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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
'''
This module provides the implementation of OMPDeclareTargetTrans
'''
from psyclone.psyir.nodes import OMPDeclareTargetDirective
from psyclone.psyGen import Transformation, Kern
from psyclone.psyir.transformations.mark_routine_for_gpu_mixin import (
MarkRoutineForGPUMixin)
[docs]
class OMPDeclareTargetTrans(Transformation, MarkRoutineForGPUMixin):
'''
Adds an OpenMP declare target directive to the specified routine.
For example:
>>> from psyclone.psyir.frontend.fortran import FortranReader
>>> from psyclone.psyir.nodes import Loop
>>> from psyclone.transformations import OMPDeclareTargetTrans
>>>
>>> tree = FortranReader().psyir_from_source("""
... subroutine my_subroutine(A)
... integer, dimension(10, 10), intent(inout) :: A
... integer :: i
... integer :: j
... do i = 1, 10
... do j = 1, 10
... A(i, j) = 0
... end do
... end do
... end subroutine
... """
>>> omptargettrans = OMPDeclareTargetTrans()
>>> omptargettrans.apply(tree.walk(Routine)[0])
will generate:
.. code-block:: fortran
subroutine my_subroutine(A)
integer, dimension(10, 10), intent(inout) :: A
integer :: i
integer :: j
!$omp declare target
do i = 1, 10
do j = 1, 10
A(i, j) = 0
end do
end do
end subroutine
'''
[docs]
def apply(self, node, options=None):
''' Insert an OMPDeclareTargetDirective inside the provided routine or
associated PSyKAl kernel.
:param node: the kernel or routine which is the target of this
transformation.
:type node: :py:class:`psyclone.psyir.nodes.Routine` |
:py:class:`psyclone.psyGen.Kern`
:param options: a dictionary with options for transformations.
:type options: Optional[Dict[str, Any]]
:param bool options["force"]: whether to allow routines with
CodeBlocks to run on the GPU.
:param str options["device_string"]: provide a compiler-platform
identifier.
'''
self.validate(node, options)
if isinstance(node, Kern):
# Flag that the kernel has been modified
node.modified = True
# Get the schedule representing the kernel subroutine
routines = node.get_callees()
else:
routines = [node]
for routine in routines:
if not any(isinstance(child, OMPDeclareTargetDirective) for
child in routine.children):
routine.children.insert(0, OMPDeclareTargetDirective())
[docs]
def validate(self, node, options=None):
''' Check that an OMPDeclareTargetDirective can be inserted.
:param node: the kernel or routine which is the target of this
transformation.
:type node: :py:class:`psyclone.psyGen.Kern` |
:py:class:`psyclone.psyir.nodes.Routine`
:param options: a dictionary with options for transformations.
:type options: Optional[Dict[str, Any]]
:param bool options["force"]: whether to allow routines with
CodeBlocks to run on the GPU.
:param str options["device_string"]: provide a compiler-platform
identifier.
:raises TransformationError: if the node is not a kernel or a routine.
:raises TransformationError: if the target is a built-in kernel.
:raises TransformationError: if it is a kernel but without an
associated PSyIR.
:raises TransformationError: if any of the symbols in the kernel are
accessed via a module use statement.
:raises TransformationError: if the kernel contains any calls to other
routines.
'''
super().validate(node, options=options)
self.validate_it_can_run_on_gpu(node, options)
