Source code for psyclone.psyir.transformations.intrinsics.sum2loop_trans

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# Author: R. W. Ford, STFC Daresbury Lab
# Modified: S. Siso, STFC Daresbury Lab

'''Module providing a transformation from a PSyIR SUM intrinsic to an
equivalent PSyIR loop structure. This could be useful if the SUM
intrinsic is not supported by the back-end, the required
parallelisation approach, or if the performance in the inline code is
better than the intrinsic.

'''
from psyclone.psyir.nodes import BinaryOperation, Literal, IntrinsicCall
from psyclone.psyir.symbols import ScalarType
from psyclone.psyir.transformations.intrinsics.array_reduction_base_trans \
    import ArrayReductionBaseTrans


[docs] class Sum2LoopTrans(ArrayReductionBaseTrans): '''Provides a transformation from a PSyIR SUM IntrinsicCall node to an equivalent PSyIR loop structure that is suitable for running in parallel on CPUs and GPUs. Validity checks are also performed. If SUM contains a single positional argument which is an array, all elements of that array are summed and the result returned in the scalar R. .. code-block:: fortran R = SUM(ARRAY) For example, if the array is two dimensional, the equivalent code for real data is: .. code-block:: fortran R = 0.0 DO J=LBOUND(ARRAY,2),UBOUND(ARRAY,2) DO I=LBOUND(ARRAY,1),UBOUND(ARRAY,1) R = R + ARRAY(I,J) If the mask argument is provided then the mask is used to determine whether the sum is applied: .. code-block:: fortran R = SUM(ARRAY, mask=MOD(ARRAY, 2.0)==1) If the array is two dimensional, the equivalent code for real data is: .. code-block:: fortran R = 0.0 DO J=LBOUND(ARRAY,2),UBOUND(ARRAY,2) DO I=LBOUND(ARRAY,1),UBOUND(ARRAY,1) IF (MOD(ARRAY(I,J), 2.0)==1) THEN R = R + ARRAY(I,J) The dimension argument is currently not supported and will result in a TransformationError exception being raised. .. code-block:: fortran R = SUM(ARRAY, dimension=2) The array passed to MAXVAL may use any combination of array syntax, array notation, array sections and scalar bounds: .. code-block:: fortran R = SUM(ARRAY) ! array syntax R = SUM(ARRAY(:,:)) ! array notation R = SUM(ARRAY(1:10,lo:hi)) ! array sections R = SUM(ARRAY(1:10,:)) ! mix of array section and array notation R = SUM(ARRAY(1:10,2)) ! mix of array section and scalar bound For example: >>> from psyclone.psyir.backend.fortran import FortranWriter >>> from psyclone.psyir.frontend.fortran import FortranReader >>> from psyclone.psyir.transformations import Sum2LoopTrans >>> code = ("subroutine sum_test(array,n,m)\\n" ... " integer :: n, m\\n" ... " real :: array(10,10)\\n" ... " real :: result\\n" ... " result = sum(array)\\n" ... "end subroutine\\n") >>> psyir = FortranReader().psyir_from_source(code) >>> sum_node = psyir.children[0].children[0].children[1] >>> Sum2LoopTrans().apply(sum_node) >>> print(FortranWriter()(psyir)) subroutine sum_test(array, n, m) integer :: n integer :: m real, dimension(10,10) :: array real :: result integer :: idx integer :: idx_1 <BLANKLINE> result = 0.0 do idx = 1, 10, 1 do idx_1 = 1, 10, 1 result = result + array(idx_1,idx) enddo enddo <BLANKLINE> end subroutine sum_test <BLANKLINE> ''' _INTRINSIC_NAME = "SUM" _INTRINSIC_TYPE = IntrinsicCall.Intrinsic.SUM def _loop_body(self, lhs, rhs): '''Provide the body of the nested loop that computes the sum of the lhs and rhs. :param lhs: the lhs value for the sum operation. :type lhs: :py:class:`psyclone.psyir.nodes.Node` :param rhs: the rhs value for the sum operation. :type rhs: :py:class:`psyclone.psyir.nodes.Node` :returns: the sum of the lhs and rhs. :rtype: :py:class:`psyclone.psyir.nodes.BinaryOperation` ''' # return lhs + rhs return BinaryOperation.create(BinaryOperation.Operator.ADD, lhs, rhs) def _init_var(self, reference): '''The initial value for the variable that computes the sum of an array. :param reference: the reference used to store the final result. :type reference: :py:class:`psyclone.psyir.node.Reference` :returns: PSyIR for the value to initialise the variable that computes the sum. :rtype: :py:class:`psyclone.psyir.nodes.Literal` ''' intrinsic = reference.datatype.intrinsic precision = reference.datatype.precision scalar_type = ScalarType(intrinsic, precision) if intrinsic == ScalarType.Intrinsic.REAL: value_str = "0.0" elif intrinsic == ScalarType.Intrinsic.INTEGER: value_str = "0" # Note, the validate method guarantees that an else branch is # not required. return Literal(value_str, scalar_type)