PETSc

The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear, nonlinear equation solvers and time integrators that may be used in application codes written in Fortran, C, C++, Python, and MATLAB (sequential). PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++ or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than “rolling them” yourself.


References in zbMATH (referenced in 1228 articles , 2 standard articles )

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  1. Alet, Fabien; Hanada, Masanori; Jevicki, Antal; Peng, Cheng: Entanglement and confinement in coupled quantum systems (2021)
  2. 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)
  3. Anderson, Robert; Andrej, Julian; Barker, Andrew; Bramwell, Jamie; Camier, Jean-Sylvain; Cerveny, Jakub; Dobrev, Veselin; Dudouit, Yohann; Fisher, Aaron; Kolev, Tzanio; Pazner, Will; Stowell, Mark; Tomov, Vladimir; Akkerman, Ido; Dahm, Johann; Medina, David; Zampini, Stefano: MFEM: a modular finite element methods library (2021)
  4. Anuprienko, Denis; Kapyrin, Ivan: Nonlinearity continuation method for steady-state groundwater flow modeling in variably saturated conditions (2021)
  5. Arndt, Daniel; Bangerth, Wolfgang; Davydov, Denis; Heister, Timo; Heltai, Luca; Kronbichler, Martin; Maier, Matthias; Pelteret, Jean-Paul; Turcksin, Bruno; Wells, David: The \textscdeal.II finite element library: design, features, and insights (2021)
  6. Ashour, Mohammed; Valizadeh, Navid; Rabczuk, Timon: Isogeometric analysis for a phase-field constrained optimization problem of morphological evolution of vesicles in electrical fields (2021)
  7. Axelsson, Owe; Liang, Zhao-Zheng; Kruzik, Jakub; Horak, David: Inner product free iterative solution and elimination methods for linear systems of a three-by-three block matrix form (2021)
  8. Badia, Santiago; Martín, Alberto F.; Neiva, Eric; Verdugo, Francesc: The aggregated unfitted finite element method on parallel tree-based adaptive meshes (2021)
  9. Badri, M. A.; Rastiello, G.; Foerster, E.: Preconditioning strategies for vectorial finite element linear systems arising from phase-field models for fracture mechanics (2021)
  10. Bevilacqua, Giulia; Ciarletta, Pasquale; Quarteroni, Alfio: Morphomechanical model of the torsional c-looping in the embryonic heart (2021)
  11. Bonart, Henning; Kahle, Christian: Optimal control of sliding droplets using the contact angle distribution (2021)
  12. Brown et al.: libCEED: Fast algebra for high-order element-based discretizations (2021) not zbMATH
  13. Bueler, Ed: PETSc for partial differential equations. Numerical solutions in C and Python (2021)
  14. Büsing, Henrik: Efficient solution techniques for two-phase flow in heterogeneous porous media using exact Jacobians (2021)
  15. Cappanera, L.; Debue, P.; Faller, H.; Kuzzay, D.; Saw, E-W.; Nore, C.; Guermond, J.-L.; Daviaud, F.; Wiertel-Gasquet, C.; Dubrulle, B.: Turbulence in realistic geometries with moving boundaries: when simulations meet experiments (2021)
  16. Chi, Heng; Zhang, Yuyu; Tang, Tsz Ling Elaine; Mirabella, Lucia; Dalloro, Livio; Song, Le; Paulino, Glaucio H.: Universal machine learning for topology optimization (2021)
  17. E. Alinovi, J. Guerrero: FLUBIO -An unstructured, parallel, finite-volume based Navier–Stokes and convection-diffusion like equations solver for teaching and research purposes (2021) not zbMATH
  18. Farrell, Patrick E.; Mitchell, Lawrence; Scott, L. Ridgway; Wechsung, Florian: A Reynolds-robust preconditioner for the Scott-Vogelius discretization of the stationary incompressible Navier-Stokes equations (2021)
  19. Hapla, Vaclav; Knepley, Matthew G.; Afanasiev, Michael; Boehm, Christian; van Driel, Martin; Krischer, Lion; Fichtner, Andreas: Fully parallel mesh I/O using PETSc DMPlex with an application to waveform modeling (2021)
  20. Kambampati, Sandilya; Chung, Hayoung; Kim, H. Alicia: A discrete adjoint based level set topology optimization method for stress constraints (2021)

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