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MPI_Reduce_scatter, MPI_Ireduce_scatter, MPI_Reduce_scatter_init - Combines values and scatters the results. SYNTAXC Syntax#include <mpi.h> int MPI_Reduce_scatter(const void *sendbuf, void *recvbuf, const int recvcounts[], Fortran SyntaxUSE MPI ! or the older form: INCLUDE 'mpif.h' MPI_REDUCE_SCATTER(SENDBUF, RECVBUF, RECVCOUNTS, DATATYPE, OP, Fortran 2008 SyntaxUSE mpi_f08 MPI_Reduce_scatter(sendbuf, recvbuf, recvcounts, datatype, op, comm, INPUT PARAMETERS
OUTPUT PARAMETERS
DESCRIPTIONMPI_Reduce_scatter first does an element-wise reduction on vector of count = S(i)recvcounts[i] elements in the send buffer defined by sendbuf, count, and datatype. Next, the resulting vector of results is split into n disjoint segments, where n is the number of processes in the group. Segment i contains recvcounts[i] elements. The ith segment is sent to process i and stored in the receive buffer defined by recvbuf, recvcounts[i], and datatype. USE OF IN-PLACE OPTIONWhen the communicator is an intracommunicator, you can perform a reduce-scatter operation in-place (the output buffer is used as the input buffer). Use the variable MPI_IN_PLACE as the value of the sendbuf. In this case, the input data is taken from the top of the receive buffer. The area occupied by the input data may be either longer or shorter than the data filled by the output data. WHEN COMMUNICATOR IS AN INTER-COMMUNICATORWhen the communicator is an inter-communicator, the reduce-scatter operation occurs in two phases. First, the result of the reduction performed on the data provided by the processes in the first group is scattered among the processes in the second group. Then the reverse occurs: the reduction performed on the data provided by the processes in the second group is scattered among the processes in the first group. For each group, all processes provide the same recvcounts argument, and the sum of the recvcounts values should be the same for both groups. NOTES ON COLLECTIVE OPERATIONSThe 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. ERRORSAlmost 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_thread, after 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 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_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 applications can also implement their own error handlers by calling:
Note that MPI does not guarantee that an MPI program can continue past an error. See the MPI man page for a full list of MPI error codes. See the Error Handling section of the MPI-3.1 standard for more information. COPYRIGHT2003-2025, The Open MPI Community
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