J.; Alonso-Jordá, Pedro; Vidal, Antonio M.; Piñero, Gema; Quintana-Orti, Enrique S.
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https://doi.org/10.1007/s11227-018-2298-5 |
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Títol
Fast block QR update in digital signal processingAutoria
Data de publicació
2019-03Editor
SpringerCita bibliogràfica
Alventosa, F.J., Alonso, P., Vidal, A.M. et al. J Supercomput (2019) 75: 1051. https://doi.org/10.1007/s11227-018-2298-5Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://link.springer.com/article/10.1007/s11227-018-2298-5Versió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
The processing of digital sound signals often requires the computation of the QR factorization of a rectangular system matrix. However, sometimes, only a given (and probably small) part of the system matrix varies ... [+]
The processing of digital sound signals often requires the computation of the QR factorization of a rectangular system matrix. However, sometimes, only a given (and probably small) part of the system matrix varies from the current sample to the next one. We exploit this fact to reuse some computations carried out to process the former sample in order to save execution time in the processing of the current sample. These savings can be critical for real-time applications running on low power consumption devices with high mobility. In addition, we propose a simple out-of-order task-parallel algorithm for the QR factorization using OpenMP that exploits the multicore capability of modern processors. Furthermore, in the presence of a Graphics Processing Unit (GPU) in the system, our algorithm is able to off-load some tasks to the GPU to accelerate the computation on these hardware devices. [-]
Proyecto de investigación
Spanish Ministry of Economy and Competitiveness under MINECO and FEDER projects TEC2015-67387-C4-1-R and TIN2014-53495-R; and the Generalitat Valenciana PROMETEOII/2014/003Drets d'accés
© Springer Science+Business Media, LLC, part of Springer Nature 2018
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