Abstract
The solution of linear systems is a key operation in many scientific and engineering applications. Traditional solvers are based on the LU factorization of the coefficient matrix, and optimized implementations of this method are available in well-known dense linear algebra libraries for most hardware architectures. The Gauss-Huard algorithm (GHA) is a reliable and alternative method that presents a computational effort close to that of the LU-based approach. In this work we present several implementations of GHA on the Intel Xeon Phi coprocessor. The experimental results show that our solvers based in GHA represent a competitive alternative to LU-based solvers, being an appealing method for the solution of small to medium linear systems, with remarkable reductions in the time-to-solution for systems of dimension \(n\le 4,000\).
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Acknowledgments
The researcher from the Universidad Jaime I was supported by the CICYT projects TIN2011-23283 and TIN2014-53495-R of the Ministerio de Economía y Competitividad and FEDER. Ernesto Dufrechou, Pablo Ezzatti and Alfredo Remón were supported by the EHFARS project funded by the German Ministry of Education and Research BMBF.
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Dufrechou, E., Ezzatti, P., Quintana-Ortí, E.S., Remón, A. (2015). Solving Linear Systems on the Intel Xeon-Phi Accelerator via the Gauss-Huard Algorithm. In: Osthoff, C., Navaux, P., Barrios Hernandez, C., Silva Dias, P. (eds) High Performance Computing. CARLA 2015. Communications in Computer and Information Science, vol 565. Springer, Cham. https://doi.org/10.1007/978-3-319-26928-3_8
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DOI: https://doi.org/10.1007/978-3-319-26928-3_8
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