MPI_REDUCE_SCATTER_BLOCK(3)

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💅 MPI_REDUCE_SCATTER_BLOCK(3) — the Open MPI glow-up 🫶

okay bestie, so this is one of those Open MPI pages, and today's main characters are MPI_Reduce_scatter_block, MPI_Ireduce_scatter_block, and MPI_Reduce_scatter_block_init. their whole personality? Combines values and scatters the results in blocks. that's it, that's the vibe. 🔥

No cap, this is literally the "everybody put your data in the group chat, then I'll slide each of you your own lil chunk" function. iconic behavior honestly.

✨ SYNTAX ✨

🌸 C Syntax

#include <mpi.h>

int MPI_Reduce_scatter_block(const void *sendbuf, void *recvbuf, int recvcount,
     MPI_Datatype datatype, MPI_Op op, MPI_Comm comm)

int MPI_Ireduce_scatter_block(const void *sendbuf, void *recvbuf, int recvcount,
     MPI_Datatype datatype, MPI_Op op, MPI_Comm comm, MPI_Request *request)

int MPI_Reduce_scatter_block_init(const void *sendbuf, void *recvbuf, int recvcount,
     MPI_Datatype datatype, MPI_Op op, MPI_Comm comm, MPI_Info info, MPI_Request *request)

🦋 Fortran Syntax

USE MPI
! or the older form: INCLUDE 'mpif.h'
MPI_REDUCE_SCATTER_BLOCK(SENDBUF, RECVBUF, RECVCOUNT, DATATYPE, OP,
             COMM, IERROR)
     <type>  SENDBUF(*), RECVBUF(*)
     INTEGER RECVCOUNT, DATATYPE, OP, COMM, IERROR

MPI_IREDUCE_SCATTER_BLOCK(SENDBUF, RECVBUF, RECVCOUNT, DATATYPE, OP,
             COMM, REQUEST, IERROR)
     <type>  SENDBUF(*), RECVBUF(*)
     INTEGER RECVCOUNT, DATATYPE, OP, COMM, REQUEST, IERROR

MPI_REDUCE_SCATTER_BLOCK_INOT(SENDBUF, RECVBUF, RECVCOUNT, DATATYPE, OP,
             COMM, INFO, REQUEST, IERROR)
     <type>  SENDBUF(*), RECVBUF(*)
     INTEGER RECVCOUNT, DATATYPE, OP, COMM, INFO, REQUEST, IERROR
🫶 yes, MPI_REDUCE_SCATTER_BLOCK_INOT is spelled exactly like that in the original — not me, not a typo I made, so don't come for me. reproduce it character for character, k? iykyk 💀

🧚 Fortran 2008 Syntax

USE mpi_f08
MPI_Ireduce_scatter_block(sendbuf, recvbuf, recvcount, datatype, op, comm,
             ierror)
     TYPE(*), DIMENSION(..), INTENT(IN), ASYNCHRONOUS :: sendbuf
     TYPE(*), DIMENSION(..), ASYNCHRONOUS :: recvbuf
     INTEGER, INTENT(IN) :: recvcount
     TYPE(MPI_Datatype), INTENT(IN) :: datatype
     TYPE(MPI_Op), INTENT(IN) :: op
     TYPE(MPI_Comm), INTENT(IN) :: comm
     INTEGER, OPTIONAL, INTENT(OUT) :: ierror

MPI_Ireduce_scatter_block(sendbuf, recvbuf, recvcount, datatype, op, comm,
             request, ierror)
     TYPE(*), DIMENSION(..), INTENT(IN), ASYNCHRONOUS :: sendbuf
     TYPE(*), DIMENSION(..), ASYNCHRONOUS :: recvbuf
     INTEGER, INTENT(IN) :: recvcount
     TYPE(MPI_Datatype), INTENT(IN) :: datatype
     TYPE(MPI_Op), INTENT(IN) :: op
     TYPE(MPI_Comm), INTENT(IN) :: comm
     TYPE(MPI_Request), INTENT(OUT) :: request
     INTEGER, OPTIONAL, INTENT(OUT) :: ierror

MPI_Reduce_scatter_block_init(sendbuf, recvbuf, recvcount, datatype, op, comm,
             info, request, ierror)
     TYPE(*), DIMENSION(..), INTENT(IN), ASYNCHRONOUS :: sendbuf
     TYPE(*), DIMENSION(..), ASYNCHRONOUS :: recvbuf
     INTEGER, INTENT(IN) :: recvcount
     TYPE(MPI_Datatype), INTENT(IN) :: datatype
     TYPE(MPI_Op), INTENT(IN) :: op
     TYPE(MPI_Comm), INTENT(IN) :: comm
     TYPE(MPI_Info), INTENT(IN) :: info
     TYPE(MPI_Request), INTENT(OUT) :: request
     INTEGER, OPTIONAL, INTENT(OUT) :: ierror

💖 INPUT PARAMETERS

  • sendbuf — Starting address of send buffer (choice). it's giving "here's my contribution to the group project" ✨
  • recvcount — Element count per block (non-negative integer). so keep it 0 or up, bestie, no negatives allowed 🙈
  • datatype — Datatype of elements of input buffer (handle).
  • op — Operation (handle). the whole reduction situation.
  • comm — Communicator (handle).
  • info — Info (handle, persistent only). only the persistent girlies need this one 🎀

👑 OUTPUT PARAMETERS

  • recvbuf — Starting address of receive buffer (choice).
  • request — Request (handle, non-blocking only). your lil ticket for the non-blocking club 💅
  • ierror — Fortran only: Error status (integer).

🌈 DESCRIPTION

so here's what actually goes down, bestie. MPI_Reduce_scatter_block first does an element-wise reduction on a vector of count = n * recvcount elements in the send buffer defined by sendbuf, count, and datatype, using the operation op, where n is the number of processes in the group of comm.

next, that resulting vector of results gets split into n disjoint segments — again, n being the number of processes in the group. each of those segments contains recvcount elements. the ith segment is sent to process i and stored in the receive buffer defined by recvbuf, recvcount, and datatype.

basically: everyone dumps their stuff, the math happens, and then each process gets handed exactly one block. fair and square, no fighting over the aux cord. 🔥

💀 USE OF IN-PLACE OPTION

when the communicator is an intracommunicator, you can do this reduce-scatter operation in-place — meaning the output buffer is used as the input buffer. just use the variable MPI_IN_PLACE as the value of the sendbuf. in that case, the input data is taken from the top of the receive buffer.

and here's the part people always get wrong: the area occupied by the input data may be either longer or shorter than the data filled by the output data. so don't go assuming they line up perfectly, because they don't have to. 🙈

🦋 WHEN COMMUNICATOR IS AN INTER-COMMUNICATOR

when the communicator is an inter-communicator, the reduce-scatter operation occurs in two phases:

  1. 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.
  2. 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. mutual understanding, mutual vibes. ✨

🎀 NOTES ON COLLECTIVE OPERATIONS

okay this one's a lil tragic. the reduction functions (MPI_Op) do not return an error value. so if they detect an error, all they can do is either call MPI_Abort or silently skip the problem. like, that's it, that's the whole toolkit 😭

so 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.

and why, you ask? the reason for this is the performance problems in ensuring that all collective routines return the same error value. the drama of consistency, honestly. ⭐

🔥 ERRORS

almost 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. that initial error handler can be changed by calling MPI_Comm_set_errhandler on MPI_COMM_SELF when using the World model, or via the mpi_initial_errhandler CLI argument to mpiexec, or via the 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_ERRORS_ARE_FATAL — Causes the program to abort all connected MPI processes. it's giving nuclear option 💀
  • MPI_ERRORS_ABORT — An error handler that can be invoked on a communicator, window, file, or session. When called on a communicator, it acts as if MPI_Abort was called on that communicator. If called on a window or file, acts as if MPI_Abort was called on a communicator containing the group of processes in the corresponding window or file. If called on a session, aborts only the local process.
  • MPI_ERRORS_RETURN — Returns an error code to the application. the polite one 🫶

MPI applications can also implement their own error handlers by calling:

  • MPI_Comm_create_errhandler then MPI_Comm_set_errhandler
  • MPI_File_create_errhandler then MPI_File_set_errhandler
  • MPI_Session_create_errhandler then MPI_Session_set_errhandler or at MPI_Session_init
  • MPI_Win_create_errhandler then MPI_Win_set_errhandler
⚠️ note that MPI does not guarantee that an MPI program can continue past an error. so like… don't count on it, bestie.

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.

⭐ SEE ALSO:

  • MPI_Reduce_scatter

2003-2026, The Open MPI Community

and that's the whole page, bestie — no crumbs left behind 🧚✨ this lil transmission came to you from the Open MPI manual, dated Sep 11, 2026, filed under MPI_REDUCE_SCATTER_BLOCK(3). slay, go reduce something. 💜🌈

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