PETSc 3.15

PETSc, the Portable, Extensible Toolkit for Scientific Computation, pronounced PET-see (/ˈpɛt-siː/), is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism. PETSc (sometimes called PETSc/TAO) also contains the TAO, the Toolkit for Advanced Optimization, software library.

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

News

News: New Book on PETSc

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

• Book from SIAM Press

• Google Play E-book

News: New paper on PETSc communication System

The PetscSF Scalable Communication Layer

News: New paper on PETSc with GPUs

Toward Performance-Portable PETSc for GPU-based Exascale Systems

News: petsc4py Support

Source code for petsc4py, developed by Lisandro Dalcin, is now distributed with the PETSc source and supported by the PETSc team and mailing lists.

Main Topics

• Overview
• Download
• Installation
• FAQ
• Documentation
• Tutorials
• Community
• Developers
• Misc.

Related 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

• 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

When citing PETSc in a publication please cite the following:

@Misc{petsc-web-page,
   Author = "Satish Balay and Shrirang Abhyankar and Mark~F. Adams and Jed Brown
   and Peter Brune and Kris Buschelman and Lisandro Dalcin and Alp Dener and Victor Eijkhout
   and William~D. Gropp and Dinesh Kaushik and Matthew~G. Knepley and Dave~A. May
   and Lois Curfman McInnes and Richard Tran Mills and Todd Munson and Karl Rupp
   and Patrick Sanan and Barry~F. Smith and Stefano Zampini and Hong Zhang and Hong Zhang",
   Title  = "{PETS}c {W}eb page",
   Note   = "https://petsc.org/",
   Year   = "2021"}

@TechReport{petsc-user-ref,
   Author = "Satish Balay and Shrirang Abhyankar and Mark~F. Adams and Jed Brown
   and Peter Brune and Kris Buschelman and Lisandro Dalcin and Alp Dener and Victor Eijkhout
   and William~D. Gropp and Dinesh Kaushik and Matthew~G. Knepley and Dave~A. May
   and Lois Curfman McInnes and Richard Tran Mills and Todd Munson and Karl Rupp
   and Patrick Sanan and Barry~F. Smith and Stefano Zampini and Hong Zhang and Hong Zhang",
   Title       = "{PETS}c Users Manual",
   Number      = "ANL-95/11 - Revision 3.15",
   Institution = "Argonne National Laboratory",
   Year        = "2021"}

@InProceedings{petsc-efficient,
   Author    = "Satish Balay and William D. Gropp and Lois C. 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",
   Pages     = "163--202",
   Publisher = "Birkhauser Press",
   Year      = "1997"}

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

@article{abhyankar2018petsc,
  title={PETSc/TS: A Modern Scalable ODE/DAE Solver Library},
  author={Abhyankar, Shrirang and Brown, Jed and Constantinescu, Emil M and Ghosh, Debojyoti and Smith, Barry F and Zhang, Hong},
  journal={arXiv preprint arXiv:1806.01437},
  year={2018}
}

If you utilize the TS adjoint solver please cite

@article{zhang2019,
  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 = {arXiv e-preprints},
  eprint = {1912.07696},
  archivePrefix = {arXiv},
  year={2019}
}

Overview and Features