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Scalable hybrid implementation of the Schur complement method for multi-GPU systems

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Abstract

This paper presents a new hybrid solver based on the Schur complement method, in which computations are distributed between multiple CPUs and GPUs. In this solver, the Schur complement is formed either on CPUs (for small problems) or on GPUs (for large problems). The interface system is solved by a new multi-GPU algorithm implementing the conjugate gradient method with explicit preconditioning. Numerical simulations performed on a hybrid multi-core multi-GPU cluster demonstrate scalability and efficiency of the proposed algorithms.

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References

  1. Agullo E, Giraud L et al (2011) Parallel hierarchical hybrid linear solvers for emerging computing platforms. Comptes Rendus Mécanique 339(2–3):96–103

    Article  MATH  Google Scholar 

  2. Ezzatti P, Quintana-Ortí E, Remón A (2011) Using graphics processors to accelerate the computation of the matrix inverse. J Supercomput 58(3):429–437

    Article  Google Scholar 

  3. He X, Holm M, Neytcheva M (2013) Parallel implementation of the Sherman–Morrison matrix inverse algorithm. In: Applied parallel and scientific computing, LNCS, vol 7782. Springer, pp 206–219

  4. Kopysov S, Kuzmin I, Nedozhogin N, Novikov A, Sagdeeva Y (2013) Hybrid multi-gpu solver based on Schur complement method. In: Parallel computing technologies. Lecture Notes in Computer Science, vol 7979. Springer, Berlin Heidelberg, pp 65–79

  5. Kopyssov S, Krasnopyorov I, Novikov A, Rytchkov V (2005) Parallel distributed object-oriented framework for domain decomposition. In: Domain decomposition methods in science and engineering, LNCSE, vol 40. Springer, pp 605–614

  6. Toselli A, Widlund OB (2005) Domain decomposition methods—algorithms and theory. In: Springer series in computational mathematics, vol 34. Springer

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Authors and Affiliations

  1. 34 ul. T. Baramzinoy, 426067 , Izhevsk, Russia

    Sergey Kopysov, Igor Kuzmin, Nikita Nedozhogin, Alexander Novikov & Yulia Sagdeeva

Authors
  1. Sergey Kopysov
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  2. Igor Kuzmin
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  3. Nikita Nedozhogin
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  4. Alexander Novikov
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  5. Yulia Sagdeeva
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Corresponding author

Correspondence to Sergey Kopysov.

Additional information

This research is supported by RFBR (projects: 13-01-00101-a, 14-01-31066-mol_a, 14-01-00055-a), the Presidium and the Ural Branch of RAS (program N18, project 12-P-1-1005).

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Kopysov, S., Kuzmin, I., Nedozhogin, N. et al. Scalable hybrid implementation of the Schur complement method for multi-GPU systems. J Supercomput 69, 81–88 (2014). https://doi.org/10.1007/s11227-014-1209-7

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  • DOI: https://doi.org/10.1007/s11227-014-1209-7

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