%0 Report %1 citeulike:13989896 %A Balay, S. %A Abhyankar, S. %A Adams, M. %A Brown, J. %A Brune, P. %A Buschelman, K. %A Dalcin, L. %A Eijkhout, V. %A Gropp, W. %A Karpeyev, D. %A Kaushik, D. %A Knepley, M. %A Curfman McInnes, L. %A Rupp, K. %A Smith, B. %A Zampini, S. %A Zhang, H. %C Argonne, Illinois %D 2015 %K petsc 65f08-preconditioners-for-iterative-methods 65f10-iterative-methods-for-linear-systems 65n30-pdes-bvps-finite-elements 65n55-pdes-bvps-multigrid-methods-domain-decomposition 35-04-pdes-explicit-machine-computation-programs 65y05-parallel-computation 65n50-pdes-bvps-mesh-generation-and-refinement 68p20-information-storage-and-retrieval mpi 35j87-nonlinear-elliptic-variational-inequalities 65h10-systems-of-nonlinear-algebraic-equations 65-04-numerical-analysis-software-source-code dmplex %N ANL-95/11 Rev 3.6 %T PETSc Users Manual %X This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. 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. • For many tasks a package such as MATLAB is often the best tool; PETSc is not intended for the classes of problems for which effective MATLAB code can be written. PETSc also has a MATLAB interface, so portions of your code can be written in MATLAB to ” try out” the PETSc solvers. The resulting code will not be scalable however because currently MATLAB is inherently not scalable. • PETSc should not be used to attempt to provide a ” parallel linear solver” in an otherwise sequential code. Certainly all parts of a previously sequential code need not be parallelized but the matrix generation portion must be parallelized to expect any kind of reasonable performance. Do not expect to generate your matrix sequentially and then ” use PETSc” to solve the linear system in parallel. Since PETSc is under continued development, small changes in usage and calling sequences of routines will occur. PETSc is supported; see the web site http://www.mcs.anl.gov/petsc for information on contacting support. A http://www.mcs.anl.gov/petsc/publications may be found a list of publications and web sites that feature work involving PETSc. We welcome any reports of corrections for this document. %7 3.6

@techreport{citeulike:13989896, abstract = {{This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. 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. • For many tasks a package such as MATLAB is often the best tool; PETSc is not intended for the classes of problems for which effective MATLAB code can be written. PETSc also has a MATLAB interface, so portions of your code can be written in MATLAB to ” try out” the PETSc solvers. The resulting code will not be scalable however because currently MATLAB is inherently not scalable. • PETSc should not be used to attempt to provide a ” parallel linear solver” in an otherwise sequential code. Certainly all parts of a previously sequential code need not be parallelized but the matrix generation portion must be parallelized to expect any kind of reasonable performance. Do not expect to generate your matrix sequentially and then ” use PETSc” to solve the linear system in parallel. Since PETSc is under continued development, small changes in usage and calling sequences of routines will occur. PETSc is supported; see the web site http://www.mcs.anl.gov/petsc for information on contacting support. A http://www.mcs.anl.gov/petsc/publications may be found a list of publications and web sites that feature work involving PETSc. We welcome any reports of corrections for this document.}}, added-at = {2017-06-29T07:13:07.000+0200}, address = {Argonne, Illinois}, author = {Balay, S. and Abhyankar, S. and Adams, M. and Brown, J. and Brune, P. and Buschelman, K. and Dalcin, L. and Eijkhout, V. and Gropp, W. and Karpeyev, D. and Kaushik, D. and Knepley, M. and Curfman McInnes, L. and Rupp, K. and Smith, B. and Zampini, S. and Zhang, H.}, biburl = {https://www.bibsonomy.org/bibtex/279eae5442d428f7affddc0906f46cbe4/gdmcbain}, citeulike-article-id = {13989896}, citeulike-attachment-1 = {balay_15_petsc_1060947.pdf; /pdf/user/gdmcbain/article/13989896/1060947/balay_15_petsc_1060947.pdf; 8682813b95a40bce4528fbc1ec07534bcf3cfd44}, edition = {3.6}, file = {balay_15_petsc_1060947.pdf}, institution = {Argonne National Laboratory}, interhash = {08fb246686dfcfc61bc258e6c376b567}, intrahash = {79eae5442d428f7affddc0906f46cbe4}, keywords = {petsc 65f08-preconditioners-for-iterative-methods 65f10-iterative-methods-for-linear-systems 65n30-pdes-bvps-finite-elements 65n55-pdes-bvps-multigrid-methods-domain-decomposition 35-04-pdes-explicit-machine-computation-programs 65y05-parallel-computation 65n50-pdes-bvps-mesh-generation-and-refinement 68p20-information-storage-and-retrieval mpi 35j87-nonlinear-elliptic-variational-inequalities 65h10-systems-of-nonlinear-algebraic-equations 65-04-numerical-analysis-software-source-code dmplex}, month = jun, number = {ANL-95/11 Rev 3.6}, posted-at = {2016-03-29 00:26:58}, priority = {5}, timestamp = {2021-07-15T12:34:30.000+0200}, title = {{PETSc} Users Manual}, year = 2015 }