MPI_Reduce_local(3) Open MPI MPI_Reduce_local(3)NAMEMPI_Reduce_local - Perform a local reduction
SYNTAXC Syntax
#include <mpi.h>
int MPI_Reduce_local(const void *inbuf, void *inoutbuf, int count,
MPI_Datatype datatype, MPI_Op op)
Fortran Syntax
INCLUDE 'mpif.h'
MPI_REDUCE_LOCAL(INBUF, INOUTBUF, COUNT, DATATYPE, OP, IERROR)
<type> INBUF(*), INOUTBUF(*)
INTEGER COUNT, DATATYPE, OP, IERROR
C++ Syntax
#include <mpi.h>
void MPI::Op::Reduce_local(const void* inbuf, void* inoutbuf,
int count, const MPI::Datatype& datatype, const MPI::Op& op) const
INPUT PARAMETERS
inbuf Address of input buffer (choice).
count Number of elements in input buffer (integer).
datatype Data type of elements of input buffer (handle).
op Reduce operation (handle).
OUTPUT PARAMETERS
inoutbuf Address of in/out buffer (choice).
IERROR Fortran only: Error status (integer).
DESCRIPTION
The MPI_Reduce_local function is proposed for MPI-2.2 and (as of 10 Jan
2009) has not yet been ratified. Use at your own risk. See
https://svn.mpi-forum.org/trac/mpi-forum-web/ticket/24.
The global reduce functions (MPI_Reduce_local, MPI_Op_create,
MPI_Op_free, MPI_Allreduce, MPI_Reduce_local_scatter, MPI_Scan) perform
a global reduce operation (such as sum, max, logical AND, etc.) across
all the members of a group. The reduction operation can be either one
of a predefined list of operations, or a user-defined operation. The
global reduction functions come in several flavors: a reduce that
returns the result of the reduction at one node, an all-reduce that
returns this result at all nodes, and a scan (parallel prefix) opera‐
tion. In addition, a reduce-scatter operation combines the functional‐
ity of a reduce and a scatter operation.
MPI_Reduce_local combines the elements provided in the input and
input/output buffers of the local process, using the operation op, and
returns the combined value in the inout/output buffer. The input buffer
is defined by the arguments inbuf, count, and datatype; the output buf‐
fer is defined by the arguments inoutbuf, count, and datatype; both
have the same number of elements, with the same type. The routine is a
local call. The process can provide one element, or a sequence of ele‐
ments, in which case the combine operation is executed element-wise on
each entry of the sequence. For example, if the operation is MPI_MAX
and the input buffer contains two elements that are floating-point num‐
bers (count = 2 and datatype = MPI_FLOAT), then inoutbuf(1) = global
max (inbuf(1)) and inoutbuf(2) = global max(inbuf(2)).
USE OF IN-PLACE OPTION
The use of MPI_IN_PLACE is disallowed with MPI_Reduce_local.
PREDEFINED REDUCE OPERATIONS
The set of predefined operations provided by MPI is listed below (Pre‐
defined Reduce Operations). That section also enumerates the datatypes
each operation can be applied to. In addition, users may define their
own operations that can be overloaded to operate on several datatypes,
either basic or derived. This is further explained in the description
of the user-defined operations (see the man pages for MPI_Op_create and
MPI_Op_free).
The operation op is always assumed to be associative. All predefined
operations are also assumed to be commutative. Users may define opera‐
tions that are assumed to be associative, but not commutative. The
``canonical'' evaluation order of a reduction is determined by the
ranks of the processes in the group. However, the implementation can
take advantage of associativity, or associativity and commutativity, in
order to change the order of evaluation. This may change the result of
the reduction for operations that are not strictly associative and com‐
mutative, such as floating point addition.
Predefined operators work only with the MPI types listed below (Prede‐
fined Reduce Operations, and the section MINLOC and MAXLOC, below).
User-defined operators may operate on general, derived datatypes. In
this case, each argument that the reduce operation is applied to is one
element described by such a datatype, which may contain several basic
values. This is further explained in Section 4.9.4 of the MPI Standard,
"User-Defined Operations."
The following predefined operations are supplied for MPI_Reduce_local
and related functions MPI_Allreduce, MPI_Reduce_scatter, and MPI_Scan.
These operations are invoked by placing the following in op:
Name Meaning
-----------------------------
MPI_MAX maximum
MPI_MIN minimum
MPI_SUM sum
MPI_PROD product
MPI_LAND logical and
MPI_BAND bit-wise and
MPI_LOR logical or
MPI_BOR bit-wise or
MPI_LXOR logical xor
MPI_BXOR bit-wise xor
MPI_MAXLOC max value and location
MPI_MINLOC min value and location
The two operations MPI_MINLOC and MPI_MAXLOC are discussed separately
below (MINLOC and MAXLOC). For the other predefined operations, we enu‐
merate below the allowed combinations of op and datatype arguments.
First, define groups of MPI basic datatypes in the following way:
C integer: MPI_INT, MPI_LONG, MPI_SHORT,
MPI_UNSIGNED_SHORT, MPI_UNSIGNED,
MPI_UNSIGNED_LONG
Fortran integer: MPI_INTEGER
Floating-point: MPI_FLOAT, MPI_DOUBLE, MPI_REAL,
MPI_DOUBLE_PRECISION, MPI_LONG_DOUBLE
Logical: MPI_LOGICAL
Complex: MPI_COMPLEX
Byte: MPI_BYTE
Now, the valid datatypes for each option is specified below.
Op Allowed Types
-------------------------------------------
MPI_MAX, MPI_MIN C integer, Fortran integer,
floating-point
MPI_SUM, MPI_PROD C integer, Fortran integer,
floating-point, complex
MPI_LAND, MPI_LOR, C integer, logical
MPI_LXOR
MPI_BAND, MPI_BOR, C integer, Fortran integer, byte
MPI_BXOR
MINLOC AND MAXLOC
The operator MPI_MINLOC is used to compute a global minimum and also an
index attached to the minimum value. MPI_MAXLOC similarly computes a
global maximum and index. One application of these is to compute a
global minimum (maximum) and the rank of the process containing this
value.
The operation that defines MPI_MAXLOC is
( u ) ( v ) ( w )
( ) o ( ) = ( )
( i ) ( j ) ( k )
where
w = max(u, v)
and
( i if u > v
(
k = ( min(i, j) if u = v
(
( j if u < v)
MPI_MINLOC is defined similarly:
( u ) ( v ) ( w )
( ) o ( ) = ( )
( i ) ( j ) ( k )
where
w = min(u, v)
and
( i if u < v
(
k = ( min(i, j) if u = v
(
( j if u > v)
Both operations are associative and commutative. Note that if
MPI_MAXLOC is applied to reduce a sequence of pairs (u(0), 0), (u(1),
1), ..., (u(n-1), n-1), then the value returned is (u , r), where u=
max(i)u(i) and r is the index of the first global maximum in the
sequence. Thus, if each process supplies a value and its rank within
the group, then a reduce operation with op = MPI_MAXLOC will return the
maximum value and the rank of the first process with that value. Simi‐
larly, MPI_MINLOC can be used to return a minimum and its index. More
generally, MPI_MINLOC computes a lexicographic minimum, where elements
are ordered according to the first component of each pair, and ties are
resolved according to the second component.
The reduce operation is defined to operate on arguments that consist of
a pair: value and index. For both Fortran and C, types are provided to
describe the pair. The potentially mixed-type nature of such arguments
is a problem in Fortran. The problem is circumvented, for Fortran, by
having the MPI-provided type consist of a pair of the same type as
value, and coercing the index to this type also. In C, the MPI-provided
pair type has distinct types and the index is an int.
In order to use MPI_MINLOC and MPI_MAXLOC in a reduce operation, one
must provide a datatype argument that represents a pair (value and
index). MPI provides nine such predefined datatypes. The operations
MPI_MAXLOC and MPI_MINLOC can be used with each of the following
datatypes:
Fortran:
Name Description
MPI_2REAL pair of REALs
MPI_2DOUBLE_PRECISION pair of DOUBLE-PRECISION variables
MPI_2INTEGER pair of INTEGERs
C:
Name Description
MPI_FLOAT_INT float and int
MPI_DOUBLE_INT double and int
MPI_LONG_INT long and int
MPI_2INT pair of ints
MPI_SHORT_INT short and int
MPI_LONG_DOUBLE_INT long double and int
The data type MPI_2REAL is equivalent to:
MPI_TYPE_CONTIGUOUS(2, MPI_REAL, MPI_2REAL)
Similar statements apply for MPI_2INTEGER, MPI_2DOUBLE_PRECISION, and
MPI_2INT.
The datatype MPI_FLOAT_INT is as if defined by the following sequence
of instructions.
type[0] = MPI_FLOAT
type[1] = MPI_INT
disp[0] = 0
disp[1] = sizeof(float)
block[0] = 1
block[1] = 1
MPI_TYPE_STRUCT(2, block, disp, type, MPI_FLOAT_INT)
Similar statements apply for MPI_LONG_INT and MPI_DOUBLE_INT.
All MPI objects (e.g., MPI_Datatype, MPI_Comm) are of type INTEGER in
Fortran.
NOTES ON COLLECTIVE OPERATIONS
The reduction operators ( 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.
The reason for this is the performance problems in ensuring that all
collective routines return the same error value.
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++ func‐
tions 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.
SEE ALSO
MPI_Allreduce
MPI_Reduce
MPI_Reduce_scatter
MPI_Scan
MPI_Op_create
MPI_Op_free
1.7.4 Feb 04, 2014 MPI_Reduce_local(3)
