.. _sec-getting-started: Getting Started --------------- PETSc consists of a collection of classes, which are discussed in detail in later parts of the manual (:doc:`programming` and :doc:`additional`). The important PETSc classes include - index sets (``IS``), including permutations, for indexing into vectors, renumbering, etc; - vectors (``Vec``); - matrices (``Mat``) (generally sparse); - over thirty Krylov subspace methods (``KSP``); - dozens of preconditioners, including multigrid, block solvers, and sparse direct solvers (``PC``); - nonlinear solvers (``SNES``); - timesteppers for solving time-dependent (nonlinear) PDEs, including support for differential algebraic equations, and the computation of adjoints (sensitivities/gradients of the solutions) (``TS``); - managing interactions between mesh data structures and vectors, matrices, and solvers (``DM``); - scalable optimization algorithms (``Tao``). Each class consist of an abstract interface (simply a set of calling sequences; an abstract base class in C++) and an implementation for each algorithm and data structure. Thus, PETSc provides clean and effective codes for the various phases of solving PDEs, with a uniform approach for each type of problem. This design enables easy comparison and use of different algorithms (for example, to experiment with different Krylov subspace methods, preconditioners, or truncated Newton methods). Hence, PETSc provides a rich environment for modeling scientific applications as well as for rapid algorithm design and prototyping. The classes enable easy customization and extension of both algorithms and implementations. This approach promotes code reuse and flexibility, and also separates the issues of parallelism from the choice of algorithms. The PETSc infrastructure creates a foundation for building large-scale applications. It is useful to consider the interrelationships among different pieces of PETSc. :any:`fig_library` is a diagram of some of these pieces. The figure illustrates the library’s hierarchical organization, which enables users to employ the solvers that are most appropriate for a particular problem. .. figure:: images/library_structure.svg :alt: PETSc numerical libraries :name: fig_library Numerical Libraries in PETSc Suggested Reading ~~~~~~~~~~~~~~~~~ The manual is divided into three parts: - :doc:`introduction` - :doc:`programming` - :doc:`additional` :doc:`introduction` describes the basic procedure for using the PETSc library and presents two simple examples of solving linear systems with PETSc. This section conveys the typical style used throughout the library and enables the application programmer to begin using the software immediately. :doc:`programming` explains in detail the use of the various PETSc libraries, such as vectors, matrices, index sets, linear and nonlinear solvers, and graphics. :doc:`additional` describes a variety of useful information, including profiling, the options database, viewers, error handling, and some details of PETSc design. PETSc has evolved to become quite a comprehensive package, and therefore this manual can be rather intimidating for new users. Bear in mind that PETSc can be used efficiently before one understands all of the material presented here. Furthermore, the definitive reference for any PETSc function is always the online manual page. Manual pages for all PETSc functions can be accessed at `www.mcs.anl.gov/petsc/documentation `__. The manual pages provide hyperlinked indices (organized by both concept and routine name) to the tutorial examples and enable easy movement among related topics. `Visual Studio Code `__ , Eclipse, Emacs, and Vim users may find their development environment's options for searching in the source code (for example, ``etags`` ``ctags`` for Emacs and Vim) are extremely useful for exploring the PETSc source code. Details of these feature are provided in :any:`sec-emacs`. The complete PETSc distribution, manual pages, and additional information are available via the `PETSc home page `__. The PETSc home page also contains details regarding installation, new features and changes in recent versions of PETSc, machines that we currently support, and a frequently asked questions (FAQ) list. **Note to Fortran Programmers**: In most of the manual, the examples and calling sequences are given for the C/C++ family of programming languages. However, Fortran programmers can use all of the functionality of PETSc from Fortran, with only minor differences in the user interface. :any:`chapter_fortran` provides a discussion of the differences between using PETSc from Fortran and C, as well as several complete Fortran examples. **Note to Python Programmers**: To program with PETSc in Python you need to install the PETSc4py package developed by Lisandro Dalcin. This can be done by configuring PETSc with the option ``--download-petsc4py``. See the `PETSc installation guide `__ for more details. .. _sec-running: Running PETSc Programs ~~~~~~~~~~~~~~~~~~~~~~ Before using PETSc, the user must first set the environmental variable ``PETSC_DIR``, indicating the full path of the PETSc home directory. For example, under the UNIX bash shell a command of the form .. code-block:: bash export PETSC_DIR=$HOME/petsc can be placed in the user’s ``.bashrc`` or other startup file. In addition, the user may need to set the environment variable ``PETSC_ARCH`` to specify a particular configuration of the PETSc libraries. Note that ``PETSC_ARCH`` is just a name selected by the installer to refer to the libraries compiled for a particular set of compiler options and machine type. Using different values of ``PETSC_ARCH`` allows one to switch between several different sets (say debug and optimized) of libraries easily. To determine if you need to set ``PETSC_ARCH``, look in the directory indicated by ``PETSC_DIR``, if there are subdirectories beginning with ``arch`` then those subdirectories give the possible values for ``PETSC_ARCH``. All PETSc programs use the MPI (Message Passing Interface) standard for message-passing communication :cite:`MPI-final`. Thus, to execute PETSc programs, users must know the procedure for beginning MPI jobs on their selected computer system(s). For instance, when using the `MPICH `__ implementation of MPI and many others, the following command initiates a program that uses eight processors: .. code-block:: bash mpiexec -n 8 ./petsc_program_name petsc_options PETSc also comes with a script that automatically uses the correct ``mpiexec`` for your configuration. .. code-block:: bash ${PETSC_DIR}/lib/petsc/bin/petscmpiexec -n 8 ./petsc_program_name petsc_options All PETSc-compliant programs support the use of the ``-help`` option as well as the ``-version`` option. Certain options are supported by all PETSc programs. We list a few particularly useful ones below; a complete list can be obtained by running any PETSc program with the option ``-help``. - ``-log_view`` - summarize the program’s performance (see :any:`ch_profiling`) - ``-fp_trap`` - stop on floating-point exceptions; for example divide by zero - ``-malloc_dump`` - enable memory tracing; dump list of unfreed memory at conclusion of the run, see :any:`detecting-memory-problems`, - ``-malloc_debug`` - enable memory debugging (by default this is activated for the debugging version of PETSc), see :any:`detecting-memory-problems`, - ``-start_in_debugger`` ``[noxterm,gdb,lldb]`` ``[-display name]`` - start all processes in debugger. See :any:`sec-debugging`, for more information on debugging PETSc programs. - ``-on_error_attach_debugger`` ``[noxterm,gdb,lldb]`` ``[-display name]`` - start debugger only on encountering an error - ``-info`` - print a great deal of information about what the program is doing as it runs .. _sec_writing: Writing PETSc Programs ~~~~~~~~~~~~~~~~~~~~~~ Most PETSc programs begin with a call to :: ierr = PetscInitialize(int *argc,char ***argv,char *file,char *help);if (ierr) return ierr; which initializes PETSc and MPI. The arguments ``argc`` and ``argv`` are the command line arguments delivered in all C and C++ programs. The argument ``file`` optionally indicates an alternative name for the PETSc options file, ``.petscrc``, which resides by default in the user’s home directory. :any:`sec_options` provides details regarding this file and the PETSc options database, which can be used for runtime customization. The final argument, ``help``, is an optional character string that will be printed if the program is run with the ``-help`` option. In Fortran the initialization command has the form .. code-block:: fortran call PetscInitialize(character(*) file,integer ierr) ``PetscInitialize()`` automatically calls ``MPI_Init()`` if MPI has not been not previously initialized. In certain circumstances in which MPI needs to be initialized directly (or is initialized by some other library), the user can first call ``MPI_Init()`` (or have the other library do it), and then call ``PetscInitialize()``. By default, ``PetscInitialize()`` sets the PETSc “world” communicator ``PETSC_COMM_WORLD`` to ``MPI_COMM_WORLD``. For those not familiar with MPI, a *communicator* is a way of indicating a collection of processes that will be involved together in a calculation or communication. Communicators have the variable type ``MPI_Comm``. In most cases users can employ the communicator ``PETSC_COMM_WORLD`` to indicate all processes in a given run and ``PETSC_COMM_SELF`` to indicate a single process. MPI provides routines for generating new communicators consisting of subsets of processors, though most users rarely need to use these. The book *Using MPI*, by Lusk, Gropp, and Skjellum :cite:`using-mpi` provides an excellent introduction to the concepts in MPI. See also the `MPI homepage `__. Note that PETSc users need not program much message passing directly with MPI, but they must be familiar with the basic concepts of message passing and distributed memory computing. All PETSc routines return a ``PetscErrorCode``, which is an integer indicating whether an error has occurred during the call. The error code is set to be nonzero if an error has been detected; otherwise, it is zero. For the C/C++ interface, the error variable is the routine’s return value, while for the Fortran version, each PETSc routine has as its final argument an integer error variable. All PETSc programs should call ``PetscFinalize()`` as their final (or nearly final) statement, as given below in the C/C++ and Fortran formats, respectively: .. code-block:: c ierr = PetscFinalize(); return ierr; .. code-block:: fortran call PetscFinalize(ierr) This routine handles options to be called at the conclusion of the program, and calls ``MPI_Finalize()`` if ``PetscInitialize()`` began MPI. If MPI was initiated externally from PETSc (by either the user or another software package), the user is responsible for calling ``MPI_Finalize()``. .. _sec_simple: Simple PETSc Examples ~~~~~~~~~~~~~~~~~~~~~ To help the user start using PETSc immediately, we begin with a simple uniprocessor example that solves the one-dimensional Laplacian problem with finite differences. This sequential code, which can be found in ``$PETSC_DIR/src/ksp/ksp/tutorials/ex1.c``, illustrates the solution of a linear system with ``KSP``, the interface to the preconditioners, Krylov subspace methods, and direct linear solvers of PETSc. Following the code we highlight a few of the most important parts of this example. .. admonition:: Listing: ``src/ksp/ksp/tutorials/ex1.c`` :name: ksp-ex1 .. literalinclude:: ../../../ksp/ksp/tutorials/ex1.c :end-before: /*TEST Include Files ^^^^^^^^^^^^^ The C/C++ include files for PETSc should be used via statements such as :: #include where ``petscksp.h`` is the include file for the linear solver library. Each PETSc program must specify an include file that corresponds to the highest level PETSc objects needed within the program; all of the required lower level include files are automatically included within the higher level files. For example, ``petscksp.h`` includes ``petscmat.h`` (matrices), ``petscvec.h`` (vectors), and ``petscsys.h`` (base PETSc file). The PETSc include files are located in the directory ``${PETSC_DIR}/include``. See :any:`sec_fortran_includes` for a discussion of PETSc include files in Fortran programs. The Options Database ^^^^^^^^^^^^^^^^^^^^ As shown in :any:`sec_simple`, the user can input control data at run time using the options database. In this example the command ``PetscOptionsGetInt(NULL,NULL,"-n",&n,&flg);`` checks whether the user has provided a command line option to set the value of ``n``, the problem dimension. If so, the variable ``n`` is set accordingly; otherwise, ``n`` remains unchanged. A complete description of the options database may be found in :any:`sec_options`. .. _sec_vecintro: Vectors ^^^^^^^ One creates a new parallel or sequential vector, ``x``, of global dimension ``M`` with the commands :: VecCreate(MPI_Comm comm,Vec *x); VecSetSizes(Vec x, PetscInt m, PetscInt M); where ``comm`` denotes the MPI communicator and ``m`` is the optional local size which may be ``PETSC_DECIDE``. The type of storage for the vector may be set with either calls to ``VecSetType()`` or ``VecSetFromOptions()``. Additional vectors of the same type can be formed with :: VecDuplicate(Vec old,Vec *new); The commands :: VecSet(Vec x,PetscScalar value); VecSetValues(Vec x,PetscInt n,PetscInt *indices,PetscScalar *values,INSERT_VALUES); respectively set all the components of a vector to a particular scalar value and assign a different value to each component. More detailed information about PETSc vectors, including their basic operations, scattering/gathering, index sets, and distributed arrays, is discussed in Chapter :any:`chapter_vectors`. Note the use of the PETSc variable type ``PetscScalar`` in this example. The ``PetscScalar`` is simply defined to be ``double`` in C/C++ (or correspondingly ``double precision`` in Fortran) for versions of PETSc that have *not* been compiled for use with complex numbers. The ``PetscScalar`` data type enables identical code to be used when the PETSc libraries have been compiled for use with complex numbers. :any:`sec_complex` discusses the use of complex numbers in PETSc programs. .. _sec_matintro: Matrices ^^^^^^^^ Usage of PETSc matrices and vectors is similar. The user can create a new parallel or sequential matrix, ``A``, which has ``M`` global rows and ``N`` global columns, with the routines :: MatCreate(MPI_Comm comm,Mat *A); MatSetSizes(Mat A,PETSC_DECIDE,PETSC_DECIDE,PetscInt M,PetscInt N); where the matrix format can be specified at runtime via the options database. The user could alternatively specify each processes’ number of local rows and columns using ``m`` and ``n``. :: MatSetSizes(Mat A,PetscInt m,PetscInt n,PETSC_DETERMINE,PETSC_DETERMINE); Generally one then sets the “type” of the matrix, with, for example, :: MatSetType(A,MATAIJ); This causes the matrix ``A`` to used the compressed sparse row storage format to store the matrix entries. See ``MatType`` for a list of all matrix types. Values can then be set with the command :: MatSetValues(Mat A,PetscInt m,PetscInt *im,PetscInt n,PetscInt *in,PetscScalar *values,INSERT_VALUES); After all elements have been inserted into the matrix, it must be processed with the pair of commands :: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); :any:`chapter_matrices` discusses various matrix formats as well as the details of some basic matrix manipulation routines. Linear Solvers ^^^^^^^^^^^^^^ After creating the matrix and vectors that define a linear system, ``Ax`` :math:`=` ``b``, the user can then use ``KSP`` to solve the system with the following sequence of commands: :: KSPCreate(MPI_Comm comm,KSP *ksp); KSPSetOperators(KSP ksp,Mat Amat,Mat Pmat); KSPSetFromOptions(KSP ksp); KSPSolve(KSP ksp,Vec b,Vec x); KSPDestroy(KSP ksp); The user first creates the ``KSP`` context and sets the operators associated with the system (matrix that defines the linear system, ``Amat`` and matrix from which the preconditioner is constructed, ``Pmat``). The user then sets various options for customized solution, solves the linear system, and finally destroys the ``KSP`` context. We emphasize the command ``KSPSetFromOptions()``, which enables the user to customize the linear solution method at runtime by using the options database, which is discussed in :any:`sec_options`. Through this database, the user not only can select an iterative method and preconditioner, but also can prescribe the convergence tolerance, set various monitoring routines, etc. (see, e.g., :any:`sec_profiling_programs`). :any:`chapter_ksp` describes in detail the ``KSP`` package, including the ``PC`` and ``KSP`` packages for preconditioners and Krylov subspace methods. Nonlinear Solvers ^^^^^^^^^^^^^^^^^ Most PDE problems of interest are inherently nonlinear. PETSc provides an interface to tackle the nonlinear problems directly called ``SNES``. :any:`chapter_snes` describes the nonlinear solvers in detail. We recommend most PETSc users work directly with ``SNES``, rather than using PETSc for the linear problem within a nonlinear solver. Error Checking ^^^^^^^^^^^^^^ All PETSc routines return an integer indicating whether an error has occurred during the call. The PETSc macro ``CHKERRQ(ierr)`` checks the value of ``ierr`` and calls the PETSc error handler upon error detection. ``CHKERRQ(ierr)`` should be used in all subroutines to enable a complete error traceback. Below, we indicate a traceback generated by error detection within a sample PETSc program. The error occurred on line 3618 of the file ``${PETSC_DIR}/src/mat/impls/aij/seq/aij.c`` and was caused by trying to allocate too large an array in memory. The routine was called in the program ``ex3.c`` on line 66. See :any:`sec_fortran_errors` for details regarding error checking when using the PETSc Fortran interface. .. code-block:: none $ cd $PETSC_DIR/src/ksp/ksp/tutorials $ make ex3 $ mpiexec -n 1 ./ex3 -m 100000 [0]PETSC ERROR: --------------------- Error Message -------------------------------- [0]PETSC ERROR: Out of memory. This could be due to allocating [0]PETSC ERROR: too large an object or bleeding by not properly [0]PETSC ERROR: destroying unneeded objects. [0]PETSC ERROR: Memory allocated 11282182704 Memory used by process 7075897344 [0]PETSC ERROR: Try running with -malloc_dump or -malloc_view for info. [0]PETSC ERROR: Memory requested 18446744072169447424 [0]PETSC ERROR: See https://www.mcs.anl.gov/petsc/documentation/faq.html for trouble shooting. [0]PETSC ERROR: Petsc Development GIT revision: v3.7.1-224-g9c9a9c5 GIT Date: 2016-05-18 22:43:00 -0500 [0]PETSC ERROR: ./ex3 on a arch-darwin-double-debug named Patricks-MacBook-Pro-2.local by patrick Mon Jun 27 18:04:03 2016 [0]PETSC ERROR: Configure options PETSC_DIR=/Users/patrick/petsc PETSC_ARCH=arch-darwin-double-debug --download-mpich --download-f2cblaslapack --with-cc=clang --with-cxx=clang++ --with-fc=gfortran --with-debugging=1 --with-precision=double --with-scalar-type=real --with-viennacl=0 --download-c2html -download-sowing [0]PETSC ERROR: #1 MatSeqAIJSetPreallocation_SeqAIJ() line 3618 in /Users/patrick/petsc/src/mat/impls/aij/seq/aij.c [0]PETSC ERROR: #2 PetscTrMallocDefault() line 188 in /Users/patrick/petsc/src/sys/memory/mtr.c [0]PETSC ERROR: #3 MatSeqAIJSetPreallocation_SeqAIJ() line 3618 in /Users/patrick/petsc/src/mat/impls/aij/seq/aij.c [0]PETSC ERROR: #4 MatSeqAIJSetPreallocation() line 3562 in /Users/patrick/petsc/src/mat/impls/aij/seq/aij.c [0]PETSC ERROR: #5 main() line 66 in /Users/patrick/petsc/src/ksp/ksp/tutorials/ex3.c [0]PETSC ERROR: PETSc Option Table entries: [0]PETSC ERROR: -m 100000 [0]PETSC ERROR: ----------------End of Error Message ------- send entire error message to petsc-maint@mcs.anl.gov---------- When running the debug version of the PETSc libraries, it does a great deal of checking for memory corruption (writing outside of array bounds etc). The macro ``CHKMEMQ`` can be called anywhere in the code to check the current status of the memory for corruption. By putting several (or many) of these macros into your code you can usually easily track down in what small segment of your code the corruption has occured. One can also use Valgrind to track down memory errors; see the `FAQ `__. .. _sec_parallel: Parallel Programming ^^^^^^^^^^^^^^^^^^^^ Since PETSc uses the message-passing model for parallel programming and employs MPI for all interprocessor communication, the user is free to employ MPI routines as needed throughout an application code. However, by default the user is shielded from many of the details of message passing within PETSc, since these are hidden within parallel objects, such as vectors, matrices, and solvers. In addition, PETSc provides tools such as generalized vector scatters/gathers to assist in the management of parallel data. Recall that the user must specify a communicator upon creation of any PETSc object (such as a vector, matrix, or solver) to indicate the processors over which the object is to be distributed. For example, as mentioned above, some commands for matrix, vector, and linear solver creation are: :: MatCreate(MPI_Comm comm,Mat *A); VecCreate(MPI_Comm comm,Vec *x); KSPCreate(MPI_Comm comm,KSP *ksp); The creation routines are collective over all processors in the communicator; thus, all processors in the communicator *must* call the creation routine. In addition, if a sequence of collective routines is being used, they *must* be called in the same order on each processor. The next example, given below, illustrates the solution of a linear system in parallel. This code, corresponding to `KSP Tutorial ex2 `, handles the two-dimensional Laplacian discretized with finite differences, where the linear system is again solved with KSP. The code performs the same tasks as the sequential version within :any:`sec_simple`. Note that the user interface for initiating the program, creating vectors and matrices, and solving the linear system is *exactly* the same for the uniprocessor and multiprocessor examples. The primary difference between the examples in :any:`sec_simple` and here is that each processor forms only its local part of the matrix and vectors in the parallel case. .. admonition:: Listing: ``src/ksp/ksp/tutorials/ex2.c`` :name: ksp-ex2 .. literalinclude:: ../../../ksp/ksp/tutorials/ex2.c :end-before: /*TEST .. raw:: latex \newpage Compiling and Running Programs ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The output below illustrates compiling and running a PETSc program using MPICH on an OS X laptop. Note that different machines will have compilation commands as determined by the configuration process. See :any:`sec_writing_application_codes` for a discussion about how to compile your PETSc programs. Users who are experiencing difficulties linking PETSc programs should refer to the FAQ on the PETSc website https://www.mcs.anl.gov/petsc or given in the file ``$PETSC_DIR/docs/faq.html``. .. code-block:: none $ cd $PETSC_DIR/src/ksp/ksp/tutorials $ make ex2 /Users/patrick/petsc/arch-darwin-double-debug/bin/mpicc -o ex2.o -c -Wall -Wwrite-strings -Wno-strict-aliasing -Wno-unknown-pragmas -Qunused-arguments -fvisibility=hidden -g3 -I/Users/patrick/petsc/include -I/Users/patrick/petsc/arch-darwin-double-debug/include -I/opt/X11/include -I/opt/local/include `pwd`/ex2.c /Users/patrick/petsc/arch-darwin-double-debug/bin/mpicc -Wl,-multiply_defined,suppress -Wl,-multiply_defined -Wl,suppress -Wl,-commons,use_dylibs -Wl,-search_paths_first -Wl,-multiply_defined,suppress -Wl,-multiply_defined -Wl,suppress -Wl,-commons,use_dylibs -Wl,-search_paths_first -Wall -Wwrite-strings -Wno-strict-aliasing -Wno-unknown-pragmas -Qunused-arguments -fvisibility=hidden -g3 -o ex2 ex2.o -Wl,-rpath,/Users/patrick/petsc/arch-darwin-double-debug/lib -L/Users/patrick/petsc/arch-darwin-double-debug/lib -lpetsc -Wl,-rpath,/Users/patrick/petsc/arch-darwin-double-debug/lib -lf2clapack -lf2cblas -Wl,-rpath,/opt/X11/lib -L/opt/X11/lib -lX11 -lssl -lcrypto -Wl,-rpath,/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/lib/clang/7.0.2/lib/darwin -L/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/lib/clang/7.0.2/lib/darwin -lmpifort -lgfortran -Wl,-rpath,/opt/local/lib/gcc5/gcc/x86_64-apple-darwin14/5.3.0 -L/opt/local/lib/gcc5/gcc/x86_64-apple-darwin14/5.3.0 -Wl,-rpath,/opt/local/lib/gcc5 -L/opt/local/lib/gcc5 -lgfortran -lgcc_ext.10.5 -lquadmath -lm -lclang_rt.osx -lmpicxx -lc++ -Wl,-rpath,/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/7.0.2/lib/darwin -L/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/7.0.2/lib/darwin -lclang_rt.osx -Wl,-rpath,/Users/patrick/petsc/arch-darwin-double-debug/lib -L/Users/patrick/petsc/arch-darwin-double-debug/lib -ldl -lmpi -lpmpi -lSystem -Wl,-rpath,/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/7.0.2/lib/darwin -L/Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/7.0.2/lib/darwin -lclang_rt.osx -ldl /bin/rm -f ex2.o $ $PETSC_DIR/lib/petsc/bin/petscmpiexec -n 1 ./ex2 Norm of error 0.000156044 iterations 6 $ $PETSC_DIR/lib/petsc/bin/petscmpiexec -n 2 ./ex2 Norm of error 0.000411674 iterations 7 .. _sec_profiling_programs: Profiling Programs ~~~~~~~~~~~~~~~~~~ The option ``-log_view`` activates printing of a performance summary, including times, floating point operation (flop) rates, and message-passing activity. :any:`ch_profiling` provides details about profiling, including interpretation of the output data below. This particular example involves the solution of a linear system on one processor using GMRES and ILU. The low floating point operation (flop) rates in this example are due to the fact that the code solved a tiny system. We include this example merely to demonstrate the ease of extracting performance information. .. _listing_exprof: .. code-block:: none $ $PETSC_DIR/lib/petsc/bin/petscmpiexec -n 1 ./ex1 -n 1000 -pc_type ilu -ksp_type gmres -ksp_rtol 1.e-7 -log_view ... ------------------------------------------------------------------------------------------------------------------------ Event Count Time (sec) Flops --- Global --- --- Stage ---- Total Max Ratio Max Ratio Max Ratio Mess AvgLen Reduct %T %F %M %L %R %T %F %M %L %R Mflop/s ------------------------------------------------------------------------------------------------------------------------ --- Event Stage 0: Main Stage VecMDot 1 1.0 3.2830e-06 1.0 2.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 0 5 0 0 0 0 5 0 0 0 609 VecNorm 3 1.0 4.4550e-06 1.0 6.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 0 14 0 0 0 0 14 0 0 0 1346 VecScale 2 1.0 4.0110e-06 1.0 2.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 0 5 0 0 0 0 5 0 0 0 499 VecCopy 1 1.0 3.2280e-06 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 VecSet 11 1.0 2.5537e-05 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 2 0 0 0 0 2 0 0 0 0 0 VecAXPY 2 1.0 2.0930e-06 1.0 4.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 0 10 0 0 0 0 10 0 0 0 1911 VecMAXPY 2 1.0 1.1280e-06 1.0 4.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 0 10 0 0 0 0 10 0 0 0 3546 VecNormalize 2 1.0 9.3970e-06 1.0 6.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 1 14 0 0 0 1 14 0 0 0 638 MatMult 2 1.0 1.1177e-05 1.0 9.99e+03 1.0 0.0e+00 0.0e+00 0.0e+00 1 24 0 0 0 1 24 0 0 0 894 MatSolve 2 1.0 1.9933e-05 1.0 9.99e+03 1.0 0.0e+00 0.0e+00 0.0e+00 1 24 0 0 0 1 24 0 0 0 501 MatLUFactorNum 1 1.0 3.5081e-05 1.0 4.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 2 10 0 0 0 2 10 0 0 0 114 MatILUFactorSym 1 1.0 4.4259e-05 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 3 0 0 0 0 3 0 0 0 0 0 MatAssemblyBegin 1 1.0 8.2015e-08 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 MatAssemblyEnd 1 1.0 3.3536e-05 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 2 0 0 0 0 2 0 0 0 0 0 MatGetRowIJ 1 1.0 1.5960e-06 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 MatGetOrdering 1 1.0 3.9791e-05 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 3 0 0 0 0 3 0 0 0 0 0 MatView 2 1.0 6.7909e-05 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 5 0 0 0 0 5 0 0 0 0 0 KSPGMRESOrthog 1 1.0 7.5970e-06 1.0 4.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 1 10 0 0 0 1 10 0 0 0 526 KSPSetUp 1 1.0 3.4424e-05 1.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00 2 0 0 0 0 2 0 0 0 0 0 KSPSolve 1 1.0 2.7264e-04 1.0 3.30e+04 1.0 0.0e+00 0.0e+00 0.0e+00 19 79 0 0 0 19 79 0 0 0 121 PCSetUp 1 1.0 1.5234e-04 1.0 4.00e+03 1.0 0.0e+00 0.0e+00 0.0e+00 11 10 0 0 0 11 10 0 0 0 26 PCApply 2 1.0 2.1022e-05 1.0 9.99e+03 1.0 0.0e+00 0.0e+00 0.0e+00 1 24 0 0 0 1 24 0 0 0 475 ------------------------------------------------------------------------------------------------------------------------ Memory usage is given in bytes: Object Type Creations Destructions Memory Descendants' Mem. Reports information only for process 0. --- Event Stage 0: Main Stage Vector 8 8 76224 0. Matrix 2 2 134212 0. Krylov Solver 1 1 18400 0. Preconditioner 1 1 1032 0. Index Set 3 3 10328 0. Viewer 1 0 0 0. ======================================================================================================================== ... .. _sec_writing_application_codes: Writing Application Codes with PETSc ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The examples throughout the library demonstrate the software usage and can serve as templates for developing custom applications. We suggest that new PETSc users examine programs in the directories ``${PETSC_DIR}/src//tutorials`` where ```` denotes any of the PETSc libraries (listed in the following section), such as ``SNES`` or ``KSP`` or ``TS``. The manual pages located at ``${PETSC_DIR}/docs/index.htm`` or https://www.mcs.anl.gov/petsc/documentation/ provide links (organized by both routine names and concepts) to the tutorial examples. To write a new application program using PETSc, we suggest the following procedure: #. Install and test PETSc according to the instructions at the PETSc web site. #. Make a working directory for your source code: for example, ``mkdir $HOME/application`` #. Change to that working directory; for example,\ ``cd $HOME/application`` #. Copy one of the examples in the directory that corresponds to the class of problem of interest into your working directory, for example, ``cp $PETSC_DIR/src/snes/tutorials/ex19.c ex19.c`` #. Copy $PETSC_DIR/share/petsc/Makefile.user to your working directory, for example, ``cp $PETSC_DIR/share/petsc/Makefile.user Makefile`` #. Compile and run the example program, for example, ``make ex19; ./ex19`` #. Use the example program as a starting point for developing a custom code. We highly recommend against the following since it requires changing your makefile for each new configuration/computing system but if you do not wish to include any PETSc utilities in your makefile, you can use the following commands in the PETSc root directory to get the information needed by your makefile: .. code-block:: bash make getlinklibs getincludedirs getcflags getcxxflags getfortranflags getccompiler getfortrancompiler getcxxcompiler All the libraries listed need to be linked into your executable and the include directories and flags need to be passed to the compiler. Usually this is done with ``CFLAGS=`` and ``FFLAGS=`` in your makefile. Citing PETSc ~~~~~~~~~~~~ If you use the TS component of PETSc please cite the following: .. code-block:: none @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} } When citing PETSc in a publication please cite the following: .. code-block:: none @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://www.mcs.anl.gov/petsc", Year = "2020"} @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 3.13", Institution = "Argonne National Laboratory", Year = "2020"} @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"} .. _sec_directory: Directory Structure ~~~~~~~~~~~~~~~~~~~ We conclude this introduction with an overview of the organization of the PETSc software. The root directory of PETSc contains the following directories: - ``docs`` (only in the tarball distribution of PETSc; not the git repository) - All documentation for PETSc. The files ``manual.pdf`` contains the hyperlinked users manual, suitable for printing or on-screen viewering. Includes the subdirectory - ``manualpages`` (on-line manual pages). - ``conf`` - Base PETSc configuration files that define the standard make variables and rules used by PETSc - ``include`` - All include files for PETSc that are visible to the user. - ``include/petsc/finclude`` - PETSc include files for Fortran programmers using the .F suffix (recommended). - ``include/petsc/private`` - Private PETSc include files that should *not* need to be used by application programmers. - ``share`` - Some small test matrices in data files - ``src`` - The source code for all PETSc libraries, which currently includes - ``vec`` - vectors, - ``is`` - index sets, - ``mat`` - matrices, - ``ksp`` - complete linear equations solvers, - ``ksp`` - Krylov subspace accelerators, - ``pc`` - preconditioners, - ``snes`` - nonlinear solvers - ``ts`` - ODE solvers and timestepping, - ``dm`` - data management between meshes and solvers, vectors, and matrices, - ``sys`` - general system-related routines, - ``logging`` - PETSc logging and profiling routines, - ``classes`` - low-level classes - ``draw`` - simple graphics, - ``viewer`` - mechanism for printing and visualizing PETSc objects, - ``bag`` - mechanism for saving and loading from disk user data stored in C structs. - ``random`` - random number generators. Each PETSc source code library directory has the following subdirectories: - ``tutorials`` - Programs designed to teach users about PETSc. These codes can serve as templates for the design of custom applications. - ``tests`` - Programs designed for thorough testing of PETSc. As such, these codes are not intended for examination by users. - ``interface`` - The calling sequences for the abstract interface to the component. Code here does not know about particular implementations. - ``impls`` - Source code for one or more implementations. - ``utils`` - Utility routines. Source here may know about the implementations, but ideally will not know about implementations for other components. .. raw:: html
.. bibliography:: ../../tex/petsc.bib :filter: docname in docnames .. bibliography:: ../../tex/petscapp.bib :filter: docname in docnames