The Great and Terrible implementation of MPI-2

function index


Accumulate data into the target process using remote memory access
int MPI_Accumulate(
  void *origin_addr,
  int origin_count,
  MPI_Datatype origin_datatype,
  int target_rank,
  MPI_Aint target_disp,
  int target_count,
  MPI_Datatype target_datatype,
  MPI_Op op,
  MPI_Win win
) ;


[in] initial address of buffer (choice)
[in] number of entries in buffer (nonnegative integer)
[in] datatype of each buffer entry (handle)
[in] rank of target (nonnegative integer)
[in] displacement from start of window to beginning of target buffer (nonnegative integer)
[in] number of entries in target buffer (nonnegative integer)
[in] datatype of each entry in target buffer (handle)
[in] predefined reduce operation (handle)
[in] window object (handle)


It is often useful in a put operation to combine the data moved to the target process with the data that resides at that process, rather then replacing the data there. This will allow, for example, the accumulation of a sum by having all involved processes add their contribution to the sum variable in the memory of one process.

Accumulate the contents of the origin buffer (as defined by origin_addr, origin_count and origin_datatype) to the buffer specified by arguments target_count and target_datatype, at offset target_disp, in the target window specified by target_rank and win, using the operation op. This is like MPI_PUT except that data is combined into the target area instead of overwriting it.

Any of the predefined operations for MPI_REDUCE can be used. User-defined functions cannot be used. For example, if op is MPI_SUM, each element of the origin buffer is added to the corresponding element in the target, replacing the former value in the target.

Each datatype argument must be a predefined datatype or a derived datatype, where all basic components are of the same predefined datatype. Both datatype arguments must be constructed from the same predefined datatype. The operation op applies to elements of that predefined type. target_datatype must not specify overlapping entries, and the target buffer must fit in the target window.

A new predefined operation, MPI_REPLACE, is defined. It corresponds to the associative function f(a,b) = b; i.e., the current value in the target memory is replaced by the value supplied by the origin.

The basic components of both the origin and target datatype must be the same predefined datatype (e.g., all MPI_INT or all MPI_DOUBLE_PRECISION).

Notes for Fortran

All MPI routines in Fortran (except for MPI_WTIME and MPI_WTICK) have an additional argument ierr at the end of the argument list. ierr is an integer and has the same meaning as the return value of the routine in C. In Fortran, MPI routines are subroutines, and are invoked with the call statement.

All MPI objects (e.g., MPI_Datatype, MPI_Comm) are of type INTEGER in Fortran.


All MPI routines (except MPI_Wtime and MPI_Wtick) return an error value; C routines as the value of the function and Fortran routines in the last argument. Before the value is returned, the current MPI error handler is called. By default, this error handler aborts the MPI job. The error handler may be changed with MPI_Comm_set_errhandler (for communicators), MPI_File_set_errhandler (for files), and MPI_Win_set_errhandler (for RMA windows). The MPI-1 routine MPI_Errhandler_set may be used but its use is deprecated. The predefined error handler MPI_ERRORS_RETURN may be used to cause error values to be returned. Note that MPI does not guarentee that an MPI program can continue past an error; however, MPI implementations will attempt to continue whenever possible.

No error; MPI routine completed successfully.
Invalid argument. Some argument is invalid and is not identified by a specific error class (e.g., MPI_ERR_RANK).
Invalid count argument. Count arguments must be non-negative; a count of zero is often valid.
Invalid source or destination rank. Ranks must be between zero and the size of the communicator minus one; ranks in a receive (MPI_Recv, MPI_Irecv, MPI_Sendrecv, etc.) may also be MPI_ANY_SOURCE.
Invalid datatype argument. May be an uncommitted MPI_Datatype (see MPI_Type_commit).
Invalid MPI window object

Example Code

The following sample code illustrates MPI_Accumulate.

#include "mpi.h"
#include "stdio.h"
/* This does a transpose-cum-accumulate operation. Uses vector and
hvector datatypes (Example 3.32 from MPI 1.1 Standard). Run on 2
processes */

#define NROWS 100
#define NCOLS 100
int main(int argc, char *argv[])
    int rank, nprocs, A[NROWS][NCOLS], i, j;
    MPI_Win win;
    MPI_Datatype column, xpose;
int errs = 0;

if (nprocs != 2)
        printf("Run this program with 2 processes\n");fflush(stdout);
if (rank == 0)
for (i=0; i<NROWS; i++)
for (j=0; j<NCOLS; j++)
                A[i][j] = i*NCOLS + j;
/* create datatype for one column */
MPI_Type_vector(NROWS, 1, NCOLS, MPI_INT, &column);
/* create datatype for matrix in column-major order */
MPI_Type_hvector(NCOLS, 1, sizeof(int), column, &xpose);

        MPI_Win_create(NULL, 0, 1, MPI_INFO_NULL, MPI_COMM_WORLD, &win);
        MPI_Win_fence(0, win);
        MPI_Accumulate(A, NROWS*NCOLS, MPI_INT, 1, 0, 1, xpose, MPI_SUM, win);

        MPI_Win_fence(0, win);
{ /* rank = 1 */
for (i=0; i<NROWS; i++)
for (j=0; j<NCOLS; j++)
                A[i][j] = i*NCOLS + j;
        MPI_Win_create(A, NROWS*NCOLS*
sizeof(int), sizeof(int), MPI_INFO_NULL,
        MPI_COMM_WORLD, &win);
        MPI_Win_fence(0, win);
        MPI_Win_fence(0, win);
for (j=0; j<NCOLS; j++)
for (i=0; i<NROWS; i++)
if (A[j][i] != i*NCOLS + j + j*NCOLS + i)
if (errs < 50)
                        printf("Error: A[%d][%d]=%d should be %d\n", j, i,
                            A[j][i], i*NCOLS + j + j*NCOLS + i);fflush(stdout);
if (errs >= 50)
            printf("Total number of errors: %d\n", errs);fflush(stdout);
return 0;