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 1182 articles , 2 standard articles )

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  1. 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)
  2. 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)
  3. 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)
  4. 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)
  5. Bueler, Ed: PETSc for partial differential equations. Numerical solutions in C and Python (2021)
  6. Büsing, Henrik: Efficient solution techniques for two-phase flow in heterogeneous porous media using exact Jacobians (2021)
  7. 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
  8. Kamensky, David: Open-source immersogeometric analysis of fluid-structure interaction using FEniCS and tIGAr (2021)
  9. Kashi, Aditya; Nadarajah, Sivakumaran: An asynchronous incomplete block Lu preconditioner for computational fluid dynamics on unstructured grids (2021)
  10. Sebastian Blauth: cashocs: A Computational, Adjoint-Based Shape Optimization and Optimal Control Software (2021) not zbMATH
  11. Steefel, Carl I.; Tournassat, Christophe: A model for discrete fracture-clay rock interaction incorporating electrostatic effects on transport (2021)
  12. Williams, J. G.; Wechsung, F.; Turney, B. W.; Waters, S. L.; Moulton, D. E.: Shape optimisation for faster washout in recirculating flows (2021)
  13. Xing, F.: New optimized Schwarz algorithms for one dimensional Schrödinger equation with general potential (2021)
  14. Zhu, Qiming; Yan, Jinhui: A moving-domain CFD solver in FEniCS with applications to tidal turbine simulations in turbulent flows (2021)
  15. 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)
  16. Abgrall, R.; Nordström, J.; Öffner, P.; Tokareva, S.: Analysis of the SBP-SAT stabilization for finite element methods I: Linear problems (2020)
  17. Abhyankar, Shrirang; Betrie, Getnet; Maldonado, Daniel Adrian; Mcinnes, Lois C.; Smith, Barry; Zhang, Hong: PETSc DMNetwork: a library for scalable network PDE-based multiphysics simulations (2020)
  18. Ahrabi, Behzad R.; Mavriplis, Dimitri J.: An implicit block ILU smoother for preconditioning of Newton-Krylov solvers with application in high-order stabilized finite-element methods (2020)
  19. Alberto Paganini, Florian Wechsung: Fireshape: a shape optimization toolbox for Firedrake (2020) arXiv
  20. Ambartsumyan, Ilona; Boukaram, Wajih; Bui-Thanh, Tan; Ghattas, Omar; Keyes, David; Stadler, Georg; Turkiyyah, George; Zampini, Stefano: Hierarchical matrix approximations of Hessians arising in inverse problems governed by PDEs (2020)

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