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.
Keywords for this software
References in zbMATH (referenced in 815 articles , 2 standard articles )
Showing results 1 to 20 of 815.
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- Beilina, L.; Cristofol, M.; Li, S.; Yamamoto, M.: Lipschitz stability for an inverse hyperbolic problem of determining two coefficients by a finite number of observations (2018)
- Constantinescu, Emil M.: Generalizing global error estimation for ordinary differential equations by using coupled time-stepping methods (2018)
- Garrett, C.Kristopher; Hauck, Cory D.: A fast solver for implicit integration of the Vlasov-Poisson system in the Eulerian framework (2018)
- Gibou, Frederic; Fedkiw, Ronald; Osher, Stanley: A review of level-set methods and some recent applications (2018)
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- Liu, Lulu; Keyes, David E.; Krause, Rolf: A note on adaptive nonlinear preconditioning techniques (2018)
- Mapakshi, N.K.; Chang, J.; Nakshatrala, K.B.: A scalable variational inequality approach for flow through porous media models with pressure-dependent viscosity (2018)
- McRae, Andrew T.T.; Cotter, Colin J.; Budd, Chris J.: Optimal-transport -- based mesh adaptivity on the plane and sphere using finite elements (2018)
- Mezzadri, Francesco; Galligani, Emanuele: An inexact Newton method for solving complementarity problems in hydrodynamic lubrication (2018)
- 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)
- Pospíšil, Lukáš; Gagliardini, Patrick; Sawyer, William; Horenko, Illia: On a scalable nonparametric denoising of time series signals (2018)
- Walker, Shawn W.: FELICITY: a Matlab/C++ toolbox for developing finite element methods and simulation modeling (2018)
- Zhao, Hong-Jie; Yang, Haijian: Semismooth Newton methods with domain decomposition for American options (2018)
- 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)
- 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)