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
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
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_Re-
duce_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 op-
erands 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 in-
outvec, len, and datatype when the function is invoked; let
w[0], ..., w[len-1] be len elements in the communication buffer de-
scribed 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 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-de-
fined 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 be-
tween the datatype handles and the datatype they represent. This corre-
spondence 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 li-
brary 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 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
4.1.2 Nov 24, 2021 MPI_Op_create(3)
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