The distributed array type constructor supports HPF-like [30] data distributions. However, unlike in HPF, the storage order may be specified for C arrays as well as for Fortran arrays.

* Advice to users.*

One can create an HPF-like file view using this type constructor
as follows.
Complementary filetypes are created by having every process of a group
call this constructor with identical arguments
(with the exception of rank which should be set appropriately).
These filetypes (along with identical disp and etype)
are then used to define the view (via MPI_FILE_SET_VIEW),
see MPI I/O, especially Section Definitions
on page Definitions
and Section File Views
on page File Views
.
Using this view,
a collective data access operation (with identical offsets)
will yield an HPF-like distribution pattern.
(* End of advice to users.*)

MPI_TYPE_CREATE_DARRAY(size, rank, ndims, array_of_gsizes, array_of_distribs, array_of_dargs, array_of_psizes, order, oldtype, newtype) | |

IN size | size of process group (positive integer) |

IN rank | rank in process group (nonnegative integer) |

IN ndims | number of array dimensions as well as process grid dimensions (positive integer) |

IN array_of_gsizes | number of elements of type oldtype in each dimension of global array (array of positive integers) |

IN array_of_distribs | distribution of array in each dimension (array of state) |

IN array_of_dargs | distribution argument in each dimension (array of positive integers) |

IN array_of_psizes | size of process grid in each dimension (array of positive integers) |

IN order | array storage order flag (state) |

IN oldtype | old datatype (handle) |

OUT newtype | new datatype (handle) |

` int MPI_Type_create_darray(int size, int rank, int ndims, int array_of_gsizes[], int array_of_distribs[], int array_of_dargs[], int array_of_psizes[], int order, MPI_Datatype oldtype, MPI_Datatype *newtype) `

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

MPI_TYPE_CREATE_DARRAY can be used to generate
the datatypes 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.
(See Example Distributed Array Datatype Constructor
, page Distributed Array Datatype Constructor
.)
For a call to MPI_TYPE_CREATE_DARRAY to be correct,
the equation *prod _{i=0}^{ndims-1} array_of_psizes[i] = size *
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
.

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.
To create such virtual process topologies, or to find the coordinates
of a process in the process grid, etc., users may use the corresponding
process topology functions,
see Chapter Process Topologies
on page Process Topologies
.
(* End of advice to users.*)

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 is erroneous to specify array_of_dargs[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 datatype 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

*
(mpiargarray_of_gsizes[i] + mpiargarray_of_psizes[i] - 1)
/ mpiargarray_of_psizes[i].
*

If array_of_dargs[i] is not MPI_DISTRIBUTE_DFLT_DARG, then MPI_DISTRIBUTE_BLOCK and MPI_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.

For MPI_ORDER_FORTRAN, an ndims-dimensional distributed array ( newtype) is defined by the following code fragment:

For MPI_ORDER_C, the code is:oldtype[0] = oldtype; for ( i = 0; i < ndims; i++ ) { oldtype[i+1] = cyclic(array_of_dargs[i], array_of_gsizes[i], r[i], array_of_psizes[i], oldtype[i]); } newtype = oldtype[ndims];

whereoldtype[0] = oldtype; for ( i = 0; i < ndims; i++ ) { oldtype[i + 1] = cyclic(array_of_dargs[ndims - i - 1], array_of_gsizes[ndims - i - 1], r[ndims - i - 1], array_of_psizes[ndims - i - 1], oldtype[i]); } newtype = oldtype[ndims];

Let the typemap of oldtype have the form:t_rank = rank; t_size = 1; for (i = 0; i < ndims; i++) t_size *= array_of_psizes[i]; for (i = 0; i < ndims; i++) { t_size = t_size / array_of_psizes[i]; r[i] = t_rank / t_size; t_rank = t_rank % t_size; }

Given the above, the function cyclic() is defined as follows:

where *count* is defined by this code fragment:

Here,nblocks = (gsize + (darg - 1)) / darg; count = nblocks / psize; left_over = nblocks - count * psize; if (r < left_over) count = count + 1;

if ((num_in_last_cyclic = gsize % (psize * darg)) == 0) darg_last = darg; else darg_last = num_in_last_cyclic - darg * r; if (darg_last > darg) darg_last = darg; if (darg_last <= 0) darg_last = darg;

** Example**
Consider generating the filetypes corresponding to the HPF distribution:

This can be achieved by the following Fortran code, assuming there will be six processes attached to the run:<oldtype> FILEARRAY(100, 200, 300) !HPF$ PROCESSORS PROCESSES(2, 3) !HPF$ DISTRIBUTE FILEARRAY(CYCLIC(10), *, BLOCK) ONTO PROCESSES

ndims = 3 array_of_gsizes(1) = 100 array_of_distribs(1) = MPI_DISTRIBUTE_CYCLIC array_of_dargs(1) = 10 array_of_gsizes(2) = 200 array_of_distribs(2) = MPI_DISTRIBUTE_NONE array_of_dargs(2) = 0 array_of_gsizes(3) = 300 array_of_distribs(3) = MPI_DISTRIBUTE_BLOCK array_of_dargs(3) = MPI_DISTRIBUTE_DFLT_ARG array_of_psizes(1) = 2 array_of_psizes(2) = 1 array_of_psizes(3) = 3 call MPI_COMM_SIZE(MPI_COMM_WORLD, size, ierr) call MPI_COMM_RANK(MPI_COMM_WORLD, rank, ierr) call MPI_TYPE_CREATE_DARRAY(size, rank, ndims, array_of_gsizes, & array_of_distribs, array_of_dargs, array_of_psizes, & MPI_ORDER_FORTRAN, oldtype, newtype, ierr)

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