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# Copyright (c) 2017-2026, Science and Technology Facilities Council.
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# Authors R. W. Ford, A. R. Porter, S. Siso and N. Nobre, STFC Daresbury Lab
# A. B. G. Chalk, V. K. Atkinson, STFC Daresbury Lab
# J. Henrichs, Bureau of Meteorology
# Modified I. Kavcic, J. G. Wallwork, O. Brunt and L. Turner, Met Office
# S. Valat, Inria / Laboratoire Jean Kuntzmann
# M. Schreiber, Univ. Grenoble Alpes / Inria / Lab. Jean Kuntzmann
# J. Dendy, Met Office
import logging
from typing import Iterable
from psyclone.psyir.nodes import (
OMPParallelDoDirective, OMPReductionClause, Loop)
from psyclone.psyir.nodes.omp_directives import MAP_REDUCTION_OP_TO_OMP
from psyclone.psyir.transformations.omp_loop_trans import OMPLoopTrans
from psyclone.utils import transformation_documentation_wrapper
[docs]
@transformation_documentation_wrapper(inherit=False)
class OMPParallelLoopTrans(OMPLoopTrans):
''' Adds an OpenMP PARALLEL DO directive to a loop. For example:
>>> from psyclone.psyir.frontend.fortran import FortranReader
>>> from psyclone.psyir.backend.fortran import FortranWriter
>>> psyir = FortranReader().psyir_from_source("""
... program do_loop
... real, dimension(10) :: A
... integer i
... do i = 1, 10
... A(i) = i
... end do
... end program do_loop
... """)
>>> from psyclone.psyir.nodes import Loop
>>> from psyclone.transformations import OMPParallelLoopTrans
>>> trans = OMPParallelLoopTrans()
>>> trans.apply(psyir.walk(Loop)[0])
>>> print(FortranWriter()(psyir))
program do_loop
real, dimension(10) :: a
integer :: i
<BLANKLINE>
!$omp parallel do default(shared) private(i) schedule(auto)
do i = 1, 10, 1
a(i) = i
enddo
!$omp end parallel do
<BLANKLINE>
end program do_loop
<BLANKLINE>
'''
def __str__(self):
return "Add an 'OpenMP PARALLEL DO' directive"
[docs]
def apply(self, node: Loop,
force_private: Iterable[str] = tuple(),
enable_reductions: bool = False,
options=None, **kwargs):
''' Apply an OMPParallelLoop Transformation to the supplied node
(which must be a Loop). In the generated code this corresponds to
wrapping the Loop with directives:
.. code-block:: fortran
!$OMP PARALLEL DO ...
do ...
...
end do
!$OMP END PARALLEL DO
:param node: the node (loop) to which to apply the transformation.
:param force_private: specify a list of symbol names
explicitly requested to be private.
:param enable_reductions: whether to enable PSyclone to compute
reduction clauses on the parallelised loop.
:param options: a dictionary with options for transformations
and validation.
:type options: Optional[Dict[str, Any]]
'''
logger = logging.getLogger(__name__)
# TODO #2668 - deprecate options dictionary.
local_options = options.copy() if options is not None else None
reduction_ops = []
if options:
enable_reductions = options.get("enable_reductions", False)
if enable_reductions:
local_options["reduction_ops"] = \
list(MAP_REDUCTION_OP_TO_OMP.keys())
else:
if enable_reductions:
# Reduction_ops isn't a supported option provided in this
# Transformation's docstring, however since its in the
# options for its superclass we give a warning and override
# it as needed.
if "reduction_ops" in kwargs:
del kwargs["reduction_ops"]
logger.warning(
f"{self.name} overrides the provided reduction_ops "
f"keyword argument to those supported by PSyclone."
)
reduction_ops = list(MAP_REDUCTION_OP_TO_OMP.keys())
# reduction_ops is the argument used by the superclass to determine
# whether to allow reductions, so we don't pass enable_reductions.
self.validate(node, options=local_options, force_private=force_private,
reduction_ops=reduction_ops, **kwargs)
# keep a reference to the node's original parent and its index as these
# are required and will change when we change the node's location
node_parent = node.parent
node_position = node.position
# add our OpenMP loop directive setting its parent to the node's
# parent and its children to the node
directive = OMPParallelDoDirective(children=[node.detach()],
omp_schedule=self.omp_schedule)
# add any inferred reduction clauses to the newly introduced directive
for (op, ref) in self.inferred_reduction_clauses:
clause = OMPReductionClause(MAP_REDUCTION_OP_TO_OMP[op])
clause.addchild(ref)
directive.addchild(clause)
# add the OpenMP loop directive as a child of the node's parent
node_parent.addchild(directive, index=node_position)
# Add explicit private variables
explicitly_private_symbols = set()
for symbol_name in force_private:
try:
sym = node.scope.symbol_table.lookup(symbol_name)
explicitly_private_symbols.add(sym)
except KeyError:
# This is not an error, but we will log the missed string
logger.warning(
"%s has been provided with the '%s' symbol name in "
"the 'force_private' option, but there is no such "
"symbol in this scope.", self.name, symbol_name)
directive.explicitly_private_symbols.update(
explicitly_private_symbols)
# For Sphinx AutoAPI documentation generation
__all__ = ["OMPParallelLoopTrans"]
