Now showing items 1-5 of 5

    • A path-level exact parallelization strategy for sequential simulation 

      Peredo Andrade, Oscar Francisco; Baeza, Daniel; Ortiz, Julian; Herrero Zaragoza, José Ramón (2018-01-01)
      Article
      Open Access
      Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian approach for simulation of conditionally dependent random events, Sequential Indicator Simulation (SIS) method draws simulated ...
    • Acceleration of the Geostatistical Software Library (GSLIB) by code optimization and hybrid parallel programming 

      Peredo Andrade, Oscar Francisco; Ortiz, Julián; Herrero Zaragoza, José Ramón (2015-12-01)
      Article
      Open Access
      The Geostatistical Software Library (GSLIB) has been used in the geostatistical community for more than thirty years. It was designed as a bundle of sequential Fortran codes, and today it is still in use by many practitioners ...
    • Acceleration strategies for large-scale sequential simulations using parallel neighbour search: Non-LVA and LVA scenarios 

      Peredo Andrade, Oscar Francisco; Herrero Zaragoza, José Ramón (2022-03)
      Article
      Open Access
      This paper describes the application of acceleration techniques into existing implementations of Sequential Gaussian Simulation and Sequential Indicator Simulation. These implementations might incorporate Locally Varying ...
    • Adjoint-based PDE-constrained optimization using HPC techniques 

      Peredo Andrade, Oscar Francisco (Universitat Politècnica de Catalunya, 2013-10-02)
      Master thesis
      Open Access
      This work focuses in the utilization of current HPC technologies to explore mathematical optimization algorithms in which a PDE acts as main constraint. A development framework is proposed, together with a novel application ...
    • Large scale geostatistics with locally varying anisotropy 

      Peredo Andrade, Oscar Francisco (Universitat Politècnica de Catalunya, 2022-06-09)
      Doctoral thesis
      Open Access
      Classical geostatistical methods are based on the hypothesis of stationarity, which allows to apply repetitive sampling in different locations of the spatial domain, in order to obtain enough information to infer cumulative ...