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.

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  1. Araujo-Cabarcas, Juan Carlos; Engström, Christian; Jarlebring, Elias: Efficient resonance computations for Helmholtz problems based on a Dirichlet-to-Neumann map (2018)
  2. Constantinescu, Emil M.: Generalizing global error estimation for ordinary differential equations by using coupled time-stepping methods (2018)
  3. Gibou, Frederic; Fedkiw, Ronald; Osher, Stanley: A review of level-set methods and some recent applications (2018)
  4. Huang, Jizu; Wang, Xiao-Ping: A lattice Boltzmann model for multiphase flows with moving contact line and variable density (2018)
  5. Oh, Duk-Soon; Widlund, Olof B.; Zampini, Stefano; Dohrmann, Clark R.: BDDC algorithms with deluxe scaling and adaptive selection of primal constraints for Raviart-Thomas vector fields (2018)
  6. Adams, Mark F.; Hirvijoki, Eero; Knepley, Matthew G.; Brown, Jed; Isaac, Tobin; Mills, Richard: Landau collision integral solver with adaptive mesh refinement on emerging architectures (2017)
  7. A.F. Sarmiento, A.M.A. Cortes, D.A. Garcia, L. Dalcin, N. Collier, V.M. Calo: PetIGA-MF: A multi-field high-performance toolbox for structure-preserving B-splines spaces (2017)
  8. Afzal, Asif; Ansari, Zahid; Rimaz Faizabadi, Ahmed; Ramis, M.K.: Parallelization strategies for computational fluid dynamics software: state of the art review (2017)
  9. Ambrosi, D.; Pezzuto, S.; Riccobelli, D.; Stylianopoulos, T.; Ciarletta, P.: Solid tumors are poroelastic solids with a chemo-mechanical feedback on growth (2017)
  10. Arndt, Daniel; Bangerth, Wolfgang; Davydov, Denis; Heister, Timo; Heltai, Luca; Kronbichler, Martin; Maier, Matthias; Pelteret, Jean-Paul; Turcksin, Bruno; Wells, David: The deal.II library, version 8.5 (2017)
  11. Baiges, Joan; Bayona, Camilo: RefficientLib: an efficient load-rebalanced adaptive mesh refinement algorithm for high-performance computational physics meshes (2017)
  12. Beilina, Larisa; Karchevskii, Evgenii; Karchevskii, Mikhail: Numerical linear algebra: theory and applications (2017)
  13. Beirão da Veiga, L.; Pavarino, L.F.; Scacchi, S.; Widlund, O.B.; Zampini, S.: Adaptive selection of primal constraints for isogeometric BDDC deluxe preconditioners (2017)
  14. Besse, Christophe; Xing, Feng: Domain decomposition algorithms for two dimensional linear Schrödinger equation (2017)
  15. Besse, Christophe; Xing, Feng: Schwarz waveform relaxation method for one-dimensional Schrödinger equation with general potential (2017)
  16. Botti, L.; Colombo, A.; Bassi, F.: $h$-multigrid agglomeration based solution strategies for discontinuous Galerkin discretizations of incompressible flow problems (2017)
  17. Čermák, Martin; Hapla, Václav; Kružík, Jakub; Markopoulos, Alexandros; Vašatová, Alena: Comparison of different FETI preconditioners for elastoplasticity (2017)
  18. Chang, J.; Karra, S.; Nakshatrala, K.B.: Large-scale optimization-based non-negative computational framework for diffusion equations: parallel implementation and performance studies (2017)
  19. Chapman, S.J.; Farrell, Patrick E.: Analysis of Carrier’s problem (2017)
  20. Cher, Yuri; Simpson, Gideon; Sulem, Catherine: Local structure of singular profiles for a derivative nonlinear Schrödinger equation (2017)

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