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MPI_Op_create(3OpenMPI)                                                              MPI_Op_create(3OpenMPI)



NAME
       MPI_Op_create - Creates a user-defined combination function handle.


SYNTAX
C Syntax
       #include <mpi.h>
       int MPI_Op_create(MPI_User_function *function, int commute,
            MPI_Op *op)


Fortran Syntax
       INCLUDE 'mpif.h'
       MPI_OP_CREATE(FUNCTION, COMMUTE, OP, IERROR)
            EXTERNAL  FUNCTION
            LOGICAL   COMMUTE
            INTEGER   OP, IERROR


C++ Syntax
       #include <mpi.h>
       void Op::Init(User function* function, bool commute)


INPUT PARAMETERS
       function  User-defined function (function).

       commute   True if commutative; false otherwise.


OUTPUT PARAMETERS
       op        Operation (handle).

       IERROR    Fortran only: Error status (integer).


DESCRIPTION
       MPI_Op_create  binds a user-defined global operation to an op handle that can subsequently be used in
       MPI_Reduce, MPI_Allreduce, MPI_Reduce_scatter, and  MPI_Scan. The user-defined operation  is  assumed
       to  be associative. If commute = true, then the operation should be both commutative and associative.
       If commute = false, then the order of operands is fixed and is defined to be  in  ascending,  process
       rank  order, beginning with process zero. The order of evaluation can be changed, taking advantage of
       the associativity of the operation. If commute = true then the order of evaluation  can  be  changed,
       taking advantage of commutativity and associativity.

       function is the user-defined function, which must have the following four arguments: invec, inoutvec,
       len, and datatype.


       The ANSI-C prototype for the function is the following:

         typedef void MPI_User_function(void *invec, void *inoutvec,
                                        int *len,
                                        MPI_Datatype *datatype);

       The Fortran declaration of the user-defined function appears below.

         FUNCTION USER_FUNCTION( INVEC(*), INOUTVEC(*), LEN, TYPE)
         <type> INVEC(LEN), INOUTVEC(LEN)
          INTEGER LEN, TYPE

       The datatype argument is a handle to the data type that was passed into the call to  MPI_Reduce.  The
       user  reduce function should be written such that the following holds: Let u[0], ..., u[len-1] be the
       len elements in the communication buffer described by the arguments invec, len, and datatype when the
       function is invoked; let v[0], ..., v[len-1] be len elements in the communication buffer described by
       the arguments inoutvec, len, and datatype when the function is invoked;  let  w[0], ..., w[len-1]  be
       len  elements in the communication buffer described by the arguments inoutvec, len, and datatype when
       the function returns; then w[i] = u[i] o v[i], for i=0 ,..., len-1, where o is the  reduce  operation
       that the function computes.

       Informally,  we can think of invec and inoutvec as arrays of len elements that function is combining.
       The result of the reduction over-writes values in inoutvec, hence the name. Each  invocation  of  the
       function  results  in the pointwise evaluation of the reduce operator on len elements: i.e, the func-tion function
       tion returns in inoutvec[i] the value invec[i] o inoutvec[i], for i = 0..., count-1, where o  is  the
       combining operation computed by the function.

       By  internally  comparing the value of the datatype argument to known, global handles, it is possible
       to overload the use of a single user-defined function for several different data types.

       General datatypes may be passed to the user function. However, use of datatypes that are not contigu-ous contiguous
       ous is likely to lead to inefficiencies.

       No MPI communication function may be called inside the user function.  MPI_Abort may be called inside
       the function in case of an error.


NOTES
       Suppose one defines a library of user-defined reduce functions  that  are  overloaded:  The  datatype
       argument is used to select the right execution path at each invocation, according to the types of the
       operands. The user-defined reduce function cannot "decode" the datatype argument that it  is  passed,
       and cannot identify, by itself, the correspondence between the datatype handles and the datatype they
       represent. This correspondence was established when the datatypes were created. Before the library is
       used,  a  library  initialization  preamble  must  be  executed.  This  preamble code will define the
       datatypes that are used by the library and store handles to these datatypes in global,  static  vari-ables variables
       ables that are shared by the user code and the library code.

       Example: Example of user-defined reduce:

       Compute the product of an array of complex numbers, in C.

           typedef struct {
               double real,imag;
           } Complex;

           /* the user-defined function
            */
           void myProd( Complex *in, Complex *inout, int *len,
                        MPI_Datatype *dptr )
           {
               int i;
               Complex c;

           for (i=0; i< *len; ++i) {
                   c.real = inout->real*in->real -inout->imag*in->imag; inout->real*in->realinout->imag*in->imag;
                              inout->imag*in->imag;
                   c.imag = inout->real*in->imag +
                              inout->imag*in->real;
                   *inout = c;
                   in++; inout++;
               }
           }

           /* and, to call it...
            */
           ...

           /* each process has an array of 100 Complexes
                */
               Complex a[100], answer[100];
               MPI_Op myOp;
               MPI_Datatype ctype;

           /* explain to MPI how type Complex is defined
                */
              MPI_Type_contiguous( 2, MPI_DOUBLE, &ctype );
               MPI_Type_commit( &ctype );
               /* create the complex-product user-op
                */
               MPI_Op_create( myProd, True, &myOp );

               MPI_Reduce( a, answer, 100, ctype, myOp, root, comm );

               /* At this point, the answer, which consists of 100 Complexes,
                * resides on process root
                */

       The  Fortran version of MPI_Reduce will invoke a user-defined reduce function using the Fortran call-ing calling
       ing conventions and will pass a Fortran-type datatype argument; the C version will use C calling con-vention convention
       vention  and the C representation of a datatype handle. Users who plan to mix languages should define
       their reduction functions accordingly.


NOTES ON COLLECTIVE OPERATIONS
       The reduction functions ( MPI_Op ) do not return an error value.   As  a  result,  if  the  functions
       detect an error, all they can do is either call MPI_Abort or silently skip the problem.  Thus, if you
       change the error handler from MPI_ERRORS_ARE_FATAL to something else, for example,  MPI_ERRORS_RETURN
       , then no error may be indicated.

       The  reason  for this is the performance problems in ensuring that all collective routines return the
       same error value.


ERRORS
       Almost all MPI routines return an error value; C routines as the value of the  function  and  Fortran
       routines  in  the  last argument. C++ functions do not return errors. If the default error handler is
       set to MPI::ERRORS_THROW_EXCEPTIONS, then on error the C++ exception mechanism will be used to  throw
       an MPI:Exception object.

       Before  the  error value is returned, the current MPI error handler is called. By default, this error
       handler aborts the MPI job, except for I/O function errors. The error handler  may  be  changed  with
       MPI_Comm_set_errhandler;  the  predefined  error handler MPI_ERRORS_RETURN may be used to cause error
       values to be returned. Note that MPI does not guarantee that an MPI  program  can  continue  past  an
       error.


SEE ALSO
       MPI_Reduce
       MPI_Reduce_scatter
       MPI_Allreduce
       MPI_Scan
       MPI_Op_free




Open MPI 1.2                                   September 2006                        MPI_Op_create(3OpenMPI)

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