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.
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.
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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.
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.
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.
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.
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.
