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  • Leveraging task-parallelism in message-passing dense matrix factorizations using SMPSs  Open access

     Martín Huertas, Alberto Francisco; Reyes, Ruyman; Badia Sala, Rosa Maria; Quintana Ortí, Enrique Salvador
    Parallel computing
    Date of publication: 2014-05
    Journal article

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    In this paper, we investigate how to exploit task-parallelism during the execution of the Cholesky factorization on clusters of multicore processors with the SMPSs programming model. Our analysis reveals that the major difficulties in adapting the code for this operation in ScaLAPACK to SMPSs lie in algorithmic restrictions and the semantics of the SMPSs programming model, but also that they both can be overcome with a limited programming effort. The experimental results report considerable gains in performance and scalability of the routine parallelized with SMPSs when compared with conventional approaches to execute the original ScaLAPACK implementation in parallel as well as two recent message-passing routines for this operation. In summary, our study opens the door to the possibility of reusing message-passing legacy codes/libraries for linear algebra, by introducing up-to-date techniques like dynamic out-of-order scheduling that significantly upgrade their performance, while avoiding a costly rewrite/reimplementation.

    In this paper, we investigate how to exploit task-parallelism during the execution of the Cholesky factorization on clusters of multicore processors with the SMPSs programming model. Our analysis reveals that the major difficulties in adapting the code for this operation in ScaLAPACK to SMPSs lie in algorithmic restrictions and the semantics of the SMPSs programming model, but also that they both can be overcome with a limited programming effort. The experimental results report considerable gains in performance and scalability of the routine parallelized with SMPSs when compared with conventional approaches to execute the original ScaLAPACK implementation in parallel as well as two recent message-passing routines for this operation. In summary, our study opens the door to the possibility of reusing message-passing legacy codes/libraries for linear algebra, by introducing up-to-date techniques like dynamic out-of-order scheduling that significantly upgrade their performance, while avoiding a costly rewrite/reimplementation.

  • A highly scalable parallel implementation of balancing domain decomposition by constraints

     Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco; Principe Rubio, Ricardo Javier
    SIAM journal on scientific computing
    Date of publication: 2014-01
    Journal article

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    In this work we propose a novel parallelization approach of two-level balancing domain decomposition by constraints preconditioning based on overlapping of fine-grid and coarse-grid duties in time. The global set of MPI tasks is split into those that have fine-grid duties and those that have coarse-grid duties, and the different computations and communications in the algorithm are then rescheduled and mapped in such a way that the maximum degree of overlapping is achieved while preserving data dependencies among them. In many ranges of interest, the extra cost associated to the coarse-grid problem can be fully masked by fine-grid related computations (which are embarrassingly parallel). Apart from discussing code implementation details, the paper also presents a comprehensive set of numerical experiments that includes weak scalability analyses with structured and unstructured meshes for the three-dimensional Poisson and linear elasticity problems on a pair of state-of-the-art multicore-based distributed-memory machines. This experimental study reveals remarkable weak scalability in the solution of problems with thousands of millions of unknowns on several tens of thousands of computational cores.

  • Implementation and scalability analysis of balancing domain decomposition methods

     Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco; Principe Rubio, Ricardo Javier
    Archives of computational methods in engineering
    Date of publication: 2013
    Journal article

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    n this paper we present a detailed description of a high-performance distributed-memory implementation of balancing domain decomposition preconditioning techniques. This coverage provides a pool of implementation hints and considerations that can be very useful for scientists that are willing to tackle large-scale distributed-memory machines using these methods. On the other hand, the paper includes a comprehensive performance and scalability study of the resulting codes when they are applied for the solution of the Poisson problem on a large-scale multicore-based distributed-memory machine with up to 4096 cores. Well-known theoretical results guarantee the optimality (algorithmic scalability) of these preconditioning techniques for weak scaling scenarios, as they are able to keep the condition number of the preconditioned operator bounded by a constant with fixed load per core and increasing number of cores. The experimental study presented in the paper complements this mathematical analysis and answers how far can these methods go in the number of cores and the scale of the problem to still be within reasonable ranges of efficiency on current distributed-memory machines. Besides, for those scenarios where poor scalability is expected, the study precisely identifies, quantifies and justifies which are the main sources of inefficiency.

  • Enhanced balancing Neumann-Neumann preconditioning in computational fluid and solid mechanics

     Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco; Principe Rubio, Ricardo Javier
    International journal for numerical methods in engineering
    Date of publication: 2013-10
    Journal article

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    In this work, we propose an enhanced implementation of balancing Neumann¿Neumann (BNN) preconditioning together with a detailed numerical comparison against the balancing domain decomposition by constraints (BDDC) preconditioner. As model problems, we consider the Poisson and linear elasticity problems. On one hand, we propose a novel way to deal with singular matrices and pseudo-inverses appearing in local solvers. It is based on a kernel identification strategy that allows us to efficiently compute the action of the pseudo-inverse via local indefinite solvers. We further show how, identifying a minimum set of degrees of freedom to be fixed, an equivalent definite system can be solved instead, even in the elastic case. On the other hand, we propose a simple implementation of the algorithm that reduces the number of Dirichlet solvers to only one per iteration, leading to similar computational cost as additive methods. After these improvements of the BNN preconditioned conjugate gradient algorithm, we compare its performance against that of the BDDC preconditioners on a pair of large-scale distributed-memory platforms. The enhanced BNN method is a competitive preconditioner for three-dimensional Poisson and elasticity problems and outperforms the BDDC method in many cases.

  • Numerical Methods and Tools for Key Exascale Computing Challenges in Engineering and Applied Sciences (NUMEXAS)

     Oñate Ibáñez de Navarra, Eugenio; Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco; Principe Rubio, Ricardo Javier
    Participation in a competitive project

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  • Block recursive LU preconditioners for the thermally coupled incompressible inductionless MHD problem  Open access

     Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco; Planas Badenas, Ramon
    Date: 2013
    Report

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    The thermally coupled incompressible inductionless magnetohydrodynamics (MHD) problem models the ow of an electrically charged fuid under the in uence of an external electromagnetic eld with thermal coupling. This system of partial dierential equations is strongly coupled and highly nonlinear for real cases of interest. Therefore, fully implicit time integration schemes are very desirable in order to capture the dierent physical scales of the problem at hand. However, solving the multiphysics linear systems of equations resulting from such algorithms is a very challenging task which requires ecient and scalable preconditioners. In this work, a new family of recursive block LU preconditioners is designed and tested for solving the thermally coupled inductionless MHD equations. These preconditioners are obtained after splitting the fully coupled matrix into one-physics problems for every variable (velocity, pressure, current density, electric potential and temperature) that can be optimally solved, e.g., using preconditioned domain decomposition algorithms. The main idea is to arrange the original matrix into an (arbitrary) 2 2 block matrix, and consider a LU preconditioner obtained by approximating the corresponding Schur complement. For every one of the diagonal blocks in the LU preconditioner, if it involves more than one type of unknown, we proceed the same way in a recursive fashion. This approach is stated in an abstract way, and can be straightforwardly applied to other multiphysics problems. Further, we precisely explain a fexible and general software design for the code implementation of this type of preconditioners.

    The thermally coupled incompressible inductionless magnetohydrodynamics (MHD) problem models the ow of an electrically charged fuid under the in uence of an external electromagnetic eld with thermal coupling. This system of partial di erential equations is strongly coupled and highly nonlinear for real cases of interest. Therefore, fully implicit time integration schemes are very desirable in order to capture the di erent physical scales of the problem at hand. However, solving the multiphysics linear systems of equations resulting from such algorithms is a very challenging task which requires e cient and scalable preconditioners. In this work, a new family of recursive block LU preconditioners is designed and tested for solving the thermally coupled inductionless MHD equations. These preconditioners are obtained after splitting the fully coupled matrix into one-physics problems for every variable (velocity, pressure, current density, electric potential and temperature) that can be optimally solved, e.g., using preconditioned domain decomposition algorithms. The main idea is to arrange the original matrix into an (arbitrary) 2 2 block matrix, and consider a LU preconditioner obtained by approximating the corresponding Schur complement. For every one of the diagonal blocks in the LU preconditioner, if it involves more than one type of unknown, we proceed the same way in a recursive fashion. This approach is stated in an abstract way, and can be straightforwardly applied to other multiphysics problems. Further, we precisely explain a fexible and general software design for the code implementation of this type of preconditioners.

  • Herramientas Computacionales para Interacción Sólido-Metal Líquido. Aplicación al diseño de módulos de ensayo de envoltura líquida (FUSSIM)

     Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco; Planas Badenas, Ramon; Otin, Ruben
    Participation in a competitive project

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  • Hybrid parallel solvers for the finite element approximation of PDEs

     Principe Rubio, Ricardo Javier; Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco
    World Congress on Computational Mechanics
    Presentation's date: 2012-07-11
    Presentation of work at congresses

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  • Leveraging Task-Parallelism in Energy-Efficient ILU preconditioners

     Aliaga, José Ignacio; Dolz Zaragozá, Manuel Francisco; Martín Huertas, Alberto Francisco; Mayo, Rafael; Quintana Ortí, Enrique Salvador
    International Conference on ICT as Key Technology against Global Warming
    Presentation's date: 2012-09
    Presentation of work at congresses

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    We analyze the energy-performance balance of a task-parallel computation of an ILU-based preconditioner for the solution of sparse linear systems on multi-core processors. In particular, we elaborate a theoretical model for the power dissipation, and employ it to explore the effect of the processor power states on the time-power-energy interaction for this calculation. Armed with the insights gained from this study, we then introduce two energy-saving mechanisms which, incorporated into the runtime in charge of the parallel execution of the algorithm, improve energy efficiency by 6.9%, with a negligible impact on performance.

  • Exploiting thread-level parallelism in the iterative solution of sparse linear systems

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Parallel computing
    Date of publication: 2011-03
    Journal article

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  • ILUPACK

     Bollhoefer, Matthias; Aliaga, José Ignacio; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Date of publication: 2011
    Book chapter

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  • Computational Methods for Fusion Technology (COMFUS)

     Badia Rodriguez, Santiago I.; Martín Huertas, Alberto Francisco; Principe Rubio, Ricardo Javier; Planas Badenas, Ramon; Otin, Ruben
    Participation in a competitive project

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  • Symmetric rank-k update on clusters of multicore processors with SMPSs  Open access

     Badia Sala, Rosa Maria; Labarta Mancho, Jesus Jose; Marjanovic, Vladimir; Martín Huertas, Alberto Francisco; Mayo, Rafael; Quintana Ortí, Enrique Salvador; Reyes, Ruymán
    International Conference on Parallel Computing
    Presentation's date: 2011-09
    Presentation of work at congresses

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    We investigate the use of the SMPSs programming model to leverage task parallelism in the execution of a message-pas sing implementation of the symmetric rank- k update on clusters equipped with multicore processors. Our experience shows that the major difficulties to adapt the code to the MPI/SMPSs instance of this programming model are due to the usage of the conventional column-major layout of matrices in numerical libraries. On the other hand, the experimental results show a considerable increase in the performance and scalability of our solution when compared with the standard options based on the use of a pure MPI approach or a hybrid one that combines MPI/multi-threaded BLAS.

  • Exploiting thread-level parallelism in the multilevel ILU preconditioning of large sparse linear systems

     Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador; Aliaga, José Ignacio; Bollhoefer, Matthias
    International Linear Algebra Society Conference
    Presentation's date: 2011-08
    Presentation of work at congresses

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  • Desarrollo e implementación de la versión paralela de ILUPACK en multiprocesadores con memoria distribuida, e integración en SLEPc

     Martín Huertas, Alberto Francisco; Aliaga, José Ignacio; Quintana Ortí, Enrique Salvador; Román Moltó, José Enrique; Romero Alcalde, Eloy
    Participation in a competitive project

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  • Towards EXaflop applicaTions - TEXT

     Valero Cortes, Mateo; Martín Huertas, Alberto Francisco
    Participation in a competitive project

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  • Red de computación de altas prestaciones sobre arquitecturas paralelas heterogéneas (CAPAP-H2)

     Quintana Ortí, Enrique Salvador; Martín Huertas, Alberto Francisco
    Participation in a competitive project

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  • Parallelization of Multilevel ILU Preconditioners on Distributed-Memory Multiprocessors

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Conference on state of the Art in Scientific and Parallel Computing
    Presentation's date: 2010-06
    Presentation of work at congresses

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  • Paralelización sobre multiprocesadores con memoria distribuida del cálculo de precondicionadores ILU multinivel

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Encuentro de Álgebra Lineal, Análisis Matricial y Aplicaciones
    Presentation's date: 2010-06
    Presentation of work at congresses

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  • Fusion Technology Programme (TECNO_FUS)

     Sedano, L.A.; Badia Rodriguez, Santiago I.; Otin, Ruben; Planas Badenas, Ramon; Principe Rubio, Ricardo Javier; Martín Huertas, Alberto Francisco
    Participation in a competitive project

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  • Construcción y optimización automáticas de bibliotecas paralelas de computación científica (COPABIB)

     Quintana Ortí, Enrique Salvador; Martín Huertas, Alberto Francisco
    Participation in a competitive project

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  • Recent advances in the parallel iterative solution of large-scale sparse linear systems

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    International Conference on Computational and Mathematical Methods in Science and Engineering
    Presentation's date: 2009-07
    Presentation of work at congresses

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  • Evaluation of parallel sparse matrix partitioning software for parallel multilevel ILU preconditioning on shared-memory multiprocessors

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    International Conference on Parallel Computing
    Presentation's date: 2009-09
    Presentation of work at congresses

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  • Avances en la resolución paralela de sistemas de ecuaciones lineales precondicionados mediante factorizaciones ILU multinivel

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Congreso de Métodos Numéricos en Ingeniería
    Presentation's date: 2009-07
    Presentation of work at congresses

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  • Fast development of dense linear algebra codes on graphics processors

     Zafont Alcázar, Maria Jesus; Martín Huertas, Alberto Francisco; Igual, Francisco D.; Quintana Ortí, Enrique Salvador
    IEEE International Parallel and Distributed Processing Symposium
    Presentation's date: 2009-05
    Presentation of work at congresses

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  • Diseño y desarrollo de una nueva generación de bibliotecas paralelas de computación matricial para procesadores multinúcleo y de herramientas para su construcción y análisis semiautomáticos

     Quintana-Ortí, Gregorio; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Participation in a competitive project

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  • Parallelization of multilevel preconditioners constructed from inverse-based ILUs (Acciones integradas Hispano-Alemanas)

     Aliaga, José Ignacio; Martín Huertas, Alberto Francisco; Bollhoefer, Matthias; Quintana Ortí, Enrique Salvador
    Participation in a competitive project

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  • Red de computación de altas prestaciones sobre arquitecturas paralelas heterogéneas (CAPAP-H)

     Quintana Ortí, Enrique Salvador; Martín Huertas, Alberto Francisco
    Participation in a competitive project

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  • Scheduling strategies for parallel sparse backward/forward substitution

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Conference on state of the Art in Scientific and Parallel Computing
    Presentation's date: 2008-05
    Presentation of work at congresses

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  • FLAG/C: una API para computación matricial sobre GPUs

     Zafont Alcázar, Maria Jesus; Martín Huertas, Alberto Francisco; Igual, Francisco D.; Quintana Ortí, Enrique Salvador
    Workshop Aplicaciones de Nuevas Arquitecturas de Consumo y Altas Prestaciones
    Presentation's date: 2008-11
    Presentation of work at congresses

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  • Scheduling strategies for parallel sparse linear algebra computacions on multithreaded architectures

     Aliaga, José Ignacio; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Jornadas de Paralelismo
    Presentation's date: 2008-09
    Presentation of work at congresses

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  • Design, tuning and evaluation of parallel multilevel ILU preconditioners

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    International Meeting High Performance Computing for Computational Science
    Presentation's date: 2008-06
    Presentation of work at congresses

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    In this paper, we present a parallel multilevel ILU preconditioner implemented with OpenMP. We employ METIS partitioning algorithms to decompose the computation into concurrent tasks, which are then scheduled to threads. Concretely, we combine decompositions which obtain significantly more tasks than processors, and the use of dynamic scheduling strategies in order to reduce the thread’s idle time, which it is shown to be the main source of overhead in our parallel algorithm. Experimental results on a shared-memory platform consisting of 16 processors report remarkable performance for our approach.

  • Parallelization of multilevel preconditioners constructed from inverse-based ILUs on shared-memory multiprocessors

     Aliaga, José Ignacio; Bollhoefer, Matthias; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    International Conference on Parallel Computing
    Presentation's date: 2007-09
    Presentation of work at congresses

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  • La interfaz de usuario de alto nivel PyPLiC para la biblioteca paralela PLiCMR

     Galiano Ibarra, Vicente; Migallón Gomis, Héctor; Migallón Gomis, Violeta; Penadés Martínez, José; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Jornadas de Paralelismo
    Presentation's date: 2007-09
    Presentation of work at congresses

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  • PyPLiC: A High-Level Interface to the Parallel Model Reduction Library PLiCMR

     Galiano Ibarra, Vicente; Martín Huertas, Alberto Francisco; Migallón Gomis, Héctor; Migallón Gomis, Violeta; Penadés Martínez, José; Quintana Ortí, Enrique Salvador
    International Conference on Civil, Structural and Environmental Engineering Computing
    Presentation's date: 2007-09
    Presentation of work at congresses

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  • Optimización de algoritmos de álgebra lineal dispersa para MMCs mediante KOJAK y VAMPIR

     Aliaga, José Ignacio; Martín Huertas, Alberto Francisco; Quintana Ortí, Enrique Salvador
    Jornadas de Paralelismo
    Presentation's date: 2007-09
    Presentation of work at congresses

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  • Plataforma de acceso computacional para la reducción de modelos entre Octave y un clúster paralelo

     Martín Huertas, Alberto Francisco; Mayo Gual, Rafael; Quintana Ortí, Enrique Salvador
    Jornadas de Paralelismo
    Presentation's date: 2006-09
    Presentation of work at congresses

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  • Computación en paralelo y sistemas heterogéneos (COMPARHE)

     Quintana Ortí, Enrique Salvador; Martín Huertas, Alberto Francisco
    Participation in a competitive project

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  • Premio Extraordinario Fin de Carrera de Ingeniería Informática (plan de 1991)

     Martín Huertas, Alberto Francisco
    Award or recognition

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  • Premio Ernest Breva Mallach to the effort and academic excellence

     Martín Huertas, Alberto Francisco
    Award or recognition

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