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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 function 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  contiguous
       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 variables 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;
                   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 calling
       conventions and will pass a Fortran-type datatype argument; the C version will use C  calling  convention
       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