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[flang][OpenMP] Privatize locally destroyed values in do concurent #112

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13 changes: 10 additions & 3 deletions flang/docs/DoConcurrentConversionToOpenMP.md
Original file line number Diff line number Diff line change
Expand Up @@ -234,9 +234,16 @@ see the "Data environment" section below.
By default, variables that are used inside a `do concurernt` loop nest are
either treated as `shared` in case of mapping to `host`, or mapped into the
`target` region using a `map` clause in case of mapping to `device`. The only
exception to this is the loop's iteration variable(s) (IV) of **perfect** loop
nest. In that case, for each IV, we allocate a local copy as shown the by the
mapping examples above.
exceptions to this are:
1. the loop's iteration variable(s) (IV) of **perfect** loop nests. In that
case, for each IV, we allocate a local copy as shown the by the mapping
examples above.
1. any values that are from allocations outside the loop nest and used
exclusively inside of it. In such cases, a local privatized
value is created in the OpenMP region to prevent multiple teams of threads
from accessing and destroying the same memory block which causes runtime
issues. For an example of such cases, see
`flang/test/Transforms/DoConcurrent/locally_destroyed_temp.f90`.

#### Non-perfectly-nested loops' IVs

Expand Down
80 changes: 74 additions & 6 deletions flang/lib/Optimizer/Transforms/DoConcurrentConversion.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,10 @@
#include "flang/Optimizer/HLFIR/HLFIRDialect.h"
#include "flang/Optimizer/HLFIR/HLFIROps.h"
#include "flang/Optimizer/Transforms/Passes.h"
#include "mlir/Analysis/SliceAnalysis.h"
#include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/Math/IR/Math.h"
#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
#include "mlir/IR/Diagnostics.h"
#include "mlir/IR/IRMapping.h"
Expand Down Expand Up @@ -468,6 +471,61 @@ void sinkLoopIVArgs(mlir::ConversionPatternRewriter &rewriter,
++idx;
}
}

/// Collects values that are local to a loop: "loop-local values". A loop-local
/// value is one that is used exclusively inside the loop but allocated outside
/// of it. This usually corresponds to temporary values that are used inside the
/// loop body for initialzing other variables for example.
///
/// \param [in] doLoop - the loop within which the function searches for values
/// used exclusively inside.
///
/// \param [out] locals - the list of loop-local values detected for \p doLoop.
static void collectLoopLocalValues(fir::DoLoopOp doLoop,
llvm::SetVector<mlir::Value> &locals) {
doLoop.walk([&](mlir::Operation *op) {
for (mlir::Value operand : op->getOperands()) {
if (locals.contains(operand))
continue;

bool isLocal = true;
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if (!mlir::isa_and_present<fir::AllocaOp>(operand.getDefiningOp()))
continue;

// Values defined inside the loop are not interesting since they do not
// need to be localized.
if (doLoop->isAncestor(operand.getDefiningOp()))
continue;

for (auto *user : operand.getUsers()) {
if (!doLoop->isAncestor(user)) {
isLocal = false;
break;
}
}

if (isLocal)
locals.insert(operand);
}
});
}

/// For a "loop-local" value \p local within a loop's scope, localizes that
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/// value within the scope of the parallel region the loop maps to. Towards that
/// end, this function moves the allocation of \p local within \p allocRegion.
///
/// \param local - the value used exclusively within a loop's scope (see
/// collectLoopLocalValues).
///
/// \param allocRegion - the parallel region where \p local's allocation will be
/// privatized.
///
/// \param rewriter - builder used for updating \p allocRegion.
static void localizeLoopLocalValue(mlir::Value local, mlir::Region &allocRegion,
mlir::ConversionPatternRewriter &rewriter) {
rewriter.moveOpBefore(local.getDefiningOp(), &allocRegion.front().front());
}
} // namespace looputils

class DoConcurrentConversion : public mlir::OpConversionPattern<fir::DoLoopOp> {
Expand Down Expand Up @@ -519,9 +577,13 @@ class DoConcurrentConversion : public mlir::OpConversionPattern<fir::DoLoopOp> {
bool hasRemainingNestedLoops =
failed(looputils::collectLoopNest(doLoop, loopNest));

mlir::IRMapping mapper;

llvm::SetVector<mlir::Value> locals;
looputils::collectLoopLocalValues(loopNest.back().first, locals);

looputils::sinkLoopIVArgs(rewriter, loopNest);

mlir::IRMapping mapper;
mlir::omp::TargetOp targetOp;
mlir::omp::LoopNestClauseOps loopNestClauseOps;

Expand All @@ -541,8 +603,13 @@ class DoConcurrentConversion : public mlir::OpConversionPattern<fir::DoLoopOp> {
genDistributeOp(doLoop.getLoc(), rewriter);
}

genParallelOp(doLoop.getLoc(), rewriter, loopNest, mapper,
loopNestClauseOps);
mlir::omp::ParallelOp parallelOp = genParallelOp(
doLoop.getLoc(), rewriter, loopNest, mapper, loopNestClauseOps);

for (mlir::Value local : locals)
looputils::localizeLoopLocalValue(local, parallelOp.getRegion(),
rewriter);

mlir::omp::LoopNestOp ompLoopNest =
genWsLoopOp(rewriter, loopNest.back().first, mapper, loopNestClauseOps);

Expand Down Expand Up @@ -919,9 +986,10 @@ class DoConcurrentConversionPass
context, mapTo == fir::omp::DoConcurrentMappingKind::DCMK_Device,
concurrentLoopsToSkip);
mlir::ConversionTarget target(*context);
target.addLegalDialect<fir::FIROpsDialect, hlfir::hlfirDialect,
mlir::arith::ArithDialect, mlir::func::FuncDialect,
mlir::omp::OpenMPDialect>();
target.addLegalDialect<
fir::FIROpsDialect, hlfir::hlfirDialect, mlir::arith::ArithDialect,
mlir::func::FuncDialect, mlir::omp::OpenMPDialect,
mlir::cf::ControlFlowDialect, mlir::math::MathDialect>();

target.addDynamicallyLegalOp<fir::DoLoopOp>([&](fir::DoLoopOp op) {
return !op.getUnordered() || concurrentLoopsToSkip.contains(op);
Expand Down
66 changes: 66 additions & 0 deletions flang/test/Transforms/DoConcurrent/locally_destroyed_temp.f90
Original file line number Diff line number Diff line change
@@ -0,0 +1,66 @@
! Tests that locally destroyed values in a `do concurrent` loop are properly
! handled. Locally destroyed values are those values for which the Fortran runtime
! calls `@_FortranADestroy` inside the loops body. If these values are allocated
! outside the loop, and the loop is mapped to OpenMP, then a runtime error would
! occur due to multiple teams trying to access the same allocation.

! RUN: %flang_fc1 -emit-hlfir -fopenmp -fdo-concurrent-parallel=host %s -o - \
! RUN: | FileCheck %s

module struct_mod
type test_struct
integer, allocatable :: x_
end type

interface test_struct
pure module function construct_from_components(x) result(struct)
implicit none
integer, intent(in) :: x
type(test_struct) struct
end function
end interface
end module

submodule(struct_mod) struct_sub
implicit none

contains
module procedure construct_from_components
struct%x_ = x
end procedure
end submodule struct_sub

program main
use struct_mod, only : test_struct

implicit none
type(test_struct), dimension(10) :: a
integer :: i
integer :: total

do concurrent (i=1:10)
a(i) = test_struct(i)
end do

do i=1,10
total = total + a(i)%x_
end do

print *, "total =", total
end program main

! CHECK: omp.parallel {
! CHECK: %[[LOCAL_TEMP:.*]] = fir.alloca !fir.type<_QMstruct_modTtest_struct{x_:!fir.box<!fir.heap<i32>>}> {bindc_name = ".result"}
! CHECK: omp.wsloop {
! CHECK: omp.loop_nest {{.*}} {
! CHECK: %[[TEMP_VAL:.*]] = fir.call @_QMstruct_modPconstruct_from_components
! CHECK: fir.save_result %[[TEMP_VAL]] to %[[LOCAL_TEMP]]
! CHECK: %[[EMBOXED_LOCAL:.*]] = fir.embox %[[LOCAL_TEMP]]
! CHECK: %[[CONVERTED_LOCAL:.*]] = fir.convert %[[EMBOXED_LOCAL]]
! CHECK: fir.call @_FortranADestroy(%[[CONVERTED_LOCAL]])
! CHECK: omp.yield
! CHECK: }
! CHECK: omp.terminator
! CHECK: }
! CHECK: omp.terminator
! CHECK: }