PETSc 3.19#

PETSc, the Portable, Extensible Toolkit for Scientific Computation, pronounced PET-see (/ˈpɛt-siː/), is for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It has bindings for C, Fortran, and Python (via petsc4py). PETSc also contains TAO, the Toolkit for Advanced Optimization, software library. It supports MPI, and GPUs through CUDA, HIP or OpenCL, as well as hybrid MPI-GPU parallelism; it also supports the NEC-SX Tsubasa Vector Engine. Immediately jump in and run PETSc code Tutorials, by Mathematical Problem.

PETSc is developed as open-source, requests and contributions are welcome.

News#

News: PETSc is now associated with NumFOCUS, a 501(c)(3) nonprofit supporting open code and reproducible science, through which you can help support PETSc.

_images/numfocus.png

News: PETSc 2024 Annual Meeting

The PETSc 2024 Annual Meeting will take place May 23, 24 in Cologne, Germany

News: Book on numerical methods using PETSc

PETSc for Partial Differential Equations: Numerical Solutions in C and Python, by Ed Bueler, is available.

Main Topics#

Toolkits/libraries that use PETSc#

  • ADflow An Open-Source Computational Fluid Dynamics Solver for Aerodynamic and Multidisciplinary Optimization

  • BOUT++ Plasma simulation in curvilinear coordinate systems

  • Chaste Cancer, Heart and Soft Tissue Environment

  • code_aster open source general purpose finite element code for solid and structural mechanics

  • COOLFluiD CFD, plasma and multi-physics simulation package

  • DAFoam Discrete adjoint solvers with OpenFOAM for aerodynamic optimization

  • DEAL.II C++ based finite element simulation package

  • DUNE-FEM Python and C++ based finite element simulation package

  • FEniCS Python based finite element simulation package

  • Firedrake Python based finite element simulation package

  • Fluidity a finite element/volume fluids code

  • FreeFEM finite element PDE solver with embedded domain specific language

  • hIPPYlib FEniCS based toolkit for solving large-scale deterministic and Bayesian inverse problems governed by partial differential equations

  • libMesh adaptive finite element library

  • MFEM lightweight, scalable C++ library for finite element methods

  • MLSVM, Multilevel Support Vector Machines with PETSc.

  • MoFEM, An open source, parallel finite element library

  • MOOSE - Multiphysics Object-Oriented Simulation Environment finite element framework, built on top of libMesh and PETSc

  • OOFEM object oriented finite element library

  • OpenCarp Cardiac Electrophysiology Simulator

  • OpenFOAM Available as an extension for linear solvers for OpenFOAM

  • OpenFVM finite volume based CFD solver

  • PermonSVM support vector machines and PermonQP quadratic programming

  • PetIGA A framework for high performance Isogeometric Analysis

  • PHAML The Parallel Hierarchical Adaptive MultiLevel Project

  • preCICE - A fully parallel coupling library for partitioned multi-physics simulations

  • PyClaw A massively parallel, high order accurate, hyperbolic PDE solver

  • SLEPc Scalable Library for Eigenvalue Problems

Citing PETSc#

You can run any PETSc program with the option -citations to print appropriate citations for the algorithms you are using within PETSc.

For general citations on PETSc please use the following:

@misc{petsc-web-page,
  author = {Satish Balay and Shrirang Abhyankar and Mark~F. Adams and Steven Benson and Jed Brown
    and Peter Brune and Kris Buschelman and Emil~M. Constantinescu and Lisandro Dalcin and Alp Dener
    and Victor Eijkhout and Jacob Faibussowitsch and William~D. Gropp and V\'{a}clav Hapla and Tobin Isaac and Pierre Jolivet
    and Dmitry Karpeev and Dinesh Kaushik and Matthew~G. Knepley and Fande Kong and Scott Kruger
    and Dave~A. May and Lois Curfman McInnes and Richard Tran Mills and Lawrence Mitchell and Todd Munson
    and Jose~E. Roman and Karl Rupp and Patrick Sanan and Jason Sarich and Barry~F. Smith
    and Stefano Zampini and Hong Zhang and Hong Zhang and Junchao Zhang},
  title        = {{PETS}c {W}eb page},
  url          = {https://petsc.org/},
  howpublished = {\url{https://petsc.org/}},
  year         = {2023},
}

@techreport{petsc-user-ref,
  author = {Satish Balay and Shrirang Abhyankar and Mark~F. Adams and Steven Benson and Jed Brown
    and Peter Brune and Kris Buschelman and Emil Constantinescu and Lisandro Dalcin and Alp Dener
    and Victor Eijkhout and Jacob Faibussowitsch and William~D. Gropp and V\'{a}clav Hapla and Tobin Isaac and Pierre Jolivet
    and Dmitry Karpeev and Dinesh Kaushik and Matthew~G. Knepley and Fande Kong and Scott Kruger
    and Dave~A. May and Lois Curfman McInnes and Richard Tran Mills and Lawrence Mitchell and Todd Munson
    and Jose~E. Roman and Karl Rupp and Patrick Sanan and Jason Sarich and Barry~F. Smith
    and Stefano Zampini and Hong Zhang and Hong Zhang and Junchao Zhang},
  title       = {{PETSc/TAO} Users Manual},
  institution = {Argonne National Laboratory},
  number      = {ANL-21/39 - Revision 3.19},
  doi         = {10.2172/1968587},
  year        = {2023},
}

@inproceedings{petsc-efficient,
  author    = {Satish Balay and William~D. Gropp and Lois Curfman McInnes and Barry~F. Smith},
  title     = {Efficient Management of Parallelism in Object Oriented Numerical Software Libraries},
  booktitle = {Modern Software Tools in Scientific Computing},
  editor    = {E. Arge and A.~M. Bruaset and H.~P. Langtangen},
  publisher = {Birkh{\"{a}}user Press},
  pages     = {163--202},
  year      = {1997}
}

For petsc4py usage please cite

@article{DalcinPazKlerCosimo2011,
  title = "Parallel distributed computing using Python",
  author = "Lisandro D. Dalcin and Rodrigo R. Paz and Pablo A. Kler and Alejandro Cosimo",
  journal = "Advances in Water Resources",
  volume = "34",
  number = "9",
  pages = "1124 - 1139",
  note = "New Computational Methods and Software Tools",
  issn = "0309-1708",
  doi = "10.1016/j.advwatres.2011.04.013",
  year = "2011",
}

For PETSc usage on GPUs please cite

@article{MILLS2021,
title = {Toward performance-portable {PETS}c for {GPU}-based exascale systems},
journal = {Parallel Computing},
volume = {108},
pages = {102831},
year = {2021},
issn = {0167-8191},
doi = {https://doi.org/10.1016/j.parco.2021.102831},
url = {https://www.sciencedirect.com/science/article/pii/S016781912100079X},
author = {Richard Tran Mills and Mark F. Adams and Satish Balay and Jed Brown and Alp Dener and Matthew Knepley and Scott E. Kruger and Hannah Morgan and Todd Munson and Karl Rupp and Barry F. Smith and Stefano Zampini and Hong Zhang and Junchao Zhang},
}

For PetscSF – parallel communication in PETSc – please cite

@article{PetscSF2022,
  author={Zhang, Junchao and Brown, Jed and Balay, Satish and Faibussowitsch, Jacob and Knepley, Matthew and Marin, Oana and Mills, Richard Tran and Munson, Todd and Smith, Barry F. and Zampini, Stefano},
  journal={IEEE Transactions on Parallel and Distributed Systems},
  title={The {PetscSF} Scalable Communication Layer},
  year={2022},
  volume={33},
  number={4},
  pages={842-853},
}

If you use the TS component of PETSc please cite the following:

@techreport{AbhyankarEtAl2018,
  author        = {Shrirang Abhyankar and Jed Brown and Emil M. Constantinescu and Debojyoti Ghosh and Barry F. Smith and Hong Zhang},
  title         = {{PETSc/TS}: {A} Modern Scalable {ODE/DAE} Solver Library},
  journal       = {arXiv e-preprints},
  eprint        = {1806.01437},
  archivePrefix = {arXiv},
  year          = {2018},
}

If you utilize the TS adjoint solver please cite

@article{Zhang2022tsadjoint,
  author = {Zhang, Hong and Constantinescu, Emil M. and Smith, Barry F.},
  title = {{PETSc TSAdjoint: A Discrete Adjoint ODE Solver for First-Order and Second-Order Sensitivity Analysis}},
  journal = {SIAM Journal on Scientific Computing},
  volume = {44},
  number = {1},
  pages = {C1-C24},
  year = {2022},
}