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MPI_Op_create(3)		   Open MPI		      MPI_Op_create(3)

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 func‐
       tion 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 ele‐
       ments that function is combining. The result  of	 the  reduction	 over-
       writes values in inoutvec, hence the name. Each invocation of the func‐
       tion 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 cor‐
       respondence 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 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  lan‐
       guages 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++ 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

1.7.4				 Feb 04, 2014		      MPI_Op_create(3)
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