MPI_OP_CREATE(3)				     Open MPI					  MPI_OP_CREATE(3)

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
	  USE MPI
	  ! or the older form: INCLUDE 'mpif.h'
	  MPI_OP_CREATE(FUNCTION, COMMUTE, OP, IERROR)
	       EXTERNAL	       FUNCTION
	       LOGICAL COMMUTE
	       INTEGER OP, IERROR

   Fortran 2008 Syntax
	  USE mpi_f08
	  MPI_Op_create(user_fn, commute, op, ierror)
	       PROCEDURE(MPI_User_function) :: user_fn
	       LOGICAL, INTENT(IN) :: commute
	       TYPE(MPI_Op), INTENT(OUT) :: op
	       INTEGER, OPTIONAL, INTENT(OUT) :: ierror

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-reduce>, MPI_Allreduce	<#mpi-allreduce>,  MPI_Reduce_scatter  <#mpi-reduce-scatter>,  and
       MPI_Scan	 <#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	<#
       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 <#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  <#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 <#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 return result of the function and Fortran
       routines in the last argument.

       Before the error value is returned, the current MPI error handler associated with the communication  object
       (e.g.,  communicator, window, file) is called.  If no communication object is associated with the MPI call,
       then the call is considered attached to MPI_COMM_SELF and will call the associated MPI error handler.  When
       MPI_COMM_SELF  is  not  initialized  (i.e., before MPI_Init <#mpi-init>/MPI_Init_thread <#mpi-init-thread>,
       after MPI_Finalize <#mpi-finalize>, or when using the Sessions Model  exclusively)  the	error  raises  the
       initial	error  handler.	 The  initial  error  handler can be changed by calling MPI_Comm_set_errhandler <#
       mpi-comm-set-errhandler> on MPI_COMM_SELF when using the World model,  or  the  mpi_initial_errhandler  CLI
       argument	  to   mpiexec	 or   info  key	 to  MPI_Comm_spawn  <#mpi-comm-spawn>/MPI_Comm_spawn_multiple	<#
       mpi-comm-spawn-multiple>.  If no other appropriate error handler has been set, then  the	 MPI_ERRORS_RETURN
       error  handler  is  called  for	MPI I/O functions and the MPI_ERRORS_ABORT error handler is called for all
       other MPI functions.

       Open MPI includes three predefined error handlers that can be used:

       • MPI_ERRORS_ARE_FATAL Causes the program to abort all connected MPI processes.

       • MPI_ERRORS_ABORT An error handler that can be invoked on a communicator, window, file, or  session.  When
	 called on a communicator, it acts as if MPI_Abort <#mpi-abort> was called on that communicator. If called
	 on  a window or file, acts as if MPI_Abort <#mpi-abort> was called on a communicator containing the group
	 of processes in the corresponding window or file. If called on a session, aborts only the local process.

       • MPI_ERRORS_RETURN Returns an error code to the application.

       MPI applications can also implement their own error handlers by calling:

       • MPI_Comm_create_errhandler	<#mpi-comm-create-errhandler>	  then	   MPI_Comm_set_errhandler	<#
	 mpi-comm-set-errhandler>

       • MPI_File_create_errhandler	 <#mpi-file-create-errhandler>	   then	    MPI_File_set_errhandler	<#
	 mpi-file-set-errhandler>

       • MPI_Session_create_errhandler	 <#mpi-session-create-errhandler>   then   MPI_Session_set_errhandler	<#
	 mpi-session-set-errhandler> or at MPI_Session_init <#mpi-session-init>

       • MPI_Win_create_errhandler	<#mpi-win-create-errhandler>	  then	    MPI_Win_set_errhandler	<#
	 mpi-win-set-errhandler>

       Note that MPI does not guarantee that an MPI program can continue past an error.

       See the MPI man page <#open-mpi> for a full list of MPI error codes <#open-mpi-errors>.

       See the Error Handling section of the MPI-3.1 standard for more information.

       See also:

	  • MPI_Reduce <#mpi-reduce>

	  • MPI_Reduce_scatter <#mpi-reduce-scatter>

	  • MPI_Allreduce <#mpi-allreduce>

	  • MPI_Scan <#mpi-scan>

	  • MPI_Op_free <#mpi-op-free>

Copyright
       2003-2026, The Open MPI Community

						   Mar 05, 2026					  MPI_OP_CREATE(3)
