MPI_ALLREDUCE(3)

📦

version 5.0.11 · 17 versions

💅 MPI_ALLREDUCE(3) — the Open MPI one, bestie 🫶

okay so this is the page for MPI_Allreduce, MPI_Iallreduce, and MPI_Allreduce_init from the Open MPI manual, and honestly? It's giving "everybody gets the answer" energy. ✨

Here's the whole vibe in one line: combines values from all processes and distributes the result back to all processes. No cap, that's literally the whole plot. 🌈

✨ SYNTAX ✨

💻 C Syntax

#include <mpi.h>

int MPI_Allreduce(const void *sendbuf, void *recvbuf, int count,
                  MPI_Datatype datatype, MPI_Op op, MPI_Comm comm)

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

int MPI_Allreduce_init(const void *sendbuf, void *recvbuf, int count,
                       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_ALLREDUCE(SENDBUF, RECVBUF, COUNT, DATATYPE, OP, COMM, IERROR)
     <type>  SENDBUF(*), RECVBUF(*)
     INTEGER COUNT, DATATYPE, OP, COMM, IERROR

MPI_IALLREDUCE(SENDBUF, RECVBUF, COUNT, DATATYPE, OP, COMM, REQUEST, IERROR)
     <type>  SENDBUF(*), RECVBUF(*)
     INTEGER COUNT, DATATYPE, OP, COMM, REQUEST, IERROR

MPI_ALLREDUCE_INIT(SENDBUF, RECVBUF, COUNT, DATATYPE, OP, COMM, INFO, REQUEST, IERROR)
     <type>  SENDBUF(*), RECVBUF(*)
     INTEGER COUNT, DATATYPE, OP, COMM, INFO, REQUEST, IERROR

🦋 Fortran 2008 Syntax

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

MPI_Iallreduce(sendbuf, recvbuf, count, datatype, op, comm, request,
             ierror)
     TYPE(*), DIMENSION(..), INTENT(IN), ASYNCHRONOUS :: sendbuf
     TYPE(*), DIMENSION(..), ASYNCHRONOUS :: recvbuf
     INTEGER, INTENT(IN) :: count
     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_Allreduce_init(sendbuf, recvbuf, count, datatype, op, comm, info, request,
             ierror)
     TYPE(*), DIMENSION(..), INTENT(IN), ASYNCHRONOUS :: sendbuf
     TYPE(*), DIMENSION(..), ASYNCHRONOUS :: recvbuf
     INTEGER, INTENT(IN) :: count
     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 — where your send buffer starts (choice). this is the tea you're contributing to the group chat ☕
count — how many elements are in the send buffer (integer).
datatype — the datatype of the elements in the send buffer (handle).
op — the operation (handle). the vibe of the combining, iykyk.
comm — the communicator (handle).
info — info (handle, persistent only). so like, only MPI_Allreduce_init gets this one 💅

🌸 OUTPUT PARAMETERS 🌸

recvbuf — where your receive buffer starts (choice). everybody gets the answer here, that's the whole point 🫶
request — the request (handle, non-blocking only).
ierror — Fortran only: error status (integer).

💖 DESCRIPTION 💖

Same as MPI_Reduce except that the result appears in the receive buffer of all the group members. Like. All of them. Not just rank 0. Main character energy for everyone. 👑

Example 1: A routine that computes the product of a vector and an array that are distributed across a group of processes and returns the answer at all nodes (compare with Example 2, with MPI_Reduce, below).

SUBROUTINE PAR_BLAS2(m, n, a, b, c, comm)
REAL a(m), b(m,n)    ! local slice of array
REAL c(n)            ! result
REAL sum(n)
INTEGER n, comm, i, j, ierr

! local sum
DO j= 1, n
  sum(j) = 0.0
  DO i = 1, m
    sum(j) = sum(j) + a(i)*b(i,j)
  END DO
END DO

! global sum
CALL MPI_ALLREDUCE(sum, c, n, MPI_REAL, MPI_SUM, comm, ierr)

! return result at all nodes
RETURN

Example 2: A routine that computes the product of a vector and an array that are distributed across a group of processes and returns the answer at node zero.

SUBROUTINE PAR_BLAS2(m, n, a, b, c, comm)
REAL a(m), b(m,n)    ! local slice of array
REAL c(n)            ! result
REAL sum(n)
INTEGER n, comm, i, j, ierr

! local sum
DO j= 1, n
  sum(j) = 0.0
  DO i = 1, m
    sum(j) = sum(j) + a(i)*b(i,j)
  END DO
END DO

! global sum
CALL MPI_REDUCE(sum, c, n, MPI_REAL, MPI_SUM, 0, comm, ierr)

! return result at node zero (and garbage at the other nodes)
RETURN

yeah bestie, that comment is not a joke — with MPI_REDUCE the other nodes get garbage. MPI_Allreduce is the one that fixes that. slay. 💀

🧊 USE OF IN-PLACE OPTION 🧊

When the communicator is an intracommunicator, you can perform an all-reduce operation in-place (the output buffer is used as the input buffer). Use the variable MPI_IN_PLACE as the value of sendbuf at all processes.

Note that MPI_IN_PLACE is a special kind of value; it has the same restrictions on its use as MPI_BOTTOM.

Because the in-place option converts the receive buffer into a send-and-receive buffer, a Fortran binding that includes INTENT must mark these as INOUT, not OUT. so like, don't @ me when your compiler yells. 🙈

🌈 WHEN COMMUNICATOR IS AN INTER-COMMUNICATOR 🌈

When the communicator is an inter-communicator, the reduce operation occurs in two phases. The data is reduced from all the members of the first group and received by all the members of the second group. Then the data is reduced from all the members of the second group and received by all the members of the first. The operation exhibits a symmetric, full-duplex behavior. it's giving mutual, two-way bestie behavior fr fr. 🦋

When the communicator is an intra-communicator, these groups are the same, and the operation occurs in a single phase.

⭐ 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.

lowkey this is the sketchy part. they can't tell you something went wrong, so they just… won't. 💀

🔥 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. 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_ERRORS_ARE_FATAL — Causes the program to abort all connected MPI processes. dramatic? yes. effective? also yes. 😭
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.

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.

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.

👑 COPYRIGHT 👑

2003-2026, The Open MPI Community. iconic, honestly. 🫶

okay that's the whole page bestie, go forth and reduce 💜✨

— with love, from the Open MPI girlies, dated Sep 11, 2026 🎀🦋💅

📦 where this page comes from

arch rolling: openmpi 5.0.11-1 · BSD-3-Clause AND LicenseRef-MPICH
💖 girlified by deepseek-ai/DeepSeek-V4.1-Flash-1017 on 2026-11-06: a language model's rewrite of the original, under its terms