petsc4py

PETSc for Python: This document describes petsc4py, a Python port to the PETSc libraries. PETSc (the Portable, Extensible Toolkit for Scientific Computation) is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It employs the MPI standard for all message-passing communication. This package provides an important subset of PETSc functionalities and uses NumPy to efficiently manage input and output of array data.


References in zbMATH (referenced in 43 articles )

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  1. Grekas, Georgios; Koumatos, Konstantinos; Makridakis, Charalambos; Rosakis, Phoebus: Approximations of energy minimization in cell-induced phase transitions of fibrous biomaterials: (\Gamma)-convergence analysis (2022)
  2. Joshaghani, M. S.; Riviere, B.; Sekachev, M.: Maximum-principle-satisfying discontinuous Galerkin methods for incompressible two-phase immiscible flow (2022)
  3. Zhang, Hong; Constantinescu, Emil M.; Smith, Barry F.: \textttPETScTSAdjoint: a discrete adjoint ODE solver for first-order and second-order sensitivity analysis (2022)
  4. Allen, Jeffery M.; Chang, Justin; Usseglio-Viretta, Francois L. E.; Graf, Peter; Smith, Kandler: A segregated approach for modeling the electrochemistry in the 3-D microstructure of li-ion batteries and its acceleration using block preconditioners (2021)
  5. Bastian, Peter; Blatt, Markus; Dedner, Andreas; Dreier, Nils-Arne; Engwer, Christian; Fritze, René; Gräser, Carsten; Grüninger, Christoph; Kempf, Dominic; Klöfkorn, Robert; Ohlberger, Mario; Sander, Oliver: The \textscDuneframework: basic concepts and recent developments (2021)
  6. Elliott, C. M.; Hatcher, L.: Domain formation via phase separation for spherical biomembranes with small deformations (2021)
  7. Gbikpi-Benissan, Guillaume; Magoulès, Frédéric: Asynchronous substructuring method with alternating local and global iterations (2021)
  8. Graham, I. G.; Pembery, O. R.; Spence, E. A.: Analysis of a Helmholtz preconditioning problem motivated by uncertainty quantification (2021)
  9. Kamensky, David: Open-source immersogeometric analysis of fluid-structure interaction using FEniCS and tIGAr (2021)
  10. Kirby, Robert C.; Klöckner, Andreas; Sepanski, Ben: Finite elements for Helmholtz equations with a nonlocal boundary condition (2021)
  11. Marazzato, Frédéric: A variational discrete element method for the computation of Cosserat elasticity (2021)
  12. Zhang, Junqi; Ankit, Ankit; Gravenkamp, Hauke; Eisenträger, Sascha; Song, Chongmin: A massively parallel explicit solver for elasto-dynamic problems exploiting octree meshes (2021)
  13. Zimmerman, Alexander G.; Kowalski, Julia: Mixed finite elements for convection-coupled phase-change in enthalpy form: open software verified and applied to 2D benchmarks (2021)
  14. Chen, Tyler; Carson, Erin: Predict-and-recompute conjugate gradient variants (2020)
  15. Nennig, Benoit; Perrey-Debain, Emmanuel: A high order continuation method to locate exceptional points and to compute Puiseux series with applications to acoustic waveguides (2020)
  16. Niewiarowski, Alexander; Adriaenssens, Sigrid; Pauletti, Ruy Marcelo: Adjoint optimization of pressurized membrane structures using automatic differentiation tools (2020)
  17. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in Python using sfepy (2019)
  18. Cotter, Colin; Crisan, Dan; Holm, Darryl D.; Pan, Wei; Shevchenko, Igor: Numerically modeling stochastic Lie transport in fluid dynamics (2019)
  19. Gjerde, Ingeborg G.; Kumar, Kundan; Nordbotten, Jan M.; Wohlmuth, Barbara: Splitting method for elliptic equations with line sources (2019)
  20. Joshaghani, M. S.; Chang, J.; Nakshatrala, K. B.; Knepley, M. G.: Composable block solvers for the four-field double porosity/permeability model (2019)

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