MPI_Reduce function

Article
09/14/2018

Performs a global reduce operation across all members of a group. You can specify a predefined mathematical or logical operation or an application-defined operation.

Syntax

int MPIAPI MPI_Reduce(
  _In_      void         *sendbuf,
  _Out_opt_ void         *recvbuf,
            int          count,
            MPI_Datatype datatype,
            MPI_Op       op,
            int          root,
            MPI_Comm     comm
);

Parameters

sendbuf [in]
The handle to a buffer that contains the data to be sent to the root process.

If the comm parameter references an intracommunicator, you can specify an in place option by specifying MPI_IN_PLACE in all processes. The sendcount and sendtype parameters are ignored. Each process enters data in the corresponding receive buffer element. The nth process sends data to the nth element of the receive buffer. The root process takes its input data from the corresponding element of the receive buffer and replaces it with the output data.
recvbuf [out, optional]
The handle to a buffer to receive the result of the reduction operation. This parameter is significant only at the root process.
count
The number of elements to send from this process.
datatype
The data type of each element in the buffer. This parameter must be compatible with the operation as specified in the op parameter.
op
The global reduction operation to perform. The handle can indicate a built-in or application-defined operation. For a list of predefined operations, see the MPI_Op topic.
root
The rank of the receiving process within the specified communicator.
comm
The MPI_Comm communicator handle.

Return value

Returns MPI_SUCCESS on success. Otherwise, the return value is an error code.

In Fortran, the return value is stored in the IERROR parameter.

Fortran

    MPI_REDUCE(SENDBUF, RECVBUF, COUNT, DATATYPE, OP, ROOT, COMM, IERROR) 
        <type> SENDBUF(*), RECVBUF(*) 
        INTEGER COUNT, DATATYPE, OP, ROOT, COMM, IERROR

Remarks

The MPI_Reduce function is implemented with the assumption that the specified operation is associative. All predefined operations are designed to be associative and commutative. Users can define operations that are designed to be associative, but not commutative. The default evaluation order of a reduction operation is determined by the ranks of the processes in the group. However, the implementation can take advantage of associativity, or associativity and commutativity to change the order of evaluation. This process can change the result of the reduction for operations that are not strictly associative and commutative, such as floating point addition.

Some applications cannot ignore the non-associative nature of floating-point operations or might use user-defined operations that require a special order of evaluation and cannot be treated as associative. In this case, you can enforce the order of evaluation explicitly. For example, in the case of operations that require a strict left-to-right, or right-to-left, evaluation order, you can use the following process:

Gather all operands at a single process, for example, by using the MPI_Gather function.
Apply the reduction operation in the required order, for example, by using the MPI_Reduce_local function.
If required, broadcast or scatter the result to the other processes.

Note

It is possible to supply different user-defined operations to the MPI_Reduce function in each process. The function does not define which operations are used on which operands in this case. You cannot make any assumptions about how the MPI_Reduce function is implemented. It is safest to specify the same operation in each process.

User-defined operators can operate on general, derived data types. In this case, each argument that the reduce operation is applied to is one element that is described by such a data type, which can contain several basic values.

Overlapping data types are permitted in send buffers, but not in receive buffers. Overlapping data types in receive buffers can give unpredictable results and are considered an error.

If the comm parameter references an intracommunicator, the MPI_Reduce function combines the elements as specified in the input buffer of each process in the group, and by using the specified operation, returns the combined value in the output buffer of the root process.

The input buffer and the output buffer have the same number of elements of the same data type. Call the function in all group members by using the same values for the count, datatype, op, root, and comm parameters. This practice ensures that all processes provide input buffers and output buffers of the same length, with elements of the same type.

Each process can provide one element, or a sequence of elements, in which case the operation is executed per element on each entry of the sequence. For example, if the operation is MPI_MAX and the send buffer contains two elements that are floating point numbers, then recvbuf(1) receives the global maximum of (sendbuf(1)) and recvbuf(2) receives the global maximum of (sendbuf(2)).

If the comm parameter references an intercommunicator, then the call involves all processes in the intercommunicator, but with one group, group A, that defines the root process. All processes in the other group, group B, set the same value in root parameter, that is, the rank of the root process in group A. The root process sets the value MPI_ROOT in the root parameter. All other processes in group A set the value MPI_PROC_NULL in the root parameter. Only send buffer parameters are significant in group B processes and only receive buffer parameters are significant in the root process.

Requirements

Product	HPC Pack 2012 MS-MPI Redistributable Package, HPC Pack 2008 R2 MS-MPI Redistributable Package, HPC Pack 2008 MS-MPI Redistributable Package or HPC Pack 2008 Client Utilities
Header	Mpi.h; Mpif.h
Library	Msmpi.lib
DLL	Msmpi.dll

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