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Keywords = PETSc

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13 pages, 1202 KiB  
Article
A Parallel Solver for FSI Problems with Fictitious Domain Approach
by Daniele Boffi, Fabio Credali, Lucia Gastaldi and Simone Scacchi
Math. Comput. Appl. 2023, 28(2), 59; https://doi.org/10.3390/mca28020059 - 10 Apr 2023
Cited by 2 | Viewed by 2302
Abstract
We present and analyze a parallel solver for the solution of fluid structure interaction problems described by a fictitious domain approach. In particular, the fluid is modeled by the non-stationary incompressible Navier–Stokes equations, while the solid evolution is represented by the elasticity equations. [...] Read more.
We present and analyze a parallel solver for the solution of fluid structure interaction problems described by a fictitious domain approach. In particular, the fluid is modeled by the non-stationary incompressible Navier–Stokes equations, while the solid evolution is represented by the elasticity equations. The parallel implementation is based on the PETSc library and the solver has been tested in terms of robustness with respect to mesh refinement and weak scalability by running simulations on a Linux cluster. Full article
(This article belongs to the Special Issue Current Problems and Advances in Computational and Applied Mechanics)
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21 pages, 4756 KiB  
Article
MPI Parallelization of Numerical Simulations for Pulsed Vacuum Arc Plasma Plumes Based on a Hybrid DSMC/PIC Algorithm
by Fuxiang Yang, Jie Li, Chuanfu Xu, Dali Li, Haozhong Qiu and Ao Xu
Aerospace 2022, 9(10), 538; https://doi.org/10.3390/aerospace9100538 - 23 Sep 2022
Cited by 3 | Viewed by 1988
Abstract
The transport characteristics of the unsteady flow field in rarefied plasma plumes is crucial for a pulsed vacuum arc in which the particle distribution varies from 1016 to 1022 m−3. The direct simulation Monte Carlo (DSMC) method and particle-in-cell [...] Read more.
The transport characteristics of the unsteady flow field in rarefied plasma plumes is crucial for a pulsed vacuum arc in which the particle distribution varies from 1016 to 1022 m−3. The direct simulation Monte Carlo (DSMC) method and particle-in-cell (PIC) method are generally combined to study this kind of flow field. The DSMC method simulates the motion of neutral particles, while the PIC method simulates the motion of charged ions. A hybrid DSMC/PIC algorithm is investigated here to determine the unsteady axisymmetric flow characteristics of vacuum arc plasma plume expansion. Numerical simulations are found to be consistent with the experiments performed in the plasma mass and energy analyzer (EQP). The electric field is solved by Poisson’s equation, which is usually computationally expensive. The compressed sparse row (CSR) format is used to store the huge diluted matrix and PETSc library to solve Poisson’s equation through parallel calculations. Double weight factors and two timesteps under two grid sets are investigated using the hybrid DSMC/PIC algorithm. The fine PIC grid is nested in the coarse DSMC grid. Therefore, METIS is used to divide the much smaller coarse DSMC grid when dynamic load imbalances arise. Two parameters are employed to evaluate and distribute the computational load of each process. Due to the self-adaption of the dynamic-load-balancing parameters, millions of grids and more than 150 million particles are employed to predict the transport characteristics of the rarefied plasma plume. Atomic Ti and Ti2+ are injected into the small cylinders. The comparative analysis shows that the diffusion rate of Ti2+ is faster than that of atomic Ti under the electric field, especially in the z-direction. The fully diffuse reflection wall model is adopted, showing that neutral particles accumulate on the wall, while charged ions do not—due to their self-consistent electric field. The maximum acceleration ratio is about 17.94. Full article
(This article belongs to the Section Astronautics & Space Science)
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16 pages, 1137 KiB  
Article
A Comparative Study of Block Incomplete Sparse Approximate Inverses Preconditioning on Tesla K20 and V100 GPUs
by Wenpeng Ma, Wu Yuan and Xiazhen Liu
Algorithms 2021, 14(7), 204; https://doi.org/10.3390/a14070204 - 30 Jun 2021
Viewed by 3095
Abstract
Incomplete Sparse Approximate Inverses (ISAI) has shown some advantages over sparse triangular solves on GPUs when it is used for the incomplete LU based preconditioner. In this paper, we extend the single GPU method for Block–ISAI to multiple GPUs algorithm by coupling Block–Jacobi [...] Read more.
Incomplete Sparse Approximate Inverses (ISAI) has shown some advantages over sparse triangular solves on GPUs when it is used for the incomplete LU based preconditioner. In this paper, we extend the single GPU method for Block–ISAI to multiple GPUs algorithm by coupling Block–Jacobi preconditioner, and introduce the detailed implementation in the open source numerical package PETSc. In the experiments, two representative cases are performed and a comparative study of Block–ISAI on up to four GPUs are conducted on two major generations of NVIDIA’s GPUs (Tesla K20 and Tesla V100). Block–Jacobi preconditioning with Block–ISAI (BJPB-ISAI) shows an advantage over the level-scheduling based triangular solves from the cuSPARSE library for the cases, and the overhead of setting up Block–ISAI and the total wall clock times of GMRES is greatly reduced using Tesla V100 GPUs compared to Tesla K20 GPUs. Full article
(This article belongs to the Section Parallel and Distributed Algorithms)
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26 pages, 2079 KiB  
Article
Parallel Implementation of a PETSc-Based Framework for the General Curvilinear Coastal Ocean Model
by Manuel Valera, Mary P. Thomas, Mariangel Garcia and Jose E. Castillo
J. Mar. Sci. Eng. 2019, 7(6), 185; https://doi.org/10.3390/jmse7060185 - 13 Jun 2019
Cited by 3 | Viewed by 5202
Abstract
The General Curvilinear Coastal Ocean Model (GCCOM) is a 3D curvilinear, structured-mesh, non-hydrostatic, large-eddy simulation model that is capable of running oceanic simulations. GCCOM is an inherently computationally expensive model: it uses an elliptic solver for the dynamic pressure; meter-scale simulations requiring memory [...] Read more.
The General Curvilinear Coastal Ocean Model (GCCOM) is a 3D curvilinear, structured-mesh, non-hydrostatic, large-eddy simulation model that is capable of running oceanic simulations. GCCOM is an inherently computationally expensive model: it uses an elliptic solver for the dynamic pressure; meter-scale simulations requiring memory footprints on the order of 10 12 cells and terabytes of output data. As a solution for parallel optimization, the Fortran-interfaced Portable–Extensible Toolkit for Scientific Computation (PETSc) library was chosen as a framework to help reduce the complexity of managing the 3D geometry, to improve parallel algorithm design, and to provide a parallelized linear system solver and preconditioner. GCCOM discretizations are based on an Arakawa-C staggered grid, and PETSc DMDA (Data Management for Distributed Arrays) objects were used to provide communication and domain ownership management of the resultant multi-dimensional arrays, while the fully curvilinear Laplacian system for pressure is solved by the PETSc linear solver routines. In this paper, the framework design and architecture are described in detail, and results are presented that demonstrate the multiscale capabilities of the model and the parallel framework to 240 cores over domains of order 10 7 total cells per variable, and the correctness and performance of the multiphysics aspects of the model for a baseline experiment stratified seamount. Full article
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17 pages, 1342 KiB  
Article
Distributing Load Flow Computations Across System Operators Boundaries Using the Newton–Krylov–Schwarz Algorithm Implemented in PETSc
by Stefano Guido Rinaldo, Andrea Ceresoli, Domenico J. P. Lahaye, Marco Merlo, Miloš Cvetković, Silvia Vitiello and Gianluca Fulli
Energies 2018, 11(11), 2910; https://doi.org/10.3390/en11112910 - 25 Oct 2018
Cited by 3 | Viewed by 3238
Abstract
The upward trends in renewable energy penetration, cross-border flow volatility and electricity actors’ proliferation pose new challenges in the power system management. Electricity and market operators need to increase collaboration, also in terms of more frequent and detailed system analyses, so as to [...] Read more.
The upward trends in renewable energy penetration, cross-border flow volatility and electricity actors’ proliferation pose new challenges in the power system management. Electricity and market operators need to increase collaboration, also in terms of more frequent and detailed system analyses, so as to ensure adequate levels of quality and security of supply. This work proposes a novel distributed load flow solver enabling for better cross border flow analysis and fulfilling possible data ownership and confidentiality arrangements in place among the actors. The model exploits an Inexact Newton Method, the Newton–Krylov–Schwarz method, available in the portable, extensible toolkit for scientific computation (PETSc) libraries. A case-study illustrates a real application of the model for the TSO–TSO (transmission system operator) cross-border operation, analyzing the specific policy context and proposing a test case for a coordinated power flow simulation. The results show the feasibility of performing the distributed calculation remotely, keeping the overall simulation times only a few times slower than locally. Full article
(This article belongs to the Section F: Electrical Engineering)
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