NAME

       MPI_Type_create_darray - Creates a distributed array datatype;

SYNTAX

C Syntax

       #include <mpi.h>
       int MPI_Type_create_darray(int size, int rank, int ndims,
            const int array_of_gsizes[], const int array_of_distribs[],
            const int array_of_dargs[], const int array_of_psizes[],
            int order, MPI_Datatype oldtype, MPI_Datatype *newtype)

Fortran Syntax

       INCLUDE 'mpif.h'
       MPI_TYPE_CREATE_DARRAY(SIZE, RANK, NDIMS, ARRAY_OF_GSIZES,
            ARRAY_OF_DISTRIBS, ARRAY_OF_DARGS, ARRAY_OF_PSIZES, ORDER,
            OLDTYPE, NEWTYPE, IERROR)

            INTEGER   SIZE, RANK, NDIMS, ARRAY_OF_GSIZES(*), ARRAY_OF_DISTRIBS(*),
                 ARRAY_OF_DARGS(*), ARRAY_OF_PSIZES(*), ORDER, OLDTYPE,
                 NEWTYPE, IERROR

C++ Syntax

       #include <mpi.h>
       MPI::Datatype MPI::Datatype::Create_darray(int size, int rank,
            int ndims, const int array_of_gsizes[],
            const int array_of_distribs[], const int array_of_dargs[],
            const int array_of_psizes[], int order) const

INPUT PARAMETERS

       size      Size of process group (positive integer).

       rank      Rank in process group (nonnegative integer).

       ndims     Number of array dimensions as well as process grid dimensions (positive integer).

       array_of_gsizes
                 Number  of  elements  of  type  oldtype  in  each  dimension of global array (array of positive
                 integers).

       array_of_distribs
                 Distribution of array in each dimension (array of state).

       array_of_dargs
                 Distribution argument in each dimension (array of positive integers).

       array_of_psizes
                 Size of process grid in each dimension (array of positive integers).

       order     Array storage order flag (state).

       oldtype   Old data type (handle).

OUTPUT PARAMETERS

       newtype   New data type (handle).

       IERROR    Fortran only: Error status (integer).

DESCRIPTION

       MPI_Type_create_darray can be used to generate the data types corresponding to  the  distribution  of  an
       ndims-dimensional  array  of oldtype elements onto an ndims-dimensional grid of logical processes. Unused
       dimensions of array_of_psizes should be set to 1. For a call to MPI_Type_create_darray to be correct, the
       equation

           ndims-1
         pi              array_of_psizes[i] = size
           i=0

       must  be  satisfied.  The ordering of processes in the process grid is assumed to be row-major, as in the
       case of virtual Cartesian process topologies in MPI-1.

       Each dimension of the array can be distributed in one of three ways:

       - MPI_DISTRIBUTE_BLOCK - Block distribution
       - MPI_DISTRIBUTE_CYCLIC - Cyclic distribution
       - MPI_DISTRIBUTE_NONE - Dimension not distributed.

       The constant  MPI_DISTRIBUTE_DFLT_DARG  specifies  a  default  distribution  argument.  The  distribution
       argument  for  a  dimension  that  is  not  distributed  is  ignored.  For  any  dimension i in which the
       distribution is MPI_DISTRIBUTE_BLOCK, it erroneous to specify array_of_dargs[i]  *  array_of_psizes[i]  <
       array_of_gsizes[i].

       For  example,  the  HPF layout ARRAY(CYCLIC(15)) corresponds to MPI_DISTRIBUTE_CYCLIC with a distribution
       argument of 15, and the HPF layout ARRAY(BLOCK) corresponds to MPI_DISTRIBUTE_BLOCK with  a  distribution
       argument of MPI_DISTRIBUTE_DFLT_DARG.

       The order argument is used as in MPI_TYPE_CREATE_SUBARRAY to specify the storage order. Therefore, arrays
       described by this type constructor may be stored in Fortran (column-major) or C (row-major) order.  Valid
       values for order are MPI_ORDER_FORTRAN and MPI_ORDER_C.

       This  routine creates a new MPI data type with a typemap defined in terms of a function called "cyclic()"
       (see below).

       Without loss of generality, it suffices to define the typemap for the  MPI_DISTRIBUTE_CYCLIC  case  where
       MPI_DISTRIBUTE_DFLT_DARG is not used.

       MPI_DISTRIBUTE_BLOCK  and  MPI_DISTRIBUTE_NONE  can  be  reduced  to  the  MPI_DISTRIBUTE_CYCLIC case for
       dimension i as follows.

       MPI_DISTRIBUTE_BLOCK  with  array_of_dargs[i]  equal  to  MPI_DISTRIBUTE_DFLT_DARG   is   equivalent   to
       MPI_DISTRIBUTE_CYCLIC with array_of_dargs[i] set to

          (array_of_gsizes[i] + array_of_psizes[i] - 1)/array_of_psizes[i]

       If array_of_dargs[i] is not MPI_DISTRIBUTE_DFLT_DARG, then MPI_DISTRIBUTE_BLOCK and DISTRIBUTE_CYCLIC are
       equivalent.

       MPI_DISTRIBUTE_NONE   is   equivalent   to   MPI_DISTRIBUTE_CYCLIC   with   array_of_dargs[i]   set    to
       array_of_gsizes[i].

       Finally,  MPI_DISTRIBUTE_CYCLIC with array_of_dargs[i] equal to MPI_DISTRIBUTE_DFLT_DARG is equivalent to
       MPI_DISTRIBUTE_CYCLIC with array_of_dargs[i] set to 1.

NOTES

       For both Fortran and C arrays, the ordering of processes in the process grid is assumed to be  row-major.
       This  is  consistent  with  the ordering used in virtual Cartesian process topologies in MPI-1. To create
       such virtual process topologies, or to find the coordinates of a process in the process grid, etc., users
       may use the corresponding functions provided in MPI-1.

ERRORS

       Almost  all  MPI  routines  return  an  error  value; C routines as the value of the function and Fortran
       routines in the last argument. C++ functions do not return errors. If the default error handler is set to
       MPI::ERRORS_THROW_EXCEPTIONS,  then  on  error  the  C++  exception  mechanism  will  be used to throw an
       MPI::Exception object.

       Before the error value is returned, the current MPI error handler  is  called.  By  default,  this  error
       handler  aborts  the  MPI  job,  except  for  I/O  function errors. The error handler may be changed with
       MPI_Comm_set_errhandler; the predefined error handler MPI_ERRORS_RETURN may be used to cause error values
       to be returned. Note that MPI does not guarantee that an MPI program can continue past an error.