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 com-
       mute = 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 argu-
       ments 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  inefficien-
       cies.

       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 exe-
       cution path at each invocation, according to the types of the operands. The user-defined reduce function cannot "decode" the datatype argu-
       ment  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 exam-
       ple, 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++ func-
       tions  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)