MPI includes a variant of the reduce operations where the result is returned to all processes in a group. MPI requires that all processes from the same group participating in these operations receive identical results.
| MPI_ALLREDUCE( sendbuf, recvbuf, count, datatype, op, comm) | |
| IN sendbuf | starting address of send buffer (choice) |
| OUT recvbuf | starting address of receive buffer (choice) |
| IN count | number of elements in send buffer (non-negative integer) |
| IN datatype | data type of elements of send buffer (handle) |
| IN op | operation (handle) |
| IN comm | communicator (handle) |
int MPI_Allreduce(void* sendbuf, void* recvbuf, int count, MPI_Datatype datatype, MPI_Op op, MPI_Comm comm)
MPI_ALLREDUCE(SENDBUF, RECVBUF, COUNT, DATATYPE, OP, COMM, IERROR)
The all-reduce operations can be implemented as a reduce, followed by a
broadcast. However, a direct implementation can lead to better performance.
( End of advice to implementors.)
The ``in place'' option for intracommunicators is specified by passing the
value MPI_IN_PLACE to the argument sendbuf
at all processes.
In this case,
the input data is taken at each process from the receive buffer,
where it will be replaced by the output data.
If comm is an intercommunicator, then the result of the reduction
of the data provided by processes in group A is stored at each process
in group B, and vice versa.
Both groups should
provide count and datatype arguments that specify the same type
signature.
The following example uses an intracommunicator.
<type> SENDBUF(*), RECVBUF(*)
INTEGER COUNT, DATATYPE, OP, COMM, IERROR
{ void MPI::Comm::Allreduce(const void* sendbuf, void* recvbuf, int count, const MPI::Datatype& datatype, const MPI::Op& op) const = 0 (binding deprecated, see Section Deprecated since MPI-2.2
) }
If comm is an intracommunicator,
MPI_ALLREDUCE behaves the
same as MPI_REDUCE except that the result
appears in the receive buffer of all the group members.
Advice
to implementors.
Example
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 (see also Example
Predefined Reduction Operations
).
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
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(Unofficial) MPI-2.2 of September 4, 2009
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