Dossier: SimRace 2015: Numerical Methods and High Performance Computing for Industrial Fluid Flows
Open Access
Issue
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 71, Number 6, November–December 2016
Dossier: SimRace 2015: Numerical Methods and High Performance Computing for Industrial Fluid Flows
Article Number 66
Number of page(s) 11
DOI https://doi.org/10.2516/ogst/2016021
Published online 20 December 2016
  • Saad Y., Schultz M.H. (1986) Gmres: a generalized minimal residual algorithm for solving nonsymmetric linear systems, SIAM J. Sci. Stat. Comput. 7, 3, 856–869. [CrossRef] [MathSciNet] [Google Scholar]
  • Hestenes M.R., Stiefel E. (1952) Methods of conjugate gradients for solving linear systems, J. Res. Natl. Bur. Stand. 49, 409–436. [CrossRef] [MathSciNet] [Google Scholar]
  • van der Vorst H.A. (1992) Bi-CGSTAB: a fast and smoothly converging variant of Bi-CG for the solution of nonsymmetric linear systems, SIAM J. Sci. Statist. Comput. 13, 2, 631–644. [CrossRef] [MathSciNet] [Google Scholar]
  • Carson E., Knight N., Demmel J. (2011) Avoiding communication in two-sided Krylov subspace methods. Technical Report UCB/EECS-2011-93, EECS Department, University of California, Berkeley, August. [Google Scholar]
  • Carson E., Knight N., Demmel J. (2013) Avoiding communication in nonsymmetric Lanczos-based Krylov subspace methods, SIAM J. Sci. Comput. 35, 5, S42–S61. [CrossRef] [Google Scholar]
  • Grigori L, Moufawad S. (2013) Communication avoiding ILU0 preconditioner, Technical Report, ALPINES - INRIA Paris-Rocquencourt, March. [Google Scholar]
  • Hoemmen M. (2010) Communication-avoiding Krylov subspace methods, PhD Thesis, EECS Department, University of California, Berkeley. [Google Scholar]
  • Mohiyuddin M., Hoemmen M., Demmel J., Yelick K. (2009) Minimizing communication in sparse matrix solvers, In Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, SC’09, New York, NY, USA, ACM, pp.1–12. [Google Scholar]
  • Chronopoulos A.T., Gear W. (1989) s-Step iterative methods for symmetric linear systems, J. Comput. Appl. Math. 25, 2, 153–168. [CrossRef] [Google Scholar]
  • Erhel J. (1995) A parallel GMRES version for general sparse matrices, Electron. Trans. Numer. Anal. 3, 160–176. [MathSciNet] [Google Scholar]
  • Walker H.F. (1988) Implementation of the GMRES method using householder transformations, SIAM J. Sci. Statist. Comput. 9, 1, 152–163. [CrossRef] [MathSciNet] [Google Scholar]
  • Demmel J., Hoemmen M., Mohiyuddin M., Yelick K. (2008) Avoiding communication in sparse matrix computations, In Parallel and Distributed Processing, 2008. IPDPS 2008. IEEE International Symposium, 14–18 April 2008, Held in Hyatt Regency Hotel in Miami, Florida, USA, pp. 1–12. [CrossRef] [Google Scholar]
  • Demmel J., Grigori L., Hoemmen M., Langou J. (2012) Communication-avoiding parallel and sequential QR factorizations, SIAM J. Sci. Comput. 34, 206–239. [CrossRef] [Google Scholar]
  • Bai Z., Hu D., Reichel L. (1994) A Newton basis GMRES implementation, IMA J. Numer. Anal. 14, 563–581. [CrossRef] [MathSciNet] [Google Scholar]
  • Reichel L. (1990) Newton interpolation at Leja points, BIT Numerical Mathematics 30, 332–346. [CrossRef] [MathSciNet] [Google Scholar]
  • Lehoucq R., Sorensen D., Yang C. (1998) ARPACK Users’ Guide, Society for Industrial and Applied Mathematics, Philadelphia, PA. [CrossRef] [Google Scholar]
  • The 10th SPE Comparative Solution Project (2000) Retrieved from http://www.spe.org/web/csp/datasets/set02.htm. [Google Scholar]
  • Anciaux-Sedrakian A., Eaton J., Gratien J., Guignon T., Havé P., Preux C., Ricois O. (2015) Will GPGPUs be finally a credible solution for industrial reservoir simulators, SPE Reservoir Simulation Symposium, 23-25 February, Houston, Texas, USA, SPE-173223-MS. DOI: 10.2118/173223-MS. [Google Scholar]
  • Anciaux-Sedrakian A., Gottschling P., Gratien J., Guignon T. (2014) Survey on efficient linear solvers for porous media flow models on recent hardware architectures, Oil Gas Sci. Technol. - Rev. IFP 69, 4, 753–766. [CrossRef] [EDP Sciences] [Google Scholar]

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