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An efficient GPU version of the preconditioned GMRES method

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An efficient GPU version of the preconditioned GMRES method

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Aliaga, JI.; Dufrechou, E.; Ezzatti, P.; Quintana-Orti, ES. (2019). An efficient GPU version of the preconditioned GMRES method. The Journal of Supercomputing. 75(3):1455-1469. https://doi.org/10.1007/s11227-018-2658-1

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Título: An efficient GPU version of the preconditioned GMRES method
Autor: Aliaga, Jose I. Dufrechou, Ernesto Ezzatti, Pablo Quintana-Orti, Enrique S.
Entidad UPV: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Resumen:
[EN] In a large number of scientific applications, the solution of sparse linear systems is the stage that concentrates most of the computational effort. This situation has motivated the study and development of several ...[+]
Palabras clave: GPUs , GMRES , Sparse triangular solver , MGSO
Derechos de uso: Reserva de todos los derechos
Fuente:
The Journal of Supercomputing. (issn: 0920-8542 )
DOI: 10.1007/s11227-018-2658-1
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/s11227-018-2658-1
Tipo: Artículo

References

Aliaga JI, Badia RM, Barreda M, Bollhöfer M, Dufrechou E, Ezzatti P, Quintana-Ortí ES (2016) Exploiting task and data parallelism in ILUPACK’s preconditioned CG solver on NUMA architectures and many-core accelerators. Parallel Comput 54:97–107

Aliaga JI, Bollhöfer M, Dufrechou E, Ezzatti P, Quintana-Ortí ES (2016) A data-parallel ILUPACK for sparse general and symmetric indefinite linear systems. In: Lecture Notes in Computer Science, 14th Int. Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms—HeteroPar’16. Springer

Aliaga JI, Bollhöfer M, Martín AF, Quintana-Ortí ES (2011) Exploiting thread-level parallelism in the iterative solution of sparse linear systems. Parallel Comput 37(3):183–202 [+]
Aliaga JI, Badia RM, Barreda M, Bollhöfer M, Dufrechou E, Ezzatti P, Quintana-Ortí ES (2016) Exploiting task and data parallelism in ILUPACK’s preconditioned CG solver on NUMA architectures and many-core accelerators. Parallel Comput 54:97–107

Aliaga JI, Bollhöfer M, Dufrechou E, Ezzatti P, Quintana-Ortí ES (2016) A data-parallel ILUPACK for sparse general and symmetric indefinite linear systems. In: Lecture Notes in Computer Science, 14th Int. Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms—HeteroPar’16. Springer

Aliaga JI, Bollhöfer M, Martín AF, Quintana-Ortí ES (2011) Exploiting thread-level parallelism in the iterative solution of sparse linear systems. Parallel Comput 37(3):183–202

Aliaga JI, Bollhöfer M, Martín AF, Quintana-Ortí ES (2012) Parallelization of multilevel ILU preconditioners on distributed-memory multiprocessors. Appl Parallel Sci Comput LNCS 7133:162–172

Aliaga JI, Dufrechou E, Ezzatti P, Quintana-Ortí ES (2018) Accelerating a preconditioned GMRES method in massively parallel processors. In: CMMSE 2018: Proceedings of the 18th International Conference on Mathematical Methods in Science and Engineering (2018)

Bollhöfer M, Grote MJ, Schenk O (2009) Algebraic multilevel preconditioner for the Helmholtz equation in heterogeneous media. SIAM J Sci Comput 31(5):3781–3805

Bollhöfer M, Saad Y (2006) Multilevel preconditioners constructed from inverse-based ILUs. SIAM J Sci Comput 27(5):1627–1650

Dufrechou E, Ezzatti P (2018) A new GPU algorithm to compute a level set-based analysis for the parallel solution of sparse triangular systems. In: 2018 IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018, Canada, 2018. IEEE Computer Society

Dufrechou E, Ezzatti P (2018) Solving sparse triangular linear systems in modern GPUs: a synchronization-free algorithm. In: 2018 26th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp 196–203. https://doi.org/10.1109/PDP2018.2018.00034

Eijkhout V (1992) LAPACK working note 50: distributed sparse data structures for linear algebra operations. Tech. rep., Knoxville, TN, USA

Golub GH, Van Loan CF (2013) Matrix computations

He K, Tan SXD, Zhao H, Liu XX, Wang H, Shi G (2016) Parallel GMRES solver for fast analysis of large linear dynamic systems on GPU platforms. Integration 52:10–22 http://www.sciencedirect.com/science/article/pii/S016792601500084X

Liu W, Li A, Hogg JD, Duff IS, Vinter B (2017) Fast synchronization-free algorithms for parallel sparse triangular solves with multiple right-hand sides. Concurr Comput 29(21)

Saad Y (2003) Iterative methods for sparse linear systems, 2nd edn. SIAM, Philadelphia

Schenk O, Wächter A, Weiser M (2008) Inertia revealing preconditioning for large-scale nonconvex constrained optimization. SIAM J Sci Comput 31(2):939–960

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